A Comparison of Kalman Filter-based Approaches for Elliptic Extended Object Tracking
Kolja Thormann, Shishan Yang, Marcus Baum
Abstract
In this work, we discuss and compare Kalman filter-based approaches for tracking an elliptic extended object parameterized with orientation and semi-axes lengths. The methods include an Extended Kalman filter (EKF) implementation of the Random Hypersurface Model (RHM) approach using a radial function, an EKF-based approach for the Multiplicative Error Model (MEM), called MEM-EKF*, and a method for tracking the semi-axes independently, the Independent Axes Estimation (IAE) approach. We discuss pros and cons of the methods and compare them in various scenarios with a maneuvering object.
Topics & Concepts
Extended Kalman filterKalman filterInvariant extended Kalman filterOrientation (vector space)Computer scienceTracking (education)Alpha beta filterFast Kalman filterMultiplicative functionObject (grammar)Parameterized complexityHypersurfaceComputer visionFilter (signal processing)Artificial intelligenceControl theory (sociology)AlgorithmMathematicsMoving horizon estimationGeometryControl (management)Mathematical analysisPsychologyPedagogyTarget Tracking and Data Fusion in Sensor NetworksImage Processing and 3D ReconstructionHistorical Geography and Cartography