西安电子科技大学学报 ›› 2024, Vol. 51 ›› Issue (3): 55-62.doi: 10.19665/j.issn1001-2400.20231201

• 信息与通信工程 • 上一篇    下一篇

存在幅相误差时二维稳健超分辨测角算法

刘敏提(), 曾操(), 胡树林(), 陈建忠(), 李军(), 李世东(), 廖桂生()   

  1. 西安电子科技大学 雷达信号处理全国重点实验室,陕西 西安 710071

Algorithm for estimation of the two-dimensional robust super-resolution angle under amplitude and phases uncertainty background

LIU Minti(), ZENG Cao(), HU Shulin(), CHENG Jianzhong(), LI Jun(), LI Shidong(), LIAO Guisheng()   

  1. National Key Laboratory of Radar Signal Processing,Xidian University,Xi’an 710071,China
  • Received:2023-07-01 Online:2024-06-20 Published:2023-12-27

摘要:

针对4D车载毫米波雷达在俯仰与方位维角度分辨力较低、阵列存在幅相误差时测角有偏的问题,提出一种基于快速稀疏贝叶斯学习的稳健二维超分辨测角方法。首先,利用空域稀疏性特点,对角度域空间进行栅格划分,构建了存在幅相误差时的二维超分辨测角信号模型;然后,通过固定点更新的MacKay SBL重构算法实现了多个邻近目标二维角度估计,并利用基于向量点乘的自校正算法对相位误差进行估计,以对有偏的角度估计进行修正;最后,给出了多输入多输出虚拟阵列下的二维角度估计的克拉美-罗界,并分析了所提算法的计算复杂度。仿真结果表明,在大陆ARS548雷达实际12发16收天线布局下,通过对比6种超分辨测角算法,所提方法在低信噪比、少量快拍下和幅相误差较小时,具有较高的角度分辨力与较低的均方根误差。

关键词: 超分辨, 多输入多输出阵列, 毫米波雷达, 贝叶斯学习, 幅相误差

Abstract:

In order to address the issues of low angle resolution in elevation and azimuth dimensions of the 4D vehicle-mounted millimeter wave radar,as well as the biased angle measurement when the array includes amplitude and phase defects.A robust two-dimensional super-resolution angle estimation method based on fast sparse Bayesian Learning(FSBL) is suggested as a solution to this issue.First,a two-dimensional super-resolution angle signal model with amplitude and phase errors is built by using grids to split the angle domain space depending on spatial sparsity.Then,the two-dimensional angle estimation for spatial proximity targets is obtained using the fixed-point updated based MacKay SBL reconstruction algorithm,with the phase error and biased angle compensation calibrated using the self-correcting algorithm based on vector dot product.Finally,the computational complexity of the proposed algorithm is analyzed,and the Cramer-Rao Lower Bound(CRB) for two-dimensional angle estimation under MIMO non-uniform sparse arrays is provided.By comparing six distinct categories of super-resolution algorithms,simulation results demonstrate that the proposed method has a high angle resolution and a low root mean square error(RMSE) in a low SNR and few snapshot numbers under the actual layout of 12 transmitting and 16 receiving antennas for the continental ARS548 radar.

Key words: super-resolution, multiple-input multiple-output(MIMO) array, millimeter wave radar, sparse Bayesian learning, amplitude and phases error

中图分类号: 

  • TN911.7