Abstract
For adaptive detectors, the presence of discrete sea spikes in sea clutter will lead to remarkable mismatch between the true and estimated value of covariance matrix, especially in higher sea states, thus affecting target detection performance. In order to solve this problem, a new knowledge-aided covariance matrix estimation method based on scene classification is proposed in this paper. The first layer of prior knowledge is the marker information given by sea spike discrimination and extraction results, and the second layer of prior knowledge is provided by long time window of sea spike samples around the cell under test (CUT) and their parameter model. The influence of background nonhomogeneity on covariance matrix estimation is reduced effectively by the method, and verification results with measured sea clutter data indicate that it can improve target detection performance effectively in sea spike background.
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