极化敏感线阵的模值约束降维Root-MUSIC算法

A Reduced-dimensional Root-MUSIC Algorithm with the Modulus Constraint Based on Polarization Sensitive Linear Array

  • 摘要: 为了解决极化敏感线阵波达方向角和极化参数联合估计运算量大的问题,本文提出了模值约束降维Root-MUSIC算法。 该算法通过对波达方向角和极化参数进行剥离,先采用Root-MUSIC算法进行DOA估计,然后根据模值约束条件构造代价函数,通过闭合式解求出极化参数估计。与传统MUSIC算法相比,该算法避免了谱峰搜索,大大提高了运算效率。与ESPRIT算法相比,该算法避免了参数配对问题。计算机仿真结果验证了该算法的正确性,且具有较高的成功率与精确度。在两目标信号入射角度接近时,也能够很好的分辨出两信号。

     

    Abstract: To reduce the large computation of joint direction-of-arrival (DOA) and polarization parameters estimation based on polarization sensitive linear array, a reduced-dimensional Root-MUSIC with the modulus constraint is proposed. The algorithm in this paper estimates the DOA and polarization parameters in two separate steps. In step one, DOA parameter is separated from polarization parameters and estimated by Root-MUSIC algorithm; in step two, cost function is constructed according to modulus constraint and polarization parameters are obtained with closed-form formulas. Compared with the traditional MUSIC algorithm, the algorithm in this paper avoids the spectrum peak search, and greatly improves the operation efficiency. Compared with the ESPRIT algorithm, this algorithm avoids parameters matching problem. The computer simulation results verify the correctness of this algorithm, and as well as its high success rate and precision of the angle estimation. When the incident angles of two target signals are close, it also can distinguish the two signals very well.

     

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