Efficient Detection of Chirp Signals Based on the Fourth-Order Origin Moment of Fractional Spectrum

A novel detection algorithm for chirp signals based on the fourth-order origin moment of fractional spectrum (OMFrS) is presented. The fourth-order OMFrS of a chirp signal in discrete form is first deduced. By using the rough search result and the symmetric property of the fourth-order OMFrS of the chirp signal, the difference between the theoretical optimal transform angle and the detected result is calculated, and a more accurate estimation is obtained. Compared to the existing one-step search and two-step search methods, the proposed algorithm achieves better accuracy with high detection speed. Simulation results were given to prove the advantages of this new approach.

[1]  Wang Dongjin,et al.  LFM signal detection using the origin moment of fractional spectrum , 2008, 2008 9th International Conference on Signal Processing.

[2]  John C. Wood,et al.  Radon transformation of time-frequency distributions for analysis of multicomponent signals , 1994, IEEE Trans. Signal Process..

[3]  Alexander M. Haimovich,et al.  SAR imagery of moving targets: application of time-frequency distributions for estimating motion parameters , 1994, Defense, Security, and Sensing.

[4]  Wang Dong-jin,et al.  LFM signal detection based on fractional power spectrum , 2009 .

[5]  Yougen Xu,et al.  Order selection in fractional Fourier transform based beamforming , 2010 .

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

[7]  Sergio Barbarossa,et al.  Analysis of multicomponent LFM signals by a combined Wigner-Hough transform , 1995, IEEE Trans. Signal Process..

[8]  Martin J. Bastiaans,et al.  On fractional Fourier transform moments , 2000, IEEE Signal Processing Letters.

[9]  Luís B. Almeida,et al.  The fractional Fourier transform and time-frequency representations , 1994, IEEE Trans. Signal Process..

[10]  Petar M. Djuric,et al.  Parameter estimation of chirp signals , 1990, IEEE Trans. Acoust. Speech Signal Process..

[11]  Fei Wang,et al.  A New Time-Frequency Analysis Method of Multi-Component Chirp Signal , 2006, 2006 8th international Conference on Signal Processing.

[12]  Andrew K. Chan,et al.  Linear frequency-modulated signal detection using Radon-ambiguity transform , 1998, IEEE Trans. Signal Process..

[13]  Rong Chen,et al.  Study of Threshold Setting for Rapid Detection of Multicomponent LFM Signals Based on the Fourth-Order Origin Moment of Fractional Spectrum , 2013, Circuits Syst. Signal Process..

[14]  Olcay Akay,et al.  Employing fractional autocorrelation for fast detection and sweep rate estimation of pulse compression radar waveforms , 2009, Signal Process..

[15]  QU Chang-wen.  Analysis of the Shading Between Multicomponent Chirp Signals in the Fractional Fourier Domain , 2007 .

[16]  Guoan Bi,et al.  LFM signal detection using LPP-Hough transform , 2011, Signal Process..

[17]  Xiaolong Chen,et al.  A fast FRFT based detection algorithm of multiple moving targets in sea clutter , 2010, 2010 IEEE Radar Conference.

[18]  Fu Ying,et al.  Detection and parameter estimation of multicomponent LFM signals based on Hilbert-Huang Hough transform , 2009, 2009 Asia-Pacific Conference on Computational Intelligence and Industrial Applications (PACIIA).

[19]  R. Tao,et al.  Detection and parameter estimation of multicomponent LFM signal based on the fractional fourier transform , 2004, Science in China Series F: Information Sciences.

[20]  Zhao Xing-hao,et al.  Dimensional Normalization in the Digital Computation of the Fractional Fourier Transform , 2005 .

[21]  V. Namias.  The Fractional Order Fourier Transform and its Application to Quantum Mechanics , 1980 .

[22]  Qinyu Zhang,et al.  Biomedical signal detection based on fractional fourier transform , 2008, 2008 International Conference on Information Technology and Applications in Biomedicine.

[23]  F. Taylor,et al.  Estimation of instantaneous frequency using the discrete Wigner distribution , 1990 .