Infrared panoramic search and track systems can provide real-time multi-target search and positioning functions for a 360? field of view. However, the involvement of the large view field introduces problems such as increased number of false targets and a large displacement of moving targets between panoramic frames. To address these problems, this study uses the image pyramid transform to reduce the panoramic image resolution and the Lucas-Kanade optical-flow method to calculate the optical flow of all predicted movement areas. Finally, the optical-flow features are analyzed to separate the real target from the false target area. In this way, false targets can be effectively detected in the panorama images, and the interference of such targets in the subsequent processing can be eliminated.