State filtering and nonlinear control of fine tracking system in quantum positioning systems

摘要

The accuracy of the fine tracking system is the premise of high-accuracy positioning in quantum positioning systems. In this paper, we propose a method combining model reference adaptive control (MRAC) strategy and adaptive strong tracking Kalman filter (ASTKF) to reduce the impacts of satellite platform jitter and environment noise. A mathematical model of the fine tracking system with disturbance and environmental noise are set up and analyzed. Aiming at colored irregular noise signal, we design an ASTKF to estimate the state of the system on-line, at the same time, the disturbance and noise changing with time are also estimated and eliminated. By combining a MRAC strategy, we enhance the robustness of the fine tracking system. Numerical experiments of tracking performances comparing different methods available in the literature are given. The numerical simulation results show that the proposed method can improve the tracking accuracy, and almost 99.7% of the spots can be projected into the square area within 2 μrad.