Adaptive Detectors for Moving Platform based Distributed Coherent Aperture Radar

Moving platform based distributed coherent aperture radar (MDCAR) is a promising technique for increasing gain, resolution, cost and flexibility. However, inherent grating lobes and coordination errors caused by large internode distance and moving platforms cause great trouble to target detection. To solve this problem, an array configuration accumulation (ACA) method is adopted. The time-varying platform motion is utilized to fill the spatial domain sampling. Then, according to the coherence between each array configuration, coherent accumulated detection (CAD) and non-coherent accumulated detection (NCAD) detectors are designed with robust steering vector estimation. Simulations are provided to validate the effectiveness of the proposed algorithm.