With the high-technique developing quickly, the traditional multi-target tracking algorithm is facing new challenges and requirements in the application of infrared warning equipment. In recent years, the approaches to MTT based on random finite set (RFS) have been achieved substantial results.This paper discusses MTT problem of sector scanning infrared warning equipment image based on multiple model label multi-Bernoulli support vector machine(MM-LMB-SVM). Firstly, the problems existing in the application of traditional algorithms to sector scanning infrared warning equipment are discussed. The advantages of MM-LMB-SVM filtering algorithm are proposed. At the same time, the problems faced by the application of MM-LMB-SVM filtering to sector scanning infrared warning equipment are analyzed and the solution are provided. The simulation results shows that under the typical complex background, the track anti-jamming success rate of weak and small targets is improved by more than 20%, and the tracking success rate of weak and small targets with only 50% detection rate is improved by more than 45%. It significantly improves the weak and small multi-target tracking ability.