Kalman Filter Tracking Algorithm Simulation Based on Angle Expansion. In the position tracking of a uniform linear moving target affected by noise, when the extended Kalman filter adopts distance as the correction amount, and the performance is greatly affected by the noise.
By introducing the current position angle observations that are away from the sensor into the observation matrix Z. and introducing the horizontal and vertical ...
In this paper, a cubature kalman filter algorithm based on variational Bayesian learning is proposed. The t-logical-scale distribution is used to model the ...
Abstract. Robust and effective real-time visual tracking is realized by combining the first order differential invariants with the stochastic filtering.
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The proposal is for an Adaptive Strong Tracking Extended Kalman Filter (EKF) algorithm that aims to address the issues of classic EKF's low accuracy and lengthy ...
The results show that the proposed algorithm can improve the accuracy of roll angle estimation even with gross measurement errors. As a result of the ...
This work addresses the target tracking problem that makes use of combined measurements, namely received signal strength (RSS) and angle of arrival (AoA).
A star spot location estimation approach with the Kalman filter for a star tracker has been proposed, which consists of three steps.
Apr 12, 2024 · This study introduces a Kalman Filter tailored for homogeneous gas Time Projection Chambers (TPCs), adapted from the algorithm utilized by the ...
Kalman filters based on multibody models: linking simulation and real ...
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Mar 20, 2023 · The Kalman filter algorithm estimates variables of linear systems combining information from real sensors and a mathematical model of the system.