A High Resolution Algorithm for 2D-DOA Estimation and Its Fast Implementation in the Presence of SαS Distributed Noise

doi:10.3969/j.issn.0372-2112.2018.06.016

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A High Resolution Algorithm for 2D-DOA Estimation and Its Fast Implementation in the Presence of SαS Distributed Noise

更新时间：2025-07-08

- A High Resolution Algorithm for 2D-DOA Estimation and Its Fast Implementation in the Presence of SαS Distributed Noise
- Acta Electronica Sinica Vol. 46, Issue 6, Pages: 1384-1389(2018)
- 作者机构：
  
  1. 东北大学高级通信与网络实验室,辽宁,沈阳,110819
  2. 北京科技大学计算机与通信工程学院,北京,100083
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2018.06.016
  CLC： TP302
- Published Online：25 June 2018，
  
  Published：2018
- 稿件说明：
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A High Resolution Algorithm for 2D-DOA Estimation and Its Fast Implementation in the Presence of SαS Distributed Noise[J]. Acta Electronica Sinica, 2018, 46(6): 1384-1389.
DOI：

A High Resolution Algorithm for 2D-DOA Estimation and Its Fast Implementation in the Presence of SαS Distributed Noise[J]. Acta Electronica Sinica, 2018, 46(6): 1384-1389. DOI： 10.3969/j.issn.0372-2112.2018.06.016.

摘要

本文设计出一种针对脉冲噪声的二维鲁棒高分辨率波达方向（DOA，Direction of Arrival）估计算法，以解决雷达、声纳等无线通信领域中脉冲噪声环境下IAA（Iterative Adaptive Approach）无法准确估计出DOA的问题.该算法中，用最小

阶范数代替WLS（Weighted Least Squares）作为最优化求解的代价函数.此外，根据Toeplitz-Block-Toeplitz（TBT）矩阵性质和FFT简化计算过程，提出该算法的快速实现方法，提高算法的计算效率.该算法在对称

-稳定（SS，Symmetric Alpha-Stable）分布噪声环境下建模，仿真结果表明：与CRCO-MUSIC（CoRrentropy based COrrelation-MUltiple Signal Classification）算法和MUSIC-FLOM（MUltiple Signal Classification-Fractional Lower-Order Moment）算法相比，二维lp-IAA算法可以在低信噪比、单快拍条件下有效分辨出相邻多目标信号；快速算法可以在保证高分辨率的前提下，算法平均运算时间降低至原来的约1/40.

Abstract

This paper presents a robust and high-resolution 2D DOA (Direction of Arrival) algorithm in the field of wireless communication such as radar and sonar

solving the problem that IAA (Iterative Adaptive Aproach) fails to provide reliable DOA estimation performance in impulsive noise environment.In the algorithm

we replace WLS (Weighted Least Squares) with least

order norm (lp-norm) as the cost function.F

urthermore

to decrease the complexity of the proposed method

a fast implementation of 2D lp-IAA is also developed based on simplifying the calculation of inverse TBT (Toeplitz-Block-Toeplitz) matrix and fast Fourier transform.Simulation results indicate that

under the condition of low GSNR (Generalized Signal-to-Noise Ratio) SS distributed noise with single snapshot

2D lp-IAA algorithm performs better in distinguishing adjacent multi-target signals than CRCO-MUSIC (CoRrentropy based COrrelation-MUltiple Signal Classification) and MUSIC-FLOM (MUltiple Signal Classification-Fractional Lower-Order Moment).Moreover

the average computation time of the fast method is reduced to nearly 1/40 of the lp-IAA algorithm.

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