Local Estimators for Multiple Spacecraft Formation Flying

In this work, we propose an approach to formation estimation that is based on local estimators for multiple spacecraft systems. In this avenue, we proceed to relax some of the assumptions in the existing research literature pertaining to feasible estimation architectures for formation flying. Specifically, we show that formation estimation objectives can be achieved by a local information-exchange network among the spacecraft, adding a level of modularity and scalability to the general problem of estimation over networks. Our approach relies on breaking up the overall network into a sequence of local subnetworks, and subsequently, invoking an agreement-type algorithm that facilitates reaching consensus on the various local estimates obtained by each local subnetwork in an optimal manner. Moreover, we show how some of the properties of the local observers remain intact as we include measurement noise in each subnetwork. The paper concludes with a comparison between the performance of the proposed distributed formation estimator for multiple spacecraft systems and the corresponding centralized estimator via a few examples. Formation flying has been identified as an enabling technology for many of the future NASA, Navy, and Air force missions. Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. As the control architecture is critically dependent on the underlying information exchange network among the spacecraft, it has become of paramount importance to consider guidance, navigation, and control strategies that have judicious requirements in terms of the necessary inter-spacecraft information exchange infrastructure. In this work, we propose local state estimators for the formation flying of multiple spacecraft. In this venue, we proceed to relax some of the assumptions in the existing research literature pertaining to estimation architectures for formation flying. For example, we show that only local observability for a formation is required to design a formation estimator- and subsequently- a formation control law. Our approach relies on breaking up the overall information-exchange network into a sequence of local subnetworks, and subsequently invoking an agreement-type filter that facilitates reaching consensus on the various local estimates obtained by each local network. Moreover, we show how some of the properties of the local observers remain intact as we include measurement noise in each subnetwork. The main contribution of this paper is introducing a new algorithm for designing networked and distributed estimation algorithms. By distributed estimation we refer to the scenario where state estimates are obtained by a set of local measurements that are subsequently passed through a set of communicating local Kalman filters to reach an overall state estimation for the formation. The objective of the estimation algorithm can be either monitoring the entire formation state or a subset of this state- nevertheless, the estimation algorithm can benefit from the information-exchange among the multiple estimators.