CLC number: TN958.97
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2020-04-10
Cited: 0
Clicked: 7019
Citations: Bibtex RefMan EndNote GB/T7714
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.
@article{title="Robust mismatched filtering algorithm for passive bistatic radar using worst-case performance optimization",
author="Gang Chen, Jun Wang",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="21",
number="7",
pages="1074-1084",
year="2020",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1900150"
}
%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
%V 21
%N 7
%P 1074-1084
%@ 2095-9184
%D 2020
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1900150
TY - JOUR
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
Abstract: 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.
[1]Abdullah RSAR, Salah AA, Ismail A, et al., 2016. Experimental investigation on target detection and tracking in passive radar using long-term evolution signal. IET Radar Sonar Navig, 10(3):577-585.
[2]Bok D, 2018. Reconstruction and reciprocal filter of OFDM waveforms for DVB-T2 based passive radar. Int Conf on Radar, p.1-6.
[3]Bournaka G, Ummenhofer M, Cristallini D, et al., 2017. Experimental study for transmitter imperfections in DVB-T based passive radar. IEEE Trans Aerosp Electron Syst, 54(3):1341-1354.
[4]Chen G, Wang J, Guo S, et al., 2018. Improved mismatched filtering for ATV-based passive bistatic radar. IET Radar Sonar Navig, 12(6):663-670.
[5]Clemente C, Soraghan JJ, 2014. GNSS-based passive bistatic radar for micro-Doppler analysis of helicopter rotor blades. IEEE Trans Aerosp Electron Syst, 50(1):491-500.
[6]Colone F, Cardinali R, Lombardo P, et al., 2009. Space-time constant modulus algorithm for multipath removal on the reference signal exploited by passive bistatic radar. IET Radar Sonar Navig, 3(3):253-264.
[7]Colone F, Bongioanni C, Lombardo P, 2013. Multifrequency integration in FM radio-based passive bistatic radar. Part I: target detection. IEEE Aerosp Electron Syst Mag, 28(4): 28-39.
[8]Garry JL, Baker CJ, Smith GE, 2017. Evaluation of direct signal suppression for passive radar. IEEE Trans Geosci Remote Sens, 55(7):3786-3799.
[9]Lorenz RG, Boyd SP, 2005. Robust minimum variance beamforming. IEEE Trans Signal Process, 53(5):1684- 1696.
[10]Lu Y, Tan D, Sun H, 2007. Air target detection and tracking using a multi-channel GSM based passive radar. Int Waveform Diversity and Design Conf, p.122-126.
[11]Lv XY, Wang J, Wang J, 2015. Robust direction of arrival estimate method in FM-based passive bistatic radar with a four-element Adcock antenna array. IET Radar Sonar Navig, 9(4):392-400.
[12]Ma H, Antoniou M, Stove AG, et al., 2018. Maritime moving target localization using passive GNSS-based multi-static radar. IEEE Trans Geosci Remote Sens, 56(8):4808-4819.
[13]Martelli T, Cardinali R, Colone F, 2018. Detection performance assessment of the FM-based AULOS® passive radar for air surveillance applications. 19th Int Radar Symp, p.1-10.
[14]Milani I, Colone F, Bongioanni C, et al., 2018. WiFi emission- based vs passive radar localization of human targets. IEEE Radar Conf, p.1311-1316.
[15]Salah AA, Abdullah RSAR, Ismail A, et al., 2013. Feasibility study of LTE signal as a new illuminators of opportunity for passive radar applications. IEEE Int RF and Microwave Conf, p.257-262.
[16]Tabassum MN, Hadi MA, Alshebeili S, 2016. CS based processing for high resolution GSM passive bistatic radar. IEEE Int Conf on Acoustics, Speech and Signal Processing, p.2229-2233.
[17]Vorobyov SA, Gershman AB, Luo ZQ, 2003. Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem. IEEE Trans Signal Process, 51(2):313-324.
[18]Wang HT, Wang J, Zhong LP, 2011. Mismatched filter for analogue TV-based passive bistatic radar. IET Radar Sonar Navig, 5(5):573-581.
[19]Yi JX, Wan XR, Li DS, et al., 2018. Robust clutter rejection in passive radar via generalized subband cancellation. IEEE Trans Aerosp Electron Syst, 54(4):1931-1946.
[20]Zaimbashi A, 2017. Target detection in analog terrestrial TV-based passive radar sensor: joint delay-Doppler estimation. IEEE Sens J, 17(17):5569-5580.
[21]Zrnic B, Zejak A, Petrovic A, et al., 1998. Range sidelobe suppression for pulse compression radars utilizing modified RLS algorithm. IEEE 5th Int Symp on Spread Spectrum Techniques and Applications, p.1008-1011.
Open peer comments: Debate/Discuss/Question/Opinion
<1>