Joint Filter and Waveform Design for Radar STAP in Signal Dependent Interference

TL;DR

This paper addresses the complex problem of joint waveform and filter design in radar STAP, proposing iterative algorithms that optimize each component separately to manage non-convexity and computational challenges.

Contribution

It introduces constrained alternating minimization algorithms for waveform and filter design in radar STAP, handling waveform dependence of clutter correlation.

Findings

Algorithms are individually convex in filter or waveform variables.

Proposed methods improve computational efficiency.

Applicable to waveform design in radar STAP systems.

Abstract

Waveform design is a pivotal component of the fully adaptive radar construct. In this paper we consider waveform design for radar space time adaptive processing (STAP), accounting for the waveform dependence of the clutter correlation matrix. Due to this dependence, in general, the joint problem of receiver filter optimization and radar waveform design becomes an intractable, non-convex optimization problem, Nevertheless, it is however shown to be individually convex either in the filter or in the waveform variables. We derive constrained versions of: a) the alternating minimization algorithm, b) proximal alternating minimization, and c) the constant modulus alternating minimization, which, at each step, iteratively optimizes either the STAP filter or the waveform independently. A fast and slow time model permits waveform design in radar STAP but the primary bottleneck is the computational complexity of the algorithms.