Optimal Sensor Planning for SSA Using System Identification Concepts

The rapid growth of man-made objects in Earth’s orbit has created a need for planning and prioritizing sensor measurements of these objects in order to keep track of their motion in orbit. In this paper, we adapt a concept from the field of system identification, namely application-oriented input design, to the sensor-planning problem. Previous methods have predominantly focused on the problem of planning the measurements of different objects such that they are as accurate as possible (in a broad sense) from a given set of possible observations. Here we view the problem differently; the objective is to find the least costly number of measurement such that the estimated orbital parameters are good enough for their intended application. To this end, we introduce the concept of an application set. The application set contains all orbital parameters that are considered of sufficient accuracy for the intended use. The objective of the optimization is hence not to find the most accurate set of parameters but find the cheapest combinations of observations such that the estimated parameters are guaranteed to be within the application set with a high probability. We show how to formulate the planning problem as a convex optimization problem that can be solved efficiently with modern algorithms, even for large-scale problems. We then demonstrate the feasibility of the method in a simulation example. Finally, the paper discusses some interesting topics for future research.