Abstract The problem of motion modelling in the range‐Doppler (R‐D) plane as well as range and Doppler estimation for the Cartesian nearly constant acceleration motion, which is a common manoeuvering motion, is investigated. The temporal evolution equation is derived based on the state vector consisting of target range, Doppler and derivatives of the product of range and range rate versus time. In this way, the measurement equation of range and Doppler measurements can be maintained in a desirable linear‐Gaussian structure. Based on the non‐linear state equation and the linear measurement equation, the unscented Kalman filter is adopted to tackle the non‐linear filtering problem. The corresponding filter initialisation method is developed b...
Establishing a symmetrical model of surrounding vehicles and accurately obtaining the driving state ...
Abstract The problem of state estimation for non‐linear systems with unknown inputs is discussed. Th...
The Kalman filter is the general solution to the recursive, minimised mean square estimation problem...
Constant acceleration movement in one, two and three dimensions can be modeled using time invariant ...
An algorithm to estimate the tangential and normal accelerations directly using the Doppler radar me...
A dual implementation of the Kalman filter is proposed for estimating the unknown input and states o...
Localization and tracking of the ground moving target (GMT) are investigated based on measurements o...
The problem is recursive Bayesian estimation of position and velocity of a moving object using async...
Attitude estimation is often inaccurate during highly dynamic motion due to the external acceleratio...
Abstract: An adaptive unscented Kalman filter (AUKF) and an augmented state method are employed to e...
Bearings-only tracking using the modified gain extended Kalman filter (MGEKF) configured in Cartesia...
Bearings-only tracking using the modified gain extended Kalman filter (MGEKF) configured in Cartesia...
A new mathematical model describing the motion of manned maneuvering targets is presented. This mode...
This thesis presents an investigation of the possibility of using the fixed-point arithmetic in the ...
In this paper a novel approach for detecting unknown target maneuver using range rate information is...
Establishing a symmetrical model of surrounding vehicles and accurately obtaining the driving state ...
Abstract The problem of state estimation for non‐linear systems with unknown inputs is discussed. Th...
The Kalman filter is the general solution to the recursive, minimised mean square estimation problem...
Constant acceleration movement in one, two and three dimensions can be modeled using time invariant ...
An algorithm to estimate the tangential and normal accelerations directly using the Doppler radar me...
A dual implementation of the Kalman filter is proposed for estimating the unknown input and states o...
Localization and tracking of the ground moving target (GMT) are investigated based on measurements o...
The problem is recursive Bayesian estimation of position and velocity of a moving object using async...
Attitude estimation is often inaccurate during highly dynamic motion due to the external acceleratio...
Abstract: An adaptive unscented Kalman filter (AUKF) and an augmented state method are employed to e...
Bearings-only tracking using the modified gain extended Kalman filter (MGEKF) configured in Cartesia...
Bearings-only tracking using the modified gain extended Kalman filter (MGEKF) configured in Cartesia...
A new mathematical model describing the motion of manned maneuvering targets is presented. This mode...
This thesis presents an investigation of the possibility of using the fixed-point arithmetic in the ...
In this paper a novel approach for detecting unknown target maneuver using range rate information is...
Establishing a symmetrical model of surrounding vehicles and accurately obtaining the driving state ...
Abstract The problem of state estimation for non‐linear systems with unknown inputs is discussed. Th...
The Kalman filter is the general solution to the recursive, minimised mean square estimation problem...