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| Adaptive Fractional Fourier Transform Based Chirp Signal Detection and Parameter Estimation |
| Qu Qiang①②; Jin Ming-lu① |
①School of Electronic and Information Engineering, Dalian University of Technology, Dalian 116024, China;
②School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114051, China |
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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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Received: 17 December 2008
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2009, Vol. 31 
