A Robust Multi-State Constraint Optimization-Based Orientation Estimation System for Satcom-on-the-Move

Abstract

Current orientation estimation system (OES) approaches can meet the Satcom-on-the-move (SOTM) accuracy requirement in low dynamics using inertial measurement unit (IMU) without Global Navigation Satellite System (GNSS). However, the estimation accuracy will decrease significantly due to the influence of the high dynamics of the vehicle. This article addresses this issue by constructing a multi-state constraint optimization-based OES (MSCO-OES). Our first contribution is a high-precision incremental inertial constraint, which adds the influence of the earth's rotation to the rotation part of the pre-integration theory to maintain the integral gyro accuracy for a longer time. The second contribution is that the nonlinear optimization method is applied to orientation estimation, making better use of historical information and having higher estimation accuracy and robustness through batch optimization and iterating. In addition, we use the lie group theory to extend the weighted least square estimation algorithm to the manifold, which can update multiple historical states to the current state in real-time through incremental inertial constraints. Compared with state-of-the-art methods, the proposed orientation estimation method has higher estimation precision and a reasonable calculation amount. The performance of the proposed method is demonstrated by comparing tests and SOTM deploying tests. Several high-dynamic and long-range tests show that the proposed OES has acceptable orientation estimation precision and reliability, which meets the high-reliable SOTM system requirements.