Title :
New structure of Kalman filter base on adaptive genetic algorithm for radar networking
Author :
Yan Mingming ; Pan Wei
Author_Institution :
Minist. of Res., Shenyang Artillery Acad., Shenyang, China
fDate :
May 31 2014-June 2 2014
Abstract :
Due to the different data rates of the sensors and communication delays in the radar netting, the research of the asynchronous multisensor data fusion problem is more practical than that of the synchronous one. Through discussing the sequential approach, which is the classical asynchronous multisensor data fusion algorithm, a new algorithm based on distributed computation structure is proposed. The adaptive crossover probability and adaptive mutation probability are proposed, which consider the influence of every generation to algorithm and the effect of different individual fitness in every generation. Simulation results show the validity of the presented algorithm.
Keywords :
Kalman filters; genetic algorithms; probability; radar; sensor fusion; Kalman filter; adaptive crossover probability; adaptive genetic algorithm; adaptive mutation probability; asynchronous multisensor data fusion algorithm; communication delay; distributed computation structure; radar networking; sequential approach; Data integration; Genetic algorithms; Kalman filters; Radar; Sensor fusion; Time measurement; adaptive genetic algorithm; crossover probability; multi-sensor; mutation probability; radar networking;
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
DOI :
10.1109/CCDC.2014.6852368
