Speed and direction Prediction-based Localization for mobile wireless sensor networks

Many low-cost localization techniques have been proposed for wireless sensor networks. However, few consider the mobility of networked sensors. In this paper, we propose an effective and practical localization technique especially designed for mobile sensor networks called Speed and direction Prediction-based Localization. It uses a single mobile anchor travelling with a predefined trajectory while periodically broadcasts its current location coordinates to the nearby sensors. We concentrate on improving the localization accuracy and efficiency by making better use of the information a sensor node gathers. Using previous location information, the node predicts its speed and direction to move the estimated position closer to its real position. The evaluation of our solution shows that our technique copes with prediction and anchor trajectory in a more effective manner than previous solutions. The simulation results show that our algorithm outperforms conventional Monte Carlo localization schemes by decreasing estimation errors by up to 56%.