Modeling of three-dimensional radar tracking system and its estimation using Extended Kalman Filter

2017 ◽  
Author(s):  
Didik Khusnul Arif ◽  
Dieky Adzkiya ◽  
Prima Aditya ◽  
Feri Winata ◽  
Diah Agustin ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Tracking System ◽  
Three Dimensional ◽  
Radar Tracking

scholarly journals Estimation of three-dimensional radar tracking using modified extended kalman filter

2018 ◽  
Vol 974 ◽  
pp. 012071 ◽  
Author(s):  
Prima Aditya ◽  
Erna Apriliani ◽  
Didik Khusnul Arif ◽  
Komar Baihaqi
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Three Dimensional ◽  
Radar Tracking

scholarly journals Integrated Estimation/Guidance Law against Exoatmospheric Maneuvering Targets

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Mao Su ◽  
Lei Liu ◽  
Yongji Wang
Keyword(s):  
Monte Carlo ◽  
Kalman Filter ◽  
Differential Game ◽  
Extended Kalman Filter ◽  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Guidance Law ◽  
Maneuvering Targets ◽  
Integrated Estimation ◽  
Guidance Problem

An integrated guidance integrated estimation/guidance law is designed for exoatmospheric interceptors equipped with divert thrusters and optical seekers to intercept maneuvering targets. This paper considers an angles-only guidance problem for exoatmospheric maneuvering targets. A bounded differential game-based guidance law is derived against maneuvering targets using zero-effort-miss (ZEM). Estimators based the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) are designed to estimate LOS rates that are contaminated by noise and target maneuver. Furthermore, to improve the observability of the range, an observability enhancement differential game guidance law is derived. The guidance law and the estimator are integrated together in the guidance loop. The proposed integrated estimation/guidance law has been tested in several three-dimensional nonlinear interception scenarios. Numerical simulations on a set of Monte-Carlo simulations prove the validity and superiority of the proposed guidance law in hit-to-kill interception.

Parameter Estimation of Nonlinear Biomedical Systems Using Extended Kalman Filter Algorithm

2017 ◽  
pp. 76-99 ◽  
Author(s):  
Kamalanand Krishnamurthy
Keyword(s):  
Parameter Estimation ◽  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Computational Models ◽  
Three Dimensional ◽  
Model Parameters ◽  
State Variables ◽  
Three Dimensional Model ◽  
Biomedical Systems ◽  
Estimation Of Model Parameters

Parameter estimation is a central issue in mathematical modelling of biomedical systems and for the development of patient specific models. The technique of estimating parameters helps in obtaining diagnostic information from computational models of biological systems. However, in most of the biomedical systems, the estimation of model parameters is a challenging task due to the nonlinearity of mathematical models. In this chapter, the method of estimation of nonlinear model parameters from measurements of state variables, using the extended Kalman filter, is extensively explained using an example of the three-dimensional model of the HIV/AIDS system.

scholarly journals Camera-Based Tracking of Floating Objects using Fixed-wing UAVs

2021 ◽  
Vol 102 (4) ◽  
Author(s):  
Håkon Hagen Helgesen ◽  
Torleiv H. Bryne ◽  
Erik F. Wilthil ◽  
Tor Arne Johansen
Keyword(s):  
Kalman Filter ◽  
Target Tracking ◽  
Covariance Matrix ◽  
Extended Kalman Filter ◽  
Tracking System ◽  
Thermal Camera ◽  
Thermal Images ◽  
Aerial Vehicle ◽  
Floating Objects

AbstractThis article concerns tracking of floating objects using fixed-wing UAVs with a monocular thermal camera. Target tracking from an agile aerial vehicle is challenging because uncertainty in the UAV pose negatively affects the accuracy of the measurements obtained through thermal images. Consequently, the accuracy of the tracking estimates is degraded if navigation uncertainty is neglected. This is especially relevant for the estimated target covariance since inconsistency is a likely consequence. A tracking system based on the Schmidt-Kalman filter is proposed to mitigate navigation uncertainty. Images gathered with an uncertain UAV pose are weighted less than images captured with a reliable pose. The UAV pose is estimated independently in a multiplicative extended Kalman filter where the estimated covariance matrix is a measure of the uncertainty. The method is compared experimentally with two traditional alternatives based on the extended Kalman filter. The results show that the proposed method performs better with respect to consistency and accuracy.

Parameter Estimation of Nonlinear Biomedical Systems Using Extended Kalman Filter Algorithm

2018 ◽  
pp. 690-713
Author(s):  
Kamalanand Krishnamurthy
Keyword(s):  
Parameter Estimation ◽  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Computational Models ◽  
Three Dimensional ◽  
Model Parameters ◽  
State Variables ◽  
Three Dimensional Model ◽  
Biomedical Systems ◽  
Estimation Of Model Parameters

Parameter estimation is a central issue in mathematical modelling of biomedical systems and for the development of patient specific models. The technique of estimating parameters helps in obtaining diagnostic information from computational models of biological systems. However, in most of the biomedical systems, the estimation of model parameters is a challenging task due to the nonlinearity of mathematical models. In this chapter, the method of estimation of nonlinear model parameters from measurements of state variables, using the extended Kalman filter, is extensively explained using an example of the three-dimensional model of the HIV/AIDS system.

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