Research On Multi - Sensor Space - Time Registration Technology

At present, the technology of multi-sensors data fusion has more and more widely used in military and civilian fields. Data fusion is not only the simple sum of data, it need complete temporal and spatial alignment before data association. And the results of alignment largely determine the result of data fusion. Therefore, temporal and spatial alignment is one of the prerequisites for data fusion. It is also one of the key technologies for data fusion. It can improve the performance of data fusion system.This paper systematically studies the basic issue of algorithms of temporal-spatial alignment. And this paper gets some conclusions and proposes some effective methods.First, for the inconsistent of sampling frequency and the start time of the sampling instant of sensors, based on the simulation analysis of time alignment algorithms which are commonly used, this paper designs unified scheme and systematically compares the performance of each algorithm from time complexity and registration precision. Conclusions can guide the choice of time alignment algorithms in practice.Second, the tests find that the measurement noise has great effect on the accuracy of time alignment. This paper proposes an improved time alignment algorithm based on Lagrange interpolation and Kalman filtering method. Simulation results show that the algorithm can effectively improve the accuracy of time alignment.Finally, for spatial alignment problems, this paper introduces common algorithms from two aspects. They are algorithms which are based on cooperative target and algorithms which are based on non-cooperative target. This paper also gives the relevant simulation results. In order to solve the problem that two-dimensional spatial registration algorithm cannot get the pitch angle error and is not suitable for long-range target, this paper proposes ECEF-Kalman algorithm based on ECEF coordinate system. Simulation results show the effectiveness of the algorithm.