Compensating for Interference in Sliding Window Detection Processes using a Bayesian Paradigm

TL;DR

This paper explores a Bayesian method for designing sliding window radar detectors that maintain a constant false alarm rate while effectively managing interference from targets, improving detection reliability in modern radar systems.

Contribution

It introduces a Bayesian framework for constructing sliding window detectors capable of handling interference while preserving the constant false alarm rate property.

Findings

Bayesian approach effectively manages interference in radar detection.

Detectors maintain constant false alarm rate with improved interference handling.

Enhanced radar detection performance in modern high-resolution systems.

Abstract

Sliding window detectors are non-coherent decision processes, designed in an attempt to control the probability of false alarm, for application to radar target detection. In earlier low resolution radar systems it was possible to specify such detectors quite easily, due to the Gaussian nature of clutter returns, in an X-band maritime surveillance radar context. As radar resolution improved with corresponding developments in modern technology, it became difficult to construct sliding window detectors with the constant false alarm rate property. However, over the last eight years this situation has been rectified, due to improved understanding of the way in which such detectors should be constructed. This paper examines the Bayesian approach to the construction of such detectors. In particular, the design of sliding window detectors, with the constant false alarm rate property, with the capacity to manage interfering targets, will be outlined.