Radar Signal Recovery using Compressive Sampling Matching Pursuit Algorithm
Keywords:
Compressed sensing, CoSaMP, EW, RMPI, RIP, Signal recovery
Abstract
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 N×N 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.
Published
2016-12-23
How to Cite
Rao, M., Naik, K., & Reddy, K. (2016). Radar Signal Recovery using Compressive Sampling Matching Pursuit Algorithm. Defence Science Journal, 67(1), 94-99. https://doi.org/10.14429/dsj.67.9906
Issue
Section
Electronics & Communication Systems
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