全球导航卫星系统应用
接收机自主完整性监测
计算机科学
基线(sea)
灵敏度(控制系统)
星座
卫星导航
实时计算
可靠性工程
算法
钥匙(锁)
工程类
全球定位系统
电子工程
电信
计算机安全
海洋学
物理
地质学
天文
作者
Young C. Lee,Brian Bian
出处
期刊:Proceedings of the Institute of Navigation ... International Technical Meeting
日期:2017-03-07
摘要
Advanced Receiver Autonomous Integrity Monitoring (ARAIM) has recently emerged as a promising candidate for future Global Navigation Satellite Systems (GNSS) that has the potential to achieve worldwide Localizer Performance with Vertical Guidance approach operations capability with a decision height as low as 200 ft (LPV- 200). A major challenge to enabling ARAIM service is the definition and provision of the ARAIM Integrity Support Message (ISM) that provides statistical characterization of the core GNSS constellations as a priori information to the airborne ARAIM algorithm. This paper presents the results of an analysis of the continuity and integrity, specifically the false alert probability (Pfa) and the probability of hazardous misleading information (Pr{HMI}), of the ARAIM algorithm as a result of core GNSS constellation performance deviation from the performance reflected in broadcast ISM parameter values. A brief summary of the key elements of the current baseline ARAIM algorithm is described to facilitate the presentation of the results of the analysis. This baseline algorithm was developed by the EU-US Cooperative Satellite Navigation Working Group C (WG-C) ARAIM Technical Subgroup (TSG). The analysis shows that both the continuity and integrity degrades with the deviation of true ISM values (i.e., values reflecting actual constellation performance) from the broadcast ISM values. This paper also investigates the sensitivity of Pfa depending on how the ranging signal bias errors in nominal conditions are characterized. The underlying causes of high sensitivity are investigated and explained. Uncovering these underlying causes points to potential solutions that fine-tune the baseline ARAIM algorithm to overcome the high Pfa. A summary of the analysis results and proposed future work are provided at the end of the paper.
科研通智能强力驱动
Strongly Powered by AbleSci AI