期刊
IEEE SIGNAL PROCESSING LETTERS
卷 15, 期 -, 页码 45-48出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2007.911180
关键词
centralized method; distributed maximum likelihood estimation; energy-based source localization; normalized incremental subgradient algorithm; sensor network
资金
- Science and Technology Committee of Shanghai Municipality [05DZ15004]
A new incremental optimization algorithm called normalized incremental subgradient (NIS) algorithm is proposed in this letter, which can be used for distributed maximum likelihood estimation (MLE). Its convergence with a diminishing stepsize has been proved and analyzed theoretically. We then apply the NIS algorithm to the energy-based sensor network source localization problem where the decay factor of the energy decay model is unknown. Simulation results show it can achieve very high estimation performance, which is only somewhat lower than that of the centralized localization method based on global optimization techniques, but with hundreds of times lower computational complexity than the centralized method.
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