紧密集成GNSS/惯性系统中的先进接收机自主完整性监测

T. Martin
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引用次数: 2

摘要

本文讨论了惯性测量单元(IMU)与全球卫星导航系统(GNSS)的紧密结合以及先进接收机自主完整性监测(ARAIM)的概念。虽然IMU和GNSS集成到GNSS/惯性综合系统是众所周知的和广泛的,但在惯性系统中使用ARAIM概念是一种新的和有前途的方法。在航空等安全关键应用中,GNSS接收器以及集成GNSS/惯性系统必须配备故障检测和排除(FDE)功能。带有接收机自主完整性监测(RAIM)的单频L1 GPS接收机是几十年来的答案。第二代GNSS提供了更多的卫星系统和更多的导航频率。该方法显著提高了多频多星座(MFMC)接收机的可见性和精度。ARAIM将这些改进转移到航空领域。具有ARAIM的MFMC接收器可以提供具有挑战性的警报限制的保护级别,例如VAL = 35 m,并且具有合理的可用性。因此,ARAIM具有lvb -200(垂直制导定位器性能,决策高度200英尺)进近的潜力。通过纳入IMU,有可能增加这一潜力。使用IMU的附加价值和集成的困难在文献中几乎没有提到。ARAIM通过将包含所有卫星的GNSS位置解与排除某些卫星的子集解(容错解)进行比较来确保完整性。将这一概念转移到紧密集成的GNSS/惯性系统中似乎很简单——用集成的GNSS/惯性位置和子集取代GNSS位置解决方案和子集。另一方面,ARAIM需要评估数百个子集,这产生了相当大的计算负荷,特别是在GNSS/惯性集成的情况下。GNSS/惯性设计面临的一个挑战是ARAIM特定的测距模型,它包括测距偏差、精度和完整性。在ARAIM中使用载波平滑距离。这些平滑信号与最佳GNSS/惯性集成相矛盾。此外,集成设计必须考虑测距信号的时间相关性,这对于ARAIM来说是可以忽略的。在本文中,我们解决了上述使用ARAIM概念的紧密GNSS/惯性集成的设计问题。我们还描述了确定可用性的模拟过程。可用性可作为集成设计的性能度量。通过仿真结果研究了减少子集数量、测距模型的解释和实现、相关时间常数以及不同IMU类别的好处和效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advanced Receiver Autonomous Integrity Monitoring in Tightly Integrated GNSS/Inertial Systems
This paper deals with the tight integration of Inertial Measurement Units (IMU), Global Navigation Satellite Systems (GNSS) and the concept of Advanced Receiver Autonomous Integrity Monitoring (ARAIM). While the integration of an IMU and GNSS to an integrated GNSS/Inertial system is well known and widespread, the use of the ARAIM concept in inertial systems is a new and promising approach. In safety critical applications such as aviation, GNSS receivers as well as integrated GNSS/Inertial systems have to be equipped with a Fault Detection and Exclusion (FDE) function. Single frequency L1 GPS receivers with Receiver Autonomous Integrity Monitoring (RAIM) were the answer for decades. The second generation of GNSS offers more satellite systems and more frequencies for navigation. The visibility and accuracy of Multi-Frequency and Multi- Constellation (MFMC) receivers are significantly improved. ARAIM transfers these improvements into aviation. MFMC receivers with ARAIM can provide protection levels for challenging Alert Limits, for instance VAL = 35 m, with reasonable availability. Therefore, ARAIM has the potential for LPV-200 (Localizer performance with vertical guidance, decision height 200 feet) approaches. By including an IMU, it is possible to increase this potential. The added value of using an IMU and the difficulties of integration are hardly mentioned in literature. ARAIM ensures integrity by comparing the GNSS position solution with all satellites in view to solutions of subsets (fault-tolerant solutions) that exclude certain satellites. A transfer of this concept into a tightly integrated GNSS/Inertial system seems straightforward – replace the GNSS position solutions and subsets by integrated GNSS/Inertial position and subsets. On the other hand, ARAIM needs to evaluate hundreds of subsets, which creates a considerable computational load, especially in the case of GNSS/Inertial integration. A challenge for GNSS/Inertial designs is the ARAIM specific ranging model, which includes ranging bias, accuracy and integrity. Carrier smoothed ranges are used in ARAIM. These smoothed signals contradict an optimal GNSS/Inertial integration. In addition, the integration design has to consider time correlations of ranging signals, neglectable for ARAIM. In this paper, we address the mentioned design issues of a tight GNSS/Inertial integration, which uses the concept of ARAIM. We also describe our simulation procedure to determine availability. The availability serves as performance measure for the integration designs. Benefits and effects of reducing the number of subsets, interpretation and implementation of ranging model, correlation time constants, as well as different IMU classes are investigated by means of simulation results.
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