An SVD based algorithm to estimate the parameters of vibration

Micro-Doppler features induced by micromotions of an object or structures of an object are a unique signature which is very useful in target identification and recognition. This paper introduces an algorithm based on singular value decomposition (SVD) to estimate the parameters of vibration. Firstly, the modulation induced by vibration is derived to be sinusoidal frequency modulation (SFM). Then, the modulation frequency is determinated through singular value ratio (SVR) spectrum. Afterwards, the frequency modulation index and the initial phase are estimated through two-dimension searching. Finally, this algorithm is demonstrated to be effective through several simulations under different SNRs (signal to noise ratio). Compared to the Hough transform (HT), the SVD based algorithm performs better in terms of computational complexity, computer storage and so on.

[1]  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).

[2]  Bin Deng,et al.  A Sinusoidal Frequency Modulation Fourier Transform for Radar-Based Vehicle Vibration Estimation , 2014, IEEE Transactions on Instrumentation and Measurement.

[3]  T. Sparr,et al.  Time-frequency analysis of vibrating targets in airborne SAR systems , 2003 .

[4]  P. Suresh,et al.  Extracting Micro-Doppler Radar Signatures From Rotating Targets Using Fourier–Bessel Transform and Time–Frequency Analysis , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Armin W. Doerry,et al.  Demonstration of target vibration estimation in synthetic aperture radar imagery , 2011, 2011 IEEE International Geoscience and Remote Sensing Symposium.

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

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

[8]  Chen Xiao-lon.  Gaussian Short-Time Fractional Fourier Transform Based Detection Algorithm of Target with Micro-Motion at Sea , 2014 .

[9]  Sarbani Palit,et al.  On multiple pattern extraction using singular value decomposition , 1995, IEEE Trans. Signal Process..

[10]  Shen Li-ran.  Parameter estimation of multicomponent SFM signals based on discrete sinusoidal frequency modulation transform , 2012 .

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

[12]  Qun Zhang,et al.  Imaging of a Moving Target With Rotating Parts Based on the Hough Transform , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Qun Zhang,et al.  Micro-Doppler Effect Analysis and Feature Extraction in ISAR Imaging With Stepped-Frequency Chirp Signals , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Zhaowen Zhuang,et al.  Estimation of micro-motion parameters based on micro-Doppler , 2010 .