Shi Bo, Wang Mengke, Wang Yunpeng, Bai Yuntian, Lin Kang, Yang Fanlin
College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266000, China.
Key Laboratory of Ocean Geomatics, Ministry of Natural Resources of China, Qingdao 266000, China.
Sensors (Basel). 2021 Jan 17;21(2):620. doi: 10.3390/s21020620.
The occlusion of buildings in urban environments leads to the intermittent reception of satellite signals, which limits the utilization of observations. This subsequently results in a decline of the positioning and attitude accuracy of Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) integrated system (GNSS/INS). This study implements a smooth post-processing strategy based on a tightly coupled differential GNSS/INS. Specifically, this strategy used the INS-estimated position to reinitialize integer ambiguity. The GNSS raw observations were input into the Kalman filter to update the measurement. The Rauch-Tung-Striebel smoothing (RTSS) algorithm was used to process the observations of the entire period. This study analyzed the performance of loosely coupled and tightly coupled systems in an urban environment and the improvement of the RTSS algorithm on the navigation solution from the perspective of fully mining the observations. The experimental results of the simulation data and real data show that, compared with the traditional tightly coupled processing strategy which does not use INS-aided integer ambiguity resolution and RTSS algorithm, the strategy in this study sufficiently utilized INS observations and GNSS observations to effectively improve the accuracy of positioning and attitude and ensure the continuity of navigation results in an obstructed environment.
城市环境中建筑物的遮挡会导致卫星信号的间歇性接收,这限制了观测数据的利用。这随后导致全球导航卫星系统(GNSS)/惯性导航系统(INS)集成系统(GNSS/INS)的定位和姿态精度下降。本研究基于紧密耦合的差分GNSS/INS实现了一种平滑后处理策略。具体而言,该策略利用INS估计的位置重新初始化整周模糊度。将GNSS原始观测数据输入卡尔曼滤波器以更新测量值。采用Rauch-Tung-Striebel平滑(RTSS)算法处理整个时间段的观测数据。本研究从充分挖掘观测数据的角度分析了城市环境中松耦合和紧耦合系统的性能以及RTSS算法对导航解的改进。模拟数据和真实数据的实验结果表明,与不使用INS辅助整周模糊度解算和RTSS算法的传统紧密耦合处理策略相比,本研究中的策略充分利用了INS观测数据和GNSS观测数据,有效地提高了定位和姿态精度,并确保了在遮挡环境下导航结果的连续性。