Risk decision based sensor scheduling in target tracking

• Published in: Engineering computations 2020-10, Vol.37 (9), p.3147-3169
• Main Authors: Pang, Ce, Shan, Ganlin
• Format: Article
• Language: English
• Subjects: Algorithms; Chaos theory; Decision theory; Game theory; Information theory; Interception; Optimization; Optimization algorithms; Project management; Risk; Scheduling; Sensors; Tracking; Two dimensional models
• ISSN: 0264-4401; 1758-7077
• DOI: 10.1108/EC-01-2020-0056

Purpose This paper aims to introduce a new target tracking method based on risk theory in a 2-D discrete environment. After that, the related sensor scheduling method is proposed. This can make up the blank of target tracking and sensor management in the 2-D discrete environment. Design/methodology/approach The definition of risk is proposed based on risk decision theory firstly. Then the target tracking model in a two-dimensional discrete environment is built. The motion state updating and estimation method of target’s motion state based on Bayes theory is given. Thirdly, the method of computing sensor emission interception risk is provided. Afterwards, the optimization rule of obtaining the minimum risk is followed to model the sensor scheduling objective function. The lion algorithm is adjusted and improved combined with Chaos theory to generate the optimal sensor management projects. Findings The risk-based sensor target tracking method and sensor management method are both effective in a 2-D discrete environment. Originality/value To the best of the authors’ knowledge, this paper is the first to study the target tracking method and sensor scheduling method in a 2-D environment. Furthermore, the lion algorithm is improved combined with Chaos theory to show a better optimization performance.