IMM Filtering Algorithm And Application

As the development of modern aviation and military, the modern air combat environment has become increasingly harsh.In order to take advantage in air combat, We not only require to minimize the area of radar reverberation and infrared reflectance characteristics, but also require the initiative sensor to reduce the time.So the passive sensor of infrared sensors play an more and more important role in airborne sensors. However, when we used infrared sensors alone, it can only provide angle information.we need to do target motion analysis (TMA).In order to estimate the target state, the target required moving with a certain criteria. But even so, the effect of objective state estimation is still not good.In order to improve the target state estimation results, we need to increase the initiative sensors or passive sensors to synergy target state estimation. Therefore, airborne multi-sensor information fusion has been put forward as an important airborne sensor technology.Gaining information from more than one sensor and using these informations to estimate the maneuvering target precisely now is a major method on the field of maneuvering target tracking. This paper describes the main technique of maneuvering target tracking, it conclude filter, data association . We will mainly focus on the Interacting Multi-Model Arithmetic (IMM) and Joint Probability of Data Association (JPDA). Finally, we will design programs base on the technique above, and use Monte Carlo method to evaluate the system. The paper introduces two methods of switching radar now,And add a switching strategy to improve the program based on the latter method. Finally focuses on The application of IMM Filter in financial analysis.