Zhang xiaoyun
Department of Information Engineering, Chongqing University of Science and Technology, Chongqing, China
ABSTRACT
The velocity estimation is an important problem in many applications such as communication and navigation. But in some application such as sea, this task is very difficult because of the strong clutter. Many algorithms have been proposed for this problem. The Maximum Likelihood (ML) is one of the good solutions. This paper describes an application of Neural Network (NN) for obtaining the global optimal solution of ML velocity estimation. It overcomes the local optima problem existing in some ML velocity estimation algorithms and improves the estimation accuracy. The computation complexity is modest.
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How to cite this article
Zhang xiaoyun, 2013. Application of Neural Network Filter to Estimate the Velocity of Targets in Strong Clutter. Information Technology Journal, 12: 7983-7988.
DOI: 10.3923/itj.2013.7983.7988
URL: https://scialert.net/abstract/?doi=itj.2013.7983.7988
DOI: 10.3923/itj.2013.7983.7988
URL: https://scialert.net/abstract/?doi=itj.2013.7983.7988
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