Faced with complex background on aerial moving platform, infrared point target detection apply background suppression policy to greatly improve detection efficiency. However, due to the background relative motion, it presents challenges for target detection. From remote observation in the air, background movement could be approximately regarded as plane rigid motion, which is the sum of translation and rotation movement. Until now, existing algorithms by comparing the adjacent frames of infrared image have good performance in the detection of translation motion, but poor effect in the situation of the rotational motion. It is proposed a rigid motion estimation algorithm based on infrared background feature point set (IRMBE) .Firstly, by processing statistical movement characteristics of the feature point set on infrared background image, the algorithm gauges out the translation motion vector. Secondly, it uses Monte Carlo method in background feature point set to estimate the vector of rotation axis and the angular velocity. Experiments show that the algorithms can perform good estimation of the complex background rigid movement, in the application of space-based Infrared observation.