Integrity Risk Under Temporal Correlation for Horizontal ARAIM

Bang, Eugene; Milner, Carl

doi:10.1109/taes.2021.3082665

Cited by 9 publications

(7 citation statements)

References 14 publications

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“…Since the integrity risk requirement is defined as the probability over the specific exposure interval, the integrity risk is required to evaluate over multiple detection epochs. Without losing generality, the integrity risk over the exposure interval can be expressed as [21],…”

Section: Problem Definitionmentioning

confidence: 99%

“…It should be noted that this section introduces two distinct definitions of HMI characterization, denoted as ( 3) and ( 4). Compared to (4), Equation (3) describes a more precise HMI event and is often utilized to precisely analyze the values of certain parameters associated with the ARAIM [21]. However, conducting an integrity risk evaluation based on this definition involves a complex challenge of determining the worst-case fault.…”

Section: Hazardous Misleading Informationmentioning

confidence: 99%

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Impact Analysis of Satellite Geometry Variation on ARAIM Integrity Risk over Exposure Interval

Li,

et al. 2024

Remote Sensing

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Accurate integrity risk evaluation is of significance in ensuring that aviation navigation applications satisfy the predefined integrity requirement. The integrity risk evaluation method over a specified exposure interval has been proposed in previous works for the development of advanced receiver autonomous integrity monitoring (ARAIM) (ARAIM technical subgroup reference airborne algorithm description document v4.1, 2022). However, this method typically relies on an underlying optimistic assumption that the satellite geometry remains constant throughout the exposure interval. The variation in satellite geometry due to potential satellite outages undermines the widely-used geometry constant assumption. Thus, we investigate the influence of satellite geometry variations throughout the exposure interval on the integrity performance by introducing a geometry-sensitive risk-evaluation model. The findings demonstrate that, under the nominal situation, the region where the ARAIM fails to meet predefined integrity requirement could expand by a maximum of 2.93% when accounting for satellite geometry variations. Furthermore, in the situation of a single satellite outage, this hazardous region has significantly expanded from 13.12% of the global coverage to 66.82%. Based on these findings, we recommend that the ARAIM should consider satellite outages as a critical factor in real-time integrity risk evaluation.

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Section: Problem Definitionmentioning

confidence: 99%

Section: Hazardous Misleading Informationmentioning

confidence: 99%

Impact Analysis of Satellite Geometry Variation on ARAIM Integrity Risk over Exposure Interval

Li,

et al. 2024

Remote Sensing

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“…With this goal, the GPS Evolutionary Architecture Study introduced a new concept of dual-frequency multiconstellation ARAIM [4]. Subsequently, many forms of ARAIM algorithms have been developed in order to support worldwide LPV-200 service [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Improved protection level for the solution-separation ARAIM based on worst-case fault bias searching

Li,

Jiang

et al. 2024

Meas. Sci. Technol.

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The aviation community is actively pursuing advanced receiver autonomous integrity monitoring (ARAIM) to enhance the safety of aircraft navigation services. Protection level calculation is a crucial task in the solution separation-based ARAIM as it determines the availability of the ARAIM. Accurately determining the worst-case fault bias (WCFB) is beneficial in improving the bounding tightness of protection level on positioning error. Unfortunately, the WCFB determination is a challenging task that requires a time-consuming searching procedure, especially when dealing with the multi-satellite faults. The traditional ARAIM protection level is achieved by constructing an over-conservative worst-case positioning error bound to avoid the unacceptable time-consumption of the brute-force searching for multi-satellite WCFBs. However, this approach comes at the cost of losing the tightness of the protection level and the availability of the ARAIM. The ARAIM milestone reports have pointed out that the availability of the baseline ARAIM needs to be continuously improved in order to satisfy the worldwide localizer precision vertical 200 (LPV-200) requirements. In response, this paper proposes a novel multi-satellite WCFBs searching method for the ARAIM to improve the tightness of protection level. The method consists of determining the worst-case fault direction and constructing an efficient WCFBs searching procedure. GPS/Galileo dual-constellation simulation result demonstrates that the proposed method not only can improve the availability of the ARAIM up to 9.33% when compared with the traditional method, but also achieves comparable computation efficiency.

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“…RAIM can be broadly classified into two categories depending on the standard implementations of the navigation processor of the receiver-weighted least squares (WLS) RAIM and Kalman filter (KF) RAIM. There exists a substantial amount of research on WLS RAIM [6][7][8]. In contrast, KF RAIM is much less explored [9].…”

Section: Introductionmentioning

confidence: 99%

Performance Analyses of a RAIM Algorithm for Kalman Filter with GPS and NavIC Constellations

Bhattacharyya

2021

Sensors

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This paper evaluates the performance of an integrity monitoring algorithm of global navigation satellite systems (GNSS) for the Kalman filter (KF), termed KF receiver autonomous integrity monitoring (RAIM). The algorithm checks measurement inconsistencies in the range domain and requires Schmidt KF (SKF) as the navigation processor. First, realistic carrier-smoothed pseudorange measurement error models of GNSS are integrated into KF RAIM, overcoming an important limitation of prior work. More precisely, the error covariance matrix for fault detection is modified to capture the temporal variations of individual errors with different time constants. Uncertainties of the model parameters are also taken into account. Performance of the modified KF RAIM is then analyzed with the simulated signals of the global positioning system and navigation with Indian constellation for different phases of aircraft flight. Weighted least squares (WLS) RAIM used for comparison purposes is shown to have lower protection levels. This work, however, is important because KF-based integrity monitors are required to ensure the reliability of advanced navigation methods, such as multi-sensor integration and vector receivers. A key finding of the performance analyses is as follows. Innovation-based tests with an extended KF navigation processor confuse slow ramp faults with residual measurement errors that the filter estimates, leading to missed detection. RAIM with SKF, on the other hand, can successfully detect such faults. Thus, it offers a promising solution to developing KF integrity monitoring algorithms in the range domain. The modified KF RAIM completes processing in time on a low-end computer. Some salient features are also studied to gain insights into its working principles.

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Integrity Risk Under Temporal Correlation for Horizontal ARAIM

Cited by 9 publications

References 14 publications

Impact Analysis of Satellite Geometry Variation on ARAIM Integrity Risk over Exposure Interval

Impact Analysis of Satellite Geometry Variation on ARAIM Integrity Risk over Exposure Interval

Improved protection level for the solution-separation ARAIM based on worst-case fault bias searching

Performance Analyses of a RAIM Algorithm for Kalman Filter with GPS and NavIC Constellations

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