Optimal Geometry and Motion Coordination for Multisensor Target Tracking with Bearings-Only Measurements

• Published in: Sensors (Basel, Switzerland) Switzerland), 2023-07, Vol.23 (14), p.6408
• Main Authors: Wang, Shen, Li, Yinya, Qi, Guoqing, Sheng, Andong
• Format: Article
• Language: English
• Subjects: Accuracy; Algorithms; bearings-only measurement; Fisher information matrix; Geometry; Localization; motion coordination; optimal geometry; Optimization; Parameter estimation; Sensors
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23146408

This paper focuses on the optimal geometry and motion coordination problem of mobile bearings-only sensors for improving target tracking performance. A general optimal sensor-target geometry is derived with uniform sensor-target distance using D-optimality for arbitrary (n≥2) bearings-only sensors. The optimal geometry is characterized by the partition cases dividing into the sum of integers no less than two. Then, a motion coordination method is developed to steer the sensors to reach the circular radius orbit (CRO) around the target with a minimum sensor-target distance and move with a circular formation. The sensors are first driven to approach the target directly when outside the CRO. When the sensor reaches the CRO, they are then allocated to different subsets according to the partition cases through matching the optimal geometry. The sensor motion is optimized under constraints to achieve the matched optimal geometry by minimizing the sum of the distance traveled by the sensors. Finally, two illustrative examples are used to demonstrate the effectiveness of the proposed approach.