Legacy and advanced receiver autonomous integrity monitoring (RAIM/ARAIM) rely on Gaussian error models that can be overly conservative for real-world non-Gaussian errors. This paper proposes an extended jackknife detector capable of detecting multiple simultaneous faults with non-Gaussian nominal errors. Furthermore, an integrity monitoring algorithm, jackknife ARAIM, is developed by systematically exploiting the properties of the jackknife detector in the range domain. We prove that the proposed method has equivalent monitoring performance with the solution separation (SS) ARAIM, but is significantly computationally efficient for single-fault cases with non-Gaussian nominal errors, while maintaining similar efficiency to SS ARAIM for multiple-fault cases. The proposed method is examined in worldwide simulations, with the nominal measurement error simulated based on authentic experimental data, which reveals different findings in existing research. In a single Global Positioning System (GPS) constellation setting, the proposed method can reduce the 99.5 percentile vertical protection level (VPL) below 45 m, outperforming 50 m VPL produced by the ARAIM algorithm using Gaussian nominal error models. In GPS-Galileo dual-constellation setting, while these Gaussian-based ARAIM algorithms suffer VPL inflation over 60 m due to Galileo's heavy-tailed errors, the proposed method maintains VPL below 40 m, achieving over 92% normal operations for 35 m Vertical Alert Limit. Moreover, we tentatively implement the SS ARAIM using non-Gaussian overbounds and compare it with the proposed Jackknife ARAIM method regarding computation efficiency. The proposed method achieves up to 59.4% reduction in median processing time compared to SS ARAIM in single-constellation scenarios.

翻译：传统及先进的接收机自主完好性监测（RAIM/ARAIM）依赖高斯误差模型，对现实中的非高斯误差可能过于保守。本文提出一种扩展的刀切法检测器，能够在非高斯标称误差下检测多个并发故障。进一步，通过系统性地利用刀切法检测器在测距域的特性，开发了一种完好性监测算法——Jackknife ARAIM。我们证明所提方法具有与解分离（SS）ARAIM等效的监测性能，但在非高斯标称误差的单故障情形下计算效率显著更高，在多故障情形下仍保持与SS ARAIM相近的效率。所提方法通过全球范围仿真进行验证，其中标称测量误差基于真实实验数据模拟，这揭示了现有研究中的不同发现。在单一全球定位系统（GPS）星座配置下，所提方法可将99.5%分位数的垂直保护水平（VPL）降低至45米以下，优于使用高斯标称误差模型的ARAIM算法产生的50米VPL。在GPS-伽利略双星座配置下，基于高斯的ARAIM算法因伽利略系统的重尾误差导致VPL膨胀超过60米，而所提方法能将VPL维持在40米以下，在35米垂直告警限下实现超过92%的正常运行率。此外，我们初步实现了使用非高斯超界包的SS ARAIM，并在计算效率方面与所提Jackknife ARAIM方法进行比较。在单星座场景下，所提方法相比SS ARAIM可实现中位数处理时间最高达59.4%的降低。