Research on Large-scale Magnetic Target Tracking Method
To address the mismatch problem of observation model caused by non-ignorable target scale in magnetic positioning,a real-time magnetic positioning algorithm of filter estimation adaptive to target scale only based on the measurement data by two three-axis magnetic sensors is proposed.Based on maximum likelihood selection idea,the uniform line array model composed of different numbers of magnetic dipoles are established as the candidate observation model,then a stochastic Gaussian filter-ing algorithm suitable for the estimation of high dimensional nonlinear dynamic parameters is deduced.The performance degradation problem caused by high dimension of large-scale target model and strong non-linearity is overcome,the real-time positioning accuracy is improved.Meanwhile,the algorithm is utilized to filter and solve each dipole linear array model respectively.The filtering results correspond-ing to the maximum likelihood value are selected as the current time estimate,the self-adaptation of target scale is realized.Finally,the validity of the algorithm is verified by finite element magnetic field simulation data of double shell submarine,the results show that the proposed algorithm is more accu-rate and can meet the accurate and real-time requirement for target positioning with better convergence performance compared with the current method.
magnetic positioningtarget scalemagnetic fieldnonlinear filteringadaptation
国家科技期刊平台
NSTL
万方数据
