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论文类型：期刊论文

发表时间：2014-05-20

发表刊物：Journal of Information and Computational Science

收录刊物：EI、Scopus

卷号：11

期号：8

页面范围：2783-2791

ISSN号：15487741

摘要：With fast development of science and technology, People gradually need more and more information, causing significant pressure on the sampling. The sampling rate must be two times higher than the highest frequency of the signal based on Nyquist sampling theorem. Compressed Sensing (CS) employs a special sampling method which can capture and represent compressible signals at a rate significantly below the Nyquist rate. It can relieve the pressure of sampling process in Wireless Sensor Networks. And a cooperative self-localization method based on probability for wireless sensor networks is proposed. The method firstly estimates the initial Position of the located node based on the joint Probability density function of the distance between the located node and the connected reference nodes. Further, based on the refinement principle, a cooperative localization method is studied by making the best of the neighbour nodes and giving the neighbour nodes some confidence. The method improves the estimation accuracy as well as makes more unknown nodes to be located. Copyright ? 2014 Binary Information Press.