Collaborative tracking and positioning of unmanned aerial vehicles over wireless sensor networks

In recent years, wireless sensor networks have been widely applied in information acquisition and real-time monitoring of consumer electronics, particularly for tracking and positioning of consumer unmanned aerial vehicles (UAVs) in outdoor rescue scenarios. However, the challenging outdoor environments introduce reliability and security concerns in the sensor data acquisition process, and there remains a significant gap in related research efforts. To address this issue, this paper introduces an amplify-and-forward relaying strategy to ensure dependable signal transmission, while a residual saturation mechanism is applied to tackle randomly occurring measurement outliers. Additionally, a recursive extended Kalman filter is developed for target tracking to address the challenge of UAVs positioning within wireless sensor networks. The efficacy of the proposed filtering algorithm is validated through simulations of UAV target positioning. When compared with alternative methods, the proposed approach demonstrates superior accuracy in UAV positioning.