Open AccessEfficient multi‐sensor path scheduling for cooperative target tracking
Author(s) -
Meng Lingtong,
Yi Wei,
Zhou Tao
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0229
Subject(s) - computer science , scheduling (production processes) , mathematical optimization , grid , gradient descent , fisher information , tracking (education) , path (computing) , limit (mathematics) , function (biology) , matrix (chemical analysis) , control theory (sociology) , algorithm , mathematics , artificial intelligence , artificial neural network , machine learning , psychology , pedagogy , mathematical analysis , geometry , control (management) , evolutionary biology , biology , programming language , materials science , composite material
This study deals with path scheduling problem of cooperative target tracking by multiple sensors with bearings only measurements. First, the authors derive a closed‐form expression of the determinant (D‐optimality criterion) of the Fisher information matrix (FIM) as the cost function, which contains the knowledge of the target and the locations of sensors. Second, a penalty function is introduced to modify the cost function for threats avoidance and physics constraints are applied to limit directions of sensors. Then, an efficient strategy based on steepest descent is proposed to solve the optimisation problem. Finally, the effectiveness of the proposed algorithm is demonstrated both in localisation of a stationary target and tracking a moving target. Simulation results show the trajectories of sensors for cooperative target tracking are almost identical to a grid‐based search method; however, the computational complexity is reduced by several orders of magnitude.