Rapid Adaptive Matched Filter for Detecting Radar Targets with Unknown Velocity

TL;DR

This paper presents a new Doppler domain localized adaptive matched filter for radar target detection that performs well in complex clutter environments with limited training data, especially when target velocity is unknown.

Contribution

The paper introduces a RPTD-based DDL-AMF detector that outperforms previous methods by not requiring clutter spectrum parameters or RODI measurements.

Findings

Outperforms RDI-based DDL-GLR in complex clutter environments.

Ensures rapid adaptive detection with near-optimum performance.

Operates effectively with unknown target Doppler frequency.

Abstract

This paper introduces a Doppler domain localized (DDL) implementation of the adaptive matched filter (AMF) for radar target detection in severely heterogeneous clutter environments with limited training data. The proposed detector uses the concept of a region of possible target detection (RPTD), a small set of Doppler bins that capture most of the target signal power. This RPTD-based DDL-AMF detector outperforms an earlier suggested DDL implementation of the generalized likelihood ratio (GLR) test, which employs the region of detection improvement (RODI) concept. Unlike the RODI-based DDL-GLR detector, the proposed DDL-AMF detector requires no information on clutter spectrum parameters and no measurements to determine the number and locations of RODIs. Moreover, the performance of the RODI-based DDL-GLR detector falls far below the optimum when the target Doppler frequency is unknown. In contrast, the RPTD-based DDL-AMF detector ensures rapid adaptive detection with near-optimum performance under unknown target Doppler frequency and multimodal clutter spectra.