Parameter Estimation of Radar Targets with Macro-Motion and Micro-Motion Based on Circular Correlation Coefficients

Micro-Doppler (m-D) signatures induced by micro-motion dynamics, which are of great importance for target classification, have received increasing attention among the radar community. For scenarios when the micro-motion of radar target is accompanied by macro-motion, the periodicity of m-D is disturbed by macro-motion. In that case, extraction of micro-motion signatures based on the periodicity of time-frequency representation (TFR) of the radar echo may become invalid. In this work, we show that the periodicity of TFR is replaced by circular periodicity in the presence of macro-motion. In view of this, the circular correlation coefficients of TFR are employed to characterize the circular periodicity of TFR and to provide an estimate of the micro-motion period. The property of circular correlation coefficients enables us to estimate the micro-motion period of radar targets in the presence of macro-motion. Experiments with synthetic data and measured radar data validate the effectiveness of the proposed method.

[1]  Igor Djurovic,et al.  Micro-Doppler-based target detection and feature extraction in indoor and outdoor environments , 2008, J. Frankl. Inst..

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

[3]  T. Thayaparan,et al.  Separation of target rigid body and micro-doppler effects in ISAR imaging , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[4]  Orelle R. Fogle,et al.  Human Micro-Range/Micro-Doppler Signature Extraction, Association, and Statistical Characterization for High-Resolution Radar , 2011 .

[5]  Peng Guo,et al.  Automatic classification of radar targets with micro-motions using entropy segmentation and time-frequency features , 2011 .

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

[7]  Jin Li,et al.  Research on micro-feature extraction algorithm of target based on terahertz radar , 2013, EURASIP J. Wirel. Commun. Netw..

[8]  Hao Ling,et al.  Application of adaptive chirplet representation for ISAR feature extraction from targets with rotating parts , 2003 .

[9]  Hongwei Liu,et al.  Hierarchical Classification of Moving Vehicles Based on Empirical Mode Decomposition of Micro-Doppler Signatures , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[10]  N. N. Tong,et al.  Micro-Doppler extraction of rotating targets based on Doppler rate , 2011, 2011 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC).

[11]  Junfeng Wang,et al.  Phase adjustment for extraction of micro-motion information of ballistic targets , 2012, 2012 5th International Congress on Image and Signal Processing.

[12]  Xiaoyi Pan,et al.  Modulation effect and inverse synthetic aperture radar imaging of rotationally symmetric ballistic targets with precession , 2013 .

[13]  Ivan W. Selesnick,et al.  The short-time Fourier transform and speech denoising , 2009 .

[14]  Tao Yang,et al.  Cooperative Control for Satellite Formation Reconfiguration via Cyclic Pursuit Strategy , 2009 .

[15]  Weixian Liu,et al.  Empirical mode decomposition of micro-Doppler signature , 2005, IEEE International Radar Conference, 2005..

[16]  Jun Wang,et al.  Research on the Life Detection Based on Mirco Doppler Features , 2013 .