结合快速傅里叶变换和线性调频变换的快速DOA估计

王薇 1; 2; 殷勤业 2; 姚博彬 3; 穆鹏程 2

doi:10.7652/xjtuxb201912017

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结合快速傅里叶变换和线性调频变换的快速DOA估计

更新时间：2025-07-09

- 结合快速傅里叶变换和线性调频变换的快速DOA估计
- A Fast Direction-of-Arrival Estimation Algorithm Based on Fast Fourier Transform and Chirp Transform
- 西安交通大学学报 2019年53卷第12期页码：131-138+160
- 作者机构：
  
  1. 西京学院信息工程学院,西安,710123
  2. 西安交通大学智能网络与网络安全教育部重点实验室,西安,710049
- 作者简介：
- 基金信息：
  
  : 2019-05-10。作者简介: 王薇(1986—),女,助教,博士生;穆鹏程(通信作者),男,副教授,博士生导师。基金项目: 国家自然科学基金青年基金资助项目(61601058);陕西省自然科学基础研究计划资助项目(2018JM6071);西京学院校科研基金资助项目(XJ180211)
- DOI：10.7652/xjtuxb201912017
  中图分类号： TN959.2
- 网络首发：2019-12-10，
  
  纸质出版：2019
- 稿件说明：
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王薇 1, 2, 殷勤业 2, 等. 结合快速傅里叶变换和线性调频变换的快速DOA估计[J]. 西安交通大学学报, 2019,53(12):131-138+160.

A Fast Direction-of-Arrival Estimation Algorithm Based on Fast Fourier Transform and Chirp Transform[J]. 2019, 53(12): 131-138+160.
王薇 1, 2, 殷勤业 2, 等. 结合快速傅里叶变换和线性调频变换的快速DOA估计[J]. 西安交通大学学报, 2019,53(12):131-138+160. DOI： 10.7652/xjtuxb201912017.

A Fast Direction-of-Arrival Estimation Algorithm Based on Fast Fourier Transform and Chirp Transform[J]. 2019, 53(12): 131-138+160. DOI： 10.7652/xjtuxb201912017.

摘要

针对阵列信号处理中传统多重信号分类(MUSIC)算法估计信号波达方向(DOA)时运算量庞大

导致其在实时性需求较高的场合应用受限的问题

提出一种结合快速傅里叶变换和线性调频变换的快速DOA估计算法。该算法以降低MUSIC算法谱峰搜索的运算复杂度为目的

首先利用分片搜索的思想并结合快速傅里叶变换对估计的信号子空间矢量进行波束形成

近似估计信号DOA

获取其对应波束指向及该波束指向对应的空域角度范围

避免了对全空域角度范围的谱峰搜索; 然后

针对已确定的空域角度范围

结合线性调频变换算法实现信号DOA的精确估计

通过将MUSIC算法中对估计的噪声子空间矢量的加权处理转化为可以快速实现的序列的圆周卷积

降低精确估计信号DOA时谱峰搜索的运算复杂度。理论分析和仿真实验表明:相比于经典的MUSIC算法

所提算法能够在保证信号DOA估计精度的前提下将MUSIC算法谱峰搜索的运算复杂度降至原复杂度的10%以下; 对于阵列孔径较大和DOA估计精度要求较高的场景

所提算法的计算效率优势更为明显。

Abstract

A novel computationally-efficient direction-of-arrival(DOA)estimation algorithm based on fast Fourier transform(FFT)and chirp transform algorithm(CTA)is proposed to reduce the computational burden of the multiple signal classification(MUSIC)algorithm in array signal processing and to improve the practical applicability of the MUSIC algorithm in the high real-time processing scenarios. Firstly

the piecewise search and FFT are used to form beams for vectors of the estimated signal subspace

and rough DOAs are estimated to obtain beam directions and their angle ranges

so that peak searches in the full angle range are avoided. Then

the CTA is used to obtain an accurate DOA estimation in the determined angle range. Vectors of estimated noise subspace in MUSIC algorithm are weighted and transformed into circular convolution of a sequence that can be quickly implemented

which reduces the computational complexity of peak search in the determined angle range. Theoretical analysis and simula

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references

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