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1. 吉林大学 通信工程学院,吉林 长春,中国,130012
2. 长春理工大学 电子信息工程学院,吉林 长春,130022
收稿日期:2017-05-02,
修回日期:2017-06-28,
纸质出版日期:2017-11-25
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单泽彪, 刘小松, 王春阳等. 多快拍加权平滑<i>l</i><sub>0</sub>范数DOA估计[J]. 光学精密工程, 2017,25(10s): 167-173
SHAN Ze-biao, LIU Xiao-song, WANG Chun-yang etc. DOA estimation of weighted smoothed <i>l</i><sub>0</sub> norm under multiple snapshots[J]. Editorial Office of Optics and Precision Engineering, 2017,25(10s): 167-173
单泽彪, 刘小松, 王春阳等. 多快拍加权平滑<i>l</i><sub>0</sub>范数DOA估计[J]. 光学精密工程, 2017,25(10s): 167-173 DOI: 10.3788/OPE.20172513.0167.
SHAN Ze-biao, LIU Xiao-song, WANG Chun-yang etc. DOA estimation of weighted smoothed <i>l</i><sub>0</sub> norm under multiple snapshots[J]. Editorial Office of Optics and Precision Engineering, 2017,25(10s): 167-173 DOI: 10.3788/OPE.20172513.0167.
针对现有基于压缩感知的DOA估计算法估计精度不高的问题,本文提出一种多快拍加权平滑
l
0
范数DOA估计方法。所提方法采用一种新的加权方式,在构造一个恰当的平滑连续函数后,根据接收数据的初始解确定一个合适的递减的{
σ
}序列[
σ
1
,
σ
2
,…,
σ
J
],并对每一个
σ
值,用最速下降法来求解
l
0
范数的逼近函数
H
σ
(
S
)的最小值;然后将该
σ
值作为下一次迭代的初始值,并在每次迭代开始时更新权值,通过多次的迭代获得逼近函数的最小解即逼近的最小
l
0
范数。所提方法可对DOA进行有效估计,且容易实现、精度较高,与未加权的多快拍平滑
l
0
范数DOA估计方法相比具有更好的估计性能。最后通过仿真实验对所提方法进行了验证,结果表明:本文所提方法在快拍数
L
=32、信噪比
SNR
=-5 dB和阵元数
M
=16的条件下,对两个窄带目标信号DOA进行估计的均方根误差为0.480 9°,基本达到了阵列信号处理中目标估计方法的设计要求。
Aimed at the problem of low estimated accuracy of existing DOA estimation algorithms based on compressed sensing
a DOA estimation method of weighted smoothed L0 norm under multiple snapshots was proposed in the thesis. A new weighting method was adopted in the proposed method. After a proper smooth continuous function was constructed
a proper decreasing sequence of set was determined according to initial solution of receiving data
and the minimum value of approximation function of L0 norm was solved by the steepest descent method for every
σ
value; then the
σ
value was taken to be initial value of the next iteration
weight was updated at the beginning of each iteration
and minimum solution of approximation function namely minimum L0 norm of approximation was obtained by multiple iterations. Proposed method could implement effective estimation for DOA. It was easy to be realized with higher accuracy and had better estimation performance compared with unweighted DOA estimation method of smoothed L0 norm under multiple snapshots. Finally
the proposed method was verified by simulation experiment. The result shows that root mean square error of DOA estimation for two narrow-band target signal is 0.480 9° under the condition that snapshots with 32
signal noise ratio with -5 dB and array elements with 6 in the proposed method
which reaches design requirement of target estimation method in array signal processing basically.
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冯俊杰, 张弓, 文方青. 基于SL0范数的改进稀疏信号重构算法[J]. 数据采集与处理, 2016, 31(1):178-183. FENG J J, ZHANG G, WEN F Q. A improved algorithm of sparse signal reconstruction based on Smoothed L0 norm[J].Data acquisition and processing, 2016, 31(1):178-183. (in Chinese)
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