Wang Guoxuan, Zheng Guimei, Wang Hongzhen, Chen Chen
Graduate School, Air Force Engineering University, Xi'an 710051, China.
Air Defense and Missile Defense College, Air Force Engineering University, Xi'an 710051, China.
Sensors (Basel). 2022 Sep 26;22(19):7298. doi: 10.3390/s22197298.
Obtaining good measurement performance with meter wave radar has always been a difficult problem. Especially in low-elevation areas, the multipath effect seriously affects the measurement accuracy of meter wave radar. The generalized multiple signal classification (MUSIC) algorithm is a well-known measurement method that dose not require decorrelation processing. The polarization-sensitive array (PSA) has the advantage of polarization diversity, and the polarization smoothing generalized MUSIC algorithm demonstrates good angle estimation performance in low-elevation areas when based on a PSA. Nevertheless, its computational complexity is still high, and the estimation accuracy and discrimination success probability need to be further improved. In addition, it cannot estimate the polarization parameters. To solve these problems, a polarization synthesis steering vector MUSIC algorithm is proposed in this paper. First, the MUSIC algorithm is used to obtain the spatial spectrum of the meter wave PSA. Second, the received data are properly deformed and classified. The Rayleigh-Ritz method is used to decompose the angle to realize the decoupling of polarization and the direction of the arrival angle. Third, the geometric relationship and prior information of the direct wave and the reflected wave are used to continue dimension reduction processing to reduce the computational complexity of the algorithm. Finally, the geometric relationship is used to obtain the target height measurement results. Extensive simulation results illustrate the accuracy and superiority of the proposed algorithm.
利用米波雷达获得良好的测量性能一直是个难题。特别是在低仰角区域，多径效应严重影响米波雷达的测量精度。广义多信号分类（MUSIC）算法是一种众所周知的测量方法，不需要去相关处理。极化敏感阵列（PSA）具有极化分集的优势，基于PSA的极化平滑广义MUSIC算法在低仰角区域表现出良好的角度估计性能。然而，其计算复杂度仍然很高，估计精度和分辨成功率需要进一步提高。此外，它无法估计极化参数。为了解决这些问题，本文提出了一种极化合成导向矢量MUSIC算法。首先，利用MUSIC算法获得米波PSA的空间谱。其次，对接收到的数据进行适当变形和分类。采用瑞利 - 里兹方法对角度进行分解，实现极化与到达角方向的解耦。第三，利用直达波和反射波的几何关系和先验信息继续进行降维处理，以降低算法的计算复杂度。最后，利用几何关系获得目标高度测量结果。大量仿真结果说明了所提算法的准确性和优越性。
