Conditions for unique graph realizations
SIAM Journal on Computing
Solving Euclidean Distance Matrix Completion Problems Via Semidefinite Programming
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part I
Localization from mere connectivity
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
GPS-Free Positioning in Mobile ad-hoc Networks
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 9 - Volume 9
Distributed weighted-multidimensional scaling for node localization in sensor networks
ACM Transactions on Sensor Networks (TOSN)
A Theory of Network Localization
IEEE Transactions on Mobile Computing
Exact Matrix Completion via Convex Optimization
Foundations of Computational Mathematics
Survey of Wireless Indoor Positioning Techniques and Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
WASP: A System and Algorithms for Accurate Radio Localization Using Low-Cost Hardware
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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We present a new method for anchorless localization of mobile nodes in wireless networks using only measured distances between pairs of nodes. Our method relies on the completion of the Euclidean distance matrix, followed by multidimensional scaling in order to compute the relative locations of the nodes. The key element of novelty of our algorithm is the method of completing the Euclidean distance matrix, which consists of gradually inferring the unknown distances, such as to align all nodes on a k-hyperplane, where typically k is 2 or 3. Our method leads to perfect anchorless localization for noise-free range measurements, if the network is sufficiently connected. We introduce refinements to the algorithm to make it robust to noisy and outlier range measurements. We present results from several localization tests, using both simulated data and experimental results measured using a large indoor network deployment of our WASP platform. Our results show improvements in localization using our algorithm over previously published techniques.