基于CS-CoSaAMP的超宽带多径信道估计

针对匹配追踪类算法要求稀疏度作先验条件的不足，提出压缩采样自适应匹配追踪（CoSaAMP）新算法。结合完备的冗余字典，算法在稀疏度未知时，可以通过自适应调整可变步长逐步逼近信道的稀疏度，用于解决超宽带信道的重建问题。仿真结果表明，提出的CoSaAMP算法性能收敛速度快，估计效果好，可有效用于实际超宽带信道估计。

UWB multi-path channel estimation based on CS-CoSaAMP algorithm

To solve the insufficiency that Matching Pursuit algorithm is required the sparsity of the channel impulse response, the Compressive Sampling Adaptive Matching Pursuit（CoSaAMP）algorithm is proposed. Together with the redundant dictionary, and even if the sparsity is unknown, the channel impulse response is recovered accurately by the adaptive adjusting the variable step length and step by step approximating the sparsity of channel, thus solving Ultra-WideBand（UWB） channel reconstruction problem. Simulation results show that, the algorithm has a good estimation performance and a high convergence speed, and can be used to solve practical UWB channel estimation.