Preliminary Design of GNC System and Multi-mode Propulsion Cooperative Control for Micro-Nano Satellite Autonomous Rendezvous and Docking

Paper · 2026

Publication6th China Conference on Space Security (CASS) · Under Review

AuthorsXinyun Chen, Jiaqing Chen, Weiyi Hou, Tianshu Wang, Zibing Qin, Yonghe Zhang, Chengyu Ma

  1. For nonlinear rendezvous and propellant–performance trade-offs in micro-nano satellites, an MEE dynamics model and CKF-based LiDAR–vision fusion navigation were built, with PMP optimal guidance covering 100 m to 0.02 m. The design achieved 62.88% fuel savings while holding terminal estimation error within 5 mm, greatly improving mission duration and accuracy.
  2. For multimodal water propulsion switching stability, a distributed 6-DoF cooperative control scheme enabled high–low thrust transitions within ≤1 s. Robustness analysis with ±30% parameter perturbation verified final docking accuracy better than 0.0148 m under extreme conditions, providing a highly reliable GNC benchmark for SpaceCrafter on-orbit servicing.

Abstract

This paper presents a simulation-based preliminary design of a GNC system for autonomous rendezvous and docking of sub-100 kg micro-nano satellites. A long-range low-thrust rendezvous dynamic model with J2 perturbation is built using modified equinoctial elements (MEE). A phased relative navigation scheme based on cubature Kalman filter (CKF) uses lidar for long-range estimation and an improved SPNv2 visual solver for short-range docking, solving the out-of-view keypoint problem. A 6-DOF cooperative control scheme based on distributed multi-mode water-based propulsion achieves seamless switching between high-thrust and low-thrust modes (≤1s). All simulation parameters are derived from physical sensor characteristics to ensure engineering relevance. Full-process simulation shows the system completes 180° phase difference rendezvous and docking from 100m to 0.02m with final position error ≤0.02m. The fuel-optimal scheme reduces fuel consumption by 62.88% compared to the time-optimal scheme. Physical validation tests are scheduled for future work.