A Data Fusion Algorithm for Multi-sensor Dynamic System Based on Interacting Multiple Model

摘要：

We present an algorithm of data fusion estimation for dynamic system with multi-sensor and uncertain system models based on Kalman filtering and Interacting Multiple Model. The algorithm estimates the target state using interacting multiple model filtering method after using augmented multi-sensor fusion method. And this method is also available when the system contains different kinds of sensors or the measurement errors of different sensors are related. We test and verify the feasibility of this estimation algorithm through simulation and discuss the effect of the number of sensor on the estimation precision. Results show that, simply increasing the number of sensor cannot always improve the performance of the estimation. Type and number of sensor should be optimized in practical applications.

关键词： Multi-sensor Interacting Multiple Model Kalman Filtering

作者: CHEN Zhifeng CAI Yunze XU Xiaoming

作者单位: Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and In Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and In

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 199-203

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）