An Asynchronous Multisensor Spatial Registration Algorithm
Xinhua Zhang, Huidong Guo, Zhi-jun Xia · 2007
Bias registration is the prerequisite of data fusion. The constant bias can be estimated efficiently by two-stage Kalman filtering. An algorithm is proposed which includes the asynchronous sensor fusion models and spatial registration with feedback mechanism. In bias-free stage, the multisensor asynchronous fusion is employed to compensate the asynchronous error; fusion results are fed back to the estimation in constant bias estimation stage. The algorithm compensates both spatial bias and temporal bias registration; it can be applied to multisensor systems. Finally, simulation is processed. The results show that the algorithm is in effect.