Use of STAP Techniques to Enhance the Detection of Slow Targets in Shipborne HFSWR

摘要

This paper addresses the detection of low-velocity targets from a shipborne High Frequency Surface Waves Radar (HFSWR). In a shipborne configuration, as a consequence of the ship's motion, the first order of Bragg lines is spread, making the detection of ships more difficult than in an onshore configuration because the Doppler frequency of these targets is expected to appear in the spreading clutter domain. This effect is more problematic as the velocities of the ship and the ship's target present the same order of magnitude. The shipborne HFSWR configuration is similar to the airborne early warning configuration in which low-altitude target echoes are embedded in the ground spread clutter. To counter this effect, signal processing techniques like Space Time Adaptive Processing (STAP) can be used to restore radar performance. During the last 10 years, the abundance of studies to optimize STAP architecture has come from the airborne radar domain. The purpose of this paper is study whether these algorithms can be adapted and implemented on a shipborne HFSWR to help the detection of slow targets. Part 1 of the paper presents a review of the physics of Bragg scattering. In part 2, simulations of Bragg clutter in a motion configuration are presented. Part 3 describes the possible architecture of a STAP processor with respect to HFSWR. Simulations are presented to assess the feasibility of STAP in shipborne HFSWR, and estimation of the clutter covariance matrix is discussed with respect to the characteristics of the radar waveform. Interleaving between the classical HFSWR waveform and a wideband learning waveform is proposed to enable the covariance estimation.