Full Text:   <1241>

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CLC number: TN958.97

On-line Access: 2014-11-07

Received: 2014-03-06

Revision Accepted: 2014-06-23

Crosschecked: 2014-10-20

Cited: 1

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Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE C 2014 Vol.15 No.11 P.1071-1085


An extended processing scheme for coherent integration and parameter estimation based on matched filtering in passive radar

Author(s):  Xin Guan, Li-hua Zhong, Dong-hui Hu, Chi-biao Ding

Affiliation(s):  Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Beijing 100190, China; more

Corresponding email(s):   xinguanxin@126.com

Key Words:  Keystone transform, Matched filtering, MDCFT, Mismatching, Passive radar, Velocity estimation

Xin Guan, Li-hua Zhong, Dong-hui Hu, Chi-biao Ding. An extended processing scheme for coherent integration and parameter estimation based on matched filtering in passive radar[J]. Journal of Zhejiang University Science C, 2014, 15(11): 1071-1085.

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%T An extended processing scheme for coherent integration and parameter estimation based on matched filtering in passive radar
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%A Dong-hui Hu
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T1 - An extended processing scheme for coherent integration and parameter estimation based on matched filtering in passive radar
A1 - Xin Guan
A1 - Li-hua Zhong
A1 - Dong-hui Hu
A1 - Chi-biao Ding
J0 - Journal of Zhejiang University Science C
VL - 15
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SP - 1071
EP - 1085
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1400074

In passive radars, coherent integration is an essential method to achieve processing gain for target detection. The cross ambiguity function (CAF) and the method based on matched filtering are the most common approaches. The method based on matched filtering is an approximation to CAF and the procedure is: (1) divide the signal into snapshots; (2) perform matched filtering on each snapshot; (3) perform fast Fourier transform (FFT) across the snapshots. The matched filtering method is computationally affordable and can offer savings of an order of 1000 times in execution speed over that of CAF. However, matched filtering suffers from severe energy loss for high speed targets. In this paper we concentrate mainly on the matched filtering method and we use keystone transform to rectify range migration. Several factors affecting the performance of coherent integration are discussed based on the matched filtering method and keystone transform. Modified methods are introduced to improve the performance by analyzing the impacts of mismatching, precision of the keystone transform, and discretization. The modified discrete chirp Fourier transform (MDCFT) is adopted to rectify the Doppler expansion in a multi-target scenario. A novel velocity estimation method is proposed, and an extended processing scheme presented. Simulations show that the proposed algorithms improve the performance of matched filtering for high speed targets.


方法提亮:基于多普勒滤波器组的失配校正可将损失控制在1 dB以内;Chirp-z变换较线性差值法性能高3–4 dB;基于MDCFT的速度估计可利用单接收站、单帧数据获取目标的速度及运动方向估计。


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


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