False alarm suppression is one of the most important tasks in infrared small target detection system.In complex scenes,there are a large number of interferences similar to the target’s grayscale features,which are easy to be recognized as false alarms.It is difficult for existing methods to accurately and efficiently distinguish the targets and filter out the false alarms.To address these problems,a highly robust infrared false alarm suppression method based on target relative motion inference is proposed in this paper.Firstly,by extracting motion information from the reported targets and analyzing the relative motion relationship between the targets,a motion information matching table is constructed.Then,the voting information is selected according to the motion information matching table to filter out the false alarms in the reported information.Experiments are conducted in eight complex scenarios containing false alarms,including a scenario in which the background is moving relative to the camera stationary target,a scenario in which the target is moving relative to the camera stationary false alarms,a scenario in which the camera frame is shaking violently,and a scenario in which all detected targets are false alarms.The experimental results show that the method proposed in this paper can accurately filter out false alarms in the above scenarios,and can reach the false alarm rate of 0 in the scenario where all the candidate targets are false alarms at the same time.The method based on the target relative motion inference performs well in complex scenes,and can work stably,quickly and with high filtering rate in different scenes.