\r\n\t* Technologies that allow control and reduction of air pollutants are encouraged to be discussed. In particular, technologies employed to treat greenhouse gases and precursors of acid rain. \r\n\t* Poor agricultural practices, improper waste management and extractive activities that contaminate soil with special attention focused on emerging techniques permitting to diminish these pollutants. \r\n\t* In the treatment of freshwater and marine and coastal waters, technologies that should be taken into account are those focused to eliminate chemicals and pathogens from mining and industrial effluents. \r\n\t* Renewable energy technologies should also be discussed, special interest in those having the lower environmental impact. In this case a watchful life-cycle analysis has to support the proposal. \r\n\t* New technologies and materials allowing the energy storage in a competitive mode should be also taken into account for the reason that they have a direct impact in the decrease of pollutants. \r\n\t* As a final point, technological innovations applied to conserve and study endangered species will be also considered.
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\n
1. Introduction
\n
Since the dawn of electronics more than 50 years ago, manufacturers have been providing customers with faster and smaller chips by fabricating increasingly better devices and improving processes. The main strategy adopted has been to shrink the gate size of the MOSFETs to improve chip performances, especially speed. Since the signal‐to‐noise ratio was large enough, the noise was not an issue and its reduction dragged very little effort among the scientific community. After a steady working frequency doubling every year, the recent downscaling of the dimension has led to high stress and increased variability and, in turn, stagnation of performances of chips. There is no doubt that the increased noise is to blame for that standstill, even if other problems such as the doping concentration could be implicated as well. Nevertheless, the distinction between noise and signal has become critical and the noise issue must be tackled. A suppressed noise level should pave the way to once again lower biases leading to less heat, better reliability, and better performances.
\n
Noise is a fluctuation of a quantity that shifts back and forth with uncertainty. In electronics, it is generally noted as a fluctuation of the voltage or current around its mean value and is ascribed to stochastic events which find their origin at a microscopic level trough the discrete nature of the transport or the Brownian nature of the carrier. There are several types of noises such as thermal noise, shot noise, generation‐recombination noise, inter‐band noise, and low‐frequency noise. They are generally classified upon their origin. Among these, the thermal noise and low‐frequency noise are of paramount importance in MOSFETs, with the latter one being of most concern since its origin is still in debate and that its evaluation for a given technology is made extremely difficult. Even if the low‐frequency noise has been a limiting factor of performances for analog circuits for several years, it has recently become as well an issue for digital ones. Indeed, even though its limitation applies in the low range of frequency, it is up‐converted into phase noise leading to time domain instabilities and therefore problems in the high‐frequency range. Its reduction is therefore mandatory not only for analog but also for digital circuits.
\n
In Section 1, the theory of the low‐frequency noise in MOSFETs is briefly reviewed. While Sections 2 and 3 present new technologies to suppress it by the means of, respectively, silicide and damage free processes, Sections 4 and 5 introduce improved MOSFETs. Thus, the results regarding buried‐channel and accumulation‐mode MOSFETs are reported, respectively, in Sections 4 and 5.
\n
\n
\n
2. Low‐frequency noise in MOSFETs
\n
The MOSFET is a complex device composed of purely resistive parts surrounding the channel whose resistance is controlled by the bias applied at the gate electrode. It is therefore natural that the noise generated inside each region is propagating up to the source and the drain electrodes. However, the noise stemming from the channel is generally the most dominant one, even though the one coming from the surrounding areas can play an important role and can even take over as the main noise source [1]. Figure 1(a) shows a schematic of a MOSFET structure while Figure 2(b) represents its equivalent noise circuit. The source access resistance, the drain access resistance, and the channel are the three main regions the noise is coming from and the total measured noise SId at a given frequency can be written [2]\n
Figure 1.
Representation of (a) MOSFET and (b) its equivalent circuit noise.
Figure 2.
Normalized noise in a MOSFET. The several contributions of each noise sources have been reported with the non‐full lines.
where SId,ch, SIRs, and SIRd are the noises generated, respectively, inside the channel, the source Rs and drain Rd access resistances. Gm and gch are, respectively, the transconductance and conductance of the channel. The left‐hand side term is the contribution coming from the channel while the right‐hand side one is the contribution coming from the access resistances.
\n
It is worth noticing that SId can become equal to SId,ch meaning that the measured noise will be the noise of the channel, whereas even if the series resistances are the main noise source, it is their contribution that will be measured and not their pure noise. The noise in a resistive material such as the access resistances of a MOSFET is either thermal noise or 1/f noise at low frequencies [3]. This 1/f noise is known to originate from the fluctuations of the fundamental mobility and it follows the Hooge\'s empirical formulae [3]:\n
SI(f)I2=αHfNE2
\n
which represents the normalized noise of the current I while N is the number of carriers. αH is the Hooge parameter suggested to be constant and to reflect the quality of the crystal. After several decades of controversies between the Hooge theory and the Mc. Whorter one [4], the latter explaining the noise in terms of fluctuation of the carrier number, Mikoshiba [5] developed a new theory able to gather all data into a single model to explain the noise stemming from the channel.
\n
His theory has been confirmed afterward by several researchers and is now well accepted among the scientific community. Within this theory, the noise is given by [6]\n
SId(f)Id2=gm2Id2(1±αμeffCoxIdgm)2SVfb(f)E3
\n
where Cox is the gate oxide capacitance, gm is the transconductance, and μeff is the effective mobility of the carriers flowing inside the channel. This theory is known as the insulator and induced mobility fluctuations, and is ascribing the origin of the noise to the traps located inside the gate insulator near the interface. The constant dynamic capture and release of carriers from and to traps generate interfacial insulator charge variation and, in turn, fluctuation of the insulator charge. These fluctuations are equivalently generating flat band variations. These fluctuations are summarized on the left‐hand side term in Eq. (3) and are proportional to the flat band voltage fluctuations SVfb, expressed as [6]\n
SVfb(f)=λkBTq2NtWLCox2fE4
\n
with kB being the Boltzmann constant, q the electron charge, T the temperature, and λ the tunnel attenuation length of the traps in the insulator equal to 0.1 nm for SiO2. Nt is the interface trap density. In addition to the variation of the insulator charge, the capture and release mechanism is locally affecting the surface potential at the interface, resulting in a Coulomb interaction between the locally deformed potential surface and the carriers flowing inside the channel. The localized scattering rate will vary and will induce fluctuations of the mobility. These fluctuations are ascribed to the right‐hand side term in Eq. (3) and are related to the fluctuations of the insulator charge through the Coulomb parameter α, which measures the strength between both quantities. With nowadays miniaturization of the gate of the MOSFETs, two kinds of noises are at stake, although they are both explained in the frame of the previous theory. Indeed, it is obvious that in the case of very small gate size involving a very limited number of carriers, the removal or introduction of a single free carrier scared within the total number of free carriers involved in the conduction will have a tremendous impact on the current, making it jump between two or several levels like randomly disposed crenels. This type of noise is called random telegraph noise and is commonly an issue for sensors, especially optical ones [7]. However, when the number of traps is more significant and for a specific distribution of their energy within the bandgap, the resulting noise is commonly called 1/f or even Flicker noise and it follows a distribution, proportional to the inverse of the frequency when plotted as a function of the frequency [1]. This noise is an issue for analog circuits, and even for some digital ones, and will even impact at high frequency due to its conversion into phase noise. Finally, the noise in MOSFETs can be summarized as depicted in Figure 2. The noise measured at the electrode of a MOSFET is the sum of three terms: the fluctuation of the insulator charge, induced fluctuation of the mobility, and the contribution coming from the access resistances. It is worth mentioning that there is a fourth term, the cross‐correlation term between the fluctuation of the insulator charge and the induced mobility one even though it does not have a physical origin.
\n
\n
\n
3. Source and drain contacts
\n
When it comes to low‐frequency noise, the contribution stemming from the source and drain access series resistances is generally overlooked. This negligence can have tremendous impact on the noise analysis especially at high gate voltage where their contribution will mostly take over as the dominant noise.
\n
As a matter of fact, this is not the noise generated inside the source and drain access series resistances, which is at stake but their contribution. Rather than reducing the noise sources, reducing their contribution is more efficient and easier. Indeed, the reduction of the resistance of the source and drain access contacts does not only mean a better drivability and a better transconductance but can guarantee a reduction of the propagation of the noise generated by the noise sources inside the contacts and, in turn, a reduction of the contribution of the source and drain contact noise to the total measured noise [8]. The performance improvement of CMOS has become of paramount importance with scaled dimension. Much effort is being made to increase the carrier mobility by several means such as strained technology [9], different silicon orientation [10], or even different semiconductor [11]. The reduction of the source and drain electrode series resistances is another means to improve the drivability and silicide has already been used for such purposes. Nitride alloy silicide is widely used to lower the Schottky barrier height to either n+ or p+ silicon down with contact resistance as low as 2 × 10–9 Ω cm2 in the best case [12]. A new structure [13] and new processes [14] have been developed in order to further lower down the series resistances. Instead of using the same silicide for both p‐ and n‐MOSFETs, erbium has been selected to perfectly fit the requirement of n‐MOSFETs and palladium for the p‐MOSFETs. Additionally, tungsten metal stack above the thin silicide layer was introduced to reduce the sheet resistance and protect erbium from being oxidized. In order to confirm the above statement, two kinds of MOSFETs have been fabricated following the very same process flow, except during the source and drain contact fabrication stage. The source and drain contacts of the reference transistors have been fabricated with aluminum (Al), while erbium silicide associated with tungsten (ErSi2/W) has been used for the second set of transistors. The respective structures have been represented in Figure 3(a) and (b). While both wafers followed the same process flow until the contact lithography step, the ErSix/W wafer followed an advanced process entirely developed at New Industry Creation Hatchery Center (NICHe). In this advanced process, the wafer has been loaded in an N2 sealed cleaning chamber after a total room temperature five‐step cleaning, which has been followed by the dipping of the cleaned wafer in O3 dissolved ultra pure water in order to form a chemical oxide at the silicon surface. The removal of the chemical oxide has been carried out by diluted HF solution and the wafer has been then transferred in clustered sputter equipment, still in N2 ambient, where the formation of a thin film of erbium followed by the deposition of a tungsten capping layer has been done by Radio Frequency (RF) sputtering.
Figure 3.
Schematic of the structure of (a) reference contacts fabricated with aluminum (Al) and (b) salicide contacts fabricated with erbium silicide (ErSix) and tungsten (W) layer. Copyright 2011 The Japan Society of Applied Physics [8].
\n
The wafer has been then loaded in lamp annealing chamber to finally form ErSix. The wafer has been then brought back to the conventional process flow to finally form aluminum contacts. Electric characterization has been carried out and the main results are summarized in Figure 4(a) and (b). As expected, the drivability has been improved by a factor of 2 on account of silicide contacts [8]. Furthermore, the maximum of the transconductance also increased and confirms the interest of low‐resistivity source and drain contacts to enhance performances of electronic circuits. Noise measurements have been performed in the linear regime and for f = 10 Hz. The result is presented in Figure 5. When compared with the noise level of the reference transistor, the noise level of the transistor featuring ErSix/W contacts is greatly reduced for positive gate overdrive voltages while it remains equivalent for lower values. The same noise level below 0 V is explained by the fact that within this range of measurement the channel is exclusively contributing to the total noise and by the fact that both devices have indeed almost the same channel, since they followed the same process flow with regard to the fabrication of the gate stack. The noise modeling has been carried out and is reported with the lines in Figure 5. The modeling reveals that from 0 V the noise from the reference device moves away from the noise stemming from the channel. The contribution of the series resistances to the total noise is increasing and is ultimately taking over as the main contribution. However, the noise of the device featuring ErSi2/W contacts is following the curve depicting the noise stemming from the channel and starts to slightly move away at high voltages. The impact of the series resistances on the noise is barely visible. The use of low‐resistivity contacts allows a drastic reduction in the contribution of the series resistances to the total noise and let the channel be the sole source of noise over the entire measurement range [8]. About 10 times reduction of the access resistance has led to 100 times reduction of the noise level.
Figure 4.
(a) Drain current and (b) transconductance versus gate overdrive voltage for n‐MOSFETs featuring Al and ErSi2/W contacts. Copyright 2011 The Japan Society of Applied Physics [8].
Figure 5.
Normalized noise of n-MOSFETs with contacts fabricated with either aluminum(Al) or erbium silicide/tungsten(ErSi2/W). (W) layer. Copyright 2011 The Japan Society of Applied Physics [8].
\n
\n
\n
4. Radical oxidation
\n
The gate stack, especially, the gate insulator, is the most critical part of the MOSFET, mainly because of the defects that can appear during the fabrication and its tremendous impact on the device performance [15]. It is absolutely true these days that the need of always‐faster devices and smaller chips also promote the appearance of undesirable effects such as increase of variability and random telegraph noise. Thermal oxidation has been the way, since the establishment of the MOSFET, to fabricate the gate insulator and while the generated SiO2 was at the beginning of poor quality, leading to high S parameters, the process has greatly evolved since and the growth of quality oxide can be achieved now [15]. Unfortunately, the dimension of nowadays MOSFETs has reached a threshold where S parameter and Vth variability are a major issue, as well as, noise level prevision [16].
Figure 6.
Diagrams of (a) single shower plate and (b) double shower plate equipment based radicals formed by the low electron temperature microwave high‐density plasma.
\n
Thermal oxidation, from its intrinsic chemical reaction, cannot be optimized anymore and will always promote the formation of damage (either inside the gate stack or cap layers) and will partly invalidate the flattening process and, in turn, deteriorate the surface roughness of the wafer. Thus, new oxidation processes have been developed to avoid these issues. They are all based on radical oxidation rather than chemical reaction to form SiO2 [17]. The specificity of the damage‐free very low electron temperature microwave exited high‐density plasma is, as represented in Figure 6, that it can be employed for oxidation at low temperature, chemical vapor deposition, or even reactive ion etching. Very high quality gate insulator and reduced damages generally occurring during the etching and the fabrication of interconnect can be achieved thanks to this advanced process as shown in Figure 7 [15, 18, 19]. Contrary to the thermal oxidation, the radical oxidation has an oxidation rate that is almost regardless of the orientation of the silicon crystal on which the oxide is grown [20]. Additionally, the radical oxidation does not only help reduce the interface trap density but also help preserve and even improve the flatness of the Si/SiO2 interface. Two sets of p‐MOSFETs have been fabricated in our clean room. They followed almost the same process flow; however, they differed in such a way that the first set featuring a radically grown oxide has been processed exclusively with advanced plasma equipment, while the second set has been processed using conventional processes, among which the thermal oxidation process.
\n
Figure 7.
Vth distributions of p‐MOSFETs fabricated by applying (a) conventional plasma processes and (b) radial line slot antenna plasma processes plotted for antenna ratio of 23, 100, 1000, and 10,000.
\n
Figure 8.
Normalized noise of p‐MOSFETs with a gate oxide fabricated by either thermal or plasma oxidation as a function of the gate overdrive voltage. The modeling, reported with the lines, refers exclusively to the transistor with a gate oxide thermally grown. Copyright 2011 The Japan Society of Applied Physics [8].
\n
Noise measurements have been performed in the linear and saturated region and for different gate sizes. The noise analysis has been carried out at 10 Hz. Results are presented in Figure 8, and they clearly indicate that the p‐MOSFET with a gate oxide fabricated by radical oxidation has a lower noise level than when the thermal oxidation process is used used, with a maximal reduction of over a decade. As expected, the noise stemming from series resistances and the noise from the channel are both contributing to the total noise, with the latter one being ascribed to the insulator charge and induced mobility fluctuations. In order to understand the origin of the noise reduction, the modeling of the p‐MOSFETs, featuring a gate oxide, fabricated by radical oxidation has been carried out. The result is reported in Figure 9 and it revealed an unexpected behavior, i.e., no induced mobility fluctuations. The contribution of the series resistances added to the sole insulator charge fluctuations has been enough to model the total noise. Even though the trapping/release mechanism at the origin of the 1/f noise induces fluctuation of the mobility, these fluctuations are, in the present case, too small to be visible when compared to the other fluctuations. The interface trap density has been extracted for both sets of devices and revealed a three‐time reduction in favor of the transistors fabricated using plasma processes with Nd = 2 × 1016 cm–3 eV–1, testifying the high integrity of the oxide when fabricated by radical oxidation.
\n
Figure 9.
Normalized noise of p‐MOSFETs with a gate oxide fabricated by plasma oxidation as a function of the gate overdrive voltage. Copyright 2011 The Japan Society of Applied Physics [8].
\n
\n
\n
5. Buried‐channel MOSFETs
\n
\n
5.1. Structure of buried‐channel MOSFET
\n
The low‐frequency noise, such as 1/f noise and random telegraph noise, is basically caused by the defects at the gate insulator and silicon interface in MOSFETs. To reduce the low‐frequency noise, the number of defects or the influence of the defects has to be reduced. Here, the channel of the buried‐channel MOSFETs is separated from the gate insulator/Si interface, and then the carriers in the channel are hard to be influenced by the defects at the interface. Usually, the buried‐channel MOSFETs are characterized as high mobility but weak short channel Field-Effect-Transistor (FET) [21–23] because the carriers flow through the bulk. In this case, the separated channel location of buried‐channel MOSFETs is very important for reducing the low‐frequency noise. Figure 10 shows the schematic illustration of the buried‐channel n‐MOSFET. The buried layer was formed by the ion implantation at the Vth adjustment process [24, 25]. Figure 11 shows the band diagram of the conventional surface channel (a) and the buried‐channel MOSFETs (b), respectively [25]. The buried layer depth was set as 170 nm from the SiO2/Si interface, and the channel was appeared at around 30 nm from the SiO2/Si interface at the bias conditions of back bias (VBS) =1.5 V and drain current (IDS) =100 nA for a gate length (L) of 0.22 μm and a gate width (W) of 0.28 μm MOSFETs.
Figure 10.
Schematic illustration of the buried‐channel MOSFET.
Figure 11.
Diagrams of surface channel (a) and buried‐channel MOSFETs. The bias condition was set at VBS = 1.5 V and IDS = 100 nA.
\n
\n
\n
5.2. Low‐frequency noise characteristics
\n
Figure 12 shows the 1/f noise characteristics for the surface channel and buried‐channel MOSFETs. Five samples were measured for each MOSFET. The size (W/L) of MOSFETs was 10 μm/5 μm and bias conditions were set as VDS = 1.5 V, VBS = 0 V, IDS = 1, 10, and 100 μA. SId increases as the drain current increasing for both MOSFETs. The noise power SId of the surface channel MOSFETs is proportional to 1/f. In contrast, SId of the buried‐channel MOSFETs for the low Id cases is not proportional to 1/f, because the noise level was smaller than the floor noise of the measurement system. For the same drain current Id, the noise power of the buried‐channel MOSFETs are less than that of the surface channel MOSFETs, especially their differences are observed for the low drain current cases. In this experiment, the gate voltage controlled the drain current. When the gate voltage increases, the distance between the channel and the interface decreases, and then it influences the defects. This indicates that the noise reduction of buried channel is very effective for the low gate voltage conditions.
Figure 12.
1/f noise characteristics of (a) surface channel and (b) buried‐channel MOSFETs.
\n
\n
Figure 13.
Distributions of (a) Vth and (b) Qch with 65536 MOSFETs for the buried‐ and surface channel MOSFETs.
\n
\n
5.3. Vth variability
\n
In the previous section, it is described that the noise can be reduced by introducing the buried‐channel MOSFETs because the channel is separated from the SiO2/Si interface. However, this means the gate capacitance becomes lower compared to the surface channel MOSFETs. Then, the Vth control becomes difficult compared with the surface channel. Figure 13 shows distributions of (a) Vth and (b) the channel charge (Qch) with 65536 MOSFETs for the buried‐ and surface channel MOSFETs [24]. These distributions are measured by the array test circuit, which can measure the Vth variation and the random telegraph signal for many MOSFETs (>1 million MOSFETs) during very short time (<1 s) [26–29]. The horizontal axis of both the graphs shows the difference values between the average values of all MOSFETs (65536 MOSFETs). The Vth variability of the buried‐channel MOSFET is larger than that the surface channel MOSFETs as shown in Figure 13(a). It is considered that the gate capacitance of buried channel is smaller than that of the surface channel. Then, the horizontal axis is converted from Vth to Qch by using the gate‐channel capacitance. Almost the same distributions are observed, and then the variability is caused by the small capacitance between the gate and the channel. Moreover, it is noticed that the noise increases by the excess capacitance decrease with the other transistor characteristics degradation, such as short channel effect and subthreshold swing degradation [22, 30].
\n\n
\n
\n
\n
6. Accumulation‐mode MOSFETs
\n
The separation between the interface and the channel is effective in reducing the noise in buried‐channel MOSFETs; however, the controllability of Vth is worse than conventional MOSFETs because the gate capacitance is reduced. Then the introduction of Silicon-on-Insulator (SOI) wafer and a new structure can solve this issue [31, 32]. The so‐called accumulation‐mode MOSFET has been developed keeping this in mind. As depicted in Figure 14, the accumulation‐mode MOSFETs differ from MOSFETs in such a way that the type of the SOI layer is the same as that of the contact. Additionally, the type of polysilicon must also be adjusted as required. Although the working of the conventional inversion‐mode MOSFETs is based on the generation of an inversion layer made of the minority carrier, the accumulation‐mode one is making use of an accumulation layer composed of majority carrier. Actually, the accumulation‐mode MOSFET without bias is at first on the off‐state since the SOI layer is completely depleted. When a bias is applied at the gate, a thin conductive layer of majority carrier is first generated at the back interface between the Buried Oxide (BOX) and the SOI. Then accumulation‐mode MOSFETs become on the on‐state. A current at the back interface flows from the source to the drain. A further increase in the bias makes this layer disappear and makes a short portion of the originally depleted SOI layer become neutral. A bulk current is generated on the BOX side. This current continues to increase with the expansion of the neutral region (due to the shrinking of the depleted region) inside the SOI until the bias applied at the gate reaches the flat‐band voltage.
Figure 14.
Schematic representation of (a) inversion‐mode and (b) accumulation‐mode p‐MOSFETs.
\n
The current generated inside the accumulation layer then adds to the bulk current. Therefore, in addition to, among other things, having an improved reliability [33] and being immune to radiation effects [34], they also have a better drivability than inversion‐mode MOSFETs since the total current is the sum of those generated inside the SOI and the accumulation layer [35]. When the bulk current has reached its maximum, corresponding to the SOI completely neutral, the majority carrier accumulates at the front interface between the gate insulator and the SOI. Accumulation‐mode fully depleted SOI MOSFETs have been fabricated on Si(100) surface to investigate the noise characteristics. The SOI layer impurity has been adjusted by ion implantation to 2 × 1017 cm–3. The thickness of the SOI layer has been reduced down to 50 nm. In order to avoid the increase of noise due to the defects at the front interface and the impact of the surface roughness of the interface, the radical oxidation [17] added to the five‐step‐cleaning process [20] has been repeated four times until reaching a flattened interface with a roughness Ra of 0.08 nm. A 7‐nm gate oxide has been formed by radical oxidation using a low electron temperature microwave high‐density plasma process at 400°C. As expected and as shown in Figure 15, the accumulation‐mode MOSFETs feature a better drivability than those of the inversion‐mode MOSFETs. The better drivability does not only owe to two distinctive currents but also from the higher carrier mobility thanks to a lower transversal electric field at the front interface [35].
Figure 15.
Drivability of accumulation‐ and inversion‐mode p‐MOSFETs.
\n
The noise of the inversion‐ and accumulation‐mode MOSFETs has been reported in Figure 16. Even though their noise level is similar at low gate overdrive voltage, the superiority of the accumulation‐mode MOSFET over the inversion mode one becomes clear for voltage over 0 V. A gap of more than 1 decade is achieved at the best. While the noise of the inversion‐mode MOSFET can be ascribed to the interface traps [6] and series resistances at high bias [3], the origin of the noise for the accumulation‐mode one must be investigated with care. Indeed, as discussed earlier, three conduction mechanisms generate the current and are therefore generating their own noise. The modeling of each noise and finally the total modeled noise have been reported with lines in Figure 16. The noise stemming from the front and back interfaces is originating from the interface traps [5], like for the inversion‐mode MOSFET while the noise from the SOI layer and access resistances is explained in terms of fundamental fluctuations of the mobility of the Hooge model [3]. Contrary to the inversion‐mode MOSFET, the front interface does not contribute to the total noise. The lower noise can be attributed to a change in the origin of the noise stemming from the channel, with the SOI region becoming the main contributor to the noise with regard to the channel and a significant shift toward the high gate voltage to turn the accumulation layer on. It is worth mentioning that the advantage of the accumulation‐mode MOSFET is effective for high doping concentration; otherwise, the accumulation layer will act like an inversion one [36] since it implies no contribution from either the back interface or the SOI layer to the total current.
Figure 16.
Normalized noise of accumulation‐ and inversion‐mode p‐MOSFETs. Lines refer to the modeling of the noise of the sole accumulation‐mode device and represent the noise generated by each region.
\n
\n
\n
7. Conclusion
\n
In this chapter, we reviewed several ways to suppress the low‐frequency noise of MOSFETs and, in turn, the noise of analog and digital circuits. One of the most underrated approaches is to optimize the contacts and interconnects by the means of low‐resistive materials, so that their contribution to the total noise can be drastically reduced. It has also been shown that a great deal must be paid to the fabrication processes. Indeed, the use of processes demonstrating very low damage generation at all the stages of fabrication can lead to MOSFETs with better performances and especially reduced noise level due to a reduction of induced defects located at the gate stack and its surroundings. Additionally, these low‐defect processes based on the damage‐free, low‐temperature, high‐density plasma technology achieved a further reduction by means of the disappearance of one component of the low‐frequency noise, the induced mobility fluctuations one, bringing the noise of MOSFETs to the sole fluctuations of the insulator charges. Focusing on a different electronic structure can also achieve low‐noise MOSFETs. For example, minimizing the interaction carrier‐traps by moving away the channel – so that fewer traps are activated and less variations of the insulator charge are generated – can achieve a reduced noise. Unfortunately, this reduction is obtained at the cost of a degradation of the electrical performances. So, the most promising structure to suppress noise is in the form of the accumulation‐mode MOSFETs. Indeed, in addition to offer reduced low‐frequency noise when compared to conventional MOSFETs, their electrical performances are greatly improved. These devices obviously feature various assets, which should consequently pave the road for a new era of very low noise and high‐performance MOSFETs and bring microelectronic manufacturers back to the realization of highly performances and high‐speed analog and digital circuits.
New Industry Creation Hatchery Center, Tohoku University, Sendai, Japan
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1. Introduction
Nowadays, the global navigation satellite systems (GNSSs) are widely used in many human activities, particularly for geodetic positioning and navigation, as well for atmospheric monitoring in scientific research. The GNSS systems have been used to obtain the ionospheric total electron content (TEC) often in near real-time and in global scale because the networks ground-based receivers cover large geographic areas. In the last decades, TEC information has given a great advance in the understanding of the ionospheric structuring and improving our forecasting capacity, which has revolutionized the ionospheric studies. Particularly, the behavior of the ionosphere during geomagnetic disturbed periods has been extensively investigated, showing that F-region response to geomagnetic storms is very complex in space and time, but a general morphology and physical processes have been defined (e.g., [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]; and references therein).
The ionospheric knowledge has been used to improve the GNSS positional accuracy, which can be strongly degraded under severe atmospheric disturbances because they can suddenly change the satellite geometry that is essential for geodetic position, in particular for kinematic precise point position (PPP), and are a limiting factor to achieve centimeter accuracy (e.g., [14, 15, 16]). The main atmospheric disturbances that affect the GNSS quality signals are the ionospheric steep density gradients, signatures of irregularities of the electron density distribution. Special attention has been given to the ionospheric irregularities investigation, which can vary on a wide range of scale sizes, from centimeters to hundreds of kilometers. The formation and the temporal/spatial evolution of these irregularities affect the propagation of radio signals, causing cycle slips and loss of lock on GNSS receivers and degrading the performance of radio communication and navigation systems [17, 18]. At L-band, amplitude scintillations are due to irregularities with a scale size from hundreds of meters down to tens of meters (according to Fresnel’s filtering mechanism), while phase scintillations are caused by structures from a few hundred meters to several kilometers (see, e.g., [18]). In addition, in your way down to the ground, the radio signals could interfere with itself due small changes in their way along the scattered ray paths, resulting in a sort of “space multipath” [19]. The overall of these atmospheric influences can produce rapid fluctuations in the amplitude and phase of GNSS signals, which are known as ionospheric scintillations.
The investigation of scintillations has shown that their activity is stronger at latitudes within the equatorial ionization anomaly (EIA), particularly during post-sunset hours when plasma bubbles are formed in the equatorial F-region driven by the Rayleigh-Taylor instability [20, 21]. Recently, the formation of ionospheric irregularities and plasma bubbles at equatorial region also have shown that they can be driven by gravity waves [22, 23]. The scintillations have been extensively studied at different longitudinal sectors and latitudes, showing a strong dependence on magnetic local time, season, magnetic activity, solar cycle, and geographic location (e.g., [6, 8, 9, 10, 11, 12, 13, 19, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36]; and references therein).
This chapter provides the characterization of ionospheric scintillations observed with GNSS networks in the South American sector (e.g., [34, 35, 37, 38, 39, 40]). The chapter is organized as follows: Section 2 presents the ionospheric variability, Section 3 presents the ionospheric scintillation indices and climatology in South American sector, Section 4 presents the impact of scintillations in a new method for high accurate single frequency precise point positioning (PPP), and finally a discussion section.
2. Ionospheric variability
The solar heating throughout the atmosphere causes large-scale variations associated with diurnal and semidiurnal tides in the thermosphere [41], while the extreme ultraviolet radiation (EUV) forms the ionosphere. The physical processes in the thermosphere are primarily driven by solar and magnetic disturbances [42], which influence the ionospheric production and recombination, as well transport and frictional heating. The ionospheric conditions have been studied for decades, and particularly there is a good understanding of F-region conditions associated with seasonal, solar cycle, and level of magnetic activity variations. Despite that the predictive capability of its condition is still very poor because the variations appear over a wide range of timescales going from minutes to several days and also depend on the magnetic local time and geographic location. Even during quiet times, that is, under undisturbed geomagnetic conditions, significant ionospheric variability is observed. The low latitude ionosphere is controlled by electrodynamic plasma (E × B) drifts driven by thermospheric neutral winds (e.g., [43, 44, 45]). The zonal electric fields drive strong daytime E-region eastward currents in the equatorial region, which form two narrow latitudinal bands centered at the dip equator that are called equatorial electrojet (e.g., [46]). The zonal electric fields drive equatorial E and F region vertical plasma drifts (e.g., [47]) that lift the ionospheric plasma at the dip equator, which goes down following the magnetic field lines leading density enhancements located at ~±10–20° from the magnetic equator. The overall process, the plasma lifting followed by their diffusion along the geomagnetic field lines and the formation of the two density maxima away from the equator, is called “fountain effect,” and the denser regions are called the crests of the equatorial ionospheric (or ionization) anomaly (EIA) [48]. The thermospheric winds are highly variable because they are driven by changes in the global tidal forcing, and effects of irregular winds, planetary and gravity waves. The planetary waves and tides have been identified as relevant factors affecting the electrodynamics of the lower thermosphere (e.g., [49, 50, 51, 52, 53, 54, 55]).
The ionospheric F-region often becomes turbulent and develops electron density irregularities during post-sunset hours [56]. During the day, the electrical field is eastward and it reverses to the west after sunset, but during sunset an enhanced eastward electric field develops, the so-called pre-reversal enhancement (PRE) [44, 57, 58]. The PRE drives an upward vertical plasma drift at magnetic equatorial region, and the bottom of the F-region becomes unstable to the Rayleigh-Taylor instability [59], developing large-scale plasma depletions (plasma bubbles). These bubbles ascend upwards over the magnetic equator, causing a redistribution of ionization similar to the fountain effect. The latitudinal extension of the plasma bubbles is defined by the upper height limit they reach in their rise up above the magnetic equator [60] and can intersect the crests of the EIA, where the steeper density gradients on the edges of the plasma bubbles favor the generation of smaller scale irregularities [56, 61, 62]. The plasma bubbles practically disappear after local midnight and are most intense during the equinoctial months and during the solar maximum years [63, 64]. These conditions favor the scintillations to occur most frequent and severe around the EIA crests, in particular after sunset due to the generation of irregularities caused by the intersection of the plasma bubbles with the regions of larger background electron density.
The ionosphere can be strongly disturbed during geomagnetic storm-time periods. These storms are terrestrial magnetospheric perturbations caused by the impact of interplanetary coronal mass ejections (ICMEs), and corotating interaction regions associated with high-speed streams (HSS), which are the most geo-effective solar wind phenomena. The coupling process involving the solar wind, the interplanetary magnetic field (IMF) and the magnetosphere strongly affects the high latitude ionospheric electrodynamics. The magnetosphere compression during geomagnetic storms induces intense electric fields and increases its convection. During these processes, the interplanetary electric field (IEF) is mapped along the magnetic field lines to the high latitude ionosphere, but can also propagate across them and promptly appears in the low latitude ionosphere, when it is called of prompt penetration electric field (PPEF). The effect of PPEF at the equatorial ionosphere has been observed during the first hours of the main phase of geomagnetic storms, suggesting a long-duration penetration of interplanetary electric field to the low-latitude ionosphere without shielding (e.g., [5, 65, 66, 67, 68]). The equatorial ionosphere under the effect of the PPEFs is convected upward in the dayside and downward in the night side [66]. The PPEFs are stronger than the fields associated with the normal fountain effect resulting in a higher elevation of the equatorial plasma [5], and consequently the crests of the EIA departs more from magnetic equator and can reach middle latitudes (~±20–30°). At high latitudes, the precipitation of energetic particles enhances ionospheric conductivities and generates intense electrical currents in the auroral zone [3]. The dissipation of these currents by the Joule effect heats the local plasma that expands, changing the lower thermospheric composition and driving large-scale neutral winds [3, 4, 42]. Thus, major geomagnetic storms results in a large-scale ionospheric thermal plasma redistribution involving all latitudes from the equatorial through the polar region. Particularly F2-region shows very complicated spatial and temporal behavior (e.g., [9]), but a general morphology and physical processes have been established (e.g., [1, 2, 3, 4, 7, 9]). F2-region variations during geomagnetic disturbed periods are called ionospheric storms and are detected as an increase (positive) or depletion (negative) of electron density associated with electrodynamics processes or neutral composition changes (e.g., [4]), respectively. Their morphology is a function of the amount of energy inputted in the high latitude during the main phase of geomagnetic storm [69], as well of the station latitude and longitude, local time of storm onset, storm time and season.
3. Ionospheric scintillations
3.1. Scintillation indices
Scintillations are rapid fluctuations in the amplitude and phase of GNSS signals produced by the ionospheric irregularities, which are responsible by the refraction and diffraction of trans-ionospheric signals [20, 70].
The ionospheric scintillations are evaluated from 60 s amplitude (S4) and phase scintillation (Phi60) indices, which give information about intermediate (around hundreds of meters) and large (above hundreds of meters)-scale size irregularities, respectively. The scintillation indices are obtained by using GNSS dual-frequency receivers recording data at a high data sampling rate of 50 Hz, which also compute the total electron content values.
The S4 index can be interpreted as the standard deviation of the received power (C/NO) normalized by its mean value and the Phi60 index is the standard deviation (in radians) of the carrier phase computed over 60 s time interval. The indices are obtained as Eqs. (1) and (2) [71].
S4=<I2>−<I>2<I>2,E1
Phi60=<∅2>−<∅>2,E2
where <> denotes 60 s average, I is the signal intensity and ∅ the signal phase at GPS L1 frequency (1.575 GHz) sampled at 20 ms (50 Hz).
The S4 and Phi60 indices are used to classify ionospheric scintillation severity, which can be separated in three categories: strong, moderate and weak scintillations, for example, as shown in Table 1.
Class
Index value
Weak
0.1 < S4 < 0.25 or 0.1 < Phi60 < 0.25
Moderate
0.25 < S4 < 0.7 or 0.25 < Phi60 < 0.7
Strong
S4 > 0.7 or Phi60 > 0.7
Table 1.
Classification of the ionospheric scintillation severity.
3.2. Ionospheric scintillation climatology in south American sector
The morphology of the Earth magnetic field favors the occurrence of strong scintillations at high latitudes, and intense at equatorial region between about 20°N and 20°S magnetic latitudes [20, 72]. Particularly in the South American sector, the F-region irregularities present peculiarities due to the large longitudinal variation in the magnetic declination angle [38, 73, 74], as well by the influence of the South American Magnetic Anomaly (SAMA). The SAMA is the region on the Earth where the magnetic field has the lowest intensity values, allowing enhancement of energetic particle precipitation into the atmosphere [75]. The enhanced ionization in the SAMA region produced by the particle precipitation is a regular feature, which modifies the quiet ionospheric physical conditions increasing the F-layer vertical drift over the eastern sector as compared to the western sector of South America, which can be drastically modified during magnetospheric disturbances (e.g., [75]; and references therein).
The investigation in the South America sector has been improved in the last decades after using GNSS receivers networks dedicated to monitor ionospheric scintillations. Today, there are three GNSS networks, the GPS Low-Latitude Ionospheric Sensor Network (LISN) that is operating since November 2011 with an array of 45 receivers [76], 15 of them over the Brazilian territory, where they are complimented with one array of 12 GPS Ionospheric Scintillation Monitoring Receivers (ISMR) of the GPS Scintillation Monitors network (SCINTMON) [38] and other with 10 ISMR of the Concept for Ionospheric Scintillation Mitigation for Professional GNSS in Latin America and Countering GNSS high Accuracy applications Limitations due to Ionospheric disturbances in Brazil (CIGALA/CALIBRA) project [77]. At high latitude, these networks are complimented with GPS ionospheric scintillation and total electron content (TEC) monitor receivers (GISTM) that covers a large area from sub-equatorial Latin America to the South Pole [71].
3.2.1. Quiet geomagnetic conditions
Ionospheric irregularities commonly appear in the regions of enhanced or depleted electron density. These regions are associated with the crests of the EIA anomaly located at latitudes ~15–20° from the magnetic equator, where strong scintillations have been observed particularly during sunset hours. Before GNSS era, Aarons [20] using ionosondes and VHF systems showed the scintillation intensities, produced by smaller scale ionospheric irregularities, were stronger in the EIA crests after sunset hours under the influence of plasma bubbles. A comprehensive study of the occurrence of irregularities over the south EIA crest in Brazil during two decades was reported by Sobral et al. [21], which shows the plasma bubbles occurrence has a broad maximum around summer months (from September to April), with a significant increase from low to high solar activity levels during the equinoctial months of March-April and September-October. De Paula et al. [38], using GPS L1-band receivers in the Brazilian territory, reported the characteristics of small-scale irregularities that produced strong scintillations in the post-sunset equatorial ionosphere from 1997 to 2002, the ascending phase of the solar cycle 23. They reported that the ionospheric irregularities are stronger in the southern crest of the EIA, and present a seasonal variation occurring predominantly from September to March during magnetic quiet periods, being more intense during December (local summer). They also show a large longitudinal variation in the South American sector showing that the irregularities are most intense in the EIA crest in Brazilian sector than over Argentinean sector, which is attributed to the large longitudinal variation of magnetic declination in this sector. During quiet magnetic periods, the irregularities occur in the sunset-midnight local time sector while during magnetic storms their occurrence can extend to the midnight-sunrise sector. Akala et al. [39] using a chain of GPS receivers along the western longitude sector of South America, during different levels of solar activity, also shows the scintillations occur predominantly at post-sunset hours and decay before or around local midnight, with stronger activity and longer durations in the months of March and January, which means in the March Equinox and December solstice; and in particular the station near northern crest of the EIA recorded the highest occurrences of scintillation especially during periods of high solar activity.
Spogli et al. [24], using GISTM receivers located between South America, South Atlantic Ocean and Antarctica, defined crucial areas in the ionosphere where the probability of scintillation occurrences is higher. These areas were called ionospheric scintillation “hot-spots” and were defined using a climatological representation given by the Ground Based Scintillation Climatology (GBSC) technique [19]. They showed that there are two main hot-spots over South America, first one associated with the post-sunset (POST) hours at low latitudes located in the magnetic latitude (MLAT) range 15–25°S and magnetic local time (MLT) between 20 and 24 h, and another one associated with particle precipitation region (SAMA) nearby SAMA region located in the MLAT range 22–24°S and MLT between 0 and 24 h. At high latitudes, they identified three scintillation hot spots, one associated with particle precipitation region in the polar cusp (CUSP, MLAT: 74–82°S and MLT: 10–14 h), other associated with place where the irregularities are induced by reconnection from the magnetotail (MLAT: 68–82°S, MLT: 20–4 h), and other one associated with polar cap patches (PATC, MLAT: 82–90°S, MLT: 0–24 h). The POST hot spot shows scintillation intensifications in March and November, in agreement with the intensification of pre-reversal at equinoxes (e.g., [78]). The hot-spot intensification is stronger in November probably due to the superposition effects associated with the spring equinox and the local summer. The SAMA hot spot also shows one stronger enhancement in November similarly the observed at POST hot spot. They also confirm that in the Brazilian longitudes, the irregularities are more intense in the September (spring) equinox and summer months [38]. At high latitude the two main hot spots identified as CUSP and PATC show enhancements at equinoxes that are attributed to direct particle precipitation.
Muella et al. [34] investigated the scintillation occurrence from 2002 to 2006, during the descending phase of the 23rd solar cycle, at two sites located in the inner regions of the northern and southern crests of the equatorial ionization anomaly in the Brazilian sector. They showed that the scintillation occurrences during sunset hours present a north-south asymmetry, being ~10% higher over the southern EIA crest than over northern one during solar maximum. This asymmetry was considered to be a possible influence of the SAMA on the scintillation activity. The scintillation occurrence also showed a broad minimum in June and maximum in December over both crests. On a recent investigation of scintillation occurrence at Cachoeira Paulista near the south EIA crest, covering almost the two last solar cycles (1998–2014), Muella et al. [37] showed that the maximum occurrence of scintillations observed during the peak of 23rd solar cycle was 20% higher than that one observed for the 24th, which was the weakest cycle in the last century. This behavior can be attributed to the scintillation intensity dependence on the electron density gradients and the thickness of irregularity layer, which are driven by the intensity of the solar extreme ultraviolet radiation (EUV). In addition, the fewer occurrences of scintillation in the maximum of the 24th solar cycle at Cachoeira Paulista could also be associated with the secular variation in the dip latitude, which changed ~3° in south direction from 1997 to 2014.These results on the long-term trend analysis and climatology of scintillations at the EIA region are shown in Figure 1. The colored contours in the upper panel of Figure 1 show the nocturnal occurrence statistics of scintillation from 1998 to 2014 for S4 > 0.2 as function of universal time (UT = LT + 3 h) and the mean F10.7 cm solar flux index. For the type of the GPS receiver used to measure scintillations, the threshold of S4> 0.2 can be considered above the level of multipath and noise effects, which may produce very weak scintillations (S4< 0.2). The middle panel shows the occurrence for the strongest levels of scintillations (threshold of S4> 0.5), whereas the color scale bar indicates the percentage of occurrence used in the plots of scintillation statistics. The monthly mean variation of the F10.7 cm solar flux is shown in the lower panel and depicts its changes from the ascending phase of solar cycle 23rd to the maximum of solar cycle 24th. Figure 1 reveals that the patches of larger occurrence of scintillations are observed from 23:00 to 04:00 UT between the months of September and March and mainly around the solar maximum years.
Figure 1.
Occurrence climatology of the GPS L1-frequency scintillation (1998–2014) at Cachoeira Paulista for two threshold levels of the S4 amplitude scintillation index as function of universal time (UT = LT + 3 h) and the mean solar radio flux in 10.7 cm (F10.7 index). The upper and middle panels denote the nocturnal occurrence climatology for the levels of S4 > 0.2 and S4 > 0.5, respectively. The colored bar indicates the percentage of scintillation occurrence used in the plots. The monthly mean variation of the F10.7 cm solar flux is shown in the bottom panel to depict the changes in the solar cycles. [after Muella et al. [37]. Reproduced with permission of the Copernicus publications on behalf of the European geoscience union].
The climatology of the onset time of ionospheric scintillations near the southern crest of EIA over Brazilian territory, covering a period between solar cycles 23 and 24, showed that their start time is about 40 min earlier in the months of November and December when compared to January and February, suggesting an association with the ionospheric pre-reversal vertical drift (PRVD) magnitude and time [79].
An investigation of the equatorial scintillations over São Luis (2.33°S, 44.21°W, dip latitude 1.3°S) was done by Muella et al. [35] during different solar activity levels of the 23rd solar cycle (1999–2006). The study showed the scintillations occurred more frequently during the years of high solar activity, but strong scintillation variability was also observed during the descending phase of the solar cycle. The scintillations occurred predominantly during pre-midnight hours with a broad maximum in the summer. They observed a weak level of scintillations all over the year, however, during the winter months near the years of solar maximum, some stronger levels of scintillations were observed at comparable rate with the weak scintillations.
The ionospheric scintillations are driven by zonal drift of the irregularities, so the investigation of the spatial and temporal variations of the irregularities have been done in the last decades. The study of the zonal drift driven scintillations in the South American sector has shown that: a latitudinal gradient in the irregularity zonal velocities is associated with the vertical shear of the zonal drift in the topside equatorial ionosphere [80]; at two magnetic conjugate sites over Brazilian territory, the magnitude of the zonal velocities in the site inside the SAMA region was ~12% larger than in the conjugate one [81]; during nighttime, there is a strong correlation between neutral winds and scintillation drifts near magnetic equator [82]; the irregularity of the zonal drifts shows a negative gradient with increasing geomagnetic latitude [83]; and that the magnitude of the zonal velocities might be reduced at the inner regions of the EIA due to the latitudinal variation in the ion drag force [35]. The nighttime zonal drift velocities of the ionospheric irregularities increase in association with increasing EUV solar radiation [37, 84, 85], which can be produced by the fact that in years of higher solar activity, the thermospheric zonal wind velocities are higher enhancing the solar thermal tide [86].
3.2.2. Disturbed geomagnetic conditions
The ionospheric electrodynamics conditions depend on magnetosphere-ionosphere-thermosphere system, which can be strongly disturbed during geomagnetic storms. During geomagnetic storms, the magnetosphere is compressed inducing intense electric fields and increasing the magnetospheric convection. The strongest geomagnetic storms are mainly produced by the impact of solar wind disturbances associated with geoeffective solar coronal mass ejections (CMEs) and coronal hole solar high speed streams (HSS) on the magnetosphere, which results in a highly inhomogeneous ionosphere, producing steep electron density gradients and irregularities. The ionospheric electron density distribution changes as a function of the solar wind input energy in the high latitude upper atmosphere, which occurs during the main phase of the geomagnetic storms [69].
The spatial and temporal variations of F2-region during geomagnetic storms are called ionospheric storms, and their morphology depends on the site location, local time of geomagnetic storm onset, storm time and season. Despite the very complex ionospheric behavior during disturbed periods, there is a general understanding about its morphology and physical processes (e.g., [1, 2, 3, 4, 7, 9]). The negative phase of ionospheric storm is attributed to changes in the thermosphere at middle and high latitudes due to the heating in the auroral zone, mainly by Joule dissipation [87], occurring at all seasons but in winter. In contrast, the positive phase occurs at middle and low latitudes mainly in winter season and involves more complex physical processes associated with uplifting due vertical drift, plasma fluxes from the plasma sphere, and downwelling produced by storm-induced thermosphere circulation at low latitudes (e.g., [3, 7, 9]). The vertical drift during daytime is controlled by equatorward winds at middle latitudes during the winter, and at equatorial region is driven by the EIA anomaly in association with prompt penetration electric field effect (PPEF) [5], resulting in an enhancement of the electron concentration because the photoionization is still operating (e.g., [3, 88]).
At middle latitudes, TEC enhancements are observed during the main phase of geomagnetic storms in the dusk sector, which are called storm-enhanced density (SED), and have been associated with large-scale redistribution of ionospheric plasma, covering a large extension from equatorial to polar region [89]. This phenomenon has been observed during the first hours of the main phase storm when the fountain effect at the equatorial region is reinforced by the PPEF, moving EIA crests from low to middle latitudes. The middle latitude EIA crest at dusk sector, under electrodynamic processes, has its plasma redistributed in longitude and latitude generating plumes of SED [90], which can be transported into dayside cusp where enter the polar cap and form the called tongue of ionization (TOI; [8, 10, 11, 12, 13, 24, 89]; and references there in) at polar region. The ionospheric plasma redistribution during geomagnetic storms is a function of their intensity, magnetic local time, storm time, latitude and season.
The ionospheric regions affected by impact of geomagnetic storms show a strong intensification of scintillation occurrence. At high and middle latitudes, these regions are the night side auroral oval due to the particle precipitation events [12, 91, 92], the cusp on the dayside in association with SED, and the polar cap in association with TOI, while at equatorial latitudes the scintillations are associated with regions under the influence of the EIA anomaly. Similarly, the ionospheric storms, the occurrence of scintillations during geomagnetic disturbed periods also are function of magnetic local time, season, magnetic activity, solar cycle, and geographic location [12, 13, 19, 25, 26]. The ionospheric irregularities can be inhibited during magnetic storms with main phase occurring during daylight hours, but can be intensified during any season when main phase storm coincides with the hours of the pre-reversal electric field is maximum (e.g., [75]). De Paula et al. [38] from an investigation of small scale irregularities (~400 m) at equatorial and low latitudes over Brazilian territory obtained that during geomagnetic storms they can occur at any epoch of the year, present largest intensities in the south EIA crest, could extend from sunset-midnight to midnight-sunrise sector during some storms, are enhanced during PPEF occurring during post sunset hours, and can be suppressed during daytime main phase storm under the disturbance dynamo effect. In association with geomagnetic storms, the large-scale irregularities (few km) have shown a seasonal variability [93]. On the other hand, an investigation of the F-region under the impact of the geomagnetic storm occurred on June 2013, from equatorial to middle latitudes in both hemispheres over American sector, showed that the ionospheric irregularities were observed confined in the equatorial region before and during the storm, which shows this storm did not affect the generation or suppression of irregularities [94].
An investigation of the 26–27 September 2011 moderately intense geomagnetic storm impact in the ionosphere at middle and high latitudes in the South American sector showed that during its dayside main phase two SEDs were observed at middle latitudes [13]. These SEDs were attributed to a combination of processes, including the PPEF effect from low latitudes during a couple of hours just after the storm onset, and dominated by the disturbance dynamo effect from high latitudes during its evolution. The plumes of these SEDs were located near the dayside cusp and result in TOI formations observed in nightside polar cap region. In association with the middle latitude SEDs and polar cap TOIs were observed strong ionospheric scintillations.
4. The impact of ionospheric scintillations in a new single-frequency PPP method
New analysis about the GNSS positioning was performed by Prol et al. [95] in order to evaluate the ionospheric delay retrieved by a new method for TEC calibration when this method was applied to correct the single-frequency PPP. The results revealed the possibility of performing the single-frequency PPP corrected by a TEC calibration and obtaining a similar accuracy to the double-frequency PPP. It suggested that almost all of the first-order ionospheric effect was eliminated by the TEC calibration method. Additionally, the single-frequency PPP corrected by the new method was very sensitive to the impact of the ionospheric scintillations. In fact, the proposed single-frequency PPP appeared to be even more sensitive to ionospheric scintillation in comparison with the single-frequency PPP corrected by traditional ionospheric models and the double-frequency PPP. In order to present the impact of the ionospheric scintillations in the proposed single-frequency PPP, this section describes the developed method for TEC calibration and some experiments and results.
TEC can be expressed as the integral of the electron density ne along the path between the GNSS satellite (s) and the receiving antenna (r), in a column whose cross sectional is equivalent to 1 m2. It can be written as:
TEC=∫rsneds,E3
being the ionospheric delay given by the following relation with TEC:
I=40,3f2TEC,E4
where I represents the ionospheric delay and f the signal frequency.
The ionospheric delay is related to the GNSS observations by the following equation for the code:
PL=ρ+cdtr−dts+IL+T+dmL+ϵP,E5
and the following equation for the carrier phase:
λLφL=ρ+cdtr−dts−IL+T+dmL+λLNL+ϵφ,E6
where the frequency-dependent terms are referred by L, ρ is the geometric distance, c is the speed of the light in vacuum, dtr and dts are the receiver and satellite clock errors, T refers to the tropospheric delay, dm is the multipath, NL is an ambiguity term, λ is the wavelength and ϵ represents the noise in code (P) and phase (φ).
The method to estimate TEC (Eq. (3)) using GNSS observations (Eqs. (5) and (6)), is performed in three steps. In the first step, a phase leveling estimation based on the code information provides the ambiguity terms. In this regard, the difference between ambiguities (ΔN) of two GPS frequencies (L1 and L2) in a unique arc of data is calculated through:
ΔN=λ1N1−λ2N2=1nobs∑j=1nobsP2j−P1j−λ1φ1j−λ2φ2j,E7
where only arcs with a minimum of 5 min of continuous data are used. Once the ΔN term is obtained for all arcs of a specific day, the receiver DCB (Differential Code Bias - Δbr) is obtained by the daily weighted mean of the phase difference (λ1φ1j−λ2φ2j), the initial TEC, the leveling ambiguity and the satellite DCB (Δbs). The receiver DCB is derived by the following weighted mean:
being σTECijgim the standard deviation of the initial TEC, which is derived from the Global Ionospheric Maps (GIMs) of the International GNSS Service (IGS) and their root-mean-square (RMS) maps. In addition, the satellite DCB Δbsi is obtained from GIMs. Therefore, as the satellite DCB and the initial TEC are obtained from GIMs, it is expected that the estimated receiver DCB is related to the DCB referential frame defined by IGS.
Once the ambiguity leveling (first step) and the receiver DCB estimation (second step) are done, the third step consists in the TEC estimation. TEC is directly calculated along the path of the GNSS signal with the following equation:
TEC=Fλ1φ1−λ2φ2−ΔN−cΔbs+Δbr,E10
where the TEC is derived for each GNSS observation, that is, TEC is estimated with the same time resolution as the phase and code collection rate.
Two close GNSS stations located at Rio de Janeiro in Brazil have been selected to make the experiments. The TEC estimation procedure was performed in the station RIOD (lat. Mag. 36.47° S), and the ionospheric delay correction was applied in the station ONRJ, which is located 12 km away. Using the configuration of short distances apart, it is possible to mitigate the problems of spatial gradients of the ionosphere. In addition, the receivers and antennas are from different brands in order to avoid possible correlations between clock and ambiguities of the stations. In this way, it has been as much as possible to isolate the degradation of the ionospheric scintillations in the PPP results.
Prol et al. [95] evaluated the analysis of the performance of the new TEC calibration procedure when applied to PPP for 120 days with six distinct configurations of base and rover stations, and the TEC performance is assessed by applying the estimated TEC from the base station to correct the ionospheric delay in a nearby rover receiver. Just to show the potentiality of the new procedure, here are shown the results of the analysis for two specific days with and without ionospheric scintillations.
Figure 2 shows an example of the calibrated TEC in RIOD during epochs with and without evidences of ionospheric scintillations. Each colored line represents the slant TEC calculated for a distinct satellite, that is, one colored line refers to the slant TEC of one GPS satellite. The Day Of Year (DOY) 005 of 2013 is shown in the top panel, which refers to the summer solstice in the south crest of EIA. On the other hand, DOY 191 of 2013 is referred to the winter. As it can be seen, the maximum of TEC in the summer solstice reaches around 150 TECU in the slant direction during the daytime. The magnitude of the TEC in daytime is reduced in the winter for up to 100 TECU, mainly due to the reduced intensity of the solar irradiation. However, TEC variability in the daytime is similar. In contrast, the nighttime between 22 and 04 LT presents a significant difference in terms of the TEC variability. The maximum TEC in the nighttime is reduced from 60 TECU in the solstice up to 30 TECU in the winter. Additionally, the high TEC variability evidenced between 22 and 04 LT is associated to the plasma depletions propagating trough the Brazilian region. In fact, the high magnitude of the TEC observations in comparison with the TEC variability makes the impact of the ionospheric scintillation not so clearing TEC. However, the impact of the ionospheric scintillations is much more easily seen when looking to the single-frequency PPP performance.
Figure 2.
TEC estimation with the proposed procedure at RIOD station on 2013 for DOY 005 during the summer (top panel) and DOY 191 during the winter (bottom panel). Each colored line represents the slant TEC calculated for a distinct GPS satellite.
RTKLIB is adapted for the use of the calibrated TEC during the single-frequency PPP. Among the PPP configurations, it is used the kinematic mode, a combined solution obtained by forward and backward filters, a cut-off angle of 10°, Earth tides corrections, the estimation of tropospheric delay during PPP, IGS precise ephemerides, satellite clock corrections with a 30 s rate (clk_30s), global positioning system constellation, correction of the phase center variation of the antenna, phase wind up corrections, no strategy for ambiguity solution and corrections of the differential instrumental bias between the civil and precise codes (C1-P1) when P1 was not available. In general, three modes of PPP are analyzed: (1) using the ion-free observation (PPP/if); (2) using L1 and the ionospheric delay from GIMs from UQRG (UPC Quarter an hour Rapid GIM), identified as PPP/uqrg; and (3) using L1 and the calibrated TEC through the proposed method (PPP/tec). Indeed, the PPP/if solutions are obtained using the ion-free observation of the carrier phase, which means that a linear combination is carried out with the L1 and L2 frequencies to eliminate the first-order effect in the ionospheric delay. In the case of PPP/uqrg, the observation used in the PPP Kalman Filter is related to the L1 frequency but corrected from the ionospheric delay derived from UQRG GIMs. The PPP/tec is similar to PPP/uqrg, but the ionospheric delay is derived directly from Eq. (10). The reference coordinates of ONRJ has been obtained from the Sistema de Referencia Geocéntrico para las Américas (SIRGAS) final solutions at epoch 2013, where a time update was performed to make the coordinates consistent with the PPP solutions.
Figure 3 shows the performance of PPP/if, PPP/tec and PPP/uqrg in terms of the three-dimensional (3D) error of the estimated coordinates. Each point represents the error of the PPP solution calculated in each processing epoch in kinematic mode. Since it was used a combined filter of forward and backward solution, there is no need for time convergence in the solution. Consequently, the remaining errors are related to the terms not efficiently mitigated and, as can be seen, the PPP/tec (blue points) was obtained with a high accuracy in many hours, except to the hours when is typically observed ionospheric scintillations.
Figure 3.
3D error of PPP at ONRJ station on 2013 for DOY 005 during summer (top panel) and DOY 191 during winter (bottom panel).
In general, the proposed method allowed having the single-frequency PPP with a similar accuracy than the double-frequency PPP. The root mean square error (RMSE) obtained for PPP/if in DOY 191 was 0.04 m with a standard of 0.04 m, the RMSE of PPP/tec was 0.09 m with a standard deviation of 0.04 m and the RMSE of PPP/uqrg was 0.47 m with a standard deviation of 0.65 m. In the case of DOY 005, the RMSE of PPP/if was 0.04 m with a standard of 0.04 m, the RMSE of PPP/tec was 0.19 m with a standard deviation of 0.05 m and the RMSE of PPP/uqrg was 0.70 m with a standard deviation of 0.66 m. By itself, this is an outstanding result, since many researchers have already used single-frequency receivers and ionospheric corrections to obtain, in general, an absolute accuracy of 0.5 m in the horizontal and 1 m in vertical for the kinematic PPP [96, 97, 98]. Now, we are showing the possibility of obtaining the single-frequency PPP accuracy similar to that from dual-frequency PPP. The horizontal accuracy in the experiment for PPP/tec was 0.12 m in DOY 005 and 0.05 m in DOY 191 and the vertical accuracy was 0.15 m in DOY 005 and 0.07 m in DOY 191. These accuracies are compatible to the double-frequency solutions. Therefore, the unique consideration for a high accuracy in single-frequency PPP is that TEC needs to be sufficient precise, which was not realistic in some epochs of DOY 005 due to the ionospheric scintillations.
A noticeable degradation of the PPP solution occurs between 00 and 04 hours LT in the summer solstice due to the high TEC variability. This PPP degradation is related to the ionospheric irregularities that impact GPS observations more effectively. At such instances, the uplifted ionosphere due to the pre-reversal drift produces high vertical gradients. It is believed that these gradients set the preconditions for plasma instability, controlling the generation of ionospheric irregularities. Therefore, the change of the GPS signal phase and amplitude imposed by ionospheric irregularities degrades the PPP solution. It is interesting to note that the PPP/if is sensitive, but not too much, to the ionospheric scintillations. In case of PPP/uqrg, it is hard to see the impact because of the high standard deviation in the PPP solution at other epochs. However, the impact of the scintillations is very evident in PPP/tec. This mainly happens because the estimated TEC was set to be very precise during the PPP, so that TEC was included with small values for standard deviation in the PPP Kalman filter. At epochs where only the first-order ionospheric delay is supposed to affect the GPS observations, the PPP/tec solution is very accurate. At epochs where the high-orders terms of the ionosphere delay impact the GPS signal, the PPP degradation becomes evident.
5. Conclusions
The ionospheric conditions are affected by electrodynamic processes that are driven by solar phenomena. During quiet geomagnetic periods, the effects are clearly associated with the seasonal variation of the solar illumination and with the 11-year solar radiation variation. These conditions can be strongly disturbed under the impact of CMEs (coronal mass ejections) and HSS (high-speed streams) in the magnetosphere producing the geomagnetic storms, which result in steeper electron density gradients and stronger irregularities. These irregularities are responsible for fluctuations in the amplitude and phase of GNSS signals, which can degrade the accuracy of the measurements. Therefore, the climatology of these irregularities is very important to define its spatial distribution and time of occurrence.
The investigation of ionospheric scintillations over South America has shown that they can occur at all longitudinal sectors during quiet geomagnetic periods, but they are stronger at post-sunset hours in the crest regions of the EIA (equatorial ionospheric anomaly), and seems to be more intense in the southern EIA crest, which is under the effect of the SAMA (South American Magnetic Anomaly) [24, 37, 81]. The scintillation occurrences strongly enhance with the increase of the solar activity [20, 21, 35, 37, 99], and during geomagnetic disturbed periods [13, 38, 75, 93, 94].
It was presented the potentiality of a new procedure for TEC calibration, showing a useful tool to correct the first-order ionospheric delay that improves the traditional single-frequency PPP solutions. Additionally, the results show a high-sensitive solution of PPP/tec to the ionospheric scintillations, even more sensitive in comparison with the impact of the ionospheric scintillation in the TEC level, which indicates that this kind of procedures are emerging as having potential for a wide range of applications for those measuring and predicting the ionospheric scintillations.
Acknowledgments
EC thanks the National Council for Research and Development (CNPq) for individual research support (processes nos. 556872/2009-6, 406690/2013-8, 303299/2016-9) and the National Institute for Space Research (INPE/MCTI). MTAHM thanks the support from CNPq through grant no. 429885/2016-4. FSP and POC are grateful to CNPq (grant no. 309924/2013-8), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP grant no. 2015/15027-7) and to Faculdade de Ciências e Tecnologia of UNESP (FCT/UNESP).
Conflict of interest
The authors declare that they have no conflict of interest.
\n',keywords:"ionospheric irregularities, scintillation, total electron content, climatology, South America, single-frequency PPP",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/62312.pdf",chapterXML:"https://mts.intechopen.com/source/xml/62312.xml",downloadPdfUrl:"/chapter/pdf-download/62312",previewPdfUrl:"/chapter/pdf-preview/62312",totalDownloads:113,totalViews:62,totalCrossrefCites:0,dateSubmitted:"March 6th 2018",dateReviewed:"May 30th 2018",datePrePublished:"November 5th 2018",datePublished:"January 16th 2019",readingETA:"0",abstract:"The radio communication and navigation systems can be strongly affected by the ionospheric conditions, which are controlled by solar phenomena associated with radiation variations and solar wind disturbances. These phenomena can generate ionospheric large-scale plasma redistribution and irregularities with scale sizes varying from centimeters to hundred kilometers. These ionospheric irregularities can produce rapid fluctuations in the amplitude and phase of global navigation satellite system (GNSS) signals, degrading the accuracy of GNSS measurements. Here we give a short review of the ionospheric variations associated with solar phenomena, and the actual state of art in the investigations of long-term (seasonal and solar cycle scales) TEC variations and climatology of scintillations, with focus on the southern American sector. It also presented a new TEC calibration procedure when applied to single-frequency PPP.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/62312",risUrl:"/chapter/ris/62312",signatures:"Emília Correia, Marcio Tadeu de Assis Honorato Muella, Lucilla\nAlfonsi, Fabricio dos Santos Prol and Paulo de Oliveira Camargo",book:{id:"7458",title:"Accuracy of GNSS Methods",subtitle:null,fullTitle:"Accuracy of GNSS Methods",slug:"accuracy-of-gnss-methods",publishedDate:"January 16th 2019",bookSignature:"Dogan Ugur Sanli",coverURL:"https://cdn.intechopen.com/books/images_new/7458.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"245723",title:"Dr.",name:"Dogan Ugur",middleName:null,surname:"Sanli",slug:"dogan-ugur-sanli",fullName:"Dogan Ugur Sanli"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"249305",title:"Dr.",name:"Emilia",middleName:null,surname:"Correia",fullName:"Emilia Correia",slug:"emilia-correia",email:"ecorreia@craam.mackenzie.br",position:null,institution:null},{id:"259537",title:"Dr.",name:"Marcio",middleName:null,surname:"Muella",fullName:"Marcio Muella",slug:"marcio-muella",email:"mmuella@univap.br",position:null,institution:null},{id:"259539",title:"Dr.",name:"Lucilla",middleName:null,surname:"Alfonsi",fullName:"Lucilla Alfonsi",slug:"lucilla-alfonsi",email:"lucilla.alfonsi@ingv.it",position:null,institution:null},{id:"259540",title:"MSc.",name:"Fabricio",middleName:null,surname:"Prol",fullName:"Fabricio Prol",slug:"fabricio-prol",email:"fabricioprol@hotmail.com",position:null,institution:null},{id:"259541",title:"Dr.",name:"Paulo",middleName:null,surname:"Camargo",fullName:"Paulo Camargo",slug:"paulo-camargo",email:"paulo@fct.unesp.br",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Ionospheric variability",level:"1"},{id:"sec_3",title:"3. Ionospheric scintillations",level:"1"},{id:"sec_3_2",title:"3.1. Scintillation indices",level:"2"},{id:"sec_4_2",title:"3.2. Ionospheric scintillation climatology in south American sector",level:"2"},{id:"sec_4_3",title:"3.2.1. Quiet geomagnetic conditions",level:"3"},{id:"sec_5_3",title:"3.2.2. Disturbed geomagnetic conditions",level:"3"},{id:"sec_8",title:"4. The impact of ionospheric scintillations in a new single-frequency PPP method",level:"1"},{id:"sec_9",title:"5. Conclusions",level:"1"},{id:"sec_10",title:"Acknowledgments",level:"1"},{id:"sec_13",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Prolss GW. Ionospheric F-region storms. In: Volland H, editor. Handbook of Atmospheric Electrodynamics. Florida: CRC Press; 1995. pp. 195-248'},{id:"B2",body:'Prolss GW. Ionospheric storms at mid-latitude: A short review. 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