摘要： The intelligent vehicle target detection system can sense and recognize the surrounding pedestrians, vehicles and other objects through sensors, which is the basis for achieving intelligent vehicle unmanned driving. The laser imaging radar actively emits laser light and receives its reflected echo, which can form an angle-angle-distance-intensity image, making it easier to realize target recognition. The combination of the lidar and the infrared characteristics of the target can obtain more information and improve target recognition and anti-interference ability. In order to achieve fast and accurate moving target detection in a complex battlefield environment, this paper studies lidar imaging and target infrared features, as well as intelligent vehicle target detection, and proposes a target recognition method that combines target infrared features and lidar. Compensation makes it difficult to describe the disadvantages of moving targets in a single source data. The experimental results show that the laser and infrared fusion detection algorithm does not increase the complexity of the algorithm, which greatly improves the adaptability and robustness of the vehicle target detection algorithm, and improves the accuracy of the measurement detection algorithm.