Date Added: Sep 2011
In many applications based on Wireless Sensor Networks (WSNs) with static sensor nodes, the availability of accurate location information of the network nodes may become essential. The node localization problem is to estimate all the unknown node positions, based on noisy pairwise distance measurements of nodes within range of each other. Maximum Likelihood (ML) estimation results in a non-convex problem, which is further complicated by the fact that sufficient conditions for the solution to be unique are not easily identified, especially when dealing with sparse networks. Thereby, different node configurations can provide equally good fitness results, with only one of them corresponding to the real network geometry.