Title :
An algorithm for multi-sensor data fusion target tracking
Author :
Liu Guo-cheng ; Wang Yong-ji
Author_Institution :
Sch. of Power & Mech. Eng., Wuhan Univ., Wuhan
Abstract :
The principle of target tracking and data fusion techniques are discussed. To resolve enormous uncertainty that exists in sensors of mobile robots, the cross-sensor and cross-modality(CSCM) data fusion algorithm is presented. The algorithm is based on particle filter techniques, fuses the information coming from multiple sensors and merges different state space models. So it can be used to eliminate system and measurement noise and estimate value of position and heading of mobile robot. On simulation experiments, different cases, such as single sensor and multi-sensor data fusion, are compared, the results demonstrate the effectiveness of this algorithm and exhibits good tracking performance.
Keywords :
mobile robots; particle filtering (numerical methods); sensor fusion; target tracking; cross-modality; cross-sensor; data fusion algorithm; mobile robot sensors; multiple sensors; multisensor data fusion; particle filter; state space model; target tracking; Control systems; Data engineering; Mechanical engineering; Mechanical sensors; Mobile robots; Monte Carlo methods; Particle filters; Power engineering and energy; Sensor fusion; Target tracking; Data Fusion; Mobile Robot; Particle Filter; Target Tracking;
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
DOI :
10.1109/CCDC.2008.4597942