A new localization algorithm for wireless sensor network

It is often very useful to know the positions of the sensor nodes in a wireless sensor network. The semidefinite programming (SDP) solution usually has a rank higher than the underlying physical space, which when projected onto the lower dimensional space generally results in high estimation error.In this paper, We describe a general subset localization based on semidefinite programming (SLSDP) approach for solving the graph realization problem, of which the sensor network localization problems is a special case. A large set is solved as a sequence of very small subsets, each of which is solved by SDP. Computational results show that the SLSDP algorithm scales well and provides excellent localization accuracy. The optimization problem is set up so as to minimize the error in sensor positions. Very few anchor nodes are required to accurately estimate the position of all the unknown nodes in a network. Also the estimation errors are minimal even when the anchor nodes are not suitably placed within the network. Experimental results validate SLSDP methods and show that it outperforms existing SDP methods.