Attenuation and relative permittivity of subsurface materials measured at 100 MHz [3].
\r\n\tThe Biomechatronic book will cover all health-related areas of mechatronic systems with emphasis on medical and health-related areas of mechatronic system components. The book will generally include the following areas: Biomechanics applications, Biomaterial systems, Mechatronic systems, Sensor systems, Control systems, Actuator systems.
",isbn:null,printIsbn:"979-953-307-X-X",pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"2a8b3299bd359d430bc9b5bfc54f9cdf",bookSignature:"Dr. Sezgin Ersoy and Dr. Ishak Ertugrul",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10029.jpg",keywords:"Biosensors, Mechatronics, Biomechatronics, Biosystem, Control, Control system, Bioactuators, Intelligent orthosis prosthesis, Implants, Upper and lower limb rehabilitation robots, Biomechanics applications",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 14th 2019",dateEndSecondStepPublish:"November 4th 2019",dateEndThirdStepPublish:"January 3rd 2020",dateEndFourthStepPublish:"March 23rd 2020",dateEndFifthStepPublish:"May 22nd 2020",remainingDaysToSecondStep:"a year",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:null,coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"156004",title:"Associate Prof.",name:"Sezgin",middleName:null,surname:"Ersoy",slug:"sezgin-ersoy",fullName:"Sezgin Ersoy",profilePictureURL:"https://mts.intechopen.com/storage/users/156004/images/system/156004.png",biography:"Sezgin Ersoy is an Associate Professor of Mechatronics Engineering and Material Science. After graduating from Marmara University, he became a faculty member at the same university. His publications include a variety of efforts to understand changes in automotive mechatronics, polymer science and biomedical technologies. He was granted fellowship at the TUBİTAK at Bourgogne University ISAT and spent one year as a visiting fellow there to study several projects between 2014 through 2015. He is the author of chapter Science Education in a Rapidly Changing World, USA 2011, and the author in Acoustic Properties of Bio Materials, Stuttgart, 2010. 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He is currently working as an Assistant Professor at Muş Alparslan University.",institutionString:"Marmara University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Marmara University",institutionURL:null,country:{name:"Turkey"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"11",title:"Engineering",slug:"engineering"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"287827",firstName:"Gordan",lastName:"Tot",middleName:null,title:"Mr.",imageUrl:"https://mts.intechopen.com/storage/users/287827/images/8493_n.png",email:"gordan@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"8883",title:"Autonomous Vehicle and Smart Traffic",subtitle:null,isOpenForSubmission:!1,hash:"841c82c0bf27716a7c800bc1180ad5de",slug:"autonomous-vehicle-and-smart-traffic",bookSignature:"Sezgin Ersoy and Tayyab Waqar",coverURL:"https://cdn.intechopen.com/books/images_new/8883.jpg",editedByType:"Edited by",editors:[{id:"156004",title:"Associate Prof.",name:"Sezgin",surname:"Ersoy",slug:"sezgin-ersoy",fullName:"Sezgin Ersoy"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophanides",surname:"Theophile",slug:"theophanides-theophile",fullName:"Theophanides Theophile"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1373",title:"Ionic Liquids",subtitle:"Applications and Perspectives",isOpenForSubmission:!1,hash:"5e9ae5ae9167cde4b344e499a792c41c",slug:"ionic-liquids-applications-and-perspectives",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/1373.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"57",title:"Physics and Applications of Graphene",subtitle:"Experiments",isOpenForSubmission:!1,hash:"0e6622a71cf4f02f45bfdd5691e1189a",slug:"physics-and-applications-of-graphene-experiments",bookSignature:"Sergey Mikhailov",coverURL:"https://cdn.intechopen.com/books/images_new/57.jpg",editedByType:"Edited by",editors:[{id:"16042",title:"Dr.",name:"Sergey",surname:"Mikhailov",slug:"sergey-mikhailov",fullName:"Sergey Mikhailov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"55272",title:"Ground‐Penetrating Radar for Close‐in Mine Detection",doi:"10.5772/67007",slug:"ground-penetrating-radar-for-close-in-mine-detection",body:'To make reliable, easily interpreted and less time‐consuming operational systems for landmine detection is a real challenge [1, 2]. Nowadays, demining is performed by using different kinds of demining systems, e.g., mechanical excavation, trained dogs/rodents, and metal detectors (Figure 1). Metal detector (MD) is one of the most used close‐range detection systems for demining. However, antipersonnel (AP) landmines are not made any more with significant amounts of metal but with plastic and other nonmetallic elements. Metal detection‐based systems available today do not efficiently detect plastic landmines with minimum metal content in a metal debris contaminated area. In order to compensate for small metal content in modern landmines, some sensors offer the possibility to the operator to increase their sensibility. However, the number of false alarms rises. Cambodian deminers are confronted with this problem daily. For each detected AP landmine, more than 500 inoffensive metallic debris such as grenade fragments and cartridges are located (some results collected after visiting a Cambodian mine‐field, Figure 2). False alarm rate as well as misdetection of low and nonmetal content of AP landmines have made mine clearance operations dangerous, time consuming, and expensive.
An example of classical demining operations in Croatia: deminers scan with metal detectors and trained dogs after the mechanical excavation [4].
Some of the objects found after demining operations with metal detectors in the M7753 minefield, Province of Siem Reap, Cambodia [4].
During the 1990s, several research groups started contributing in solving this problem by developing hardware and software for demining applications [1–3]. However, only a few are currently employed in real mine‐affected areas. One of these relatively new technologies is ground penetrating radar (GPR), an attractive choice for landmine detection due to their advantages over other sensors. GPR can detect both metallic and plastic mines in a variety of soils by noninvasive subsurface sensing [3]. GPR sends a series of microwave pulses ranging from about 1 to 4 GHz into the ground. It then looks for anomalies in the reflected signal, which could indicate the presence of a landmine. In terms of buried target detection, the strength of radar echoes is usually associated with contrasts of electromagnetic characteristics between targets and their surrounding soils. For antipersonnel mines, GPR is usually used in combination with a metal detector [3, 4]. The metal detector would detect all metal contents in the soil, and the GPR is used to discriminate on the size of the objects: smaller metal objects are discarded and larger metal objects are confirmed as dangerous. Note that the GPR has the capacity to detect nonmetal mines. But when used alone its possible large false alarm rate makes it more suited to look for antitank mines. Moreover, its weight can be light, so that it can be installed in a hand‐held system or in a vehicle‐mounted system in the form of an array of multiple antenna elements [3].
This chapter addresses two of the major challenges in the application of GPR in humanitarian demining operations: (i) development of affordable and practical GPR‐based systems and (ii) development of robust GPR signal processing techniques for landmine detection and identification. This chapter also reviews research carried out at the Royal Military Academy in these topics.
Electrical properties of materials are determined by electrical conductivity, permittivity and permeability, which are function of frequency. The relative permittivity (or dielectric constant) of a medium impacts the electric field propagation and is the most important parameter for GPR. The relative permeability affects the magnetic field propagation. The electromagnetic wave attenuation in the subsurface is strongly dependent on the electrical conductivity of the medium and its variation. The latter is normally controlled by water [4–8]. For a conductive material, the electromagnetic field is diffusive and cannot propagate as an electromagnetic wave. When it is resistive, or dielectric, an electromagnetic field can propagate as an electromagnetic wave. When an electromagnetic wave is send into the ground, GPR measures the reflected echoes from any electrical property discontinuity in the subsurface structure. Figure 3 shows a block diagram of a generic GPR system [5].
Block diagram of a generic GPR system [5].
The velocity and reflectivity of the electromagnetic wave in soil are characterized by the dielectric constant (relative permittivity) of the soil. When the dielectric constant of the soil is
where
Material | Attenuation (dB/m) | Relative permittivity |
---|---|---|
Air | 0 | 1 |
Clay | 10–100 | 2–40 |
Concrete: dry | 2–12 | 4–10 |
Concrete: wet | 10–25 | 10–20 |
Fresh water | 0.1 | 80 |
Sand: dry | 0.01–1 | 4–6 |
Sand: saturated | 0.03–0.3 | 10–30 |
Sandstone: dry | 2–10 | 2–3 |
Sandstone: wet | 10–20 | 5–10 |
Seawater | 1000 | 81 |
Soil: firm | 0.1–2 | 8–12 |
Soil: sandy dry | 0.1–2 | 4–6 |
Soil: sandy wet | 1–5 | 15–30 |
Soil: loamy dry | 0.5–3 | 4–6 |
Soil: loamy wet | 1–6 | 10–20 |
Soil: clayey dry | 0.3–3 | 4–6 |
Soil: clayey wet | 5–30 | 10–15 |
TNT | – | 3 |
Plastic | – | 2–4 |
Attenuation and relative permittivity of subsurface materials measured at 100 MHz [3].
When GPR transmits electromagnetic waves from a transmitting antenna located off‐the‐ground, signals travel in the air layer and when the electromagnetic wave encounters any dielectrical discontinuity, a reflection occurs. The latter is received by a receiving antenna, located off‐the‐ground, and it is referred to as an A‐scan, e.g., a single waveform recorded by GPR, with the antennas at a given position (x, y). In this data set, the time t is the only variable, related to the depth z by the propagation velocity of the EM waves in the medium. Its representation in the time domain can be seen in Figure 4 [5]. The time axis or the related depth axis is usually pointed downward.
Representation of an A‐scan [5].
When moving the GPR antennas on a line along the x‐axis, a set of A‐scans can be gathered, which form a two‐dimensional (2D) data set called a B‐scan (Figure 5). When the amplitude of the received signal is represented by a color scale (e.g., gray‐scale), a 2D image is obtained and is shown in Figure 6. The 2D image represents a vertical slice in the ground. Reflections on a point scatter located below the surface appear, due to the beamwidth of the transmitting and the receiving antenna, as hyperbolic structures in a B‐scan. Finally, when moving the antenna over a (regular) grid in the xy‐plane, a three‐dimensional (3D) data set can be recorded, called a C‐scan (Figure 6). Usually a C‐scan is represented as a two‐dimensional image by plotting the amplitudes of the recorded data at a given time
Configuration and representation of a B‐scan.
A gray‐scale illustration of a B‐scan (left) and a series of B‐scans forming a C‐scan (right).
Representation of a C‐scan by horizontal slices at different depths (left), arbitrary cut in the 3D volume (center), and isosurface (right) [5].
Table 2 gives a schematic overview of the various possible types of GPR systems that exist today. GPR systems can be classified by the domain in which they work and by the type of modulation. GPR systems operate either in time domain or in frequency domain. In the time domain GPR there are two major categories: the amplitude modulated and the carrier‐free GPR. The first one sends a pulse with a carrier frequency. This carrier frequency is modulated by a (square) envelope. Good depth resolution is achieved by reducing the duration of the pulse as short as possible. Most of the commercially available GPRs belong to this group [5].
GPR design options | ||||
---|---|---|---|---|
Domain | Time | Frequency | ||
Modulation | Amplitude (mono cycle) | Carrier‐free | Linear sweep | Stepped frequency |
Different types of GPR systems.
The need for larger bandwidth has led to the development of a second category of time domain GPR: the carrier‐free GPR. The pulse sent by the GPR has no carrier. The shape of the pulse can vary, but typically a Gaussian pulse is used. The carrier‐free radar is also called an ultra‐wide band (UWB) GPR because of the large bandwidth. Before, GPR systems were developed based on time domain waveform. Nowadays GPRs are also developed in the frequency domain. In the latter, systems can have two possible modulation types: either the frequency modulated (FM) continuous wave (CW) or stepped frequency (SF) GPR [5].
FM systems transmit a carrier frequency, which changes continuously by using a voltage‐controlled oscillator over a certain frequency range. The frequency sweeps according to a function within a certain time. After reception, the reflected wave is mixed with the emitted one, and the target depth can be calculated from the difference in frequency between the transmitted and received wave. FM systems have poor dynamic range, which is an important limitation. Since FM radars receive signals at the same time as it is transmitting, leakage signals between the antennas can obscure small reflections. Those two facts deviate the attention from FM systems to SF radars for ground applications.
An SF GPR uses a frequency synthesizer to go through a range of frequencies equally spaced by an interval
Besides the domain of operation, GPR antennas may be either monostatic (single emitting and receiving antenna), bistatic (different emitting and receiving antenna), or an array configuration of different antenna types and sizes. In the mine detection application, high depth resolution is needed and therefore ultra‐wide band (UWB) antennas play an important role [8]. Vehicle‐based systems generally use array antenna mode [10] in combination with other sensors such as metal detectors [11]. Laboratory prototypes of UWB GPR systems are built in bistatic mode [12, 13], and such a configuration is adopted for hand‐held GPR‐based systems [14, 15]. For all these configurations, different types of antennas such as horn, loop, spiral, Vivaldi, and combinations of them are used. An overview of their characteristics, advantages, and drawbacks for demining applications can be found in Refs. [5, 16].
Landmine detection using GPR is a very particular problem. Commercial GPRs are mostly designed for geophysical applications and use central frequencies up to 1 GHz. As landmines are small objects, a large bandwidth is needed for a better depth resolution. Therefore, we have decided to build our own UWB system in the frame of the HUDEM (Humanitarian Demining) project (in collaboration with the Microwave Engineering and Applied Electromagnetism Department of the Catholic University of Louvain, UCL) and to use a GPR‐based system (under the BEMAT (Belgian Mine Action Technologies) project) developed at the Environmental Sciences Institute of the UCL. These choices were made following five technical and practical requirements [5]:
The GPR system must be UWB (working in the frequency range 500 MHz to 4.5 GHz).
The GPR system must be used off ground (safety reasons and to increase mobility of the system, see point 3 below). Therefore, the antenna must be highly directive in order to couple sufficient energy into the ground for achieving a penetration depth of 15 cm in any soil [17].
The GPR system must guarantee a high degree of mobility, i.e., attention should be paid to dimensions and weight. Minefields have often rough surfaces, steep slopes and/or are covered with dense vegetation. Not all systems can guarantee a sufficient flexibility in such scenes.
The antenna properties must be independent of the ground properties.
The GPR system must be cheap in production to limit the overall cost of the sensor. This will always be asked for in the case of humanitarian demining.
Based on the requirements listed before, many researchers have focused their attention into transverse electromagnetic (TEM) horn antennas, which have a high directivity, can work broadband and are nondispersive. A traveling wave TEM horn consists of a pair of triangular conductors forming a V structure (Figure 8), which can transmit and receive a fast transient pulse [18, 19]. It is presumed that the TEM horn conducts mainly the TEM mode within a selected frequency range by conserving constant characteristic impedance and that, by omitting the edge diffraction effect and fringe fields, a linearly polarized spherical wave is diffused.
Conventional design of the TEM horn antenna characterized by three parameters: L the length of the antenna plates, φ0 the azimuth half‐angle, and θ0 the elevation half‐angle.
This type of antenna is totally parameterized by three characteristics: L is the length of the antenna plates,
For improving the directivity and reducing the physical antenna dimensions without diminishing the bandwidth, TEM horns can be filled with a silicone. A silicone characterized by a real relative permittivity
For preserving the same surge impedance as without the silicone, the angle
The antenna plates are replaced by printing sets of 41 wires on circuit boards (Figure 9). Since the distance between the wires is small, the antenna characteristics are preserved. In addition, the currents are forced to be radial, limiting the surface of conducting metal. In this application, this is of great importance since GPRs are often used in combination with metal detectors.
Lower and upper antenna plates, etched on a printed circuit board.
In order to feed the TEM horn in its balanced configuration (Figure 8) with an unbalanced coaxial line, an UWB (frequency‐independent) balun is required to prevent currents on the coax. Several realizations of a TEM horn were made, and, at first, measurements revealed an unbalanced current component on the coax exterior. This means that the coaxial feedline was reacting as an antenna. A common way of eliminating such currents is to add chokes (ferrite cylinders) around the feeding cable [21]. For this design, a new kind of balun is tested, which principle lays on an electrostatic reasoning described in Ref. [22]. The function of the taper in the bottom plate is to provide a gradual transition between the unbalanced upper antenna plates on a ground‐plane, toward a balanced alignment with two symmetrical antenna plates. However, a slide change of the surge impedance along the antenna is introduced by such a transition. The surge impedance of one antenna plate on a ground‐plane is half the value calculated using the wire model. Since
The dielectric‐filled antennas were integrated in a laboratory UWB GPR. For this, a study was made in order to optimize the position and orientation of the Tx and Rx antennas. To reduce the coupling between the two TEM horns, they were put side by side with a common H‐plane (E‐field of both antennas is parallel to the interface). Generally speaking, antenna coupling is not critical since it could be neutralized. However, if the ringing between the two antennas lasts too long, it could obscure interesting parts of the returned signal. After some tests, the antennas were fixed at around 25 cm above the surface [12].
When configuring the Tx‐Rx antenna system, it is important to consider the two antennas as one antenna. Therefore, the combined antenna pattern should be analyzed. The 3 dB beamwidth that results of this combination is normally function of the offset angle
Dielectric‐filled TEM horn antenna configuration in bistatic mode [12].
Figure 11 represents a GPR image of a PMN AP landmine (12.5 cm diameter, plastic case), buried at 1 cm depth in dry sand. Data are acquired by an impulse UWB GPR emulated using a picosecond pulse labs step‐generator type PSPL 4050B, followed by an impulse‐forming‐network and connected to two identical dielectric‐filled TEM horn antennas. Data are taken by displacing the Tx and Rx antennas by steps of 1 cm (represented on the x‐axis). In each antenna position, a short Gaussian impulse is radiated and the backscattered signal is recorded (y‐axis).
Time domain representation of the impulse UWB GPR measurements performed on sand for the PMN AP mine, buried at 1 cm.
An SFCW system is considered in the frame of the BEMAT project, which also covers several of the requirements mentioned before. It is based on the frequency domain radar‐antenna‐multilayered medium model developed by Lambot et al. [23], which applies for SFCW radars operating off the ground in monostatic mode (in our case, a portable vector network analyzer (VNA) connected to a monostatic horn antenna, see Figure 12). In this approach, it is assumed that the distribution of the backscattered electric field measured by the antenna does not rely upon the elements of propagation (air and subsurface layers), i.e., only the amplitude and phase of the field change. Therefore, the antenna can be described by a model of linear transfer functions in series and in parallel, acting as global transmittances and reflectances (Figure 13).
The UWB SFCW GPR system emulated using the hand‐held VNA connected to the horn antenna via a 50‐Ohm N‐type coaxial cable.
The VNA‐antenna‐multilayered medium system modeled as linear transfer functions in series and in parallel.
In this model,
The latter equation is represented in the frequency domain and the transfer functions are frequency dependent complex quantities. The multiple wave reflections occurring inside the antenna, which, as stated before, are a result of the impedance differences between the antenna feed point and the antenna aperture are represented by the return loss function
The antenna transfer function
On the one hand, a necessary condition for this antenna model is to employ the antenna sufficiently far from the surface. On the other hand, it is necessary to minimize losses by spherical divergence in wave propagation, keep a high SNR, and ensure a high spatial resolution, conditions that are achieved by minimizing the distance between the antenna and the surface. In Ref. [25], laboratory experiments were carried out to characterize the transfer functions
In order to emulate the UWB SFCW radar, a low‐cost hand‐held VNA connected to a monostatic horn antenna via a 50 N‐type coaxial cable is used. The VNA comprises a spectral analyzer (FSH6, Rohde and Schwarz), which uses a bridge and power divider (VSWR, Rohde and Schwarz) to give vector measurements. A linear polarized double‐ridged broadband horn antenna (BBHA 9120A, Schwarzbeck Mess‐Elektronik), with 22 cm length and 14 × 24 cm2 aperture area, is used to collect data. For this application and from antenna characteristics, it can be considered as directive (3‐dB beamwidth of 45° in the E‐plane and 30°in the H‐plane at 1 GHz and 27° in the E‐plane and 22°in the H‐plane at 2 GHz, when working in the 0.8–5.0 GHz frequency range).
This UWB SPCW radar is easy to use and affordable, and it covers several of the requirements listed before. It has a linear dynamic range of 60 dB, allowing detecting weak scatterers. Internal reflections inside the antenna are accurately calculated and included in the EM model described before. As a result, they do not influence negatively the signal‐to‐noise ratio of the system. Besides, amplitude drift (that can be due to mechanical or temperature changes on the connection point of the antenna) is limited by a precise and easy‐to‐do calibration method using a standard Open‐Short‐Match calibration kit. While gathering data, this calibration could be performed once more.
Figure 14 shows a time domain representation of radar measurements performed in a homogeneous sand for the PMN AP landmine (12.5 cm diameter, plastic case) buried at 10 cm. The horn antenna was displaced over the x‐axis following constant steps of 2 cm. The height of the antenna aperture is 20 cm above the soil surface.
Time domain representation of the SFCW UWB GPR measurements performed on sand for the PMN AP mine, buried at 10 cm.
During the past 10 years, the development of GPR applied to landmine detection has evolved from the laboratory conditions and test fields to real minefields. Nowadays, systems using dual sensor technology combining MD and GPR (hand‐held dual sensors) have enabled improved discrimination against small metal fragments to be demonstrated in live minefields. Some of them have reached the stage where they are being produced in large numbers. Such systems work with both MD and GPR, and they differ on the operating principle of GPR, the signal processing and the user interface. In this section, three of them are introduced.
MINEHOUND/VMR2 has been developed by ERA Tech., U.K., in collaboration with Vallon Gmbh, Germany. It combines a pulse induction MD and an impulse GPR. This dual‐sensor transforms MD and GPR signals into two separated audio signals of different frequency of vibration and tone. MINEHOUND/VMR2 has been tested in different mine‐affected countries including Afghanistan, Angola, Bosnia and Cambodia [26].
ALIS (Advanced Landmine Imaging System) is a Japanese detector developed at the Tohoku University. It incorporates an MD and a GPR, in combination with a sensor tracking system, which makes possible to analyze and visualize the data (after migration). Its hand‐held version is equipped with a VNA‐based GPR and a pulse induction MD. This dual‐sensor provides two different user interfaces: audio for MD signal and images for both MD and GPR signals. Different trials have been performed with ALIS in mine‐affected countries including Afghanistan, Cambodia, Croatia, and Egypt [27].
AN/PSS‐14 (former HSTAMIDS, Hand‐held Standoff Mine Detection System) was originally a project founded by the Defense Advanced Research Projects Agency, DARPA, U.S., and has been produced later by CyTerra Corp. (now L3 Communications). It is equipped with a pulse induction MD and a GPR based on a wide‐band, SF radar. AN/PSS14 gives to the user an audio signal when a metallic object is detected. If there is a metal detection and the GPR system identifies other mine‐like material as well, a second sound, of a different frequency of vibration and tonality, is played as aided target recognition. This system has been produced since 2006 for U.S. Army operations in Iraq [28].
GPR principal function is to detect differences on the electromagnetic (EM) properties in the soil‐target medium. This permits to locate even low and nonmetallic landmines. Apart from the response from a potential target, the backscattered signal carries also undesirable effects from antenna coupling, system ringing and subsurface reflections, which hide the target signature [1–3]. These effects have to be filtered out from the signal to enhance landmine detection.
As stated before, using GPR in landmine detection operations could be advantageous since the number of false alarms could be reduced and since low‐metallic content landmines that are not detected by metal detection could be detected by GPR. However, extracting the landmine signature from GPR data is negatively affected by a list of influencing elements categorized as clutter, which can partly or totally obscure or deform the backscattered signal from a buried object. Mainly, these influencing elements are: (1) antenna reactions causing multiple reflections and signal deformation; (2) the subsoil EM characteristics and their spatiotemporal distribution controlling wave propagation velocity, attenuation, and surface and subsoil reflections; (3) the EM variation between the buried object and the subsoil influencing the strength of the landmine response; and (4) surface roughness causing diffuse scattering. Thus, it is necessary to investigate suitable techniques in order to reduce clutter while maintaining high landmine detection rates. This could be very challenging due to the complicated EM phenomena taking place in the theoretically unknown antenna‐air‐soil‐mine system.
Different approaches are used to reduce this clutter and to recognize the landmine signal. Widely used approaches to reduce clutter are average and moving average background subtraction (BS). Other BS techniques are based on wavelet transform and system identification. Once these approaches suppress part of the clutter, the next expected procedure is to detect the buried object. In this step, different signal processing techniques for the identification of the target signal are applied, including advanced algorithms for hyperbola detection [29], convolutional models and migration techniques [5]. An overview of different signal processing techniques for landmine detection using GPR can be found in Refs. [1, 3].
In Ref. [30], we propose a method to filter out the antenna internal reflections and multiple reflections between the antenna and the ground, as well as the related distortion effects, by using the frequency‐dependent linear transfer functions model developed in [23]. These functions also account for the antenna gain and wave propagation time, fixing time‐zero at the antenna phase center. An example of data before and after filtering the antenna effects is presented in Figure 15 (note that in the radar data represented in Figure 14, these effects were previously removed).
Time domain representation of the SFCW UWB GPR measurements performed on sand for an antitank (AT) mine, buried at 30 cm depth, before (left) and after (right) removing antenna effects.
On the left image we can observe the multiple reflections occurring in the antenna, between about 0 and 2 ns. These unwanted signals obscure the backscattered response when looking down in the time axis. At around 3.2 ns, the air‐soil interface reflection appears. Then, a second‐order reflection taking place between the antenna and the soil surface arrives at about 4.5 ns. Later in time, the backscattered signal coming from an antitank (AT) landmine appears around 6.5 ns (hyperbolic shape). Thanks to its relatively large size and metal content, as well as the strong electromagnetic contrast between this one and the sand, and to the low attenuation of the EM waves in the sand (the electric conductivity tends to zero), this landmine is easily noticeable to the naked eye. After filtering‐out antenna effects (image on the right), the true time zero corresponds now to the antenna phase center, located at about 7 cm from the antenna aperture, inside the antenna, resulting in a time‐shifting (note that the soil reflection and hyperbola originating from the AT landmine are shifted in time). The multiple antenna reflections have been taken away and the surface reflection appears clearer, around 1.9 ns, allowing the precise calculation of the antenna height. Moreover, the hyperbolic signature of the AT landmine is highlighted. There are some remaining oscillations which are still visible in the figure. These could be a consequence of the distinct suppositions postulated in the antenna model, mainly, (i) the condition of being in the far‐field, (ii) the virtual Tx‐Rx point of the antenna which is approximated at a fixed position (in reality, its position varies with frequency, the high frequencies being emitted nearer the feed point, and the low frequencies being emitted in the proportionally larger part of the antenna), and (iii) the fact that only the x‐component of the electric field is supposed to be measured and that only an x‐directed current source is available. These could also appear as a result of applying the inverse Fourier transform to data collected in a restricted frequency range. This chapter will show later that such oscillations are not a disadvantage for the detection and identification of AP landmines.
The surface reflection may be removed from a full GPR transect by subtracting from all measurements a mean measurement or an A‐scan performed over a landmine‐free area. In order to do this, the EM properties of the subsoil should be homogenous over the transect, all measurements should be performed with the antenna situated at a constant height above the ground, and the soil surface should be totally flat. In practice, real minefields cannot satisfy these requirements. For filtering the soil surface reflection we propose to subtract from the radar signal, preliminarily filtered for antenna effects, a computed Green\'s function
Figure 16 shows data after filtering the ground surface reflection. The effect of the AT landmine is isolated, which permits to differentiate the hyperbolic signature. The response of the target is then calculated by using Eqs. (2)–(4) and can be written as:
Results after filtering the soil surface reflection from radar data of Figure 15 (AT landmine).
The radar antenna transmits energy with a beamwidth pattern such that an object several centimeters away from the beam axis may be detected. As a result, objects of finite dimensions appear as hyperbolic reflectors on the B‐scans. Migration techniques are used to reconstruct the reflecting structure present in the subsurface by focusing the reflections back into the true position of the object. We propose to filter out the effects of the antenna radiation pattern using the common Stolt\'s migration method [32], which applies a Fourier transform to back‐propagate the scalar wave equation, extended in Ref. [30] for two media.
Consider the filtered signal
The Fourier transformation along the
Considering the wavenumber
where
Assuming only upward coming waves and by introducing Eq. (7) into Eq. (6), the Fourier transform of the wavefront at depth
The migrated image will be the inverse Fourier transform of Eq. (8) at t = 0 as
Figure 17 shows results after applying Slot\'s migration to the data set presented in Figures 14 and 15.
Results after applying the Slot\'s migration method for the datasets presented in Figure 14 (PMN AP landmine, left) and Figure 16 (AT landmine, right).
As described above, the aim of migration is to focus target reflections in the recorded data back into their true position and physical shape. In this respect, migration can be seen as a form of spatial deconvolution that increases spatial resolution. It is a common practice not to include in the migration approaches the characteristics of the radar system, e.g., antenna patterns, antenna impulse response, and source waveform. In this section, a migration approach that considers the system characteristics and to a certain extent, the ground characteristics, is presented [5]. Its strategy is based on the deconvolution of the collected data with the point‐spread function of the radar system. As in most of migration algorithms, it is assumed that the interaction between the scatterers present in the medium is totally disregarded.
In order to perform the migration process by deconvolution, the data acquired by the UWB GPR have to be a convolution between the different layers and configurations present in the subsoil and the point‐spread function of the system. This is valid under certain premises. In the interest of simplifying the analysis, a monostatic antenna configuration is taken as an example. The velocity of propagation through the propagation element can only vary in the groundward direction. The antennas are change location following a xy‐plane at z = 0. The 3D data,
Where
Eq. (11) represents a space‐time convolution along the co‐ordinates x, y, and t, and can be written as
where
Synthetic C‐scan of a fictive point scatterer at a depth of 6 cm below the air‐ground interface, calculated by forward modeling.
Even though the point‐spread function
Figures 19–21 show the results of the migration method on data taken by a laboratory UWB GPR described in Section 2.3, with the antennas mounted on an indoor xy‐scanning table. The data are acquired over an area of 50 cm × 50 cm with a step of 1 cm in both x‐ and y‐direction. Results are shown in Figure 19 for a PMN mine buried at 5 cm of depth in sand, in Figure 20 for a brick of dimensions 15 cm × 9 cm × 6 cm buried at the same depth, and in Figure 21 for a piece of 20 cm barbed wire. There is a green, three‐dimensional representation of the collected data in each of the figures, which is obtained after applying first a Hilbert transformation to the A‐scan in order to calculate the cover for each A‐scan. As a second step, the data are plotted by an isosurface 3D plot, accentuating all the pixel of a given intensity or higher. In each figure, the raw data are plotted the left. On the right, the migrated image is displayed. For clarity, the ground reflection is suppressed in Figures 20 and 21. When observing the targets from above, the rounded form of the PMN mine is clearly displayed, and the form of the brick is more box‐like. Figure 21b shows how the form of the barbed wire can be easily distinguished from the other two forms and the three sets of pins present on the real wire are clearly noticeable. It is demonstrated with these three examples that the shape of a target in the subsoil can be extracted from the data gathered by the UWB GPR after applying the migration procedure explained above.
Results after applying deconvolution in order to focus the data collected on a PMN mine (diameter of 11 cm) located at 5 cm depth. (a) Photo of PMN mine ; (b) 3D C‐scan view of raw data; (c) 3D C‐scan view of migrated data; (d) 2D C‐scan horizontal slide of migrated data.
Results after applying deconvolution in order to focus the data collected on a brick (15cm × 9cm × 6cm) located at 5 cm depth. (a) Photo of the brick; (b) 3D C‐scan view of raw data; (c) 3D C‐scan view of migrated data; (d) 2D C‐scan horizontal slide of migrated data.
Results after applying deconvolution in order to focus the data collected on barbed wire (approx. 20 cm length) located at 5 cm depth. (a) Photo of the barbed wire; (b) 3D C‐scan view of raw data; (c) 3D C‐scan view of migrated data; (d) 2D C‐scan horizontal slide of migrated data.
The aim of migration is not only to focus reflections on objects back into the true physical shape of the object but also into its true position. To illustrate the latter, an AP mine was buried under an angle of about 30° in dry sand, with the highest point of the mine at a depth of 5 cm. In the raw B‐scan presented in Figure 22a, the strongest reflections on the mine are found in the lower right corner of the image, whereas in reality the mine (designated by the rectangular box) is situated in the middle of the image. This shift can be simply explained as follows. When the antennas are right above a tilted object, the latter will appear as a strong reflection in a direction away from the receiving antenna. For the antennas in the direction perpendicular to the flat top of such a target, the reflections going toward the receiving antenna will be stronger than in the case the antennas are right above the tilted object, causing a displacement of the target in the raw data. Figure 22b shows how, after applying the migration using the deconvolution approach presented before, the target is found in its actual position. Results of the migration not only show that the target was at the wrong position in the raw data, but also clearly show that the target is tilted. Because of the different backscatter structures in the target, its dimensions in the
Oblique PMN mine under an angle of 30°. (a) Raw data, (b) image after migration by deconvolutions, and (c) image after Kirchhoff migration.
GPR may allow detecting buried objects such as metallic and nonmetallic AP landmines. However, this detection technique can be affected by false alarm rates as other reflectors (e.g., stones, metal fragments, roots) can produce similar echoes. In this regards, resonance features in backscattered signals are proposed here in order to identify unknown targets. These features can be studied in either the time‐domain (TD) or the frequency‐domain (FD). In Ref. [33], functions of both variables, time and frequency, are considered for this particular application. Time‐frequency distributions, which are 2D functions, can reveal the time‐varying frequency content of 1D signals. One of these 2D functions is the Wigner‐Ville distribution (WVD), which is widely used for target recognition. This section shows how the application of the WVD on GPR data can yield to extract important information about the physical features of AP landmines located in the subsoil.
The WVD is one of the approaches of the time‐frequency representations. It has a main advantage when compared to other representations such as the short‐time Fourier transform or spectrogram, which is a higher time resolution. The WVD of a 1D signal
where
is the analytic signal consisting of the real signal
and
Figure 23 represents the WVD of one A‐scan from Figure 16 (AT landmine). The WVD is applied only to the A‐scan containing the highest amount of energy backscattered from the target, calculated after filtering and migration. The dotted line in the left figure represents raw data acquired with the SFCW UWB GPR and filtered data are presented with the solid line.
WVD (right) applied to a filtered and migrated A‐scan data (left) for an antitank landmine buried in sand (from Figure 16).
At any time (frequency) point, the WVD can be considered as the summed spectrum (correlation) of the signal power at this point and the cross‐power of two signals parts, spaced symmetrically with respect to the current time point.
As this distribution is a two‐dimensional representation (matrix) of a one‐dimensional signal, this transform inferred a given amount of redundancy. In order to confront this problem, Ref. [34] suggested the singular value decomposition (SVD), which is used here in conjunction with the concept of the center of mass (CM) to extract discriminant features [35].
SVD is intended for representing the WVD matrix
where the matrixes
Since the singular values and vectors are unique for any matrix, these triplets contain energy, time, and frequency features which help in discriminating different targets. Therefore, following Ref. [35], the CM (the center of mass is the strongest point in any distribution) of the singular vectors
This approach is applied to different targets, including landmines, improvised explosive devices (IED), and false alarms (FA), which are buried in different types of soils. A description of the targets is done in Table 3.
Target | Type | Shape | Diameter (cm) | Metal content |
---|---|---|---|---|
C3A1 | Plastic AP | Irregular | 5.1 | Low |
PMA | Plastic AP | Rectangular | 15.2 | Low |
Stone1 | FA | Irregular | 12.0 | No |
Metallic can | FA | Irregular | 12.0 | High |
IED5 | PVC | Cylindrical | 6.3 | No |
IED6 | PVC | Cylindrical | 6.3 | Low |
IED7 | Glass | Cylindrical | 5.5 | No |
IED8 | Glass | Cylindrical | 5.5 | Low |
Stone2 | FA | Irregular | 8.0 | No |
Metallic debris | FA | Irregular | 6.0 | High |
Some characteristics of the objects used.
Figure 24 shows the calculated values from Eqs. (17) to (19) for targets of Table 3. The features of the AP landmines are well clustered and well separated from those of the metallic false alarms and stones. The false alarms are clearly separated as well. Classification between different AP landmines (with different shapes) and between different IEDs (with different materials) could be also obtained. Results also show that the extracted features could be independent of the target depth.
Extracted features from different targets buried at different depths.
In this chapter, two of the major challenges in the application of GPR in humanitarian demining operations are addressed: (i) development and testing of affordable and practical GPR‐based systems, which can be used off‐ground and (ii) development of robust GPR signal processing techniques for landmine detection and identification.
Different approaches developed at RMA in order to demonstrate the possibility of enhancing close‐range landmine detection and identification using GPR under laboratory and outdoor conditions are summarized here. Raw GPR profiles give us a large quantity of information about the underground, and therefore performant signal processing techniques are needed to filter and improve the data quality in order to extract the right information. Data acquired using different affordable and practical GPR‐based systems are used to validate a number of promising developments in signal processing techniques for target detection and identification. Removing undesirable reflections by filtering and focusing the data using migration algorithms are some of the techniques applied in image reconstruction which are introduced here. The proposed approaches have been validated with success for the imaging, detection and classification of buried objects in laboratory and outdoor conditions. Validation has been done for different scenarios, including AP, low‐metal content landmines and IEDs, and real mine‐affected soils.
The work presented in this chapter was carried out at the Signal and Image Centre, École Royale Militaire, Belgium, in collaboration with the Microwave Engineering and Applied Electromagnetism Department, the Telecommunications Laboratory and the Dept. of Environmental Sciences and Land Use Planning of the UCL (Belgium), and with the Dept. de Ingeniera Eléctrica y Electrónica of the Universidad de Los Andes (Colombia). They were funded by the Ministry of Defense of Belgium in the scope of HUDEM and BEMAT projects. The Instituto Colombiano para el Desarrollo de la Ciencia y la Tecnología—Colciencias (Colombia), the Batallón Baraya (Colombia) and the Escuela de Ingenieros Militares (Colombia) are gratefully acknowledged for their outstanding support during some trials.
Analysis is considered the resolution, by application of logic, of complex structures, facts, propositions and concepts into their elements. By extension, it is the tracing of things to their source and the resolution of knowledge into its original principles, the discovery of general principles underlying concrete phenomena. Music analysis, therefore, is the dissection of the musical composition to separate the component parts of the whole in order to take a proper examination of the nature, function, connotations, compatibility, complementary and unitary contributions of these components. This exercise will, among other things, offer the analyst a chance for proper appraisal of the effects of different compositional and performance techniques on the consumers of the musical product. It will also ensure personal and institutional in-depth studies of the composition. In the words of Achinivu,
\nThrough analysis, the various elements of musical architecture become less technical and less dry to music students. Conversely, by their application of the knowledge they have of musical elements and concepts in the analysis of a piece of music, they obtain greater insights into and understanding of musical design and content of form.
\nIn the recent applications of the theory of observational learning, terms such as mastery learning, teaching machines, programmed instruction, computer-based training (CBT), computer-aided instruction (CAI) and audiovisual education have found their place in the center stage of the twenty-first century educational procedures.
\nSidney Leavitt Pressey had, in the 1920s, designed the first set of teaching machines, which provided immediate feedback for multiple-choice tests. In using the machine, the learners had the advantage of correcting their errors immediately. This immediate feedback system enabled the learners to work at the test items until their answers were correct. Improving on the efforts of Pressey, B. F. Skinner, in 1954—exploring the possibilities of his operant conditioning, developed his own version of teaching machine that became known as programmed instruction. The basis of Skinner’s programming includes simple principles, namely, presentation of information in small steps called frames, immediate confirmation of the learner’s response, active responding to induce sustained activity, self-pacing and dual evaluation of learner’s progress by both learner and teacher [1, 2, 3, 4].
\nThe application of the programmed-learning theory in analyzing music in the twenty-first century, obviously, engages the computer as an inseparable aid. The elements and items for analysis are codified and, thereby, reduced to icons which are packaged in music software (programmed). The programme then becomes the model to be observed and interacted with by the analyst, in a multimedia of presentation. Sociocultural, ideological and historical issues in music—through a human and machine collaboration—can equally, and easily, be reduced into electronic forms for analysis in the same interactive manner as in musical issues [5].
\nIn trying to dissect music, to separate the component parts of the whole in order to take a proper examination of the nature, function, connotations, compatibility, complementary and unitary contributions of these components, the scholar has already embarked on an analytical assignment that would stretch his/her studies into other disciplines than music. Such studies, whether carried out by an individual or a team, would demand the application of knowledge from at least such academic disciplines as sociology, history, anthropology, semiology, linguistics, economics and philosophy. Because of these interpretative demands, there is a need to engage with music analysis from various approaches.
\nCertain elements are globally accepted as intrinsic commonalities in the phenomenon of sound. Such elements as rhythm, pitch, timbre and duration when consciously or subconsciously manipulated distinguish the musical sound from the rest. Analyzing music along the lines of its sonic elements, exposing the inherent stylistic features, conventions and idioms is basically in the domain of systematic musicology. This approach tends to describe ‘the over-all structure of a piece of music, and … the interrelationships of its various sections. In most cases, indeed, it is the fitting of this structure into a preconceived mode’ [6].
\nFor instance, ‘form’, as a basic element in music, refers to the structural make-up of a musical composition. It exposes the basic shape of the composition that gives it its distinctive character. Musical form, as one of the characteristic elements of music, is the bases of the systematic and coherent arrangement of the structural design of a musical composition. Apel, therefore, expresses the fact that:
\nMusic, like all art, is not a chaotic conglomeration of sounds, but…it consists of sounds arranged in orderly manner according to numerous obvious principles as well as to a still greater number of subtle and hidden relationships which evade formulation. In this meaning, form is so essential to music that it is difficult to imagine a procedure by which it could be avoided [7].
\nThe musical approach to analysis exposes the stylistic features of the piece, the conventions and the exceptions in the application of those features by the composer and the performers of the piece. In this approach, the analyst is trying to appreciate the composer’s application of expressive variables in music—like tonality, rhythm, form, tempo, metre, timbre, intensity and texture.
\nIn the sociocultural approach, music is considered not just as a sonic material but also a symbolical representation of entities, deities, communities, age-grades, generations, classes, races, norms and societies. Analysis under this approach must expose and explain the determinate associations that are implied in the musical expression and the functionality of music in society.
\nThe sociocultural issues in music—especially the ‘popular’ genre—are implicated more in the processes and negotiated decisions that lead to the creation and consumption of the musical product, than in the textual pronouncements that make up the lyrics of the song, those belong to the ideological angle of the piece. Other sociocultural-related issues in popular music include recording/performance contracts, copyright protection, signing on a record label, publicity, promotion, marketing, publishing, artiste-patron agreements, collaborations, public performance and broadcasting rights and hiring the services of an entertainment law attorney.
\nPersonal opinions held by individual composers and other stakeholders in the musical enterprise, expressed in the textual materials and the musical product, form the bulk of the ideological stance of the music. These opinions could be philosophical, religious, spiritual, political, interpersonal relationships and the total world-view of the composers, which are perceptible, not just in the lyrics but also in the CD sleeves, video clips, interviews, press releases, personality image of the artistes and their style of usage of metalanguage and polyglottism.
\nIn the historical approach, the analyst embarks on a retrospective study of schemata of music and how they have developed over time. He/she studies the major stylistic features that characterize each particular period and relate them to parallel developments in other forms of the arts and sciences of the same period, and how each individual composer has interpreted the dominating music of his/her own time. In addition, she/he exposes the practices that marked the points of transition from one era to the different practices of another era, thereby establishing the trends that distinguish one period from another.
\nThe computer technology which saw its modest beginnings in the 1960s and, within a decade of its development, succeeded in turning the world into a global village, has its impact felt in music production. From the introduction and advancement of music synthesizers and other complementary devices, the once dominating analogue audio recording devices have progressively and dexterously been replaced by digital equivalents [8]. The introduction of computer technology, therefore, started a radical turning point in audio production. This turning point has finally eclipsed the analogue system of recording, giving way to the more efficient, real-time and almost real-life digital system [9, 10, 11].
\nAn audio recording in which the raw sounds emanating from the initial sources are represented by the spacing between pulses (bits) rather than by waves, thereby making the sounds less susceptible to degradation, is known as digital recording. In digital recording, computer programmes are used to manipulate the audio data stored in the form of alphanumeric codes. This manipulation is done through mathematical processes [8, 10, 12]. The process involves ‘the description of a sound waveform as sequence of numbers representing the instantaneous amplitudes of the wave over small successive intervals of time’ [9]. Some of the advantages of the digital technique, according to Salt (as cited in [13]), are:
\nIn digital recording systems, many of the distortions are removed because the continuously varying sound signal is transformed into a digital signal (a sequence of binary values, or a series of bits), by a process called quantizing or quantization, as soon as it is captured. This enables the stored sound data to be checked and processed so that it can, in theory, be reproduced exactly as it was recorded.
\nThe basic advantage of digital storage of the musical sound is the ease of processing, manipulation and analyzing of the data. This flexibility of the digital data has made it a nearly effortless task to create sound effects, enhance quality and ease editing of the recorded sound. This flexibility makes it possible for the analyst to not only engage but also interact with the digitized items. However, the challenge lies in the reversibility of such digitized items.
\nThe creative and production processes involve computer synthesis in digital recording—starting from the generation of audio samples from analogue sources to conversion to digital equivalents through series of voltage steps, electronic means of creating, filtering and modifying sound—mediated via special interfaces such as effects boxes, tone generators, MIDI, drumulator, vocoder and keyboard sampler.
\nThrough the use digital audio software such as Cakewalk, Cubase, Sonar, Nuendo, Adobe Audition and Fruity Loops, among others, audio projects ranging from sampling, sequencing, quantizing, voicing, boosting, compressing, mixing, recording, re-mixing, etc. are successfully delivered. Music analysis is greatly favored by the instant generation of notated music scores by these audio production music software.
\nIn the application of the computer as the analytical tool, the musical elements are codified and, thereby, reduced to icons which are packaged in music software (programmed). The programme then becomes the model to be observed and interacted with by the analyst, in a multimedia of presentation. The reduction of the elements into electronic forms is the major duty of the computer programmers. The analyst, working with professional computer programmers who are adepts in computer programming language, reduces the issues and elements in music into icons for which the options for digitized items are only a click away.
\nIn analyzing the musical elements of tonality, rhythm, form, tempo, metre, timbre, intensity, texture, vocal/performance techniques and orchestration, among others, the items are reduced to icons backed up with motion pictures, simulations, musical examples, sound clips, diagrams, graphs and charts, all of which are activated as soon as the right icon is clicked at. By engaging the computer programmes, any analyst can dissect a piece of music by selecting and clicking at the right icons to access and interact with the compositional rationalizations of the music composer.
\nSociocultural, ideological and historical issues in music can equally, and easily, be reduced to electronic forms for analysis in the same interactive manner as in musical issues. In this multimedia formats, computer-aided music analysis encourages interactive relationships between the analyst and the models through the use of images (still and motion), animations, speeches, sounds, figures and, mostly, music. It is advantageous that the analyst can quickly access information, get immediate feedback, move at his/her own pace, monitor his/her progress, motivate him/herself and learn independently [14, 15, 16, 17].
\nIn this era of digital technology, the prospects of computer-aided music analysis have inspired computer programmers to create many programmes with different capabilities and limitations. Some of the programmes are the Digital Alternative Representation of the Musical Score (DARMS), Humdrum, Finale, Sibelius, Lemon and Studio 4. Others with some specialization in audio analysis include Fourier, SoundEdit, AudioSculpt, SARA and Lemur [18, 19, 20].
\nSociocultural issues in music are implicated more in the processes and negotiated decisions that lead to the creation and consumption of the musical product than in the textual pronouncements that make up the lyrics of the song. Here music is considered not just as a sonic material but also a symbolical representation of entities, deities, communities, age-grades, generations, classes, races, norms and societies. Analysis must expose and explain the determinate associations that are implied in the musical expression. The functionality of music in society becomes the main focus of the analyst. Is the purpose for music-making self-fulfilling or group-fulfilling? Is it to train, to communicate, to enlighten, to worship, to praise, to heal, to supplicate, to mourn, to mock, to invoke, to curse, to defy, to survive or what? And what social events are they linked with?
\nWhether on a live stage or an electronic stage, one observes that the emotions expressed by music performers are not always felt by the artistes; sometimes they are feigned to create a contingent, a utilitarian or an esthetic value. The simulated emotions are constructively packaged by the producers to disguise the commercial intent, thereby succeeding in presenting the art as necessary, useful or entertaining in itself.
\nThe stochastic nature of the foregoing makes it difficult for the computer to detect or decode the creative intent of the composers of such musical phenomena and activities. This limitation also applies to the subject matter encoded in CD sleeves, video clips, interviews, press releases, personality image of the artistes and their style of usage of metalanguage and polyglottism.
\nThe foregoing makes the human-machine collaboration imperative. While the computer analyzes the machine-modifiable music notations, simulations, animations and icons, the rest of the variables that are largely psychological, sociological and philosophical are humanly analyzed to make up for the limitations of the machine. This model of collaboration therefore bestrides the music domain and other related disciplines including visual arts, architecture, design and film-making and editing.
\nThe chapter has proposed the effective collaboration of human and the machine in analyzing music—especially in this twenty-first century where the computer age has expanded the frontiers of the audiovisual creativity—via the system of computer-aided music analysis.
\nResources for the composition and performance of electronic music have recently been broadened considerably through the introduction and use of the Musical Instrument Digital Interface (MIDI). The MIDI, as a remarkable system, enables composers to manage quantities of complex information and allow computers, synthesizers, sound modules, drum machines and other electronic devices from many manufacturers to communicate with each other. Originally of interest only to a few so-called serious composers, today MIDI-based systems, are used to analyze and teach music, write and perform film scores, create rhythm tracks for popular music and provide music for computer games. Also with the MIDI, the numbers of ways in which the electronic synthesizer may serve composers seem limited only by the boundaries of human initiative and perception [21, 22].
\nMusic, bestriding art and science, affects a zone where emotion intersects with processes taking place at a corporeal level and is capable of producing tactile, sensuous and involuntary reactions. The musical sound has the ability to change the emotional and physical states of people and could equally alter one in many ways, depending on the composer’s manipulation of musical elements and the producer’s manipulation of post-production sonic enhancements [23].
\nBy acknowledging this protean nature of music, the chapter has identified the limitations of a single mode of analysis and therefore recommends the dual mode of man-machine collaboration in ‘diginalysis’. In this effective collaboration, the computer analyzes the machine-modifiable music notations, simulations, animations and icons, while the human handles the psychological, sociological and philosophical elements of music. While the utilitarian value of this effective collaboration collapse time and energy by providing immediate feedback, technical accuracy and dependable results, the contingent will benefit other related disciplines including visual arts, architecture, design and film-making and editing.
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