Research On Passive TDOA Location System And Tracking Technology

In the modern information war environment, with the continuous development of electronic countermeasure and defense technology, the traditional active positioning tracking system in such aspects as concealment, anti-jamming and viability faced the threat of more and more serious, in addition to the active positioning system and improvement of passive location tracking system due to its simple equipment, good concealment, distance, the advantages of strong survival ability is more and more attention from domestic and international military powers. This topic, taking the research of passive location technology and its tracking algorithm. From the location principle, the tracking filter algorithm and system models has carried on the detailed research and simulation analysis.In this paper, based on time difference method of passive location tracking technology is studied. First introduced the source positioning system, the paper introduces the method of time difference stand the basic principle of passive location and its localization algorithm, and the positioning accuracy is analyzed, factors, which affect the positioning accuracy is verified by simulation experiments. Then aiming at the problem of passive locating and tracking, introduces the nonlinear filtering algorithm of extended kalman filter algorithm and no trace of kalman filtering algorithm, list and the concrete implementation steps of the two kind of filter, and through the simulation experiment compares the two kinds of tracking error performance of the algorithm. Target mobility problem, this paper introduces the basic principle of several motion model and the implementation steps, through the simulation experiment compares the various models in the process of tracking target motion tracking error. Finally, this paper introduces the interactive multiple model algorithm based on UKF, parallel computing, it through multiple filter for target tracking under different motion model, can effectively track the maneuvering target, and through the simulation experiment compares the two kinds of interactive model for target tracking error and using the probability of each model, get a better model for target tracking algorithm.