摘要
PADEC算法中引入已知波形信号源的信息,使得相干多径信号的DOA估计性能大大提高,而DEESE算法异于传统空间平滑算法的独特去相关策略,使它在低信噪比、天线阵阵元数较少时有着良好的DOA估计性能。结合这两种算法各自的优点,将DEESE算法的去相关策略应用于PADEC算法中,形成PADEC-DEESE算法。计算机仿真结果表明,PADEC-DEESE算法完全能够实现相干多径信号的DOA估计,并在天线阵阵元数较少、低信噪比情况下的DOA估计精度优于PA-DEC、DEESE及传统的MUSIC-SS算法。
The PADEC algorithm, which introduces the information of reference signals, improves the performance of direction of arrivals (DOA) estimation of co herent multi-path signals. Unlike the conventional spatial smoothing techniques, the DEESE algorithm has unique decorrelation performance, in which the decomposition is applied on the eigenvectors that span the signal subspace. When the number of antenna array's elements is small and the signal-to-noise ratio is low, the DEESE algorithm exhibits excellent performance. In this paper, because of their respective excellence, we applied the decorrelation method of the DEESE algorithm to PADEC algorithm, and named the new algorithm PADEC-DEESE. The computer simulation shows that the PADEC-DEESE algorithm can estimate the direction of arrivals of coherent multi-path signals properly. Under the condition of smaller number of antenna array's elements and lower signal-to-noise, the PADEC-DEESE algorithm has better precision of DOA estimation than PADEC, DEESE and MUSIC-SS.
出处
《电波科学学报》
EI
CSCD
北大核心
2006年第1期33-36,52,共5页
Chinese Journal of Radio Science