Abstract:

Non-homogeneous background clutter usually results in the performance degradation of traditional adaptive detectors. To improve the detection performance in scarce secondary data environment, an adaptive structured detector of radar targets is addressed herein. By utilizing the persymmetry of the clutter covariance matrix, an adaptive structured detector is designed based on the generalized likelihood ratio test, which enhances the information utilization of the structural character of clutter spectral properties and the clutter in the cell under test. In the sequel, a real domain version is derived. The experimental results show that, the proposed detector has the constant false alarm rate and it performs robustly for different correlations of clutter. It is shown that, the proposed detector outperforms the traditional structured and unstructured detectors in scarce secondary data environment; and this advantage augments as the number of secondary data approaches the available minimum limit.