Applications and Prospect of Micro-motion Theory in the Detection of Sea Surface Target

Micro-Doppler signature is one of the physical characteristics of the target. The radar signature of a target with micro-motion can make fine characterizations of the shape, structure, and moving state of target, which reflects the nonstationary property of a radar signal. Hence, it has great superiority in the analysis of sea clutter and target detection in the case of high sea states based on the micro-Doppler theory. In this paper, to show the need for micro-Doppler, the modeling of scattering clutter from time-varying sea surface and analysis methods of sea clutter Doppler are first reviewed based on the principles and characteristics of micro-Doppler. Then, applications and technological approaches of micro-Doppler in sea surface target detection are introduced from the perspective of micro-motion target modeling and detection methods of micro-motion signatures. Finally, future research interests are highlighted based on problems experienced in present studies.

[1]  Xiaoli Zhang,et al.  Subspace detection for range and Doppler distributed targets with Rao and Wald tests , 2011, Signal Process..

[2]  Xiaolong Chen,et al.  Study on the fractional power spectrum of the scattered echoes from 1-D time-varying sea surface , 2012, 2012 IEEE Asia-Pacific Conference on Antennas and Propagation.

[3]  Xiaolong Chen,et al.  Fractal Feature Discriminant of Sea Clutter in FRFT Domain and Moving Target Detection Algorithm: Fractal Feature Discriminant of Sea Clutter in FRFT Domain and Moving Target Detection Algorithm , 2011 .

[4]  Fulvio Gini,et al.  Identification and analysis of sea radar clutter spikes , 2010 .

[5]  Xiang Li,et al.  ISAR Imaging of Targets With Complex Motion Based on Discrete Chirp Fourier Transform for Cubic Chirps , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[6]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[7]  R. L. Rogers,et al.  Micro-Doppler analysis of multiple frequency continuous wave radar signatures , 2007, SPIE Defense + Commercial Sensing.

[8]  Jian Zhang,et al.  Weak Target Detection Based on Intrinsic Mode Energy Entropy: Weak Target Detection Based on Intrinsic Mode Energy Entropy , 2011 .

[9]  Wen Hong,et al.  Micromotion Parameter Estimation of Free Rigid Targets Based on Radar Micro-Doppler , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[10]  David J. McLaughlin,et al.  Numerical comparison of techniques for estimating Doppler velocity time series from coherent sea surface scattering measurements , 1998 .

[11]  Simon Watts,et al.  Use of sea clutter models in radar design and development , 2010 .

[12]  D. Walker.  Experimentally motivated model for low grazing angle radar Doppler spectra of the sea surface , 2000 .

[13]  Zhang Qun,et al.  Extraction of micro-Doppler of ballistic missile based on compressive sensing , 2011 .

[14]  M. Derakhtian,et al.  Generalised likelihood ratio test-based multiple-target detection for fluctuating targets with unknown parameters , 2011 .

[15]  Moeness G. Amin,et al.  Analysis of micro-Doppler signals using linear FM basis decomposition , 2006, SPIE Defense + Commercial Sensing.

[16]  Fulvio Gini,et al.  High resolution sea clutter data: statistical analysis of recorded live data , 1997 .

[17]  Sammy W. Henderson,et al.  Micro-Doppler lidar signals and noise mechanisms: theory and experiment , 2000, Defense, Security, and Sensing.

[18]  Hui Chen,et al.  Facet-Based Investigation on EM Scattering From Electrically Large Sea Surface With Two-Scale Profiles: Theoretical Model , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[19]  Remke Rutgers,et al.  Coherent laser radar for vibrometry: robust design and adaptive signal processing , 1995, Defense, Security, and Sensing.

[20]  Eugene F. Greneker,et al.  Extraction of micro-Doppler data from vehicle targets at x-band frequencies , 2001, SPIE Defense + Commercial Sensing.

[21]  William Z. Lemnios,et al.  Overview of the Lincoln Laboratory Ballistic Missile Defense Program , 2002 .

[22]  Victor C. Chen,et al.  Doppler signatures of radar backscattering from objects with micro-motions , 2008 .

[23]  Mengdao Xing,et al.  Inverse synthetic aperture radar imaging of ship target with complex motion , 2008 .

[24]  Yanhong Tang,et al.  A Combined Denoising Algorithm Approach to Sea Clutter in Wave Monitoring System by Marine Radar , 2008, 2008 Second International Symposium on Intelligent Information Technology Application.

[25]  Weixian Liu,et al.  Radar Micro-Doppler Signature Analysis with HHT , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[26]  Kuang Yong.  Research on precession of ballistic missile warhead based on micro-Doppler analysis , 2008 .

[27]  Ljubisa Stankovic,et al.  Analysis of radar micro-Doppler signatures from experimental helicopter and human data , 2007 .

[28]  Yuri I. Abramovich,et al.  Order Estimation and Discrimination Between Stationary and Time-Varying (TVAR) Autoregressive Models , 2007, IEEE Transactions on Signal Processing.

[29]  Ran Tao,et al.  Short-Time Fractional Fourier Transform and Its Applications , 2010, IEEE Transactions on Signal Processing.

[30]  Lingjiang Kong,et al.  Target Parameters Extracted from Multi-harmonic Micro-Doppler Signal Analysis: Target Parameters Extracted from Multi-harmonic Micro-Doppler Signal Analysis , 2011 .

[31]  K. Parker,et al.  On estimating the amplitude of harmonic vibration from the Doppler spectrum of reflected signals , 1990 .

[32]  Jin Liu,et al.  Micro-Doppler characteristics of sliding-type scattering center on rotationally symmetric target , 2011, Science China Information Sciences.

[33]  Kai Huo,et al.  Parameters Estimation of Signals with Sinusoid Modulated Phase Based on Cyclostationary Character: Parameters Estimation of Signals with Sinusoid Modulated Phase Based on Cyclostationary Character , 2010 .

[34]  Alessio Balleri,et al.  Frequency-agile non-coherent ultrasound radar for collection of micro-Doppler signatures , 2011, 2011 IEEE RadarCon (RADAR).

[35]  M. Martorella,et al.  On the fractal dimension of sea surface backscattered signal at low grazing angle , 2004, IEEE Transactions on Antennas and Propagation.

[36]  Santanu Manna,et al.  The fractional Fourier transform and its applications , 2012 .

[37]  Yingning Peng,et al.  Radon-Fourier Transform for Radar Target Detection, I: Generalized Doppler Filter Bank , 2011, IEEE Transactions on Aerospace and Electronic Systems.

[38]  Joong-Sun Won,et al.  An Efficient Method of Doppler Parameter Estimation in the Time–Frequency Domain for a Moving Object From TerraSAR-X Data , 2011, IEEE Transactions on Geoscience and Remote Sensing.

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

[40]  You He,et al.  Sea clutter suppression and moving target detection method based on clutter map cancellation in frft domain , 2011, Proceedings of 2011 IEEE CIE International Conference on Radar.

[41]  Xiaolong Chen,et al.  Adaptive fractional fourier transform-based detection algorithm for moving target in heavy sea clutter , 2012 .

[42]  Vincent B. Sylvester,et al.  Use of the envelope detection method to detect micro-Doppler , 2003, SPIE Defense + Commercial Sensing.

[43]  Simon Haykin,et al.  Uncovering nonlinear dynamics-the case study of sea clutter , 2002, Proc. IEEE.

[44]  Wu Zhen-sen,et al.  Modified Two-Scale Model for Electromagnetic Scattering from the Non-Gaussian Oceanic Surface , 2005 .

[45]  Jian Guan,et al.  Weak Target Detection Based on the Average Bandwidth of the Partial Hilbert Spectrum: Weak Target Detection Based on the Average Bandwidth of the Partial Hilbert Spectrum , 2012 .

[46]  T. Thayaparan,et al.  Time-frequency method for detecting an accelerating target in sea clutter , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[47]  Qun Zhang,et al.  Micro-Doppler Signature Extraction and ISAR Imaging for Target With Micromotion Dynamics , 2011, IEEE Geoscience and Remote Sensing Letters.

[48]  Jiang Yi-cheng.  A method of ISAR ship imaging based on match Fourier transform , 2009 .

[49]  Mengdao Xing,et al.  High Resolution ISAR Imaging of Targets with Rotating Parts , 2011, IEEE Transactions on Aerospace and Electronic Systems.

[50]  Li Xiang.  The Achievements of Target Characteristic with Micro-Motion , 2007 .

[51]  V.C. Chen,et al.  Spatial and temporal independent component analysis of micro-Doppler features , 2005, IEEE International Radar Conference, 2005..

[52]  J Grajal,et al.  Facet Model of Moving Targets for ISAR Imaging and Radar Back-Scattering Simulation , 2010, IEEE Transactions on Aerospace and Electronic Systems.

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

[54]  Xiaojun Yang,et al.  Parameter Estimation of Multicomponent Chirp Signals via Sparse Representation , 2011, IEEE Transactions on Aerospace and Electronic Systems.