Chen Wei, Wan Xian-rong, Zhang Xun, Rao Yun-hua, Cheng Feng. Parallel Implementation of Multi-channel Time Domain Clutter Suppression Algorithm for Passive Radar[J]. Journal of Radars, 2014, 3(6): 686-693. doi: 10.12000/JR14157
Citation: Rao Yunhua, Ming Yanzhen, Lin Jing, Zhu Fengyuan, Wan Xianrong, Gong Ziping. Reference Signal Reconstruction and Its Impact on Detection Performance of WiFi-based Passive Radar[J]. Journal of Radars, 2016, 5(3): 284-292. doi: 10.12000/JR15108

Reference Signal Reconstruction and Its Impact on Detection Performance of WiFi-based Passive Radar

DOI: 10.12000/JR15108
Funds:

National Natural Science Foundation of China (61271400, 41106156)

  • Received Date: 2015-09-26
  • Rev Recd Date: 2016-01-26
  • Publish Date: 2016-06-28
  • While Wireless Fidelity (WiFi)-based passive radar can achieve high detection resolution in both the range and Doppler domain, it is difficult to extract the reference signal because of the complexities of its signal format and application scenarios. In this study, we analyze a typical application of WiFi-based passive radar and discuss different methods for reference signal extraction. Based on the format and features of WiFi signals, we propose a method for reference signal reconstruction, and analyze the influence of the reconstructed reference signal's performance on detection. The results show that higher reference SNRs generate lower decoding bit rate errors and better clutter suppression with the reconstructed reference signal. Moreover, we propose a method for removing irrelevant signals to avoid the impact on target detection of a non-direct path signal in the receiving signal. The experimental results validate the efficacy of the proposed signal processing method.

     

  • [1]
    Griffiths H D. New direction in bistatic radar[C]. IEEE RADAR Conference, Rome, 2008: 1-6.
    [2]
    万显荣, 易建新, 程丰, 等. 单频网分布式外辐射源雷达技术[J]. 雷达学报, 2014, 3(6): 623-631. Wan Xian-rong, Yi Jian-xin, Cheng Feng, et al.. Single frequency network based distributed passive radar technology[J]. Journal of Radars, 2014, 3(6): 623-631.
    [3]
    Chen Q, Tan B, Woodbridge K, et al.. Indoor target tracking using high Doppler resolution passive Wi-Fi radar[C]. 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), South Brisbane, QLD, 2015: 5565-5569.
    [4]
    Falcone P, Colone F, Macera A, et al.. Two-dimensional location of moving targets within local areas using WiFi-based multistatic passive radar[J]. IET Radar, Sonar Navigation, 2014, 8(2): 123-131.
    [5]
    Colone F, Pastina D, Falcone P, et al.. WiFi-based passive ISAR for high-resolution cross-range profiling of moving targets[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(6): 3486-3501.
    [6]
    Falcone P, Bongioanni C, and Lombardo P. WiFi-based passive bistatic radar: data processing schemes and experimental results[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(2): 1061-1079.
    [7]
    Colone F, Woodbridge K, Guo H, et al.. Ambiguity function analysis of wireless lan transmissions for passive radar[J]. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(1): 240-264.
    [8]
    Chetty K, Smith G E, and Woodbridge K. Through-The-Wall sensing of personnel using passive bistatic WiFi radar at standoff distances[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(4): 1218-1226.
    [9]
    饶云华, 朱逢园, 张修志, 等. WiFi 外辐射源雷达信号模糊函数及副峰抑制分析[J]. 雷达学报, 2012, 1(3): 225-231. Rao Yun-hua, Zhu Feng-yuan, Zhang Xiu-zhi, et al.. Ambiguity function analysis and side peaks suppression of passive radar[J]. Journal of Radars, 2012, 1(3): 225-231.
    [10]
    万显荣, 唐慧, 王俊芳, 等. DTMB外辐射源雷达参考信号纯度对探测性能的影响分析[J]. 系统工程与电子技术, 2013, 35(4): 725-729. WAN Xian-rong, Tang Hui, Wang Jun-fang, et al.. Influence of reference signal purity on target detection performance in DTMB-based passive radar[J]. Systems Engineering and Electronics, 2013, 35(4): 725-729.
    [11]
    Mazhar H and Hassan S A. Analysis of target multipaths in WiFi-based passive radars[J]. IET Radar, Sonar Navigation, 2016, 10(1): 140-145.
    [12]
    吴海洲, 陶然, 单涛. 数字电视辐射源雷达基于空域滤波的直达波获取[J]. 兵工学报, 2009, 30(2): 226-230. Wu Hai-zhou, Tao Ran, and Shan Tao. Direct-path signal obtaining to digital video broadcasting transmitter radar based on the spatial filtering[J]. Acta Armamentarii, 2009, 30(2): 226-230.
    [13]
    万显荣, 岑博, 易建新, 等. 中国移动多媒体广播外辐射源雷达参考信号获取方法研究[J]. 电子与信息学报, 2012, 34(2): 338-343. Wan Xian-rong, Cen Bo, Yi Jian-xin, et al.. Reference signal extraction methods for CMMB-based passive bistatic radar[J]. Journal of Electronics Information Technology, 2012, 34(2): 338-343.
    [14]
    Harms H A, Davis L M, and Palmer J. Understanding the signal structure in DVB-T signals for passive radar detection[C]. IEEE Radar Conference, Washington DC, 2010: 532-537.
    [15]
    Chetty K, Smith G, Guo H, et al.. Target detection in high clutter using passive bistatic WiFi radar[C]. IEEE Radar Conference, Pasadena, 2009: 1-5.
    [16]
    IEEE Std 802.11g-2003. Telecommunications and information exchange between systems local and metropolitan area networks specific requirements Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications-Amendment 4: Furtherhigher-speed physical layer extension in the 2.4 GHz Band[S]. New York: Institue of Electrical and Electronics Engineers, Inc., 2003.
    [17]
    Nasraoui L, Atallah L N, and Siala M. An efficient reduced-complexity two-stage differential sliding correlation approach for OFDM synchronization in the multipath channel[C]. 2012 IEEE Wireless Communications and Networking Conference (WCNC),Paris,2012: 2059-2063.
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