A Decentralized Positioning Method Based on Recursive Weighted Least Absolute Value Optimization for Wireless Sensor Networks

This letter presents a new positioning method based on recursive weighted least absolute value (RWLAV) optimization for wireless sensor networks. The proposed method is derived by minimizing a recursive-in-time cost function and can be realized in a decentralized and iterative manner. During each iteration, the target's location is computed by taking a weighted average (in terms of the measurement's reliability) of the previous location estimate and the local observation that is expressed as the difference between the previous location estimate and the current subgradient value. Computer simulation results show that the RWLAV method performs better than previous related methods.