Research On Tracking Of Maneuvering Targets Based On New Particle Filter Algorithms

The maneuvering target tracking is an extremely important research topic in national defense, the processing of radar signals and other related areas. In recent years, target tracking technology has been widely studied, and has made plentiful and substantial achievements. Some research results have been widely applied to military fields, such as air reconnaissance and early warning, ballistic missile defense, battlefield surveillance, etc. Some research results have been applied to civil fields, such as air traffic control, traffic navigation and robot vision system, etc. This paper researches nonlinear filtering algorithms of maneuvering target tracking more systemic.Firstly, basic principle of maneuvering target tracking is summarized and some familiar target maneuvering models, basic filtering and data association algorithms are also discussed. Following the discussion, this paper analyzes and compares several nonlinear filtering algorithms, the simulation results demonstrate the Cost Reference particle filter has an excellence filtering performances.Secondly, in order to solve nonlinear and non-Gaussian maneuvering target tracking problems, this paper integrates the advantages of the Cost Reference particle filter with the Current Statistical Model, and proposes a new current statistical model adaptive tracking algorithm, and the simulation results demonstrate its availability for maneuvering target tracking. This paper also discusses the multiple models adaptive tracking algorithm based on Cost Reference particle filter, and analyzes the blemish that the over randomicity of resample algorithm, as a result this paper puts forward a improved algorithm and the simulation validates the availability and applicability of the improved algorithm. The effects on algorithm performances by the amount of selected models in the multiple models tracking algorithm are investigated, and the tracking performances of the two tracking algorithms based on Cost Reference particle filter are compared through separate simulation in this paper.Finally, aiming at the data association problems of multiple targets, this paper expatiates some representative algorithms of multiple targets data association. Another new Rao-Blackwellised Particle Filter algorithm is discussed in details, and then is applied to solve the single maneuvering target tracking problem and the data association problem of multiple targets. The simulation results demonstrate the algorithm has highly real-time performance and the tracking accuracy rate. This paper also presents the future development of maneuvering target tracking.