估计大气延迟参数的中长基线卡尔曼滤波算法A medium and long baseline Kalman filter algorithm for estimating atmospheric delay parameters
李玉星,秘金钟,徐彦田,李建彬
摘要(Abstract):
为了削弱中长基线差分后大气延迟残留误差对实时动态模糊度固定和定位精度的影响,该文提出了一种估计大气延迟参数的卡尔曼滤波算法,采用相对对流层天顶延迟和相对电离层天顶延迟作为残留大气延迟误差参数,与坐标向量和模糊度向量参数一起进行卡尔曼滤波估计。通过41 km参考站数据对算法进行验证。结果表明,BDS-3(B1C/B2a)与GPS精度相当,平面精度优于1.5 cm,高程精度优于2.7 cm; BDS-3(B1C/B2a)/GPS组合平面精度优于1.1 cm,高程精度优于2.7 cm,相比BDS-3(B1C/B2a)单系统平面精度提升了23.8%,估计大气延迟参数的中长基线卡尔曼滤波方法可有效提高模糊度固定成功率,提高中长基线条件下的定位精度。
关键词(KeyWords): BDS-3/GPS;卡尔曼滤波;中长基线实时动态;大气延迟误差
基金项目(Foundation): 国家重点研发计划课题项目(2021YFB3900803)
作者(Author): 李玉星,秘金钟,徐彦田,李建彬
DOI: 10.16251/j.cnki.1009-2307.2022.09.004
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