Tien M. Nguyen

By Tien M. Nguyen, Andy T. Guillen, Sumner S. Matsunaga, Hien T. Tran and Tung X. Bui

This chapter describes an innovative modeling and simulation approach using newly proposed Advanced Game-based Mathematical Framework (AGMF), Unified Game-based Acquisition Framework (UGAF) and a set of War-Gaming Engines (WGEs) to address future space systems acquisition challenges. Its objective is to assist the DoD Acquisition Authority (DAA) to understand the contractor’s perspective and to seek optimum Program-and-Technical-Baseline (PTB) solution and corresponding acquisition strategy under both the perspectives of the government and the contractors. The proposed approach calls for an interdisciplinary research that involves game theory, probability and statistics, and non-linear programming. The goal of this chapter is to apply the proposed war-gaming frameworks to develop and evaluate PTB solutions and associated acquisition strategies in the context of acquisition of future space systems. Our simulation results suggest that our optimization problem for the acquisition of future space systems meets the affordability and innovative requirements with minimum acquisition risk.

Part of the book: Simulation and Gaming

By Tien M. Nguyen, Hung H. Nguyen, Tom Freeze and Andy Guillen

In a modern mobile satellite communication (SATCOM) system, a ground terminal receiver receives a radio frequency signal that is demodulated to generate a baseband digital signal waveform containing a self-clocking bit stream of digital data. The received baseband digital signal waveform is recovered and tracked using a timing recovery loop (TRL). The traditional TRLs use early-and-late gates, digital transition tracking, filter-and-square, and delay-and-multiply functions. In bit timing detection, the bit stream is self-clocking and the timing differential dithers about correct bit timing in the TRLs. For mobile satellite communication environments, the traditional TRLs drop lock when the loop signal-to-noise ratio (SNR) is smaller than a threshold value or the residual Doppler frequency is larger than the operating loop bandwidth. After dropping lock, the traditional TRLs experience long hang up time due to the need to reacquire the timing pulses. Recently, random walk filters (RWF) have been adapted to improve the bit clock locking stability and are applied to recover bit timing information of a digital data stream. This chapter describes random walk model for timing jitter and discusses how RWF solution can address the timing recovery challenges in mobile satellite communication environments.

Part of the book: Recent Trends in Communication Networks

By Tien M. Nguyen

This chapter discusses existing and future trends on the design and build of “Modular” and “Open” satellite Bus and mission payload along with practical design issues associated with the use of Modular Open System Approach (MOSA). Existing modular Bus and mission payload architectures for typical commercial, civilian, and military satellite systems will be discussed. The chapter provides space industry views on “Open” versus “Close” interfaces design and addresses the challenges associated with open interfaces using Open System Architecture (OSA) approach using MOSA principles. The system interfaces discuss in this chapter include (i) internal to satellite Bus and mission Payload (PL), (2) between satellite Bus and mission payload, and (3) external to both satellite Bus and mission payload.

Part of the book: Satellite Systems

By Tien M. Nguyen

The objective of this chapter is to (i) define System-of-Systems Enterprise (SOSE), SOSE Concept of Operations (CONOPS), and SOSE Architecture (SOSEA) CONOPS assessment, and (ii) discuss their differences using examples from existing space and airborne systems. The chapter also describes the SOS design challenges and presents an SOSE Architecture design approach addressing these challenges. In addition, DOD Architecture Framework Version 2.02 (DODAF-v2.02) views will be discussed along with a recommendation for a set of key DODAF views to capture system architecture artifacts with practical examples involving SOS Enterprise architectures for notional space-based communications system and manned airborne Intelligence, Surveillance, and Reconnaissance (ISR) platform.

Part of the book: Systems-of-Systems Perspectives and Applications

By Thomas O. Freeze, Tien M. Nguyen and Charles H. Lee

This chapter discusses the implementation of System-of-Systems Enterprise Architecture (SOSEA) CONOPS assessment framework and models in Matlab, and presents preliminary results concerning SOSEA resiliency in the presence of a notional Radio Frequency Interference (RFI) scenario. The chapter provides an overview of the SOSEA CONOPS Assessment Framework, and discusses related SOS Resiliency Models including Resilient Assessment Index Against RFI (RAI-RFI), Spectrum Resiliency Assessment Index (SRAI), and Resilient Capacity (RC).

Part of the book: Systems-of-Systems Perspectives and Applications

By Tien M. Nguyen and Tung X. Bui

Part of the book: Systems-of-Systems Perspectives and Applications

By Tien M. Nguyen

This chapter discusses advanced modeling, simulation and analysis (MS&A) approaches for supporting complex space system, gaming and decision support system (DSS) using systems-of-systems perspective. The systems-of-systems MS&A approaches presented here also address capability-based approach for supporting US defense acquisition life cycle with a laser focus on the pre-award acquisition phase and combined game theory and wargaming for acquiring complex defense space systems. The chapter also provides an overview of existing models and tools for the design, analysis and development of the government reference system architecture solution and corresponding acquisition strategy in a complex defense systems-of-systems environment. Although, the proposed MS&A approaches presented here are focused on defense space systems, but the approaches are flexible and robust that can be extended to any civilian and commercial applications.

Part of the book: Simulation Modeling