Range Spread Target Detection Using Clutter Prior Information and Reference Data

For the radar target detection, the estimation performance of clutter covariance matrix of the cell under test is directly related to the detection performance. There are two approaches to estimate the clutter covariance matrix, using some reference data, or using some prior information of the clutter. In this paper, we consider the problem of range spread target detection using both prior information of clutter covariance matrix and some reference data. One-step generalized ratio test (GLRT) and two-step GLRT are proposed based on Bayesian approach. Compared with conventional detection algorithms, which only uses prior information or reference data, these detection algorithms have more flexibility. The computer simulation results show that, using the both prior information and reference data, the detection performance can be improved significantly. And the algorithms proposed in this paper are more robust than other algorithms under the small sample size condition or mismatched prior information condition.