Optimal design experiments for navigation

This paper considers the following optimization problems: (1) a measurable parameter structure and the choice of navigational means, (2) spacecraft control with the purposes of observability-condition improvement, and (3) joint operation of spacecraft navigation and control means. These problems are traditionally regarded as Riccati-equation control problems, being an essential element of optimal filtration and control-algorithm synthesis. A new general solution approach makes it possible to transform the initial nonlinear control problems to equivalent linear-in-phase variables at the expense of the Riccati-equation analytic properties. The results obtained can be considered as generalization of the classic theory of regression-experiment design to Kalman filtration in controllable dynamic systems.