Open AccessDecentralized multisensor estimation of motion parameters of an object moving along a complex trajectory
Author(s) -
A. V. Golubkov,
A. Tsyganov,
Julia V. Tsyganova,
I. O. Petrishchev
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1368/4/042041
Subject(s) - trajectory , kalman filter , state vector , motion (physics) , object (grammar) , computer science , computer vision , artificial intelligence , set (abstract data type) , motion estimation , mathematics , physics , classical mechanics , astronomy , programming language
The paper addresses the problem of multisensor estimation of the motion parameters of an object moving along a complex trajectory which consists of parts of the uniform linear and circular motion subject to noisy measurements. To solve the problem, we describe the object motion as a set of linear stochastic models responsible for different parts of the trajectory and use a decentralized multisensor algorithm for estimating the object state vector based on the information form of the Kalman filter. The results of numerical experiments confirm the applicability of the proposed approach.