压缩传感方位估计

信源方位估计是阵列信号处理的一个重要问题。基于信源空间分布稀疏的本质,利用压缩传感理论,构造出一种稀疏信源方位估计模型,仿真结果表明,在不考虑噪声的理想情况和满足压缩传感的条件下,不仅可以准确的恢复出原始信源的方位,而且精确的得到各个信源信号的强度,并且,这种新的模型只需要一次时间采样,从而大大降低了成本。

Bearing Estimation of Compressed Sensing

Sources hearing estimation is an important issue in array signal processing area. In this paper, based on the sparsity essence of source spatial distribution and by using compressed sensing theory, anew sparse source bearing estimation model is constructed. The simulation result shows that, under the ideal noise-free environment and the satisfaction of compressed sensing theory, precise estimation of the original sources bearing is realized while the exact source signal strength is obtained, and this new model demands only one single time sampling, thus greatly reducing the cost.