Novel Whale Cooperative Positioning Algorithm for UWB Sensor Networks

UWB positioning can be modeled as an optimization problem for a fitness function, which is resolved through the conventional whale optimization algorithm. The fitness function used in the conventional whale positioning algorithm does not use the range measurement data between labels, and the range measurement data is incomplete, which leads to a limited improvement in its positioning accuracy. Consequently, a novel whale cooperative positioning algorithm that can increase positioning accuracy is presented in this paper. First, a fitness function is established during the positioning process that contains the range measurement data between the labels to improve positioning accuracy. Then, the conventional whale positioning method provides a good initial position for the labels, enabling the proposed algorithm to quickly search for the optimal position. Finally, Levy flight mode is adopted to prevent the positioning result from converging to the local optimal solution. According to simulation results, the proposed algorithm can provide better positioning accuracy than the conventional whale positioning algorithm while realizing simultaneous positioning of all the labels.