DocumentCode :
71460
Title :
A Fast Maneuvering Target Motion Parameters Estimation Algorithm Based on ACCF
Author :
Xiaolong Li ; Guolong Cui ; Wei Yi ; Lingjiang Kong
Author_Institution :
Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Volume :
22
Issue :
3
fYear :
2015
fDate :
Mar-15
Firstpage :
270
Lastpage :
274
Abstract :
This letter considers the motion parameters estimation problem for a maneuvering target with arbitrary parameterized motion. The slant range of the target is modeled as a polynomial function in terms of its multiple motion parameters and a fast estimation method based on adjacent cross correlation function (ACCF) is proposed, where the iterative adjacent cross correlation operation is employed to remove the range migration and reduce the order of Doppler frequency migration. Then the motion parameters are estimated via Fourier transform. Compared with the generalized Radon Fourier transform (GRFT), the proposed method can estimate the parameters without searching procedure and acquire close estimation performance at high signal-to-noise ratio (SNR) with a much lower computational cost. Finally, simulations are provided to demonstrate the effectiveness.
Keywords :
Fourier transforms; Radon transforms; image motion analysis; iterative methods; parameter estimation; ACCF; Doppler frequency migration; Fourier transform; GRFT; SNR; adjacent cross correlation function; arbitrary parameterized motion; fast estimation method; fast maneuvering target motion parameters estimation algorithm; generalized Radon Fourier transform; iterative adjacent cross correlation operation; motion parameters; motion parameters estimation problem; polynomial function; signal-to-noise ratio; Correlation; Fourier transforms; Parameter estimation; Polynomials; Radar; Signal processing algorithms; Terrorism; Adjacent cross correlation function; maneuvering target; motion parameters estimation; range migration;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2014.2358230
Filename :
6899616
Link To Document :
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