Design of Customized Adaptive Radar Detectors in the CFAR Feature Plane

TL;DR

This paper presents a novel methodology for designing customized adaptive CFAR radar detectors in Gaussian noise, ensuring specified detection probabilities and false alarm rates even with unknown disturbance statistics.

Contribution

It introduces a new feature-plane-based design approach and a reduced-complexity algorithm to optimize detector performance under various conditions.

Findings

Effective approximation of desired detectors achieved

Ensures fixed false alarm probability under unknown noise

Controls detection behavior with signal mismatch

Abstract

The paper addresses the design of adaptive radar detectors having desired behavior, in Gaussian disturbance with unknown statistics. Specifically, given detection probability specifications for chosen signal-to-noise ratios and steering vector mismatch levels, a methodology for the optimal design of customized CFAR detectors is devised in a suitable feature plane based on maximal invariant statistics. To overcome the analytical and numerical intractability of the resulting optimization problem, a novel general reduced-complexity algorithm is developed, which is shown to be effective in providing a close approximation of the desired detector. The proposed approach solves the open problem of ensuring a prefixed false alarm probability while controlling the behavior under both matched and mismatched conditions, so enabling the design of fully customized adaptive CFAR detectors.