Adaptive Fractional Fourier Transform Based Chirp Signal Detection and Parameter Estimation

Qu Qiang; Jin Ming-lu

doi:10.3724/SP.J.1146.2008.01716

Volume 31 Issue 12

Dec. 2010

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Article Navigation > Journal of Electronics & Information Technology > 2009 > 31(12): 2937-2940

Qu Qiang, Jin Ming-lu. Adaptive Fractional Fourier Transform Based Chirp Signal Detection and Parameter Estimation[J]. Journal of Electronics & Information Technology, 2009, 31(12): 2937-2940. doi: 10.3724/SP.J.1146.2008.01716

Citation:

Qu Qiang, Jin Ming-lu. Adaptive Fractional Fourier Transform Based Chirp Signal Detection and Parameter Estimation[J]. Journal of Electronics & Information Technology, 2009, 31(12): 2937-2940. doi: 10.3724/SP.J.1146.2008.01716

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Adaptive Fractional Fourier Transform Based Chirp Signal Detection and Parameter Estimation

doi: 10.3724/SP.J.1146.2008.01716

Received Date: 2008-12-17
Rev Recd Date: 2009-06-01
Publish Date: 2009-12-19

Abstract

Abstract

An adaptive method of fractional Fourier transform based on Least Mean Square (LMS) algorithm is proposed and is used to detect and estimate parameters of multicomponent chirp signals. Through the discrete sampling of continuous inverse fractional Fourier transform, a discrete form for numerical calculation is obtained, and then an adaptive filter is constructed with the appropriate choices of the input vector and the desired sequence. The weight vector of the adaptive filter is trained according to LMS algorithm, and the stable weight vector is just the result of fractional Fourier transform. The simulation results show that the proposed algorithm can be used to calculate fractional Fourier transform and to detect and estimate parameters of chirp signals and the delay of calculation is relatively small.

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References

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