Title
Multi-sensor fusion using an adaptive multi-hypothesis tracking algorithm
Author
TNO Fysisch en Elektronisch Laboratorium
Kester, L.J.H.M.
Contributor
Dasarathy B.V., (editor)
Publication year
2003
Abstract
The purpose of a tracking algorithm is to associate data measured by one or more (moving) sensors to moving objects in the environment. The state of these objects that can be estimated with the tracking process depends on the type of data that is provided by these sensors. It is discussed how the tracking algorithm can adapt itself, depending on the provided data, to improve data association. The core of the tracking algorithm is an extended Kalman filter using multiple hypotheses for contact to track association. Examples of various sensor suites of radars, electro-optic sensors and acoustic sensors are presented.
Subject
Data association
MHT
Sensor fusion
Tracking
Acoustic devices
Adaptive algorithms
Cameras
Electrooptical devices
Kalman filtering
Optical sensors
Radar tracking
Tracking radar
Acoustic sensors
Data association
Electrooptic sensors
Extended Kalman filtering
Multihypothesis tracking
Sensor data fusion
To reference this document use:
http://resolver.tudelft.nl/uuid:e322e150-03d0-4d3e-ba9c-e88904fd1070
DOI
https://doi.org/10.1117/12.487365
TNO identifier
237285
Source
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2003, 23-25 April 2003, Orlando, FL, USA, 164-172
Series
Proceedings of SPIE
Document type
conference paper