Yanbo Zhu

Reduced ARAIM monitoring subset method based on satellites in different orbital planes

With the development of the Global Navigation Satellite System, the increased number of satellites has resulted in more fault hypothesis situations and subset solutions. This situation represents a new challenge for advanced receiver autonomous integrity monitoring (ARAIM) in terms of the computational load. To efficiently detect faults and reduce the computational load, a method based on the association between satellite features in the same orbital plane is proposed. This approach first tests subsets that exclude entire constellations to narrow the search range for faults. Next, we evaluate multiple-fault cases directly by utilizing the subsets that exclude entire orbit satellites. Compared with the baseline Multiple Hypothesis Solution Separation (MHSS) method, our method can clearly reduce the number of subsets and the computational time under a typical multi-constellation situation while satisfying the localizer precision vertical 200 performance requirement, i.e., the guidance supports approach operations down to 200-foot altitudes. Furthermore, the experimental results illustrate that the number of subsets is reduced at most by two orders of magnitude, from 1330 to 87, and the computational time is decreased by 66.6%. The effective monitoring threshold and the fault-free 10−7 error bound on the accuracy of our method are much closer to those of the baseline MHSS method, and the usability coverage of both methods reaches 100%. This study verifies that the monitoring subsets and the calculation time for ARAIM are dramatically reduced by the new method.

Upper bound estimation of positioning error for ground-based augmentation system

Ground-based augmentation systems (GBAS) calculate protection levels (PL), which are bounds of the GBAS positioning errors associated with given integrity levels. In practice, PLs calculated using a Gaussian overbound method tend to be overestimated when the actual (non-Gaussian-distributed) GBAS ranging errors exhibit heavy tails. We propose a stable distribution-based method to overcome this problem. The heavy-tailed stable distribution gives a more appropriate representation of the GBAS ranging error. Based on a symmetric stable distribution, the overbound of the GBAS ranging error is estimated using numerical computations. The stable overbound can tightly bound both the core and the tails of the GBAS ranging error. The PL calculated using this stable overbound is less conservative than that calculated using the Gaussian overbound, although both methods have similar computational complexity. A performance evaluation based on simulated measurements collected from a GBAS prototype shows that the proposed approach increases the availability of GBAS.

Availability prediction method for EGNOS

Following the recent development of wide-area differential technology, satellite-based augmentation systems (SBASs) have been applied in many fields. However, the capability of monitoring stations used for generating error correction might degenerate with the aging of ground equipment over time, and the poor geometry between ranging and integrity monitoring stations (RIMS) and satellites could affect the reliability of navigation systems in supplying safety of life service. Therefore, it is necessary to predict SBAS availability so that users can choose a safe and efficient navigation system. Predictions of user difference range error indicator (UDREI) and grid ionospheric vertical error indicator (GIVEI) are the two difficulties in predicting SBAS availability. Considering the effect of geometry on UDREI, satellite geometric dilution of precision is defined to distinguish different geometries such that the relationship between the number of visible RIMS and UDREI in different geometries can be obtained. With regard to the effect of geometry on GIVEI, a weighted number of visible ionospheric pierce points (IPPs) is defined to describe the geometric IPP distribution such that the relationship between the number of visible IPPs and GIVEI in different geometries can be achieved. Finally, experiments are performed to evaluate the effectiveness of our proposed method. With the prediction algorithm, the prediction is consistent with actual performance over 75.17% of the entire European region. In particular, when focusing on central Europe, where the distribution of RIMS is uniform, the level of consistency can reach 95–100%. It can be concluded that the prediction performance of the algorithm is encouraging and that this model may be considered a good contender for predicting SBAS availability.

GBAS heavy-tail error overbounding with GARCH model

To reduce the inflation for statistical uncertainty and describe the real error distribution objectively, generalized autoregressive conditional heteroskedasticity (GARCH) model is utilized in this paper to model and overbound ground based augmentation system (GBAS) heavy-tail errors. Based on the GARCH model, heavy-tail errors are normalized to the standard Gaussian distribution, and error samples from all elevations are mixed together to calculate overbound without being grouped. By this means, compared with classic error distribution models, the heavy-tail errors are overbounded more tightly, and the calculated inflation factors, error confidence limits in pseudorange domain and protection levels in position domain are reduced correspondingly.

GBAS protection level calculation with GARCH model

To eliminate the time correlation and model the heavy distribution tail of ground based augmentation system (GBAS) errors, a method utilizing generalized autoregressive conditional heteroscedasticity (GARCH) model is introduced in this paper. Considering the statistical uncertainty of model parameters, a strategy for using the GARCH model in nonstationary situations is proposed. Based on that, a protection level calculation framework is established with an online/offline structure to calculate error overbound and protection level in real time. As the heavy-tail errors are normalized to standard Gaussian distribution, and all the normalized errors from different satellites and elevation groups are mixed together to calculate Gaussian overbound, the Gaussian overbound is much tighter than the one calculated by classic heavy-tail errors. That leads to smaller protection levels and higher system availability.

Analysis of BDS ARAIM user receiver nominal bias

Beidou navigation satellite system (BDS) has provided open services for the most part of the AsiaPacific region and plans to provide global service in 2020. In the future, it is necessary for BDS to support ARAIM. As an important parameter of ARAIM, the maximum nominal bias (Bnom) of BDS need to be determined. This paper aims to estimate the impact of nominal biases on ARAIM user performance of BDS. In particular, we focus on the signal deformation and the satellite group delay of BDS signal. To estimate the nominal bias caused by the signal deformation, it is assumed that the code measurements are affected by the correlation loss. The ICAO has described the fault signal distortions of broadcast signal. But it is not appropriate to BDS. We chose a model modified by the comprehensive consideration of the filter provided by Stanford University and 2OS TMB configuration provided by Beijing Satellite Navigation Center. Ideally, the satellite antenna is supposed as a point source for the signals. But the real antenna has biases with the look angle. To estimate the nominal bias caused by the satellite group delay, we assume that BDS signal group delay is similar to GPS IIR-A. In order to guarantee the rationality of Bnom, a simulation of maximum nominal bias for GPS+BDS has been operated in this paper.

Architectural optimization of extensible ground-based GNSS augmentation system

An extensible ground-based GNSS augmentation system architecture is proposed and detailed in this paper. Operational issues related to interoperability of the system are discussed. Restrictions on reference stations site selection are derived from requirements of integrity monitoring center algorithms. Simulation using different combinations of GPS constellations and reference stations configurations indicates that 16 reference stations are enough to provide reliable integrity monitoring service to all users inside China.