AR Model-based Rapid Detection of SAR Phase History Data with Wald Tests

In this paper, we report a novel algorithm of automatic target detection applied directly to the SAR phase history data in a state of non-imaging. The proposed algorithm is based on a sequential Wald test. The inherently time-sequential behavior of the SAR phase history is modeled as a stationary 2D autoregressive (AR) stochastic process. The sequential Wald test is employed to dynamically ascertain the presence or absence of a target while the SAR phase history data is being collected during SAR platform flying along its trajectory. Compared with conventional image-based detection methods, both simulation and experimental results show that significant savings in collection aperture can be obtained using the proposed algorithm which dynamically control the SAR resource allocation (azimuth aperture dwell time) to increase system search rate capabilities