Design and implementation of a distributed WLS localization and tracking algorithm in wireless sensor network

In this paper, a distributed algorithm for localization and tracking in wireless sensor network is designed and implemented. Combining the fingerprint approach and subgradient optimization, the proposed algorithm, called golf algorithm, uses different strategies to attain fast movement for tracking a moving object and a fine tune to approach a stationary object, like a drive and a putt on the putting green in the golf. Based on the WLS objective function, a recursive form for both the fingerprint approach and subgradient optimization is derived and can be accomplished by anchor nodes in collaboration. From simulation results, we can see the proposed algorithm has better estimation performance than the conventional decentralized algorithms to localize a stationary or moving target in large wireless sensor networks. In addition, its hardware architecture is designed. The CORDIC operation is employed to compute the vector norm. Parallel processing is used to handle the calculation of fingerprint data. The tracking trajectories of the floating-point program and fixed-point hardware implementation are shown to be quite similar with small finite precision effect, which verifies the feasibility of this hardware solution.