A novel ambiguity resolution model of BeiDou navigation satellite system/inertial navigation system tightly coupled for kinematic-to-kinematic precise relative positioning

IF 1.9 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Ling Wu, Yongrong Sun, Xiyu Fu, Qing-hua Zeng
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引用次数: 0

Abstract

The carrier-based kinematic-to-kinematic relative positioning can obtain the precise baseline between two moving stations, which greatly expands the application field of dynamic relative positioning. However, the relative positioning performance is degraded greatly with low fixation rate of ambiguity with low-cost receivers. Especially, in the complex dynamic environment, ambiguity resolution effect is influenced by the satellite signal blocked, multipath outlier, and abnormal state prediction. Aiming at the problems, a novel inertial navigation system–aided robust adaptive filtering ambiguity resolution model is proposed. In addition, a hierarchical filtering strategy is developed to eliminate ambiguity parameters in BeiDou navigation satellite system/inertial navigation system tightly coupled integrated system. Finally, the precise relative position can be calculated with the “best” ambiguity solution. Both experiments with static data and field vehicle test were carried out to evaluate the algorithm efficiency in different data configurations. The results indicate that IRAFAR-TCRP method can effectively suppress the influence of observation outliers and model prediction abnormalities, which improves the success rate of ambiguity resolution, raises the accuracy as well as the continuity of relative positioning. The success rate of ambiguity resolution with single-frequency BeiDou navigation satellite system can reach 90% in the gross error and abnormal disturbance environments and centimeter-level accuracy can be achieved.
一种新型的北斗卫星导航系统/惯性导航系统紧耦合的运动-运动精确相对定位模糊度解算模型
基于载体的运动学到运动学相对定位可以获得两个移动站之间的精确基线,极大地扩展了动态相对定位的应用领域。然而,在低成本接收机中,由于模糊度的固定率低,相对定位性能大大降低。特别是在复杂的动态环境中,卫星信号的阻塞、多径异常和异常状态预测会影响模糊度的解决效果。针对这些问题,提出了一种新的惯性导航系统辅助鲁棒自适应滤波模糊度求解模型。此外,针对北斗卫星导航系统/惯性导航系统紧耦合集成系统中的模糊度参数,提出了一种分层滤波策略。最后,可以使用“最佳”模糊度解来计算精确的相对位置。分别进行了静态数据实验和现场车辆测试,以评估算法在不同数据配置下的效率。结果表明,IRAFAR-TCRP方法可以有效地抑制观测异常值和模型预测异常的影响,提高了模糊度解算的成功率,提高了相对定位的准确性和连续性。单频北斗导航卫星系统在粗误差和异常干扰环境下解模糊成功率可达90%,精度可达厘米级。
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来源期刊
CiteScore
6.50
自引率
4.30%
发文量
94
审稿时长
3.6 months
期刊介绍: International Journal of Distributed Sensor Networks (IJDSN) is a JCR ranked, peer-reviewed, open access journal that focuses on applied research and applications of sensor networks. The goal of this journal is to provide a forum for the publication of important research contributions in developing high performance computing solutions to problems arising from the complexities of these sensor network systems. Articles highlight advances in uses of sensor network systems for solving computational tasks in manufacturing, engineering and environmental systems.
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