Study On Time Registration Technology For Multi-sensor Information Fusion

Time registration technology is a key technology of data preprocessing for multi-sensor information fusion. It is a common problem related to information fusion applications on how to improve the effectiveness of time registration. For the nonidentity of sampling periods and start-up time, time registration technology is widely used in the multi-sensor information fusion systems. Interpolation method and Least Squares (LS) method are two common approaches for time registration. But the above two approaches may make relatively larger errors when processing complex moving objects; also they don't take into account influences of observation errors and real-time processing.In order to solve the above problems, this paper unfolds the work in the following three aspects. Firstly, time registration models are spread out according to the analysis of the common models and processing flows. Secondly, two movement models of which are variant linear motivation and variant curvilinear motivation have been analyzed for time registration. In this part, the formulas of Interpolation method and Least Squares (LS) method have been deduced and registration errors and multi-sensor data procedures have been analyzed for further work. Lastly, we combine the existing approaches for time registration with Kalman filter and put forward a new time registration approach for real-time processing which is based on Kalman filter technology. The approach utilizes Kalman filter to carry through data filtering and predict the state of data collecting which can improve the accuracy and the real time ability. Moreover, experimental results show the good performance of our work.