Compressive Sensing Signal Detection Algorithm Based on Location Information of Sparse Coefficients

Without reconstructing the signal themselves, signal detection could be solved by detection algorithm, which directly processes sampling value obtained from compressive sensing signal. In current detection algorithm, as the judgment criterion, the threshold depends on Monte Carlo simulations, which takes too much time, affecting detection efficiency. Therefore in this paper we propose an algorithm to detect known signal in noise. First, get the sparse coefficients position information of to-be-detected signal in Transform domain. Then, acquire the position information of interested signal based on prior information. Finally, use the correlation of them as judgment criterion to complete detection. Simulation shows that under the same circumstances, compared with traditional algorithm, the algorithm this paper introduced can complete detection rapidly without reducing success rate.

• Type: Journal
• Year: 2010
• Where: JDCTA
• Authors: Bing Liu, Ping Fu, Shengwei Meng, Lunping Guo
• Keywords: Algorithm, Detection, JDCTA 2010, Judgment Criterion