Route-Based Dynamics Modeling and Tracking with Application to Air Traffic Surveillance

Linfeng Xu, Yan Liang, Zhansheng Duan, Gongjian Zhou

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

In transportation networks, the majority of moving vehicles are route-based or trajectory-scheduled. Taking advantage of such predictive information generally produces more accurate dynamic models and better surveillance performance. This paper is concerned with the route-based dynamic modeling along with the route-aided tracking. First, the evolution of the positions across the route is formulated as a stationary Markov process from the characteristics of the route-based dynamics, which follows that the second- and third-order models of the straight-line route-based motions are constructed. This novel modeling strategy is in reverse to the conventional ones starting from the acceleration and its resultant dynamic models are easy to implement due to the linearity with respect to the system states. Second, an optimal initialization technique for route-aided tracking is proposed by utilizing the stationary process information sufficiently. Furthermore, an extension to the circular route-based dynamic modeling and a combinational modeling structure are also presented. Finally, in the context of aerial surveillance, numerical simulations are provided to show the effectiveness of the proposed dynamic modeling and to verify the theoretical results given in the paper.

Original languageEnglish
Article number8614428
Pages (from-to)209-221
Number of pages13
JournalIEEE Transactions on Intelligent Transportation Systems
Volume21
Issue number1
DOIs
StatePublished - Jan 2020

Keywords

  • dynamics modeling
  • optimal filtering initialization
  • Stationary Markov process

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