Title :
Optimal asynchronous multisensor centralized fusion estimate
Author :
Qiu, Ai-bing ; Wen, Cheng-lin
Author_Institution :
Coll. of Autom. Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
Abstract :
In this paper the problem of asynchronous multisensor fusion estimate is considered. A new optimal asynchronous centralized fusion algorithm based on left synchronization lifting is presented. Comparing with the existing sequential filtering algorithm, the proposed algorithm has an advantage in computation. Comparing with the asynchronous centralized fusion algorithm based on right synchronization lifting, it guarantees that the lifted system is causal. The equivalence of the algorithms based on right and left synchronization lifting is also proved to show the optimality of the proposed algorithm. An illustrative example is provided to demonstrate the performance of the proposed algorithm.
Keywords :
filtering theory; sensor fusion; left synchronization lifting; optimal asynchronous centralized fusion algorithm; optimal asynchronous multisensor centralized fusion estimation; right synchronization lifting; sequential filtering algorithm; Computational complexity; Cybernetics; Filtering algorithms; Intelligent sensors; Machine learning; Noise measurement; Sampling methods; Sensor fusion; Sensor systems; Time measurement; Asynchronous; Kalman filter; data fusion; synchronization lifting;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212782