现代雷达2013，Vol.35Issue(6)：34-37,41,5.
基于迭代自适应稀疏分解的雷达信号去噪
Radar Signal Denoising Via Adaptive Iterative Sparsity Decomposition
摘要
Abstract
Sparse decomposition is effective in separating signal and noise,and it can be used to remove noise.In this paper,a redundancy match dictionary is designed for radar echo signal sparse representation,and the signal sparsity is equal to the detecting target number.As the stop threshold of the sparsity adaptive matching pursuit(SAMP) algorithm is not applicable for sparse decomposition in low signal-to-noise ratio(SNR) conditions,the iteration adaptive matching pursuit(IAMP) algorithm is proposed using normalized residual difference as stop condition,making sparse decomposition adaptively stop according to noise level.Signal sparsity estimation is implemented by way of successive approximation,and much improvement on decomposition accuracy is obtained.Extensive simulation results show that the IAMP algorithm is effective in radar echo signal sparse decomposition in low SNR conditions without sparsity information,and the SNR of sparse decomposition signal is largely improved.关键词
迭代自适应/稀疏分解/匹配追踪/冗余字典/雷达信号Key words
adaptive iteration/ sparse decomposition/ matching pursuit / redundancy dictionary/ radar signal分类
信息技术与安全科学引用本文复制引用
樊甫华..基于迭代自适应稀疏分解的雷达信号去噪[J].现代雷达,2013,35(6):34-37,41,5.基金项目
国家自然科学基金资助项目(61171170) （61171170）
