GA-based optimal allocation of sensor resources

This work examines a straightforward solution to a problem of space surveillance resource allocation by exploring the application of an optimal algorithm to a subset of the general scheduling problem. Due to the resource constraints of the surveillance resource, there could be some serious conflicts among observation requirements. To solve the problem of conflicts in the work of sensor resources allocation, the Genetic Algorithm (GA) and the adapting priority weights method are used to optimize the allocation of sensor resources to maximize the satisfaction of the object observation requirements and the higher priority visibilities can be scheduled with higher success likelihoods.