Adaptive Sampling with Bayesian Compressive Sensing in Radar Sensor Networks and Image
The theory of Bayesian compressive sensing is briefly introduced and the differential entropy for recovery signal is deduced. An evaluation index based on differential entropy is devised and the adaptive compressive sampling procedure without any prior information of the measured signals is presented in block manner. Numerical simulations on random step signal and real radar signal and 2D image verify that the proposed adaptive sampling algorithm has good performance. This novel algorithm offers great potential for adaptive compressive sampling in real time radar signal and image.