GNSS / INS coupling positioning method and system based on factor graph optimization
The GNSS/INS coupled positioning method optimized by factor graphs utilizes joint optimization within a sliding window and a robust kernel function to design a time-varying covariance model. This solves the problems of linearization error accumulation and filter divergence in complex environments that traditional methods face, achieving high-precision and robust positioning results.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NAT INNOVATION INST OF DEFENSE TECH PLA ACAD OF MILITARY SCI
- Filing Date
- 2026-03-12
- Publication Date
- 2026-06-19
AI Technical Summary
Existing GNSS/INS compact combination methods based on extended Kalman filtering are prone to linearization error accumulation and filter divergence in complex environments, resulting in unreliable positioning results. In particular, they suffer from slow convergence speed, low positioning accuracy, and poor robustness in environments such as urban canyons.
A GNSS/INS coupled positioning method based on factor graph optimization is adopted. Nonlinear errors are eliminated by joint optimization within a sliding window and multiple iterations of linearization. A robust kernel function is introduced to suppress abnormal observations. A time-varying covariance model based on signal quality is designed, and nonlinear least squares optimization is performed by combining IMU pre-integration factor and robust GNSS observation factor.
It significantly improves the convergence speed of positioning and robustness in complex environments, enhances positioning accuracy and trajectory smoothness, and can maintain high-precision positioning in scenarios with discontinuous signals, such as urban canyons.
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Abstract
Citation Information
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