TAF PUBLISHING

To increase accuracy for dynamic detection obstacles, this paper presents a Kalman filter observation error model based on 77 GHz middle range radar (MRR). In recently, the vehicle equips advanced driver assistance system (ADAS), which becomes more popular. Among these, the accuracy of the obstacle information, such as distance, relative speed, and position, is the most important purpose. However, radar is one of the main detection sensors, but its data transmission delay, including millimeter-wave reflection, the analogy to digital signal conversion, and data process, would influence radar tracking correction. Therefore, algorithm of the proposed model adopts detection time and a dynamic estimated model of an obstacle to compensate detection delay, such that the dynamic correction means error can be reduced. Next, the testing condition sets RTK-GPS as the real-world reference frame, the experimental would be realized with the dynamic scene. According to the above results, when the target distance closer 100 meter, our model's dynamic correction mean error was improved 59%, 74%, 78% during in 20kph, 40kph, and 60kph relatively speed, respectively.