Sequential measurement fusion second-order extended Kalman filter for multi-sensor nonlinear systems
A sequential measurement fusion second-order extended Kalman filter(SOEKF)algorithm is proposed for multi-sensor nonlinear systems.The main idea of the algorithm is to successively process the data according to the sequence of the data of the sensor arriving at the fusion center.The studied results show that the proposed sequential measurement fusion SOEKF algorithm has higher accuracy than the centralized measurement fusion EKF algorithm,and is comparable to the centralized measurement fusion SOEKF algorithm,with a lower computational complexity.The simulation of a target tracking system verifies the effectiveness of the algorithm.
multi-sensor information fusionsequential measurement fusionnonlinear systemsecond-order extended Kalman filter
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