To track and recognize the projective spots of a cooperation target in the vehicle simulation test, a tracking and recognition method is proposed by combining the advantages of statistical methods and heuristic methods. This method tracks and recognizes the projective spots in a "prediction-recognition-modification" loop. In the prediction phase, the traditional Kalman filter is improved based on the movement characteristics of projective spots so as to precisely predict the projective spot positions. According to the predicted positions, the recognition of the projective spots in the recognition phase is divided into two parts. If a projective spot is in the field-of-view at next time instance, its optimal matching spot in the image will be rapidly searched with the gain function and matching strategy. If the projective spot is out of the field-of-view at next time instance, its position on the image plane will be calculated with the measuring system information, and the calculated position will be added into the corresponding trajectory. Once the recognition of the projective spots is completed, the parameters related to projective spots are modified with the recognition results. Simulation and real experimental results indicate that the proposed method can effectively track and recognize the projective spots, whose maximum error is no more than 2.5 pixel, even if the projective spots exit and enter the scene during the measurement.