Research for Parameter Estimation of Linear Frequency Modulation Signals

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Abstract:

In order to conduct estimation of parameters in signal processing, using maximum likelihood estimate and the minimum mean square error estimate and maximum a posteriori probability in Bayes estimate . The experimental results show that: the maximum likelihood estimate accuracy, but search volume greatly; and Bias estimation to a certain extent, can improve the operation speed, but lower precision. So in the actual operation, select appropriate estimate methods based on the specific conditions.

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3698-3701

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August 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Abatzoglou T.Fast Maximum Likelihood Joint Estimation of Frequency and Frequency Rate[J].IEEE Trans on AES,1986,22(6):708-715.

DOI: 10.1109/taes.1986.310805

Google Scholar

[2] Liang R M,Arun K s.Parameter Estimation for Superimposed Chirp Signals[C]IEEE International Conference 0n ASSP,San Francisco,1992:273—276.

Google Scholar

[3] Xu Jia-jia,Liu Yu. The starting point problem of parameters estimation for LFM signal based on Newton's method[J]. Acta Electronica Sinica , 2009, 37(3) : 598 - 602.

Google Scholar

[4] Yang Guang, Li Shao-bing. Real time estimation of space-borne SAR signal parameter using FrFT [J]. Systems Engineering and Electronics , 2010, 32(8) : 1649 - 1651.

Google Scholar

[5] Tao R, Li X M. Time-delay estimation of chirp signals in the fractional Fourier domain[J]. IEEE Trans. on Signal Processing, 2009, 57 (6) : 2852 - 2855.

DOI: 10.1109/tsp.2009.2020028

Google Scholar

[6] Pei S C, Hsue W L. Random discrete fractional Fourier transform[J]. IEEE Signal Processing Letters, 2009, 16(12): 1015- 1018.

DOI: 10.1109/lsp.2009.2027646

Google Scholar