基于稀疏分解的毫米波辐射计信号去噪

MMW Radiometer Signal Denoising Based on Sparse Decomposition

信号的稀疏逼近可以取代原始数据,从而降低信号处理的成本。根据稀疏分解不断地跟踪并提取最能匹配于原始信号及其残差信号的原子向量作为信号的特点,提出3σ准则选取阈值,将其应用于毫米波辐射计信号的去噪,并用粒子群算法克服计算量过大难以实现的问题。实验表明:选取适当的迭代停止条件,即可获得最优的去噪效果,并且在普通计算机上就可以快速地完成计算。

Sparse approximation of signal replaces original data to reduce cost of signal processing.Atom vector is constantly tracked and picked up from original signal or its survivor as signal segment according to sparse decomposition.In millimeter wave radiometer signal denoising,3σ rule is introduced to select threshold,and particle swarm optimization is used to overcome the oversized computation.Experiments results show that appropriate iterative stopping condition can receive better denoising effect,and the met...