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基于時頻集中度指標(biāo)的多旋翼無人機(jī)微動特征參數(shù)估計(jì)方法

宋晨,  周良將,  吳一戎,  丁赤飚

宋晨, 周良將, 吳一戎, 丁赤飚. 基于時頻集中度指標(biāo)的多旋翼無人機(jī)微動特征參數(shù)估計(jì)方法[J]. 電子與信息學(xué)報(bào), 2020, 42(8): 2029-2036. doi: 10.11999/JEIT190309
引用本文: 宋晨, 周良將, 吳一戎, 丁赤飚. 基于時頻集中度指標(biāo)的多旋翼無人機(jī)微動特征參數(shù)估計(jì)方法[J]. 電子與信息學(xué)報(bào), 2020, 42(8): 2029-2036. doi: 10.11999/JEIT190309
Chen SONG, Liangjiang ZHOU, Yirong WU, Chibiao DING. An Estimation Method of Micro-movement Parameters of UAV Based on The Concentration of Time-Frequency[J]. Journal of Electronics & Information Technology, 2020, 42(8): 2029-2036. doi: 10.11999/JEIT190309
Citation: Chen SONG, Liangjiang ZHOU, Yirong WU, Chibiao DING. An Estimation Method of Micro-movement Parameters of UAV Based on The Concentration of Time-Frequency[J]. Journal of Electronics & Information Technology, 2020, 42(8): 2029-2036. doi: 10.11999/JEIT190309

基于時頻集中度指標(biāo)的多旋翼無人機(jī)微動特征參數(shù)估計(jì)方法

doi: 10.11999/JEIT190309 cstr: 32379.14.JEIT190309
  • 1.

    微波成像技術(shù)重點(diǎn)實(shí)驗(yàn)室 北京 100190

  • 2.

    中國科學(xué)院電子學(xué)研究所 北京 100190

  • 3.

    中國科學(xué)院大學(xué) 北京 100049

詳細(xì)信息
    作者簡介:

    宋晨：男，1992年生，博士生，研究方向?yàn)槔走_(dá)信號處理、目標(biāo)檢測與識別等

    周良將：男，1981年生，研究員，研究方向?yàn)楹铣煽讖嚼走_(dá)系統(tǒng)設(shè)計(jì)、系統(tǒng)誤差補(bǔ)償及其相關(guān)信號處理技術(shù)

    吳一戎：男，1963年生，研究員，中國科學(xué)院院士，研究方向?yàn)楦叻直鏅C(jī)載合成孔徑雷達(dá)、SAR信號處理算法研究、遙感衛(wèi)星地面處理與應(yīng)用系統(tǒng)的體系結(jié)構(gòu)等

    丁赤飚：男，1969年生，研究員，研究方向?yàn)橄冗M(jìn)合成孔徑雷達(dá)系統(tǒng)和信號處理技術(shù)、數(shù)字信號處理等

    通訊作者:

    周良將　ljzhou@mail.ie.ac.cn

  • 中圖分類號: TN911.7

An Estimation Method of Micro-movement Parameters of UAV Based on The Concentration of Time-Frequency

  • 1.

    Science and Technology on Microwave Imaging Laboratory, Beijing 100190, China

  • 2.

    Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China

  • 3.

    University of Chinese Academy of Sciences, Beijing 100049, China

  • 摘要:

    無人機(jī)旋翼轉(zhuǎn)動產(chǎn)生的微多普勒調(diào)制能夠反映此類目標(biāo)的微動特性，準(zhǔn)確估計(jì)無人機(jī)旋翼長度、轉(zhuǎn)動頻率對于無人機(jī)的檢測與識別具有重要意義。該文針對調(diào)頻連續(xù)波體制雷達(dá)，提出一種基于時頻集中度指標(biāo)(CTF)的多旋翼無人機(jī)微動特征參數(shù)估計(jì)方法，推導(dǎo)了無人機(jī)旋翼微動特征參數(shù)與微多普勒分量信號參數(shù)之間的映射關(guān)系，在時頻旋轉(zhuǎn)域基于時頻集中度指標(biāo)，提高了各微動分量的區(qū)分度，相比于傳統(tǒng)方法，提高了多分量微多普勒信號的參數(shù)估計(jì)精度，在低信噪比環(huán)境下也具有很好的魯棒性。通過仿真和實(shí)際場景實(shí)驗(yàn)驗(yàn)證了方法的有效性。

    Abstract:

    The micro-Doppler modulation generated by the rotor rotation of UAV can reflect the micro-movement characteristics of such targets. Accurately estimating the rotor length and rotation frequency of the UAV is of great significance for UAV detection and recognition. In this paper, a method for estimating micro-movement parameters of multi-rotor UAV based on Concentration of Time-Frequency (CTF) is proposed for FMCW radar system. The mapping relationship between dynamic parameters of UAV rotor and signal parameters of micro-Doppler component is deduced. Based on time-frequency concentration index in time-frequency rotation domain, the discrimination of micro-motion components is improved. Compared with the traditional methods, the proposed method can improve the accuracy of multi-component micro-Doppler parameter. Furthermore, it has good robustness in low SNR. The validity of the method is verified by simulation and field test.

    • HTML全文

  • 圖  1  旋翼投影到雷達(dá)平面示意圖

    圖  2  多分量微多普勒信號參數(shù)估計(jì)方法流程圖

    圖  3  仿真數(shù)據(jù)時頻旋轉(zhuǎn)前后對比

    圖  4  時頻分析結(jié)和Hough變換仿真結(jié)果對比

    圖  5  頻譜集中度指標(biāo)仿真結(jié)果

    圖  6  不同方法微動參數(shù)估計(jì)誤差對比

    圖  7  實(shí)驗(yàn)數(shù)據(jù)處理結(jié)果

    表  1  微多普勒信號參數(shù)估計(jì)方法的計(jì)算效率對比

    方法STFT-HoughWVD-HoughHHTGWTCTF
    運(yùn)算時間(s)89.420391.492464.842757.252671.2180
    下載: 導(dǎo)出CSV

    表  2  多次實(shí)驗(yàn)微動目標(biāo)參數(shù)估計(jì)結(jié)果

    實(shí)驗(yàn)次數(shù)分量序號旋翼長度(cm)初始角度(°)旋翼轉(zhuǎn)速(Hz)
    1112.5824.290.90
    212.5975.683.33
    2112.6148.5104.58
    212.63147.195.25
    3112.575.475.54
    212.55126.171.22
    下載: 導(dǎo)出CSV
  • TAHMOUSH D. Review of micro-Doppler signatures[J]. IET Radar, Sonar & Navigation, 2015, 9(9): 1140–1146. doi: 10.1049/iet-rsn.2015.0118
    CHEN V C, LI F, HO S S, et al. Micro-Doppler effect in radar: Phenomenon, model, and simulation study[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(1): 2–21. doi: 10.1109/TAES.2006.1603402
    XIONG Xiangyu, LIU Hui, DENG Zhenmiao, et al. Micro-Doppler ambiguity resolution with variable shrinkage ratio based on time-delayed cross correlation processing for wideband radar[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(4): 1906–1917. doi: 10.1109/TGRS.2018.2870149
    張群, 胡健, 羅迎, 等. 微動目標(biāo)雷達(dá)特征提取、成像與識別研究進(jìn)展[J]. 雷達(dá)學(xué)報(bào), 2018, 7(5): 531–547. doi: 10.12000/JR18049

    ZHANG Qun, HU Jian, LUO Ying, et al. Research progresses in radar feature extraction, imaging, and recognition of target with micro-motions[J]. Journal of Radars, 2018, 7(5): 531–547. doi: 10.12000/JR18049
    HE Yongfu, PENG Yu, WANG Shaojun, et al. ADMOST: UAV flight data anomaly detection and mitigation via online subspace tracking[J]. IEEE Transactions on Instrumentation and Measurement, 2019, 68(4): 1035–1044. doi: 10.1109/TIM.2018.2863499
    SEJDI? E, OROVI? I, and STANKOVI? S. Compressive sensing meets time-frequency: An overview of recent advances in time-frequency processing of sparse signals[J]. Digital Signal Processing, 2018, 77: 22–35. doi: 10.1016/j.dsp.2017.07.016
    OH B S, GUO Xin, WAN Fangyuan, et al. Micro-Doppler mini-UAV classification using empirical-mode decomposition features[J]. IEEE Geoscience and Remote Sensing Letters, 2018, 15(2): 227–231. doi: 10.1109/LGRS.2017.2781711
    SONG Chen, WU Yirong, ZHOU Liangjiang, et al. A multicomponent micro-Doppler signal decomposition and parameter estimation method for target recognition[J]. Science China Information Sciences, 2019, 62(2): 29304. doi: 10.1007/s11432-018-9491-y
    章鵬飛, 李剛, 霍超穎, 等. 基于雙雷達(dá)微動特征融合的無人機(jī)分類識別[J]. 雷達(dá)學(xué)報(bào), 2018, 7(5): 557–564. doi: 10.12000/JR18061

    ZHANG Pengfei, LI Gang, HUO Chaoying, et al. Classification of drones based on micro-Doppler radar signatures using dual radar sensors[J]. Journal of Radars, 2018, 7(5): 557–564. doi: 10.12000/JR18061
    REN Lingyun, TRAN N, FOROUGHIAN F, et al. Short-time state-space method for micro-Doppler identification of walking subject using UWB impulse Doppler radar[J]. IEEE Transactions on Microwave Theory and Techniques, 2018, 66(7): 3521–3534. doi: 10.1109/TMTT.2018.2829523
    ZHAO Yichao and SU Yi. Cyclostationary phase analysis on micro-Doppler parameters for radar-based small UAVs detection[J]. IEEE Transactions on Instrumentation and Measurement, 2018, 67(8): 2048–2057. doi: 10.1109/TIM.2018.2811256
    MARáK K, PET? T, BILICZ S, et al. Electromagnetic simulation of rotating propeller blades for radar detection purposes[J]. IEEE Transactions on Magnetics, 2018, 54(3): 7203504. doi: 10.1109/TMAG.2017.2752904
    胡健, 羅迎, 張群, 等. 空間旋轉(zhuǎn)目標(biāo)窄帶雷達(dá)干涉式三維成像與微動特征提取[J]. 電子與信息學(xué)報(bào), 2019, 41(2): 270–277. doi: 10.11999/JEIT180372

    HU Jian, LUO Ying, ZHANG Qun, et al. Three-dimensional interferometric imaging and micro-motion feature extraction of rotating space targets based on narrowband radar[J]. Journal of Electronics &Information Technology, 2019, 41(2): 270–277. doi: 10.11999/JEIT180372
    SPARR T and KRANE B. Micro-Doppler analysis of vibrating targets in SAR[J]. IEE Proceedings-Radar, Sonar and Navigation, 2003, 150(4): 277–283. doi: 10.1049/ip-rsn:20030697
    STANKOVIC L, DAKOVIC M, THAYAPARAN T, et al. Inverse radon transform-based micro-Doppler analysis from a reduced set of observations[J]. IEEE Transactions on Aerospace and Electronic Systems, 2015, 51(2): 1155–1169. doi: 10.1109/TAES.2014.140098
    ZHOU Yang, BI Daping, SHEN Aiguo, et al. Hough transform-based large micro-motion target detection and estimation in synthetic aperture radar[J]. IET Radar, Sonar & Navigation, 2019, 13(4): 558–565. doi: 10.1049/iet-rsn.2018.5407
    CHEN Shiqian, YANG Yang, WEI Kexiang, et al. Time-varying frequency-modulated component extraction based on parameterized demodulation and singular value decomposition[J]. IEEE Transactions on Instrumentation and Measurement, 2016, 65(2): 276–285. doi: 10.1109/TIM.2015.2494632
    LI Ao, WU Zhiqiang, LU Huaiyin, et al. Collaborative self-regression method with nonlinear feature based on multi-task learning for image classification[J]. IEEE Access, 2018, 6: 43513–43525. doi: 10.1109/ACCESS.2018.2862159
    STANKOVIC L, DAKOVIC M, and THAYAPARAN T. Time-Frequency Signal Analysis with Applications[M]. Norwood, USA: Artech House, 2013: 205–243.
    李明, 吳嬌嬌, 左磊, 等. 基于實(shí)測數(shù)據(jù)的空中目標(biāo)分類識別算法[J]. 電子與信息學(xué)報(bào), 2018, 40(11): 2606–2613. doi: 10.11999/JEIT180024

    LI Ming, WU Jiaojiao, ZUO Lei, et al. Aircraft target classification and recognition algorithm based on measured data[J]. Journal of Electronics &Information Technology, 2018, 40(11): 2606–2613. doi: 10.11999/JEIT180024
    YANG Yang, PENG Zhike, DONG Xingjian, et al. Application of parameterized time-frequency analysis on multicomponent frequency modulated signals[J]. IEEE Transactions on Instrumentation and Measurement, 2014, 63(12): 3169–3180. doi: 10.1109/TIM.2014.2313961
    羅迎, 龔逸帥, 陳怡君, 等. 基于跟蹤脈沖的MIMO雷達(dá)多目標(biāo)微動特征提取[J]. 雷達(dá)學(xué)報(bào), 2018, 7(5): 575–584. doi: 10.12000/JR18035

    LUO Ying, GONG Yishuai, CHEN Yijun, et al. Multi-target micro-motion feature extraction based on tracking pulses in MIMO radar[J]. Journal of Radars, 2018, 7(5): 575–584. doi: 10.12000/JR18035
    XU Huajian, YANG Zhiwei, TIAN Min, et al. An extended moving target detection approach for high-resolution multichannel SAR-GMTI systems based on enhanced shadow-aided decision[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(2): 715–729. doi: 10.1109/TGRS.2017.2754098
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  • 收稿日期:  2019-04-30
  • 修回日期:  2019-12-23
  • 網(wǎng)絡(luò)出版日期:  2020-06-28
  • 刊出日期:  2020-08-18

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