Research On Automotive Anti-collision Target Identification Based On Information Fusion

Information fusion technology is a new technology appeared in 1980s in the 20th century, it is used in every walk of life along with the development of computer technology and information technology. The characteristic of multi-sensor information technology is that it cans fusion information coming from different sensors, so the information losing and unilateralism problem caused by single sensor can be avoided. Now, automotive anti-collision is mainly about passive equipments, and active anti-collision equipments are more in some western countries, but they need another more research in our country. The mainly function of automation anti-collision is collecting athletic information of target automation to help the driver to estimate the state of auto car effectively. In this paper, combined the characteristics of multi-sensor information fusion and automation anti-collision system, target recognition algorithms based on information fusion in automation anti-collision system is deeply researched. Main work and contents are as follows:In this paper, the structure and work elements of the automation anti-collision system are analyzed, then the problem of target recognition based on information fusion in automation anti-collision system is put forward, and target recognition and measurement theory are deeply analyzed and discussed.Based on the analysis of elements of multi-sensor information fusion and its fusion model, multi-sensor information fusion and the elements, algorithms of target recognition are deeply analyzed, providing strong foundation for automation anti-collision system's information fusion target recognition.The principle, structure and algorithm of federal Kalman filter are introduced and analyzed, and then the algorithm of information fusion based on federal Kalman filter is given. Simulation results show that this algorithm is very useful in fusion the radar and IRI data, data veracity is improved and the safety of automotive anti-collision system is enhanced.The target recognition method based on information fusion in automotive anti-collision is given. In this method, the outputs of partial filter and overall filter in federal Kalman filter are fused to get the state of target auto car, which is used in the automotive anti-collision system to improve the effect of target recognition. Simulation results show the method discussed in this paper is effective and reliable.