Do We Need Ambiguity Resolution in Multi-GNSS PPP for Accuracy or Integrity?

Seepersad, Garrett; Aggrey, John; Bisnath, Sunil

doi:10.33012/2017.15378

Cited by 6 publications

(9 citation statements)

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“…There has been preliminary work [2] on the application of integrity to PPP, but it remains a challenge to translate the benefits of PPP to accuracy while maintaining high integrity. Most of the integrity work in PPP and RTK has dealt with the ambiguity resolution process under nominal error conditions [3], [4], and less on the integrity of the position solution under fault conditions.…”

Section: Introductionmentioning

confidence: 99%

Design and Evaluation of Integrity Algorithms for PPP in Kinematic Applications

Gunning¹,

Blanch²,

Walter³

et al. 2018

ION GNSS+, the International Technical Meeting of the Satellite Division of the Institute of Navigation

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UAV and autonomous platforms can greatly benefit from an assured position solution with high integrity error bounds. The expected high degree of connectivity in these vehicles will allow users to receive real time precise clock and ephemeris corrections, which enable the use of Precise Point Positioning techniques. Up to now, these techniques have mostly been used to provide high accuracy, rather than focusing on high integrity applications. In this paper we apply the methodology and algorithms used in aviation to determine position error bounds with high integrity (or protection levels) for a PPP position solution.

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Section: Introductionmentioning

confidence: 99%

Design and Evaluation of Integrity Algorithms for PPP in Kinematic Applications

Gunning¹,

Blanch²,

Walter³

et al. 2018

ION GNSS+, the International Technical Meeting of the Satellite Division of the Institute of Navigation

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“…Figure 8 shows the probability histograms for the statistic T (blue bars), together with the PDF of the χ 2 (3) distribution (red curves) before and after the stochastic model refinement for the receiver-related error term. Before refinement, Equation (20) with constant coefficients is used to characterize the third term on the right side of Equation ( 2). After refinement, Equation (11), with adaptive coefficients listed in Table 2, is used.…”

Section: Dataset and Resultsmentioning

confidence: 99%

“…Schemes D-F are the counterparts of A-C for the ground-based positioning applications, where the stochastic model of the receiver-related error term is now defined by Equation (20). Scheme G is intended for the evaluation of the ARAIM performance improvement brought about by using a more accurate tropospheric correction model, via a comparison with the results of Scheme F.…”

Section: Ground-based Positioningmentioning

confidence: 99%

“…More recently, there has been increasing interest in investigating RTK or PPP integrity on the basis of the ARAIM concept [16][17][18]. Most of the RTK and PPP integrity investigations have focused more on the ambiguity resolution process under nominal error conditions [19,20], and less on the integrity of the position solution under faulty conditions. In general, for vehicle-based GNSS positioning applications, IM comprehensively considering the following issues is still an open question:…”

Section: Introductionmentioning

confidence: 99%

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ARAIM Stochastic Model Refinements for GNSS Positioning Applications in Support of Critical Vehicle Applications

Yang

Sun

Rizos

et al. 2022

Sensors

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Integrity monitoring (IM) is essential if GNSS positioning technologies are to be fully trusted by future intelligent transport systems. A tighter and conservative stochastic model can shrink protection levels in the position domain and therefore enhance the user-level integrity. In this study, the stochastic models for vehicle-based GNSS positioning are refined in three respects: (1) Gaussian bounds of precise orbit and clock error products from the International GNSS Service are used; (2) a variable standard deviation to characterize the residual tropospheric delay after model correction is adopted; and (3) an elevation-dependent model describing the receiver-related errors is adaptively refined using least-squares variance component estimation. The refined stochastic models are used for positioning and IM under the Advanced Receiver Autonomous Integrity Monitoring (ARAIM) framework, which is considered the basis for multi-constellation GNSS navigation to support air navigation in the future. These refinements are assessed via global simulations and real data experiments. Different schemes are designed and tested to evaluate the corresponding enhancements on ARAIM availability for both aviation and ground vehicle-based positioning applications.

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“…In addition, successful ambiguity resolution in these methods in the harsh environments depends on the availability of observations from several GNSS systems as presented in [83,84], using observations from a number of frequencies and having a good satellite geometry. The need for ambiguity resolution in case of PPP was studied in [85], highlighting the need for fixed ambiguities in case of the accuracy requirement at a few centimetres. However, for the few decimetres accuracy needed for most ITS applications, float solutions could be sufficient.…”

Section: Figure 4 Tightly-coupled Integration Of Gnss Inertial Naviga...mentioning

confidence: 99%

A review of system integration and current integrity monitoring methods for positioning in intelligent transport systems

Hassan

El‐Mowafy

Wang

2020

IET Intelligent Trans Sys

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Applications of intelligent transportation systems are continuously increasing. Since positioning is a key component in these systems, it is essential to ensure its reliability and robustness, and monitor its integrity so that the required levels of positioning accuracy, integrity, continuity and availability can be maintained. In challenging environments, such as urban areas, a single navigation system is often difficult to fulfil the positioning requirements. Therefore, integrating different navigation sensors becomes intrinsic, which may include the global navigation satellite systems, the inertial navigation systems, the odometers and the light detection and ranging sensors. To bind the positioning errors within a pre‐defined integrity risk, the integrity monitoring is an essential step in the positioning service, which needs to be fulfilled for integrated vehicular navigation systems used in intelligent transportation systems. Developing such innovative integrity monitoring techniques requires knowledge of many relevant aspects including the structure, positioning methodology and different errors affecting the positioning solution of the individual and integrated systems. Moreover, knowledge is needed for the current mitigation techniques of these errors, for possible fault detection and exclusion algorithms and for computation of protection levels. This paper provides an overview and discussion of these aspects with a focus on intelligent transportation systems.

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Do We Need Ambiguity Resolution in Multi-GNSS PPP for Accuracy or Integrity?

Cited by 6 publications

References 0 publications

Design and Evaluation of Integrity Algorithms for PPP in Kinematic Applications

Design and Evaluation of Integrity Algorithms for PPP in Kinematic Applications

ARAIM Stochastic Model Refinements for GNSS Positioning Applications in Support of Critical Vehicle Applications

A review of system integration and current integrity monitoring methods for positioning in intelligent transport systems

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