A robust single-port DOA estimation algorithm based on compressive sensing

To enhance the performance of multi-targets direction of arrival (DOA) estimation using compressive sensing(CS), when there exists different gain among radio frequency (RF) channels and mismatch error between system sensing model and target angle information, a novel CS-DOA algorithm based on single-port array is proposed. First, a DOA sparse sensing model based on single-port array is derived by exploiting the mismatch between system sensing model and target angle information. Then, the Dantzig Selector (DS) algorithm and genetic algorithm are employed to optimize the target angle information and system model mismatch error iteratively. Comparing to traditional CS-DOA algorithms, this method can suppress the system model mismatch error and inconsistency gain among different RF channels effectively. Numerical examples show that the presented algorithm performs better than traditional DOA algorithms for signals with any coherence and offers higher angle resolution and estimation accuracy．