Abstract:

A dynamic multi-sensor management algorithm based on task control is proposed to overcome the multi-sensor management difficulties during tracking multi-targets on the platform of an information fusion system. According to the diversities of error covariance of filtered targets and expectations under different battlefield situations, the accuracy demands of the current target are measured. Using fuzzy-matter element analysis, Euclid approach degree is calculated to achieve the degree of the target’s threat depending on the target values of their own property and the current state. Considering the sensor functions and resource consumption, a task demand model is found. The model can control a number of sensors to measure and update the target, thus the optimal solution for the model is found. The simulation results show that the algorithm can both appropriately control resource consumption and reduce the total energy consumption of the system while tracking to multi-targets with accuracy and timeliness.