Rapid Adaptive Matched Filter for Detecting Radar Targets With Unknown Velocity

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 captures 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 RODI-based DDL-GLR detector’s performance 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.

Keywords

• Adaptive detection
• adaptive matched filter (AMF)
• constant false alarm rate (CFAR)
• Doppler domain localized (DDL) adaptivity
• generalized likelihood ratio (GLR)
• heterogeneous clutter