3D AOA target tracking using distributed sensors with multi-hop information sharing

This paper investigates the problem of angle-of-arrival (AOA) target tracking in the three-dimensional (3D) space using multiple distributed sensors. Some sensors cannot share information directly because of the communication distance constraint arising from the broadcast power limitation of communication equipment. This can lead to reduced estimation performance as a result of limited information exchange. To improve the estimation performance, delayed information transmitted by intermediate sensors through multiple hops is utilized. A neighborhood matrix is proposed to sort the received information in terms of the number of hops. The information is classified into current information, 1-step delayed information and multi-step delayed information. A distributed pseudolinear Kalman filter (DPLKF) is developed based on out-of-sequence measurement updates to process the current and delayed information. Simulation examples demonstrate the effectiveness of the proposed algorithm in improving the tracking performance, in particular, during the initial convergence phase.