High Range Resolution Profile Construction Exploiting Modified Fractional Fourier Transformation

This paper addresses the discrimination of closely spaced high speed group targets with radar transmitting linear frequency modulation (LFM) pulses. The high speed target motion leads to range migration and target dispersion and thereby the discriminating capability of the high range resolution profile (HRRP) deteriorating significantly. An effective processing approach composed of stretch processing (SP), modified fractional Fourier transform (FrFT), and multiple signal classification (MUSIC) algorithm is proposed to deal with this problem. Firstly, SP is adopted to transform the received LFM with Doppler distortions into narrow band LFM signals. Secondly, based on the two-dimensional range/velocity plane constructed by the modified FrFT, the velocity of the high speed group target is estimated and compensated with just one single pulse. After the compensation of range migration and target dispersion simultaneously, the resolution of the HRRP achieved by single pulse transmission improves significantly in the high speed group targets scenarios. Finally, MUSIC algorithm with superresolution capability is utilized to make a more explicit discrimination between the scatterers in comparison with the conventional SP method. Simulation results show the effectiveness of the proposed scheme.

[1]  Kainam Thomas Wong,et al.  Viable/Inviable Polynomial-Phase Modulations for "Stretch Processing" , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[2]  Karl Granström,et al.  On Spawning and Combination of Extended/Group Targets Modeled With Random Matrices , 2013, IEEE Transactions on Signal Processing.

[3]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[4]  S. Blunt,et al.  Aspects of Radar Range Super-Resolution , 2007, 2007 IEEE Radar Conference.

[5]  Hsueh-Jyh Li,et al.  Using range profiles as feature vectors to identify aerospace objects , 1993 .

[6]  Mengdao Xing,et al.  A Novel Method for Imaging of Group Targets Moving in a Formation , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[7]  Xiaolong Chen,et al.  Detection of low observable moving target in sea clutter via fractal characteristics in fractional fourier transform domain , 2013 .

[8]  Soo-Chang Pei,et al.  Fractional Fourier Transform, Wigner Distribution, and Filter Design for Stationary and Nonstationary Random Processes , 2010, IEEE Transactions on Signal Processing.

[9]  Gozde Bozdagi Akar,et al.  Digital computation of the fractional Fourier transform , 1996, IEEE Trans. Signal Process..

[10]  Hyo-Tae Kim,et al.  Efficient radar target recognition using the MUSIC algorithm and invariant features , 2002 .

[11]  Yongxiang Liu,et al.  A new approach for synthesizing the range profile of moving targets via stepped-frequency waveforms , 2006, IEEE Geoscience and Remote Sensing Letters.

[12]  T. Abatzoglou,et al.  Range, radial velocity, and acceleration MLE using radar LFM pulse train , 1998 .

[13]  R. S. Berkowitz,et al.  Characteristics of autoregressive spectral estimation in range-Doppler imaging , 1988, Proceedings of the 1988 IEEE National Radar Conference.

[14]  Thomas H Einstein,et al.  Generation of High Resolution Radar Range Profiles and Range Profile Auto-Correlation Functions Using Stepped-Frequency Pulse Train , 1984 .

[15]  Sanjay Kumar,et al.  Caputo-Based Fractional Derivative in Fractional Fourier Transform Domain , 2013, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[16]  Joseph A. O'Sullivan,et al.  Automatic target recognition using sequences of high resolution radar range-profiles , 2000, IEEE Trans. Aerosp. Electron. Syst..

[17]  Mengdao Xing,et al.  A Unified Focusing Algorithm for Several Modes of SAR Based on FrFT , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Simon J. Godsill,et al.  Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods , 2011, IEEE Transactions on Signal Processing.

[19]  Gui Gao,et al.  An Improved Scheme for Target Discrimination in High-Resolution SAR Images , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[20]  William J. Caputi,et al.  Stretch: A Time-Transformation Technique , 1971, IEEE Transactions on Aerospace and Electronic Systems.

[21]  Nadav Levanon,et al.  Stepped-frequency pulse-train radar signal , 2002 .

[22]  Huadong Meng,et al.  Motion Compensation of Moving Targets for High Range Resolution Stepped-Frequency Radar , 2008, Sensors.

[23]  W. F. Gabriel.  Improved range superresolution via bandwidth extrapolation , 1993, The Record of the 1993 IEEE National Radar Conference.

[24]  Jian Li,et al.  Joint super-resolution moving target feature extraction and stationary clutter suppression , 2000 .

[25]  W. F. Gabriel.  Superresolution techniques in the range domain , 1990, IEEE International Conference on Radar.

[26]  C. Fukushima,et al.  A Study on Stepped Frequency Radar by Using Intra-Pulse Phase Coded Modulation , 2008 .

[27]  Raj Mittra,et al.  Scattering center analysis via Prony's method , 1987 .

[28]  Jacek Misiurewicz,et al.  Stretch processing for masking effect removal in noise radar , 2008 .

[29]  Eric K. Walton.  Comparison of Fourier and maximum entropy techniques for high‐resolution scattering studies , 1987 .

[30]  Cheng Chen,et al.  A new super-resolution 3D-SAR imaging method based on MUSIC algorithm , 2011, 2011 IEEE RadarCon (RADAR).

[31]  Gang Li,et al.  Velocity Estimation and Range Shift Compensation for High Range Resolution Profiling in Stepped-Frequency Radar , 2010, IEEE Geoscience and Remote Sensing Letters.

[32]  Randolph L. Moses,et al.  Autoregressive modeling of radar data with application to target identification , 1988, Proceedings of the 1988 IEEE National Radar Conference.

[33]  S.K. Wong.  High Range Resolution Profiles as Motion-Invariant Features for Moving Ground Targets Identification in SAR-Based Automatic Target Recognition , 2009, IEEE Transactions on Aerospace and Electronic Systems.