基于分维处理的单通道阵列频率与角度联合估计

针对现有无源单通道阵列频率与角度联合估计算法的信号采样时间较长以及运算复杂度较高等问题,提出了分维处理的频率与角度联合估计算法.其信号采样数据由时域采样数据与空域采样数据构成,前者来自于对参考阵元的多次采样,后者来自各阵元.仅对时域采样数据进行处理即可得到各信源的频率估计值；然后基于空域采样数据以各频率估计值为搜索频率,估计出各频率对应的空间谱,再利用频率误差与角度误差的关系以及方向矢量与噪声子空间的正交性从各空间谱中提取出与各频率估计值对应的角度估计值.与已有算法相比,该算法采样时间较短,复杂度较低,且直接对采样信号进行处理,避免了信号失真.理论推导与仿真分析证明了该算法的有效性.

Joint Estimation of Frequency and Azimuth for Passive Switch Antenna Array Based on Fractal Dimension Processing

For joint estimation of frequency and azimuth in passive switch antenna array, existing al-gorithms exhibit long signal sampling time and high computational complexity. This paper presents a new joint estimation algorithm based on fractal dimension processing. The signal sampling data con-sists of time domain sampling data and spatial domain sampling data, with the former obtained from multiple sampling of the reference elements and the latter from all elements. Frequency estimation can be realized by processing the time domain sampling data. Taking the estimated frequency value as the search term, based on spatial domain sampling data, each frequency＇ s corresponding spatial spectrum can be estimated. Then, according to the relationship between frequency error and azimuth error as well as the orthogonality of direction vector and noise subspace, the corresponding azimuth can be estimated. Compared with existing algorithms, the proposed algorithm exhibits shorter sam-pling time and lower computation complexity, with signal distortion avoided. Theoretical analysis and simulation results demonstrate the effectiveness of this algorithm.