Please use this identifier to cite or link to this item:
|Title:||Maximum likelihood DOA estimation in distributed wireless sensor network using adaptive particle swarm optimization|
Maximum likelihood estimation
|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. Copyright � 2011 ACM.|
|Appears in Collections:||Research Publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.