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Fast Adaptive Method of the Multi-LFM Signal Detection and Parameter Estimation Based on Fractional Fourier Transform

XU Xiang-hui

Open publisher page 1 citations

Abstract

Two fast adaptive methods of the multi-LFM signal detection and parameter estimation based on FRFT are presented.Against FRFT's two-dimensional search problem,two pre-judge ways are proposed: using single-phase method to analyze the time autocorrelation sequence's spectrum and predicting the chirp rate.The computational complexity has a significant reduction without affecting the estimation accuracy of the premise and can also get good results in low SNR.Computer simulations verify the effectiveness of this method.

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What this paper is about

Two fast adaptive methods of the multi-LFM signal detection and parameter estimation based on FRFT are presented.Against FRFT's two-dimensional search problem,two pre-judge ways are proposed: using single-phase method to analyze the time autocorrelation sequence's spectrum and predicting the chirp rate.The computational complexity has a significant reduction without affecting the estimation accuracy of the premise and can also get good results in low SNR.Computer simulations verify the effectiveness of this method.

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Available abstract

Two fast adaptive methods of the multi-LFM signal detection and parameter estimation based on FRFT are presented.Against FRFT's two-dimensional search problem,two pre-judge ways are proposed: using single-phase method to analyze the time autocorrelation sequence's spectrum and predicting the chirp rate.The computational complexity has a significant reduction without affecting the estimation accuracy of the premise and can also get good results in low SNR.Computer simulations verify the effectiveness of this method.

Key concepts: Chirp, Autocorrelation, Fractional Fourier transform, Algorithm, Computational complexity theory, Computer science, SIGNAL (programming language), Fourier transform

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