An Interval Shrinking Trust Region Algorithm for GNSS/eLoran Pseudorange Fusion Positioning Initialization

Kai Liu, Wenhe Yan, Jiangbin Yuan, Zaihui Xiao, Chaozhong Yang, Yu Hua
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Abstract

Fusion of Global Navigation Satellite System (GNSS) with eLoran can greatly improve the coverage and availability of Positioning Navigation and Timing (PNT) services. However, due to the strong nonlinearity in the eLoran pseudorange equations, traditional methods may fail to converge or converge incorrectly when solving the fused pseudorange equation system. In this paper, an interval shrinking trust region algorithm (ISTR) is proposed to solve the pseudorange-based eLoran/GNSS fusion positioning problem, especially when no reliable initial values are available. Simulation and measured data verify that the ISTR algorithm can help the receiver to complete reliable positioning initialization without reliable initial values, and the initialization success rate is 100%.
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GNSS/eLoran伪距融合定位初始化的区间收缩信任域算法
全球导航卫星系统(GNSS)与eLoran的融合可以极大地提高定位导航授时(PNT)服务的覆盖范围和可用性。然而,由于eLoran伪距方程组具有较强的非线性,传统方法在求解融合伪距方程组时可能无法收敛或收敛不正确。针对基于伪橙的eLoran/GNSS融合定位问题,提出了一种区间缩小信赖域算法(ISTR)。仿真和实测数据验证了ISTR算法可以在不需要可靠初始值的情况下,帮助接收机完成可靠的定位初始化,初始化成功率为100%。
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