Liu Feng, Xu Hui-Fa, Tao Ran. Detection and Parameter Estimation of Symmetrical Triangular LFMCW Signal Based on Fractional Fourier Transform[J]. Journal of Electronics & Information Technology, 2011, 33(8): 1864-1870. doi: 10.3724/SP.J.1146.2010.01150
Citation:
Liu Feng, Xu Hui-Fa, Tao Ran. Detection and Parameter Estimation of Symmetrical Triangular LFMCW Signal Based on Fractional Fourier Transform[J]. Journal of Electronics & Information Technology, 2011, 33(8): 1864-1870. doi: 10.3724/SP.J.1146.2010.01150
Liu Feng, Xu Hui-Fa, Tao Ran. Detection and Parameter Estimation of Symmetrical Triangular LFMCW Signal Based on Fractional Fourier Transform[J]. Journal of Electronics & Information Technology, 2011, 33(8): 1864-1870. doi: 10.3724/SP.J.1146.2010.01150
Citation:
Liu Feng, Xu Hui-Fa, Tao Ran. Detection and Parameter Estimation of Symmetrical Triangular LFMCW Signal Based on Fractional Fourier Transform[J]. Journal of Electronics & Information Technology, 2011, 33(8): 1864-1870. doi: 10.3724/SP.J.1146.2010.01150
The Symmetrical Triangular Linear Frequency Modulated Continuous Wave (STLFMCW) signal is a sort of typical Low Probability of Intercept (LPI) radar signal. The spectrum distribution characteristics of the STLFMCW signal is analyzed in the FRactional Fourier Transform (FRFT) domain. It is discovered that the each segment of Linear Frequency Modulated (LFM) signal contained by the STLFMCW signal has an energy peak in its optimal fractional Fourier transform, and the spectrum of all the LFM signal segments contained by the STLFMCW signal folds together completely in the Fourier domain, so the amplitude of the spectrum is very high. It badly influences the detection and parameter estimation of the STLFMCW signal on the low SNR condition. Therefore, this problem must be solved when FRFT is used to detect the STLFMCW signal. A novel method is presented to detect STLFMCW signal and estimate its parameters based on the FRFT and clustering analysis. The method solves the problem brought by the spectrum folding of the STLFMCW signal, and this method overcomes the limit that the peaks of the STLFMCW signal must be higher than the amplitude of the noise. On the low SNR condition, this method still has better effect to detect STLFMCW signal. Finally, simulations verify the effectiveness of the method.