通过残差判断时机，提升惯导初始精度
GNSS-Inertial State Initialization Using Inter-Epoch Baseline Residuals
- 用连续历元基线残差抑制惯性漂移
- 基于海森矩阵奇异值变化判断何时引入全球约束
- 适合低观测条件下的高精度初始化场景
传感器平台的状态初始化常因测量数据有限且高度非线性而困难，易导致初始估计不佳并陷入局部最优。本文提出一种自适应的GNSS-惯性初始化策略，延迟引入全局GNSS约束，直至其信息量足够。初期利用连续历元间基线向量残差抑制惯性漂移。通过分析海森矩阵奇异值演变，提出通用判据以量化系统可观测性，决定激活全局约束的时机。在EuRoC、GVINS和MARS-LVIG数据集上的实验表明，该方法显著优于从一开始就融合所有测量的朴素策略，实现了更准确、更鲁棒的初始化结果。
原文摘要 · Abstract (English)
Initializing the state of a sensorized platform can be challenging, as a limited set of measurements often provide low-informative constraints that are in addition highly non-linear. This may lead to poor initial estimates that may converge to local minima during subsequent non-linear optimization. We propose an adaptive GNSS-inertial initialization strategy that delays the incorporation of global GNSS constraints until they become sufficiently informative. In the initial stage, our method leverages inter-epoch baseline vector residuals between consecutive GNSS fixes to mitigate inertial drift. To determine when to activate global constraints, we introduce a general criterion based on the evolution of the Hessian matrix's singular values, effectively quantifying system observability. Experiments on EuRoC, GVINS and MARS-LVIG datasets show that our approach consistently outperforms the naive strategy of fusing all measurements from the outset, yielding more accurate and robust initializations.
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