Abstract
This paper proposes a waveform-cross-entropy (WCEN)-based detection scheme to detect manoeuvring range-spread targets in homogeneous weather clutter. The input of the detector is composed of complex-valued high resolution range profiles (HRRPs) from a train of coherent pulses in the observation window. The observation window contains a detection window and a reference window, where the received data in reference window is clutter-only secondary data. The detector consists of temporal approximate whitening filtering for clutter suppression followed by the waveform-cross-entropy-based detection. The former is operated on the received vector at each range cell to whiten the clutter and enhance target returns. Then, the WCEN of each pair of filtered power-HRRPs is calculated to capture their sparsity, similarity and energy. The average of the WCENs of all the pairs is utilized as the test statistic to decide whether a target is present or not. Finally, we assess the proposed detector by the raw radar target data collected by high range resolution radar and simulated weather clutter. The experimental results show that the WCEN-based detector outperforms the existing detectors in detection performance for manoeuvring range-spread targets.
Highlights
Wideband or ultra-wideband high range resolution radars (HRR) can spatially resolve a target into a number of scatterers distributed along the radial range
These returns distributed along the range cells form a complex high resolution range profile (HRRP) for each pulse
Range-spread target detection is based upon the received complex data matrix composed by the complex HRRPs collected from a train of coherent pulses
Summary
Wideband or ultra-wideband high range resolution radars (HRR) can spatially resolve a target into a number of scatterers distributed along the radial range. The two recent non-coherent detectors in white Gaussian noise, the SSD-GLRT detector [4] and the MCOM detector [5], exploit the waveform characteristics Compared with those detectors in white Gaussian noise, detecting range-spread targets in nonstationary clutter environments is more complicated and has recently received much more attentions [6,7,8,9,10,11,12,13,14,15]. The GLRT-based detector using the 2D model is difficult to efficiently detect high-speed manoeuvring range-spread targets, because too many parameters have to be estimated from the received data of low SNR or SCR. A new detector based upon temporal whitening filters and waveform cross-entropy (WCEN) is proposed to detect high-speed manoeuvring range-spread targets in weather clutter.
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