基于FFT和波束空间MUSIC的快速超分辨算法

Fast Super-Resolution Algorithm Based on FFT and Beam Space MUSIC

摘要: MUSIC (Multiple Signal Classification)算法具有优良的估计精度和高分辨率，但是存在运算复杂、抗噪声性能差、无法对相干信号解相干等问题，因此难以广泛应用。文中将空域FFT测角融合到波束域MUSIC中，通过对阵列信号进行波束变换降低数据维度，结合空域FFT提供的先验信息为角度谱的峰值搜索提供搜索范围，从而有效地避免了角度谱中的栅瓣干扰、全谱搜索。该方案能够对单快拍数据进行快速角度估计，在降低传统超分辨方法运算量的同时，可以获得更稳健的性能。仿真结果表明，该方案的测角性能优于MUSIC算法，运算复杂度低于MUSIC算法，验证了该方案的有效性和优越性。

Abstract: The MUSIC algorithm has excellent estimation accuracy and high resolution, but it is difficult to be widely used because of its disadvantages such as complex operation, poor anti-noise performance and inability to conduct decoherence. In this paper, the spatial FFT Angle measurement is integrated into the beam domain MUSIC, and the data dimension is reduced by the beam transform of the array signal. According to the prior information provided by the spatial FFT, the search range is provided for the peak searching of the Angle spectrum, thus effectively avoiding the grid lobe interference and full spectrum searching in the Angle spectrum. The proposed scheme can be used to estimate the Angle of single snapshot data quickly, which can reduce the computation cost of the traditional super-resolution method and achieve more robust performance. The simulation results show that the performance of the proposed scheme is better than that of MUSIC algorithm, and the complexity is lower than that of MUSIC algorithm, which verifies the effectiveness and superiority of the scheme.