Philip D. West

Systems-of-Systems Analysis of Ballistic Missile Defense Architecture Effectiveness Through Surrogate Modeling and Simulation

Analysis of a ballistic missile defense (BMD) system effectiveness is limited infidelity due to the inherent complexity of the subject. A BMD battle manager must examine a scenario where many participants interact in a process taking a target from sensor detection through intercept kill. Each participant evolves independently such that the battle management process functions as a true system-of-systems (SoS). Proper SoS analysis requires architecture level engineering, dealing with component functionality allocation and inter-component interaction rather than the internal workings of individual participants. Methods that address BMD effectiveness have been documented, but each sacrifices analysis fidelity of both process elements and individual participants to enable timely decision making. Modeling and simulation (M&S) tools can now be brought forward in architecture level analysis by creating neural network surrogate models of those tools, which are equation representations of those M&S tools which can be executed rapidly with negligible loss in fidelity. Surrogate models were created of a BMD analysis tool including multi-sensor fusion target tracking codes. Results will show the benefit of integrating M&S to architecture level analysis. Specific examples include sensitivity of operational level metrics to formation of an integration tracking picture, and the enabling architecture level decision making.

Assessment of the relationship of cerebral hemisphere arousal asymmetry to perceptual asymmetry

This study examined the hypothesis that characteristic individual differences in cerebral hemisphere arousal asymmetry are related to individual differences in perceptual asymmetry observed in verbally based visual half-field tasks. The study used electrophysiological measures of arousal asymmetry rather than behaviorally derived measures (Levy, Heller, Banich, & Burton, 1983). Measures of alpha asymmetry were obtained from 20 right-handed males during a baseline relaxation condition and during a visual half-field version of the lexical decision task. Reaction time measures of perceptual asymmetry were obtained during this task. The results indicated that a basal arousal asymmetry measured at the temporal recording location during the baseline condition was significantly related to individual perceptual asymmetry during the subsequent lexical decision task. This basal arousal asymmetry was relatively stable across different task conditions. A task-related arousal asymmetry measured at the parietal location during the lexical decision task also made a significant contribution in predicting individual perceptual asymmetry. These two measures of individual arousal asymmetry were able to predict 50% of the variance in perceptual asymmetry. The implications of the results for explaining more wide-ranging individual differences in behavioral style and personality are discussed.

Tracking in the presence of range deception ECM and clutter by Decomposition and Fusion

Range deception, such as range-gate-pull-off (RGPO) is a common electronic countermeasure (ECM) technique used to defeat or degrade tracking radars. Although a variety of heuristic approaches/tricks have been proposed to mitigate the impact of this type of ECM on the target tracking algorithms, none of them involve a systematic means to reject the countermeasure signals. This paper presents a general and systematic approach, called Decomposition and Fusion (DF) approach, for target tracking in the presence of range deception ECM and clutter. It is effective against RGPO, range-gate-pull-in, and range false target ECM techniques for a radar system where the deception measurements have virtually the same angles as the target measurement. This DF approach has four fundamental components: (a) decomposing the validated measurements by determination of range deception measurements using hypothesis testing; (b) running one or more tracking filters using the detected range deception measurements only; (c) running a conventional tracking-in-clutter filter using the remaining measurements; (d) fusing the tracking filters by a probabilistically weighted sum of their estimates. Several algorithms within the DF approach are discussed.

A MIMO radar benchmarking environment

With the growing amount of research being devoted to the concept of multiple-input multiple-output (MIMO) radar, there has been a lack of a common simulation and benchmarking environment for determining the viability and cost-effectiveness of MIMO radar architectures and algorithms. To this end, GTRI has developed a MIMO Benchmark environment to serve this purpose, which is to be made publically available to researchers in order to compare the performance of MIMO techniques with those of more conventional phased array radar systems. This paper describes the problem that the MIMO Benchmark is intended to be used to assist in solving, in the form of a new challenge problem for the MIMO community, as well as providing a summary of the architecture of the MIMO Benchmark infrastructure.123

ECM modeling for assessment of target tracking algorithms

We describe techniques, concepts, and important issues associated with the development of electronic countermeasures (ECM) models for testing advanced target tracking algorithms. The developments are specifically geared toward the benchmark radar model which has been presented by Blair et al. (see Proc. ACC, p.2071-5, 1994, and Proc. ACC, p.2601-05, 1995). Our ECM focus is specifically on range denial and range deception ECM techniques.

On the observability of linear stochastic switching systems

In this paper, we investigate the observability and detectability of stochastic discrete-time hybrid switching systems. The observability test is based on a mutual information measure between the system state and the observations. Monte Carlo results and an upper bound are presented.

Tracking a maneuvering target using jump filters

The concept of the jump filter, developed in previous work, is employed to track the maneuvering targets in the benchmark problem. The jump filter, which is based on the technique of input estimation, provides a simple and straightforward approach to track maneuvering targets. The jump filter tracks the benchmark data with an average track loss of about 1% using a 2 Hz sample rate.

Tracking a maneuvering target in the presence of false returns and ECM using a variable state dimension Kalman filter

In this paper, we show the performance of a variable state dimension Kalman filter for tracking a maneuvering target under the real-world conditions defined in the second benchmark problem. The second benchmark problem extends the first benchmark problem by including false alarms (FA) and electronic countermeasures (ECM). A modified version of the nearest neighbor PDA data association method of Fitzgerald (1986) is used to handle multiple measurement conditions. Adaptive waveform and dwell revisit time selection methods, and track filter coasting, are used to handle the uncertainties introduced by false alarms, missed detection, maneuvers, and ECM. Special features for integrating the adaptive methods into the variable state dimension filter are discussed. The results of this paper should provide a baseline to which other more sophisticated tracking and data association approaches can be compared.

Systems-of-Systems Analysis of Ballistic Missile Defense Architecture Effectiveness through Surrogate Modeling and Simulation

Traditionally, the analysis of Ballistic Missile Defense System (BMDS) effectiveness has been limited in fidelity due to the inherent complexity of the subject. Indeed, the BMDS battle management process involves monitoring and controlling the actions of many interacting participants (e.g. radar sensors, communications networks and interceptor missiles) in a process whereby a target moves from launch through sensor detection through intercept kill assessment. Because the actions of each participant may evolve independently, the battle management process functions as a true system-of-systems (SoS). Proper SoS analysis requires architecture level engineering, dealing with component functional allocation and inter-component interaction rather than the internal workings of individual participants. Although prior work has been identified that addresses BMD effectiveness at the SoS level, each method sacrifices analysis fidelity of both process elements and individual participants to enable timely decision making. This paper proposes a modeling and simulation (M&S) framework that supports architecture level analysis of the BMDS. The key innovation is the application of neural network surrogate models, which are representations of other high- or medium-fidelity M&S tools, and can be executed rapidly with negligible loss in fidelity. Surrogate models were created of a BMDS analysis tool that included multisensor target tracking and fusion codes. Results will show the benefit of integrating M&S to architecture level analysis. Specific examples include sensitivity of operational level metrics to formation of an integration tracking picture, and the enabling architecture level decision making.

Extracting in-phase and quadrature signal components from a bandlimited real signal using a closed form optimal (MSE) halfband multirate filter design and its implementation on the Motorola DSP56001/DSP56ADC16

Extraction of the in-phase (I) and quadrature (Q) components from an RF signal is an important problem in radar and communication systems. In analog systems, the image spur suppression is a function of the phase and amplitude balance between the mixers and splitters in the two channel of the I/Q demodulation network. In the proposed system, an all digital scheme is described that allows arbitrary image spur rejection to be achieved by increasing the filter coder. An MMSE optimal FIR halfband filter is proposed and results are presented from a real-time implementation on the Motorola DSP56001 digital signal processor and the DSP56ADC16 delta-sigma A/D converter.<<ETX>>