"The Data of Robust Heteroscedastic Attitude Measurement for High-Rate Fine Guidance Sensors With Online Reliability Enhancement"

"This dataset supports the paper \u201cRobust Heteroscedastic Attitude Measurement for High-Rate Fine Guidance Sensors With Online Reliability Enhancement.\u201d It contains two focal-plane star-coordinate samples used for evaluating robust line-of-sight attitude measurement from high-rate fine-guidance-sensor data under heteroscedastic noise, outliers, and weak rotational observability. ExperientmentSample.mat provides 6000 frames of four-star centroid coordinates (X and Y, each 6000\u00d74) from a ground-test sequence and preserves the original experimental star-coordinate data used in the paper. SkySample.mat provides 8000 frames of three-star centroid coordinates (X1\u2013X3, Y1\u2013Y3) from a real-observation sequence. These data are used for noise estimation, robust alignment evaluation, sensitivity analysis, and comparison of alignment\/attitude-estimation algorithms."

本数据集为论文《面向带在线可靠性增强的高速精密制导传感器的鲁棒异方差姿态测量》提供支撑。数据集包含两组焦面星坐标样本，用于在异方差噪声、异常值与弱旋转可观测性条件下，基于高速精密制导传感器数据开展鲁棒视轴姿态测量的评估工作。ExperientmentSample.mat 包含源自地面测试序列的6000帧四星质心坐标（X、Y维度均为6000×4），完整保留了论文中使用的原始实验星坐标数据。SkySample.mat 包含源自真实观测序列的8000帧三星质心坐标（X1–X3、Y1–Y3）。上述数据可用于噪声估计、鲁棒对准评估、敏感性分析，以及对准/姿态估计算法的对比验证。