An Expert system approach to bistatic space-time adaptive processing

Date of Award

2021

Degree Name

Ph.D. Electrical and Computer Engineering

Department

Department of Electrical and Computer Engineering

Advisor/Chair

Andrew Bogle

Abstract

Space-Time Adaptive Processing (STAP) is a modern radar signal processing technique that leverages additional Degrees of Freedom (DoF) to cancel clutter from a background environment and produce detections of slow-moving targets. STAP is well-documented and understood; however, bistatic applications, or applications in which a radar transmitter and receiver are physically separated, present additional complications. This work explores techniques in Bistatic Space-Time Adaptive Processing (B-STAP) for Ground-Moving Target Indication (GMTI)---the detection of slow-moving surface targets through ground clutter. Due to the complexity and availability of B-STAP data, the evaluation of bistatic algorithms is challenging. A simulation framework has been created to test and evaluate monostatic and bistatic STAP algorithms, mitigating the lack of representative test data. The framework leverages foundational techniques and characteristics to provide a flexible and extensible mechanism for testing and evaluation. Additionally, the design of a new pluggable bistatic Expert System (ES) processor is presented. The ES leverages existing data excision and warping techniques and pairs them with new Range-Based Compensation (RBC) and Clutter Scoring methods to optimize covariance estimation. The simulation framework is used to evaluate the effectiveness of the ES compared to a variety of previously established bistatic processing techniques. The results validate the approach taken in the ES and provide a path for future exploration.

Keywords

Electrical Engineering, bistatic radar, space-time adaptive processing, bistatic stap, stap, radar, expert system

Rights Statement

Copyright © 2021, author.

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