Non-Unitary Joint Diagonalization Method for Estimating Two-Dimension Direction of Arrival

聂卫科; 冯大政; 刘建强

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Non-Unitary Joint Diagonalization Method for Estimating Two-Dimension Direction of Arrival

更新时间：2025-12-08

- Non-Unitary Joint Diagonalization Method for Estimating Two-Dimension Direction of Arrival
- Vol. 42, Issue 6, Pages: 747-750(2008)
- 作者机构：
  
  西安电子科技大学雷达信号处理国家重点实验室,西安,710071
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.7
- Online First：09 June 2008，
  
  Published：2008
- 稿件说明：
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聂卫科, 冯大政, 刘建强. Non-Unitary Joint Diagonalization Method for Estimating Two-Dimension Direction of Arrival[J]. 2008, 42(6): 747-750.
DOI：

聂卫科, 冯大政, 刘建强. Non-Unitary Joint Diagonalization Method for Estimating Two-Dimension Direction of Arrival[J]. 2008, 42(6): 747-750. DOI：

摘要

针对高斯白噪声中的二维角度估计问题

提出一种非酉联合对角化方法.该方法利用平移不变结构阵列信号子空间的旋转不变性

构造一组具有对角结构的空时相关矩阵

通过降维相关矩阵组的联合对角化

估计出阵列导向矢量矩阵

实现二维波达方向估计

所得二维角度能自动配对.该方法的计算量小于交替列对角化中心(ACDC)算法

且由于每步迭代具有精确的最小二乘闭式解

消除了ACDC算法的误差积累问题

其估计精度比二维旋转不变子空间方法和ACDC算法至少高5 dB和2 dB.

Abstract

A non-unitary joint diagonalization method was proposed to estimate the two-dimension(2D)direction of arrival(DOA)embedded in additive Gaussian noise. Using the rotational invariance property among signal subspace induced by an array of sensors with a displacement invariance structure

a set of spatio-temporal correlation matrices which possess diagonal structure were introduced. By implementing the joint-diagonalization of dimension-reduction correlation matrices

the array response matrix was obtained and the 2D DOA can be achieved. The computational complexity of the proposed iterative algorithm is lower than the alternating columns diagonal centers(ACDC)algorithm and the 2D DOA can be paired automatically. Since each iteration step of the proposed algorithm poses a typical least square problem having a unique closed solution

there is no error accumulation as the ACDC algorithm. Simulations show that the estimation performance of the proposed algorithm is at least higher than the 2D estimation of signal parameters via rotational invariance techniques and ACDC algorithm with 5 dB and 2 dB

respectively.

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references

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ROUQUETTE S, NAJIM M. Estimation of frequencies and damping factors by two-dimensional ESPRIT type methods [J]. IEEE Trans on Signal Processing, 2001, 49(1): 237-245.

van der VEEN A J, OBER P B. Azimuth and elevation computation in high resolution DOA estimation [J]. IEEE Trans on Signal Processing, 1992, 40(7): 1828-1832.

YEREDOR A. Non-orthogonal joint diagonalization in the least-squares sense with application in blind source separation [J]. IEEE Trans on Signal Processing, 2002, 50(7): 1545-1553.

FENG Dazheng, ZHANG Xianda, BAO Zheng. A neural network learning for adaptively extracting cross-correlation features between two high-dimension data streams [J]. IEEE Trans on Neural Networks, 2004, 15(6): 1541-1554.

张华,冯大政,聂卫科,等. 非正交联合对角化盲源分离算法 [J]. 西安电子科技大学学报,2008, 35(1): 27-31.

ZHANG Hua, FENG Dazheng, NIE Weike, et al. Non-orthogonal joint diagonalization for blind source separation [J]. Journal of Xidian University, 2008, 35(1): 27-31.

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