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 importance of equations of state (EOS) has brought about the proliferation of hundreds of EOS. Nearly all prevailing cubic EOS could be regarded as the results of reforming the original vdW EOS. However, the accur...The importance of equations of state (EOS) has brought about the proliferation of hundreds of EOS. Nearly all prevailing cubic EOS could be regarded as the results of reforming the original vdW EOS. However, the accuracy of the vdW EOS is so low. In view of this, a new general equation is proposed that could be used to value or compare vdW type of EOS, and consequently develop a better vdW type of EOS.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 importance of equations of state (EOS) has brought about the proliferation of hundreds of EOS. Nearly all prevailing cubic EOS could be regarded as the results of reforming the original vdW EOS. However, the accuracy of the vdW EOS is so low. In view of this, a new general equation is proposed that could be used to value or compare vdW type of EOS, and consequently develop a better vdW type of EOS.
