Improved line of sight robot tracking toward a moving target

• Main Authors: Shulin Feng, Guilin Zhang, Yihua Dong, Xianwen Zhang, Peiliang Wang
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2018-09-01
• Series: Systems Science & Control Engineering
• Subjects: LOS guidance law; tracking; information fusion; n-step ahead Kalman predictor
• Online Access: http://dx.doi.org/10.1080/21642583.2018.1547886

In this paper, the line of sight (LOS) guidance law is improved to implement tracking toward a moving target. In the presence of sensor noise, an optimal information fusion Kalman filter weighted by scalars is utilized for two-sensor information fusing, improving the trajectory tracking precision. Under the communication delay, n-step ahead Kalman predictor compensates for communication delay and provides LOS guidance law with more accurate target estimates. The results of the simulation demonstrate the feasibility and effectiveness of the proposed control strategy.