Title :
Interacting multiple sensor unscented Kalman filter for accelerating object tracking
Author :
Liu, Zhigang ; Wang, Jinkuan ; Qu, Wei
Author_Institution :
Dept. of Autom. Eng., Northeastern Univ., Qinhuangdao, China
Abstract :
Due to limited sensing range for sensor nodes, moving object tracking has to be realized by relaying from one node to the other in a cluster. By taking object tracking in a fixed cluster as a Markov jump nonlinear system, the interacting multiple sensor unscented Kalman filter(IMSUKF) algorithm is designed to deal with distributed tracking. The proposed method can be divided into two parts: one-step unscented Kalman filter for object tracking and the fusion of the information provided by all the nodes. Finally, simulation results show the effectiveness of the proposed method.
Keywords :
Kalman filters; Markov processes; object detection; sensor fusion; target tracking; Markov jump nonlinear system; accelerating object tracking; distributed tracking; fixed cluster; information fusion; interacting multiple sensor; unscented Kalman filter; Acceleration; Algorithm design and analysis; Automation; Clustering algorithms; Collaboration; Filtering; Kalman filters; Nonlinear systems; Sensor systems; State estimation;
Conference_Titel :
Networking, Sensing and Control (ICNSC), 2010 International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-6450-0
DOI :
10.1109/ICNSC.2010.5461518
