系统工程与电子技术

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模值约束的降维MUSIC二维DOA估计

蔡晶晶, 秦国栋, 李鹏, 赵国庆   

  1. 西安电子科技大学电子信息攻防对抗与仿真技术教育部重点实验室, 陕西 西安 710071
  • 出版日期:2014-09-12 发布日期:2010-01-03

Two-dimensional DOA estimation with reduced-dimensional#br# MUSIC algorithm using the modulus constraint

CAI Jing-jing, QIN Guo-dong, LI Peng, ZHAO Guo-qing   

  1. Key Laboratory of Electronic Information Countermeasure and Simulation Technology,
    Ministry of Education, Xidian University, Xi’an 710071, China
  • Online:2014-09-12 Published:2010-01-03

摘要:

利用传统二维多重信号分类(multiple signal classification, MUSIC)算法进行二维波达方向(direction of arrival, DOA)估计时,往往带来巨大的运算量,限制了算法的实际应用。提出了一种能够大大降低二维DOA估计运算量的模值约束降维MUSIC算法,该算法将二维DOA估计问题转化为优化方程的求解问题,并采用模值约束法定义附加条件,使方向向量得到了较强约束,进而使求解结果更加接近最优解。理论分析和仿真实验表明,本文算法所需运算量较低,且角度估计的成功率与精确度较高。

Abstract:

A large amount of computation is required when using the traditional two-dimensional multiple signal classification (2D-MUSIC) algorithm for two-dimensional direction of arrival (DOA) estimation, so the practical application of 2D-MUSIC algorithm is limited. A reduced-dimensional MUSIC algorithm using the modulus constraint to solve the computation-intensive problem in two-dimensional DOA estimation is proposed. The proposed algorithm can distinctly reduce the computational load, because the two-dimensional DOA estimation can be decomposed into two stages of one-dimensional DOA estimation by the quadratic optimization method. In this algorithm, the modulus constraint is used to construct the constraint condition of the quadratic optimization function, and the steering vectors are strongly constrained in the solving process, so the result is closer to the optimal solution than the other’s. The theoretical analysis and simulation results show that the proposed algorithm not only requires less computation, but also performs well in success rate and precision of angle estimation.