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

• Published in: Signal processing 2018-03, Vol.144, p.192-200
• Main Authors: Xu, Sheng, Doğançay, Kutluyıl, Hmam, Hatem
• Format: Article
• Language: English
• Subjects: Delayed information; Distributed pseudolinear Kalman filter; Multi-hop communication; Multi-sensor; Out-of-sequence measurements
• ISSN: 0165-1684; 1872-7557
• DOI: 10.1016/j.sigpro.2017.10.014

•A 3D AOA tracking algorithm is proposed based on multi-hop information sharing to realize out-of-sequence data transmission.•To account for time delay of received information and to learn the network topology, a neighborhood matrix method is developed.•The proposed algorithm incorporates the estimates of out-of-sequence data employing packet-delay classification and performs close to the centralized method. 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.