Distributed pseudolinear estimation and UAV path optimization for 3D AOA target tracking

• Published in: Signal processing Vol. 133; pp. 64 - 78
• Main Authors: Xu, Sheng, Doğançay, Kutluyıl, Hmam, Hatem
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.04.2017
• Subjects: Angle-of-arrival (AOA); Distributed path optimization; Distributed pseudolinear Kalman filter (DPLKF); Path optimization; Unmanned aerial vehicle (UAV); Path optimization; Angle-of-arrival (AOA); Distributed path optimization; Unmanned aerial vehicle (UAV); Distributed pseudolinear Kalman filter (DPLKF)
• ISSN: 0165-1684; 1872-7557
• DOI: 10.1016/j.sigpro.2016.10.012

We address the problem of angle-of-arrival (AOA) target tracking using multiple unmanned aerial vehicles (UAVs) in three-dimensional (3D) space. A distributed 3D AOA target tracking method is proposed consisting of a distributed estimator and path optimization algorithm for multiple UAVs. First a novel 3D distributed pseudolinear Kalman filter (DPLKF) is developed to improve the stability of an extended Kalman filter solution. The DPLKF consists of two coupled filters; viz., an xy-DPLKF and a z-DPLKF. The bias problem of the 3D DPLKF is analyzed and a bias reduction method is proposed. A distributed path optimization algorithm is developed subject to communication range constraints and no-fly zones. This algorithm computes UAV waypoints using gradient-descent optimization on the xy-plane and grid search along the z-axis. To improve the tracking performance, the trace of the error covariance matrix is minimized. The properties and effectiveness of the proposed strategy are discussed and validated with simulation examples. •A novel distributed pseudolinear Kalman filter (DPLKF) is developed for 3D AOA target tracking.•The bias problem of the 3D DPLKF is analyzed and a bias reduction method is proposed.•A distributed path optimization algorithm is developed subject to communication range constraints and no-fly zones.