The Anti-collision Algorithm Based On Information Fusion

The Vehicle collision control algorithm based on information fusion applying in the process of vehicle, detecting traffic ahead by on-board sensors and combining with its running status to analysis, which to make effective decisions to control. This algorithm can advance the stability of the vehicle at high speeds, make great significance in the process of automobile collision control areas, enhance the stability and comfort when vehicle at high speeds to deal with emergency situations and improve the car’s active safety.In the first, the compose and basic principles of the radar sensor were detailed analyzed and selecting the FMCW radar system. Using the MATLAB simulation to product the transmitting signal, receiving signals and frequency signal which pays a key role of the system parameter values on the basis of the above analysis. Secondly, the data signals are analyzed which obtained from collision warning radar and the importance of filtering signal was proposed. Aiming at the analysis of multi-sensor information fusion algorithm, the Federated Kalman filter algorithm can perform the data fusion processing of information which was collected by the heterogeneous radar efficiently, and the anti-collision system accuracy was optimized reasonably. In the end, the ideal fusion was obtained. Finally, by researching the control strategy of vehicle collision, the Simulink model of the vehicle was built and the simulation of traditional PID control and fuzzy control are analyzed.The optimized algorithm can achieve accurate data which is collected by the two sensors by Matlab / Simulink.It can improve the security situation in the car, and effectively prevent traffic accidents. At the same time, it is very usefull in the stability and comfort of increasing speed of the car, and in the automotive anti-collision control.