In order to improve tracking accuracy when initial estimate is inaccurate or outliers exist,a bearings-only tracking approach called the robust range-parameterized cubature Kalman filter(RRPCKF)was proposed.Firstly,th...In order to improve tracking accuracy when initial estimate is inaccurate or outliers exist,a bearings-only tracking approach called the robust range-parameterized cubature Kalman filter(RRPCKF)was proposed.Firstly,the robust extremal rule based on the pollution distribution was introduced to the cubature Kalman filter(CKF)framework.The improved Turkey weight function was subsequently constructed to identify the outliers whose weights were reduced by establishing equivalent innovation covariance matrix in the CKF.Furthermore,the improved range-parameterize(RP)strategy which divides the filter into some weighted robust CKFs each with a different initial estimate was utilized to solve the fuzzy initial estimation problem efficiently.Simulations show that the result of the RRPCKF is more accurate and more robust whether outliers exist or not,whereas that of the conventional algorithms becomes distorted seriously when outliers appear.展开更多
The paper is going to introduce some methods about select distributional model、select an estimation technique、iterate to minimize objective function、record estimated parameters、select one or more models which had ...The paper is going to introduce some methods about select distributional model、select an estimation technique、iterate to minimize objective function、record estimated parameters、select one or more models which had low value of the objective function and test of fit of selected model by empirical distribution function、mean of residual life function、minimum distance and minimum chi square.This should prove especially useful to those readers who want to set up a computer system to perform the model fitting operation.展开更多
基金Projects(51377172,51577191) supported by the National Natural Science Foundation of China
文摘In order to improve tracking accuracy when initial estimate is inaccurate or outliers exist,a bearings-only tracking approach called the robust range-parameterized cubature Kalman filter(RRPCKF)was proposed.Firstly,the robust extremal rule based on the pollution distribution was introduced to the cubature Kalman filter(CKF)framework.The improved Turkey weight function was subsequently constructed to identify the outliers whose weights were reduced by establishing equivalent innovation covariance matrix in the CKF.Furthermore,the improved range-parameterize(RP)strategy which divides the filter into some weighted robust CKFs each with a different initial estimate was utilized to solve the fuzzy initial estimation problem efficiently.Simulations show that the result of the RRPCKF is more accurate and more robust whether outliers exist or not,whereas that of the conventional algorithms becomes distorted seriously when outliers appear.
文摘The paper is going to introduce some methods about select distributional model、select an estimation technique、iterate to minimize objective function、record estimated parameters、select one or more models which had low value of the objective function and test of fit of selected model by empirical distribution function、mean of residual life function、minimum distance and minimum chi square.This should prove especially useful to those readers who want to set up a computer system to perform the model fitting operation.
