基于GPU加速的双向平滑MUSIC相干信号DOA估计算法
A GPU-Accelerated Forward-Backward Spatial Smoothing MUSIC Algorithm for DOA Estimation of Coherent Signals
曹泽坤 1怀园园 1张昕 1邱天1
作者信息
- 1. 西安电子工程研究所 西安 710100
- 折叠
摘要
针对传统MUSIC算法不能有效分辨相干信号以及其特征值计算量庞大的问题,本文提出一种基于GPU加速的双向平滑MUSIC相干信号DOA估计算法.该算法首先对各子阵协方差矩阵求平均得到双向平滑协方差矩阵;然后对该协方差矩阵进行特征值分解,得到正交的信号和噪声子空间;接着建立算法空间谱函数,进行谱峰搜索,得到DOA估计;最后使用GPU对以上步骤进行加速.仿真结果表明,本文所提基于GPU加速的双向平滑MUSIC算法能快速实现相干信号DOA估计.
Abstract
To address the issue that traditional MUSIC algorithms cannot effectively resolve coherent signals as well as their large computational burden related to eigenvalue calculations,this paper proposes a GPU-accelerated for-ward-backward spatial smoothing MUSIC algorithm for DOA estimation of coherent signals.The algorithm first de-rives the forward-backward smoothed covariance matrix by averaging the covariance matrices of subarrays.It then performs eigenvalue decomposition on the obtained covariance matrix to derive the orthogonal signal and noise sub-spaces.Subsequently,a spatial spectrum function is constructed,and spectral peak search is conducted to obtain the DOA estimation.Finally,the above steps are accelerated using GPU.The simulation results show that the pro-posed GPU-accelerated forward-backward spatial smoothing MUSIC algorithm can rapidly complete DOA estimation of coherent signals.
关键词
相干信号/DOA估计/双向平滑MUSIC算法/GPU加速Key words
coherent signal/DOA estimation/forward-backward spatial smoothing MUSIC algorithm/GPU acceleration引用本文复制引用
出版年
2024
NETL
NSTL
万方数据