基于m-Capon的多阵列直接定位算法

Multi-array Direct Position Determination Based on m-Capon

多重信号分类(Music)直接定位算法需要先估计目标个数,然后根据目标个数估计确定其噪声子空间,进而得到空间谱函数。在低信噪比情况下,目标个数估计的错误往往会导致直接定位算法的失效。针对上述问题,提出了一种基于m-Capon的多阵列目标直接定位算法。该算法综合了Capon算法无需目标个数估计和Music算法定位性能较高的优点,在不进行目标个数估计的情况下,利用近似估计的方法得到逼近于Music算法的空间谱函数,解决了Capon算法在低信噪比下性能不足的问题。仿真结果表明,在无需估计目标个数的条件下,所提算法的性能与Music算法的性能大致相同,且逼近于克拉美罗下界。

The multi-signal classification(Music)algorithm needs to estimate the number of targets first and determine the noise subspace according to the estimated target number,and then the spatial spectral function is obtained. In the case of low signal-to-noise ratio,the error of the estimated number of targets often leads to the failure of the direct positioning algorithm. A multi-array target direct positioning algorithm based on m -Capon is proposed to solve the problems.This algorithm combines the advantages of Capon without estimating the target number and the higher positioning performance of Music. Without the estimation of the target number,the approximate spectral method is used to approximate the spatial spectrum function of Music. The algorithm solves the problem of low positioning performance of Capon algorithm at low SNR. The simulation results show that the performance of the proposed algorithm is almost the same as that of Music algorithm and approachs CRLB without estimating the number of targets.