Multi-sensor Management Method Based on Multi-step Prediction of Bidirectional Joint Risk

In a multi-sensor collaborative tracking system, rational multi-sensor management methods can achieve optimal system performance. However, the complexity and variability of environmental risks, will lead to the accuracy and safety of tracking system reduce. Therefore, this paper proposes a multi-sensor management method based on multi-step prediction of bidirectional joint risk to rationally allocate limited sensor resources. Firstly, the paper comprehensively considers three risks including the radiation risk of our multi-sensors, the risk of detection loss, and the threat risk of opposing targets, meanwhile constructs a bidirectional joint risk model. Secondly, adaptive weights for the three risks are proposed to adjust the three risks in the above model. Then, based on the framework of time series prediction, the bidirectional joint risk are predicted. Finally, based on this, the problem of minimizing multi-step prediction bidirectional joint risk is proposed, and then achieving the rational allocation of multi-sensor resources. The simulation results demonstrate that the propose method is feasible, as it can effectively allocate limited sensor resources in a multi-risk environment, improving the accuracy and security of the tracking system.