Adaptive block greedy algorithms for receiving multi-narrowband signal in compressive sensing radar reconnaissance receiver

This paper extends the application of compressive sensing (CS) to the radar reconnaissance receiver for receiving the multi-narrowband signal. By combining the concept of the block sparsity, the self-adaption methods, the binary tree search, and the residual monitoring mechanism, two adaptive block greedy algorithms are proposed to achieve a high probability adaptive reconstruction. The use of the block sparsity can greatly improve the efficiency of the support selection and reduce the lower boundary of the sub-sampling rate. Furthermore, the addition of binary tree search and monitoring mechanism with two different supports self-adaption methods overcome the instability caused by the fixed block length while optimizing the recovery of the unknown signal. The simulations and analysis of the adaptive reconstruction ability and theoretical computational complexity are given. Also, we verify the feasibility and effectiveness of the two algorithms by the experiments of receiving multi-narrowband signals on an analog-to-information converter (AIC). Finally, an optimum reconstruction characteristic of two algorithms is found to facilitate efficient reception in practical applications.