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The proposed algorithm has a recursive algorithm based on combining mass spring method [13 15] and Kalman filtering [4, 16 18] to update location estimates while reducing oscillation, the repetitive variation of estimates, by the changes of information.
In [14], the mass spring method is adopted for range-free schemes.
These methods model nodes as masses connected using springs, referred to as mass spring method.
The mass spring method is an optimization tool minimizing the difference between an interest and a desire.
To the best of authors' knowledge, this is the first approach combining the mass spring method and Kalman filtering for range-free localization.
Our algorithm also refines location estimates iteratively by mass spring method and Kalman filtering to minimize variance of links of all pairs of one-hop neighbors.
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