Solving First Order Fuzzy Initial Value Problem by Fourth Order Runge-Kutta Method Based on Different Means

Abadi, Ashraf H.; Cao, Bing

doi:10.1007/978-3-319-66514-6_36

Cited by 1 publication

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To avoid the decreasing precision of compensation tracking, the estimation of registration errors will be introduced to a LFOF when ( 53 ) is true, that is

where u is the error items, y is the output of the filter,

is the propotionality coefficient. The fourth-order Runge-Kutta algorithm [ 32 , 33 ] can be used to solve the above differential equation.…”

Section: Target Tracking With Error Compensationmentioning

confidence: 99%

Improved Spatial Registration and Target Tracking Method for Sensors on Multiple Missiles

Lü

Xie

Zhou

2018

Sensors

View full text Add to dashboard Cite

Inspired by the problem that the current spatial registration methods are unsuitable for three-dimensional (3-D) sensor on high-dynamic platform, this paper focuses on the estimation for the registration errors of cooperative missiles and motion states of maneuvering target. There are two types of errors being discussed: sensor measurement biases and attitude biases. Firstly, an improved Kalman Filter on Earth-Centered Earth-Fixed (ECEF-KF) coordinate algorithm is proposed to estimate the deviations mentioned above, from which the outcomes are furtherly compensated to the error terms. Secondly, the Pseudo Linear Kalman Filter (PLKF) and the nonlinear scheme the Unscented Kalman Filter (UKF) with modified inputs are employed for target tracking. The convergence of filtering results are monitored by a position-judgement logic, and a low-pass first order filter is selectively introduced before compensation to inhibit the jitter of estimations. In the simulation, the ECEF-KF enhancement is proven to improve the accuracy and robustness of the space alignment, while the conditional-compensation-based PLKF method is demonstrated to be the optimal performance in target tracking.

show abstract

“…To avoid the decreasing precision of compensation tracking, the estimation of registration errors will be introduced to a LFOF when ( 53 ) is true, that is

where u is the error items, y is the output of the filter,

is the propotionality coefficient. The fourth-order Runge-Kutta algorithm [ 32 , 33 ] can be used to solve the above differential equation.…”

Section: Target Tracking With Error Compensationmentioning

confidence: 99%

Improved Spatial Registration and Target Tracking Method for Sensors on Multiple Missiles

Lü

Xie

Zhou

2018

Sensors

View full text Add to dashboard Cite

show abstract

Solving First Order Fuzzy Initial Value Problem by Fourth Order Runge-Kutta Method Based on Different Means

Cited by 1 publication

References 10 publications

Improved Spatial Registration and Target Tracking Method for Sensors on Multiple Missiles

Improved Spatial Registration and Target Tracking Method for Sensors on Multiple Missiles

Contact Info

Product

Resources

About