Research On Key Technology Of Radar Maneuvering Target Tracking

With the rapid development of modern shipping industry,the situation of shipping transport is becoming increasingly severe,and the maneuverability of modern targets is becoming more and more complex and changeable.Therefore,higher requirements for tracking performance of aquatic moving targets are required,especially the stable and accurate tracking of the maneuvering target is more critical.Therefore,the research on the tracking of maneuvering target is carried out in this paper.Firstly,the basic principle of maneuvering target tracking is analyzed,and some common target motion models are described,then the classic Kalman filter is introduced,the "current" statistical(CS)model used in maneuvering target tracking is emphatically analyzed.Experimental simulation and analysis based on commonly used motion models,namely uniform speed(CV)model,uniformly accelerated(CA)model,Singer model filtering algorithm and maneuvering target tracking performance based on the "current statistical" model filtering algorithm,which provides a theoretical basis for the improved algorithm in the later paper.Secondly,in order to adapt to the change of high maneuvering target,based on the analysis of "current" statistical model filtering algorithm and its shortcoming is discussed,further more based on the "current" statistical model of fuzzy adaptive filtering algorithm(CSFA)is discussed.On this basis,the application of strong tracking filter in tracking maneuvering target is analyzed,and the improved fuzzy reasoning system is combined with it,the improvement based on the "current" statistical model of fuzzy adaptive filtering algorithm(ICSFA)is put forward.The simulation results show that,comparing with the traditional CS algorithm and CSFA algorithm,the ICSFA improves the tracking performance of maneuvering target and non-maneuvering target.Finally,due to the complexity of target movement,a single model is difficult to meet all of the maneuvering target tracking accuracy,therefore,the traditional interactive multiple model algorithm(IMM)and its shortcomings is discussed,and then the filter algorithm that combines the fuzzy reasoning and CS model(CSFA)is analyzed.On this basis,an improved algorithm based on fuzzy adaptive multiple model(IFA-IMM)is proposed,which adopts two grade fuzzy reasoning,a fuzzy mapping by maneuver value characterizing target mobility,the mobile value as the input of two level fuzzy mapping,finally the model probability updating is gotten.At the same time,the Kalman filter for each sub filter is improved,which adjusts the noise variance of the filter in real time,and finally through the simulation experiment proves that the algorithm of this paper verifies the effectiveness and superiority of the algorithm proposed in this paper.