Abstract
Target detection is one of the most important parts of high-frequency surface wave radar (HFSWR) signal processing, to find targets in noise or clutter and obtain targets’ information. However, some factors, such as the influence of clutter and the increase of detection range, will degrade the signal-to-clutter ratio (SCR). In the low SCR scenario, the classical detector of HFSWR, which uses the amplitude of receipt signal only, could hardly detect targets. To solve this problem, this study proposes a novel detector called joint domain localised matrix constant false-alarm rate (CFAR) detector based on receipt signal's multi-dimensional information. This detector employs joint domain localised algorithm to get signal information in angle and Doppler domain, and use information geometry method to map them to Hermitian positive-definite (HPD) matrix space which can be depicted as Riemannian manifold. Then, based on HPD matrix, in the range domain the matrix CFAR detector is built to detect targets. The experiments’ results verify that the detector can improve radar detection performance effectively.
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