基于周期FRFT的多分量LFMCW雷达信号分离

doi:10.7527/S1000-6893.2013.0145

Abstract

Abstract:

The interception and feature extraction of multi-component linear frequency modulation continuous waveform (LFMCW) signals is difficult to perform for a radar intelligence reconnaissance system. In order to fast detect and efficiently separate multi-component LFMCW radar signals, a novel method is presented. First, with the introduction of periodic fractional Fourier transform (PFRFT), the relationship between PFRFT and FRFT is analyzed, and the PFRFT of a LFMCW signal is discussed. Then, a numerical computation method of discrete PFRFT is given, and the separation of the multi-component LFMCW signals is realized by narrowband filtering on the periodic fractional Fourier domain (PFRFD) with CLEAN. Finally, simulation results show several conclusions: (a) the computation efficiency of PFRFT outperforms periodic Wigner-Hough transform (PWHT); (b) the LFMCW signal component has energy peak on a certain PFRFD and preserves its time-frequency characteristic after separating; (c) when the powers of two LFMCW signals are widely different, it is efficient to separate on the PFRFD, otherwise separation on the time domain is better; (d) when the two LFMCW signal components have similar powers and the signal noise ratio (SNR) is 0 dB, the correlation coefficients between the separated and original LFMCW signal components are both greater than 0.9.

Key words: fractional Fourier transform, linear frequency modulation continuous waveform, detection, signal separating, feature extraction

CLC Number:

HUANG Yu, LIU Feng, WANG Zezhong, XIANG Chongwen, DENG Bing. Periodic FRFT-based Multi-component LFMCW Radar Signal Separating[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, doi: 10.7527/S1000-6893.2013.0145.

References

[1] Muoz-Ferraras J, Perez-Martinez F, Burgos-Garcia M. Helicopter classification with a high resolution LFMCW radar. IEEE Transactions on Aerospace and Electronic Systems, 2009, 45(4): 1373-1384.

[2] Gonzalez-Partida J T, Almorox-Gonzalez P, Burgos-Garcia M, et al. Through-the-wall surveillance with millimeter-wave LFMCW radars. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(6): 1796-1805.

[3] Pace P E. Detecting and classifying low probability of intercept radar. 2rd ed. Massachusetts: Artech House, 2009: 31-37.

[4] Barbarossa S. Analysis of multicomponent LFM signals by a combined Wigner-Hough transform. IEEE Transactions on Signal Processing, 1995, 43(6): 1511-1515.

[5] Guo Q, Li Y J, Wang C H, et al. Novel detection method for multi-component LFM signals. First International Conference on Pervasive Computing Signal Processing and Applications, 2010: 759-762.

[6] Liu F, Sun D P, Tao R, et al. Multi-component LFM signal feature extraction based on improved Wigner-Hough transform. 4th International Conference on Wireless Communications, Networking and Mobile Computing, 2008: 1-4.

[7] Yuan Y, Fu Y, Li Q F. Detection and parameter estimation of multicomponent LFM signals based on Hilbert-Huang Hough transform. Asia-Pacific Conference on Computational Intelligence and Industrial Applications (PACIIA 2009), 2009(1): 476-479.

[8] Cowell D M J, Freear S. Separation of overlapping linear frequency modulated (LFM) signals using the fractional Fourier transform. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 2010, 57(10): 2324-2333.

[9] Qi L, Tao R, Zhou S Y, et al. Detection and parameter estimation of multicomponent LFM signals based on the fractional Fourier transform. Science in China Series F: Information Sciences, 2004, 47(2): 184-198.

[10] Liu F, Xu H F, Sun D P, et al. Feature extraction of symmetrical triangular LFMCW signal using Wigner-Hough transform. Journal of Beijing Institute of Technology, 2009, 18(4): 478-483.

[11] Liu F, Xu H F, Tao R. Detection and parameter estimation of symmetrical triangular LFMCW signal based on fractional Fourier transform. Journal of Electronics & Information Technology, 2011, 33(8): 1864-1870. (in Chinese) 刘锋, 徐会法, 陶然. 基于FRFT的对称三角线性调频连续波信号检测与参数估计. 电子与信息学报, 2011, 33(8): 1864-1870.

[12] Millioz F, Davies M. Sparse detection in the chirplet transform: application to FMCW radar signals. IEEE Transactions on Signal Processing, 2012, 60(6): 2800- 2813.

[13] Geroleo F G, Brandt-Pearce M. Detection and estimation of multi-pulse LFMCW radar signals. 2010 IEEE Radar Conference, 2010: 1009-1013.

[14] Geroleo F G, Brandt-Pearce M. Detection and estimation of LFMCW radar signals. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(1): 405-418.

[15] Wang Z Z. Interception and waveform recognition of a kind of continuous wave radars signals based on periodic WHT. Yantai: Naval Aeronautical Engineering Institute, 2012. (in Chinese) 王泽众. 基于周期WHT的一类连续波雷达信号截获与波形识别. 烟台: 海军航空工程学院, 2012.

[16] Tao R, Deng B, Wang Y. Fractional Fourier transform and its applications. Beijing: Tsinghua University Press, 2009: 12-26. (in Chinese) 陶然, 邓兵, 王越. 分数阶傅里叶变换及其应用. 北京: 清华大学出版社, 2009: 12-26.

[17] Liu F, Xu H F, Tao R, et al. Research on resolution among multi-component LFM signals in the fractional Fourier domain. Science China Information Sciences, 2012, 55(6): 1301-1312.

[18] Deng B, Tao R, Qu C W. Analysis of the shading between multicomponent chirp signals in the fractional Fourier domain. Acta Electronica Sinica, 2007, 35(6): 1095-1098. (in Chinese) 邓兵, 陶然, 曲长文. 分数阶Fourier域中多分量chirp信号的遮蔽分析. 电子学报, 2007, 35(6): 1095-1098.

[19] Bultheel A. A two-phase implementation of the fractional Fourier transform. Report TW 588, 2011: 1-11.

[20] Zhao X H, Deng B, Tao R. Dimensional normalization in the digital computation of the fractional Fourier transform. Transactions of Beijing Institute of Technology, 2005, 25(4): 361-364. (in Chinese) 赵兴浩, 邓兵, 陶然. 分数阶傅立叶变换数值计算中的量纲归一化. 北京理工大学学报, 2005, 25(4): 361-364.

Periodic FRFT-based Multi-component LFMCW Radar Signal Separating

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	Naxi TIAN, Jianan XIE, Hui JIANG, Yu YANG. Characterization of space X-ray reflective focusing system by using synchrotron radiation facility [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(3): 527386-527386.
[2]	Liansheng LI, Zhiwu MEI, Jun XIE, Kun JIANG, Yongqiang SHI, Zhen CAO, Fuchang ZUO. A review of applications of X⁃ray focused optics in field of pulsar detection [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(3): 528286-528286.
[3]	SU Hang, XU Congan, YAO Libo, LI Jianwei, LING Qing, GAO Long. A lightweight oriented ship detection method in SAR images [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(S1): 726922-726922.
[4]	LIU Lei, LIU Dawei, WANG Xiaoguang, CHEN Junnan, LIU Dongxing. Development status and outlook of UAV clusters and anti-UAV clusters [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(S1): 726908-726908.
[5]	LIU Peidong, JIAO Bohan, DANG Zhaohui. Design method of polygon formation for space-based gravitational-wave detection [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(S1): 726907-726907.
[6]	LIU Huan, LIU Xiaojia, WANG Yufei, WANG Ning, CAO Lijun. Weld defect classification technology based on compound convolution neural network structure [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(S1): 726928-726928.
[7]	YANG Te, YANG Zhichun, LIANG Shuya, KANG Zaifei, JIA You. Feature extraction and identification of stationary random dynamic load using deep neural network [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 225952-225952.
[8]	HAN Songyu, SHAO Haidong, JIANG Hongkai, ZHANG Xiaoyang. Intelligent fault diagnosis of aero-engine high-speed bearings using enhanced CNN [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 625479-625479.
[9]	ZHAO Liangyu, LI Dan, ZHAO Chenyue, JIANG Fei. Some achievements on detection methods of UAV autonomous landing markers [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 25882-025882.
[10]	TANG Li, HAO Peng, REN Peige, ZHANG Zuyao, HE Xiang, ZHANG Xuejun. UAV abnormal behavior detection based on improved iForest algorithm [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(8): 326789-326789.
[11]	QI Liangang, HAN Yanze, WANG Yani, GUO Qiang, Kaliuzhny MYKOLA. Multi-component LFM interference suppression method based on chirp rate turning point and FrFT [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(8): 326840-326840.
[12]	LYU Shuaishuai, YANG Yu, WANG Binwen, YIN Chenfei. A crack identification method of aircraft structure based on improved FaceNet [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(6): 525463-525463.
[13]	JIAO Weidong, WANG Ruidong, YAO Junqiang, PANG Yanli. Conformal geometric algebraic description of runway incursion and conflict detection [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(5): 325297-325297.
[14]	LIU Fang, HAN Xiao. Adaptive aerial object detection based on multi-scale deep learning [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(5): 325270-325270.
[15]	LIU Shiming, LI Sihai, ZHENG Jiangtao, FU Qiangwen, TAO Yuanbo. Detection of slowly growing faults of GNSS/INS ultra-tight integration based on prefilters and two-stage AIME [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(3): 325168-325168.