基于压缩感知理论的二维DOA估计

    Two-dimensional DOA Estimation Based on Compressed Sensing Theory

    • 摘要: 二维波达方向(direction of arrival,DOA)估计在雷达探测、电子对抗、医学成像等领域有着广泛的应用.针对现有算法估计精度不足、计算量巨大的问题,在基于压缩感知理论的背景下提出一种二维均匀L型阵列信号的DOA估计算法.该算法首先对阵列信号的俯仰角和方位角构建空间合成角,并对空间合成角构建过完备冗余字典;再利用正交化高斯随机矩阵构造观测矩阵;最后通过改进RM-FOCUSS算法和求解三角函数的方法还原出方位角和俯仰角.理论研究表明,该方法在高信噪比、多快拍条件下比传统算法具有更高的估计精度和分辨力,且通过压缩采样降低了运算量.仿真实验验证了上述结论.

       

      Abstract: Two-dimensional direction of arrival (DOA) estimation has been widely used in radar detection, electronic reconnaissance, medical imaging and other fields. Aiming at the problems of inadequate estimation accuracy and enormous computational load of existing algorithms, a DOA estimation algorithm for two-dimensional uniform L-shaped array signals was presented in this paper based on compressed sensing theory. First, an over-complete redundant dictionary was established by using the space frequency of the azimuth angle and pitch angle. Then the orthogonal Gaussian random matrix was used to construct the measurement matrix. Finally, azimuth and elevation were restored by improving RM-FOCUSS algorithm and solving trigonometric function. The theoretical research shows that the proposed method has higher estimation accuracy and resolution than the traditional algorithm under the conditions of high SNR and multi-snapshot, and it reduces the computational complexity by compressing sampling. The simulation results verify the effectiveness and correctness.

       

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