Radar Signal Recovery using Compressive Sampling Matching Pursuit Algorithm
In this study, we propose compressive sampling matching pursuit (CoSaMP) algorithm for sub Nyquist based electronic warfare (EW) receiver system. In compressed sensing (CS) theory time frequency plane localisation and discretisation into a NxN grid in union of subspaces is established. The train of radar signals are sparse in time and frequency can be under sampled with almost no information loss. The CS theory may be applied to EW digital receivers to reduce sampling rate of analog to digital converter; to improve radar parameter resolution and increase input bandwidth. Simulated an efficient approach for radar signal recovery by CoSaMP algorithm by using a set of various sample and different sparsity level with various radar signals. This approach allows a scalable and flexible recovery process. The method has been satisfied with data in a wide frequency range up to 40 GHz. The simulation shows the feasibility of our method.