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This paper deals with the problem of traditional constant false-alarm rate (CFAR) detection methods are difficult to adapt the temporal and spatial varying K-distributed clutter. An improved clutter-map detector combining a near optimal detector under K-distributed clutter and Nitzberg clutter-map technology is proposed. Obtaining a stable test statistic estimate of the clutter of the cell under test (CUT) according to the data of the CUT from past several scans, and the modified clutter map stores the test statistic estimate of each CUT. Each test statistic estimate is updated based on the data from a new scan as the new test statistic estimate of the current primary data. According to this proposed method, Nitzberg clutter-map technology can be combined with many different detectors to adapt different clutter model. Then the proposed method and the existing methods are compared from the aspect of performance with simulation data. The experiments results demonstrate that the proposed method has better performance than the existing detectors.
Inspec keywords: radar clutter; object detection; statistical testing; radar detection; estimation theory
Subjects: Radar equipment, systems and applications; Signal detection; Other topics in statistics