Title :
Unified tracking and fusion for airborne collision avoidance using log-polar coordinates
Author :
Franken, Dietrich ; Hupper, Andreas
Author_Institution :
Data Fusion Algorithms & Software, Cassidian, Ulm, Germany
Abstract :
Collision avoidance applications require state estimators that are able to deliver estimates of relevant quantities with sufficient quality under hard real-time constraints. In this paper, we will present a unified approach to tracking and data fusion in this context. The proposed approach is easy to implement and allows for a kinematics integration of data stemming from a variety of sensor types. Initialization, prediction, and update in a common state space extended Kalman filter are elaborated. Simulation results show strengths and weaknesses of the proposed approach.
Keywords :
Kalman filters; air traffic; aircraft; collision avoidance; nonlinear filters; sensor fusion; state estimation; state-space methods; tracking; airborne collision avoidance; data fusion; data stemming; hard real-time constraints; kinematics integration; log-polar coordinates; relevant quantity; sensor types; state estimators; state space extended Kalman filter; tracking fusion; unified fusion; unified tracking; Collision avoidance; Equations; Jacobian matrices; Kalman filters; Mathematical model; Optical sensors; Radar tracking; Collision avoidance; log-polar coordinates; polar tracking; unobservable states;
Conference_Titel :
Information Fusion (FUSION), 2012 15th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4673-0417-7
Electronic_ISBN :
978-0-9824438-4-2