Distributed Extended Object Tracking Based on Diffusion Strategy
Yuanyuan Ren, Wei Xia
Abstract
In this work, we study the problem of ellipse extended object tracking with multiple measurements. We propose a distributed extended object tracking algorithm for heterogeneous networks based on the diffusion extended Kalman filter. We use a set of nodes with different parameters to estimate the kinematic state and extension of the extended object simultaneously. Simulation results verify that the proposed distributed approach could outperform the method without cooperation.
Topics & Concepts
Tracking (education)Kalman filterComputer scienceObject (grammar)EllipseVideo trackingKinematicsDiffusionSet (abstract data type)Computer visionArtificial intelligenceMathematicsGeometryProgramming languageClassical mechanicsPedagogyPsychologyThermodynamicsPhysicsTarget Tracking and Data Fusion in Sensor NetworksAdvanced Adaptive Filtering TechniquesNeural Networks and Applications