利用状态空间模型联合估计波达方向和频率

张志成; 石要武

doi:10.3788/OPE.20111904.0916

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利用状态空间模型联合估计波达方向和频率

信息科学 | 更新时间：2020-08-12

- 利用状态空间模型联合估计波达方向和频率
- estimation of direction-of-arrival and frequency based on state-space model
- 光学精密工程 2011年19卷第4期页码：916-921
- 作者机构：
  
  吉林大学通信工程学院,吉林长春,130022
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(No.51075175)()
- DOI：10.3788/OPE.20111904.0916
  中图分类号： TN911.23
- 收稿日期：2011-02-28，
  
  修回日期：2011-03-23，
  
  网络出版日期：2011-04-26，
  
  纸质出版日期：2011-04-26
- 稿件说明：
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张志成, 石要武. 利用状态空间模型联合估计波达方向和频率[J]. 光学精密工程, 2011,19(4): 916-921

ZHANG Zhi-cheng, SHI Yao-wu. estimation of direction-of-arrival and frequency based on state-space model[J]. Editorial Office of Optics and Precision Engineering, 2011,19(4): 916-921
张志成, 石要武. 利用状态空间模型联合估计波达方向和频率[J]. 光学精密工程, 2011,19(4): 916-921 DOI： 10.3788/OPE.20111904.0916.

ZHANG Zhi-cheng, SHI Yao-wu. estimation of direction-of-arrival and frequency based on state-space model[J]. Editorial Office of Optics and Precision Engineering, 2011,19(4): 916-921 DOI： 10.3788/OPE.20111904.0916.

摘要

针对阵列信号多维参数估计计算量大

需要参数配对运算等问题

提出了一种利用状态空间模型联合估计波达方向(DOA)和频率的方法。首先

构造一个特殊的状态空间模型

其系统矩阵包含信号的波达方向和频率信息;然后

通过选取合适的辅助变量

利用信号的二阶统计特性抑制噪声干扰

并利用正交投影理论和奇异值分解得到广义可观测矩阵的估计值;最后

由广义可观测矩阵得到系统矩阵的估计值

由系统矩阵估计值的特征分解得到信号的波达方向和频率。实验结果表明

在信噪比为0 dB的情况下同时估计两个信源时

信号频率估计的均方根误差为0.003 5 rad

信号到达角估计的均方根误差为0.38

基本达到了联合估计算法的设计要求。

Abstract

In order to reduce the computational complexity and pair the parameters automatically in multiparameter estimation for array sensors

an algorithm for joint the Direction-of-arrival (DOA) signal and frequency signal based on a state-space model was presented. Firstly

a special state-space model with system matrices including the DOA and frequency information was constructed. Then the second order statistical properties were taken to restrain the noise by using appropriate auxiliary variable

and the extended observability matrix was estimated by using orthogonal projection theory and singular value decomposition. Finally

the estimation of system matrices was obtained from the generalized observability matrix

and the DOA and frequency of the signal were estimated from the eigenvalue decomposition of system matrix. Simulation results are presented to demonstrate the effectiveness of the algorithm

and the results show that the RMSE of frequency estimation is 0.003 5 rad and that of DOA estimation is 0.38 under the condition of estimating two signal sources with 0 dB for SNR.

关键词

Keywords

references

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