Anchorless localization with local manifold flattening

We present a new method for anchorless localization of mobile nodes in wireless networks using only measured distances between pairs of nodes. The novelty of the algorithm lies in the method to complete the Euclidean distance matrix by inferring the unknown distances such as to align all nodes on a k-hyperplane, where typically k is 2 or 3. The relative locations of the nodes are then computed using multidimensional scaling. We also present experimental results with data collected using our WASP platform to verify the improvement in localization using our algorithm over previously published techniques.