Three-dimensional micromotion trajectory reconstruction of rotating targets by interferometric radar

Abstract. Imaging, feature extraction, and recognition of targets with micromotion by retrieving their three-dimensional micromotion trajectories (3-D MMTs) have attracted a lot of interest in recent years. We propose a method for retrieving the 3-D MMT of a rotating target based on the interferometric phases obtained using a wideband interferometric radar system with three antennas positioned in L-shape. First, the micro-Doppler effect of rotating target is theoretically analyzed with formulas derived. Then, the instantaneous frequencies are extracted via the short-time Fourier transform and the Viterbi algorithm. The echo signals received by these three antennas are decomposed by the intrinsic chirp component decomposition method, and the interferometric phases of different scatterers are respectively obtained. Finally, the 3-D MMTs of rotating target are reconstructed by exploring the interferometric phases and the range-slow-time data. The effectiveness of the proposed method is validated by both simulations and practical experiment using a Ka-band interferometric radar.

[1]  Mengdao Xing,et al.  A Matched-Filter-Bank-Based 3-D Imaging Algorithm for Rapidly Spinning Targets , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Mengdao Xing,et al.  High-Resolution Three-Dimensional Radar Imaging for Rapidly Spinning Targets , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Yang Yang,et al.  Intrinsic chirp component decomposition by using Fourier Series representation , 2017, Signal Process..

[4]  Victor C. Chen,et al.  Analysis of radar micro-Doppler with time-frequency transform , 2000, Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing (Cat. No.00TH8496).

[5]  T. Yeo,et al.  Imaging of Moving Target with Rotating Parts Based on Hough Transform , 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

[6]  Ljubisa Stankovic,et al.  Signal Decomposition of Micro-Doppler Signatures , 2014 .

[7]  H. Wechsler,et al.  Micro-Doppler effect in radar: phenomenon, model, and simulation study , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[8]  Jr. G. Forney,et al.  Viterbi Algorithm , 1973, Encyclopedia of Machine Learning.

[9]  Mengdao Xing,et al.  High-Resolution Three-Dimensional Imaging of Spinning Space Debris , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[10]  Wei Zhang,et al.  Extraction of Vibrating Features With Dual-Channel Fixed-Receiver Bistatic SAR , 2012, IEEE Geoscience and Remote Sensing Letters.

[11]  Hao Chen,et al.  High-resolution inverse synthetic aperture radar imaging for large rotation angle targets based on segmented processing algorithm , 2017 .

[12]  Qun Zhang,et al.  Estimation of three-dimensional motion parameters in interferometric ISAR imaging , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Guang Meng,et al.  Separation of Overlapped Non-Stationary Signals by Ridge Path Regrouping and Intrinsic Chirp Component Decomposition , 2017, IEEE Sensors Journal.

[14]  Qun Zhang,et al.  Micromotion Feature Extraction and Distinguishing of Space Group Targets , 2017, IEEE Geoscience and Remote Sensing Letters.

[15]  Qun Zhang,et al.  Three-dimensional interferometric imaging and precession feature extraction of space targets in wideband radar , 2018 .

[16]  Lu Wang,et al.  Separation of micro-Doppler signals based on time frequency filter and Viterbi algorithm , 2013, Signal Image Video Process..

[17]  Yunhua Zhang,et al.  Micro-Doppler feature extraction for interferometric radar based on Viterbi algorithm and intrinsic chirp component decomposition , 2018, 2018 22nd International Microwave and Radar Conference (MIKON).

[18]  Yan Huang,et al.  Imaging of Spinning Targets via Narrow-Band T/R-R Bistatic Radars , 2013, IEEE Geoscience and Remote Sensing Letters.

[19]  Jiaqi Liu,et al.  Extraction of Micro-Doppler Frequency From HRRPs of Rotating Targets , 2017, IEEE Access.

[20]  Qun Zhang,et al.  Narrowband Radar Imaging and Scaling for Space Targets , 2017, IEEE Geoscience and Remote Sensing Letters.

[21]  Yunhua Zhang,et al.  Micro-motion of a moving train observed by a Ka-band interferometric radar , 2016 .

[22]  Richard L. Scheaffer,et al.  Probability and statistics for engineers , 1986 .

[23]  Zheng Bao,et al.  High-Resolution Three-Dimensional Imaging of Space Targets in Micromotion , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[24]  Mengdao Xing,et al.  Scaling the 3-D Image of Spinning Space Debris via Bistatic Inverse Synthetic Aperture Radar , 2010, IEEE Geoscience and Remote Sensing Letters.

[25]  Qun Zhang,et al.  Time-varying three-dimensional interferometric imaging for space rotating targets with stepped-frequency chirp signal , 2017 .

[26]  T. Sparr,et al.  Micro-Doppler analysis of vibrating targets in SAR , 2003 .

[27]  Feng Zhu,et al.  Three-dimensional precession feature extraction of space targets , 2014, IEEE Transactions on Aerospace and Electronic Systems.

[28]  Ram M. Narayanan,et al.  Multistatic micro-doppler radar for determining target orientation and activity classification , 2016, IEEE Transactions on Aerospace and Electronic Systems.

[29]  Jian Hu,et al.  Three-dimensional interferometric imaging and micromotion feature extraction of spinning space debris in low-resolution radar , 2018, Journal of Applied Remote Sensing.

[30]  H. Wechsler,et al.  Analysis of micro-Doppler signatures , 2003 .

[31]  Dianne P. O'Leary,et al.  The Use of the L-Curve in the Regularization of Discrete Ill-Posed Problems , 1993, SIAM J. Sci. Comput..

[32]  Stephan Herminghaus,et al.  Radar for tracer particles. , 2016, The Review of scientific instruments.