Performance analysis of bootstrap based distributed detector under correlated K-distributed clutter

To deal with the signal detection with multiple sensors under correlated K-distributed clutter with unknown parameter, a bootstrap based distributed detector (BBDD for short) was presented where detection decisions of local sensors are transmitted from each bootstrap detector to the data fusion center, where the overall decision is made based on k-out-of-N fusion rule. Considering the assumption that the samples from different range cells are independent, block is extracted along the direction of azimuth. Monte Carlo simulations show that the BBDD has much higher CFAR capability than the distributed generalized sign detector (DGSD for short) with the same fusion rule proposed in the literature. However, under independent k-distributed clutter, BBDD has a signal-to-clutter loss of up to 3 dB compared with DGSD. The BBDD, therefore, is a good choice for signal detection under correlated K-distributed clutter.