Full Text:   <452>

Summary:  <21>

CLC number: TN958.97

On-line Access: 2020-07-10

Received: 2019-03-19

Revision Accepted: 2019-08-23

Crosschecked: 2020-04-10

Cited: 0

Clicked: 562

Citations:  Bibtex RefMan EndNote GB/T7714


Gang Chen


Jun Wang


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Frontiers of Information Technology & Electronic Engineering  2020 Vol.21 No.7 P.1074-1084


Robust mismatched filtering algorithm for passive bistatic radar using worst-case performance optimization

Author(s):  Gang Chen, Jun Wang

Affiliation(s):  National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Corresponding email(s):   chengang_xidian@163.com, wangjun@xidian.edu.cn

Key Words:  Passive bistatic radar, Range sidelobes, Low signal-to-noise ratio, Mismatched filtering, Worst-case performance optimization

Gang Chen, Jun Wang. Robust mismatched filtering algorithm for passive bistatic radar using worst-case performance optimization[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(7): 1074-1084.

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author="Gang Chen, Jun Wang",
journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Robust mismatched filtering algorithm for passive bistatic radar using worst-case performance optimization
%A Gang Chen
%A Jun Wang
%J Frontiers of Information Technology & Electronic Engineering
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%N 7
%P 1074-1084
%@ 2095-9184
%D 2020
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1900150

T1 - Robust mismatched filtering algorithm for passive bistatic radar using worst-case performance optimization
A1 - Gang Chen
A1 - Jun Wang
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 21
IS - 7
SP - 1074
EP - 1084
%@ 2095-9184
Y1 - 2020
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1900150

passive bistatic radar detects targets by exploiting available local broadcasters and communication transmissions as illuminators, which are not designed for radar. The signal usually contains a time-varying structure, which may result in high-level range ambiguity sidelobes. Because the mismatched filter is effective in suppressing sidelobes, it can be used in a passive bistatic radar. However, due to the low signal-to-noise ratio in the reference signal, the sidelobe suppression performance seriously degrades in a passive bistatic radar system. To solve this problem, a novel mismatched filtering algorithm is developed using worst-case performance optimization. In this algorithm, the influence of the low energy level in the reference signal is taken into consideration, and a new cost function is built based on worst-case performance optimization. With this optimization, the mismatched filter weights can be obtained by minimizing the total energy of the ambiguity range sidelobes. Quantitative evaluations and simulation results demonstrate that the proposed algorithm can realize sidelobe suppression when there is a low-energy reference signal. Its effectiveness is proved using real data.





Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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