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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1389

Title: Maximum Likelihood DOA Estimation in Distributed Wireless Sensor Network Using Adaptive Particle Swarm Optimization
Authors: Panigrahi, T
Hanumantharao, A D
Panda, G
Majhi, B
Mulgrew, B
Keywords: MUSIC
Maximum Likelihood Estimation
Issue Date: Jan-2011
Citation: International Conference on Communication, Computing and Security (ICCCS-2011), National Institute of Technology, Rourkela, 12-14th Jan 2011.
Abstract: Source direction of arrival (DOA) estimation is one of the challenging problem in wireless sensor network. Several methods based on maximum likelihood (ML) criteria has been established in literature. Generally, to obtain the exact ML (EML) solutions, the DOAs must be estimated by optimizing a complicated nonlinear multimodal function over a high-dimensional problem space. An adaptive particle swarm optimization (APSO) based solution is proposed here to compute the ML functions and explore the potential of superior performances over traditional PSO algorithm. Simulation results confirms that the APSO-ML estimator is significantly giving better performance at lower SNR compared to conventional method like MUSIC in various scenarios at less computational costs.
Description: Copyright belongs to proceeding publisher
URI: http://hdl.handle.net/2080/1389
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