Data Fusion Theory And Method Of The Maneuvering Target Tracking

It might be said that tracking target is one of the basic problems.In the natural world, no matter for survival or for living better. In thepast twenty years or more, with the progress of sciences and technologies, as well as the development of modern military strategy and tactics, the theory and method of maneuvering target Tracking have been greatly developed and become one of the hot areas of research.First,this paper particularly discuss PDA ,IMM algorithm, adaptive algorithm of mean value and variance based on current statistical model, and Kalman filter algorithm based on Neural network. Radar or multi-sensor is non-synchronization when they are tracking maneuvering target ,for example ,their boot-strap time is different ,or they may have different impulse repeating period and scan period, and we also call they have different sampling rate, or because they have observation time difference .observation datas from different radar or sensor can not be got at the same time. So observation datas must be synchronized before fusion. Aiming at non-synchronization of sensors,I adopt sequential filter .namely,We can say it constant kalman filter method that one radar is working .The track which arrives firstly should be filtered according time order whichever radar is measuring. This method can save time- synchronization and strengthen the continuity of the track. The effectiveness of the proposed method is verified by a series of simulations.