Application of an Enhanced Location System with the Virtual Multi-Sensor

Due to uncertainties in the working environment and effect of various noises, it is hard for location system to estimate the state and track the target directly. Therefore a strongly algorithm has a great significant for the location system. In this paper we propose an accurate kinetic model obtained from experiments in the Robocup 3D Serve system and apply the virtual multi-sensor collaboration method to research on the state estimation in Extended Kalman Filter algorithms with the delayed observation as well as analyze filtering stability under the uncertain observation condition based this system. The experiment results show that the algorithms through the application of virtual multi-sensor have a good performance even under the observation delay.