Detection in sea clutter based on nonlinear ARCH model |
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| Affiliation: | 1. Institut TELECOM, TELECOM SudParis, Département CITI, CNRS UMR 5157, 91011 Evry Cedex, France;2. Department of Electrical Engineering, University of Taif, Al-Haweiah 21974, Saudi Arabia;1. Faculty of Electrical and Electronics Engineering, Ho Chi Minh City University of Technology, Viet Nam;2. School of Engineering, University of Warwick, UK;3. School of Computing, University of Kent, UK;1. Laboratoire Signal et Communication, Ecole Nationale Polytechnique, 10, Av. Hassen Badi, P.O. Box 182, 16200 El-Harrach, Algeria;2. Signal Processing Group, Institute of Telecommunications, Technische Universität Darmstadt, Merckstr. 25, 64283 Darmstadt, Germany;1. Industrial Technology Research Institute, Zhengzhou University, Zhengzhou, China;2. School of Electrical Engineering, Zhengzhou University, Zhengzhou, China |
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| Abstract: | In this paper, a complex nonlinear autoregressive conditional heteroscedasticity (CNARCH) model is proposed to model sea clutter. For heteroscedastic model, since the likelihood function is not obtained from explicit probability density function (PDF) expression, it is typically referred to as a quasi-likelihood function. The corresponding quasi-maximum likelihood estimation (QMLE) of the model parameters is derived. Furthermore, the corresponding detection algorithm is derived based on this model. We also conduct the simulations of both synthetic and practical data, demonstrate that the proposed model offers higher accuracy in detection, than the linear ARCH model, when used in the sea clutter. |
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| Keywords: | Detection Nonlinear ARCH model Quasi-maximum likelihood estimation Radar Sea clutter |
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