This study proposes three novel integrity monitoring algorithms based on Bayesian Receiver Autonomous Integrity Monitoring (BRAIM). Two problems of integrity monitoring for land-based applications for GNSS challenging environments are explored: requirements for sufficient measurement redundancy and the presence of large biases. The need for measurement redundancy was mitigated by using BRAIM. This enabled the employment of a Fault Detection and Exclusion (FDE) algorithm without the required minimum availability of six measurements. To increase the estimated integrity, a Spatial Feature Constraint (SFC) algorithm was implemented to constrain solutions to feasible locations within a road feature. The performance of the proposed FDE+BRAIM, SFC+BRAIM and FDE+SFC+BRAIM algorithms was evaluated for GPS and multi-sensor data. For the non-Gaussian measurement error distribution and under the test conditions, the best achieved probability of misleading information was of the order of magnitude 10-8 for road-level requirements. The results provide an initial proof-of-concept for non-Gaussian non-linear multi-sensor integrity monitoring algorithms.
{"title":"Case study of Bayesian RAIM algorithm integrated with Spatial Feature Constraint and Fault Detection and Exclusion algorithms for multi‐sensor positioning","authors":"J. Gabela, A. Kealy, M. Hedley, B. Moran","doi":"10.1002/NAVI.433","DOIUrl":"https://doi.org/10.1002/NAVI.433","url":null,"abstract":"This study proposes three novel integrity monitoring algorithms based on Bayesian Receiver Autonomous Integrity Monitoring (BRAIM). Two problems of integrity monitoring for land-based applications for GNSS challenging environments are explored: requirements for sufficient measurement redundancy and the presence of large biases. The need for measurement redundancy was mitigated by using BRAIM. This enabled the employment of a Fault Detection and Exclusion (FDE) algorithm without the required minimum availability of six measurements. To increase the estimated integrity, a Spatial Feature Constraint (SFC) algorithm was implemented to constrain solutions to feasible locations within a road feature. The performance of the proposed FDE+BRAIM, SFC+BRAIM and FDE+SFC+BRAIM algorithms was evaluated for GPS and multi-sensor data. For the non-Gaussian measurement error distribution and under the test conditions, the best achieved probability of misleading information was of the order of magnitude 10-8 for road-level requirements. The results provide an initial proof-of-concept for non-Gaussian non-linear multi-sensor integrity monitoring algorithms.","PeriodicalId":30601,"journal":{"name":"Annual of Navigation","volume":"68 1","pages":"333-351"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/NAVI.433","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44042948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Prior work established a model for uncertain Gauss-Markov (GM) noise that is guaranteed to produce a Kalman filter (KF) covariance matrix that overbounds the estimate error distribution. The derivation was conducted for the continuous-time KF when the GM time constants are only known to reside within specified intervals. This paper first provides a more accessible derivation of the continuous-time result and determines the minimum initial variance of the model. This leads to a new, non-stationary model for uncertain GM noise that we prove yields an overbounding estimate error covariance matrix for both sampled-data and discrete-time systems. The new model is evaluated using covariance analysis for a one-dimensional estimation problem and for an example application in Advanced Receiver Autonomous Integrity Monitoring (ARAIM).
{"title":"Overbounding the effect of uncertain Gauss‐Markov noise in Kalman filtering","authors":"S. Langel, Omar García Crespillo, M. Joerger","doi":"10.1002/NAVI.419","DOIUrl":"https://doi.org/10.1002/NAVI.419","url":null,"abstract":"Prior work established a model for uncertain Gauss-Markov (GM) noise that is guaranteed to produce a Kalman filter (KF) covariance matrix that overbounds the estimate error distribution. The derivation was conducted for the continuous-time KF when the GM time constants are only known to reside within specified intervals. This paper first provides a more accessible derivation of the continuous-time result and determines the minimum initial variance of the model. This leads to a new, non-stationary model for uncertain GM noise that we prove yields an overbounding estimate error covariance matrix for both sampled-data and discrete-time systems. The new model is evaluated using covariance analysis for a one-dimensional estimation problem and for an example application in Advanced Receiver Autonomous Integrity Monitoring (ARAIM).","PeriodicalId":30601,"journal":{"name":"Annual of Navigation","volume":"68 1","pages":"259-276"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/NAVI.419","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46563383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Banville, Elyes Hassen, Philippe Lamothe, Justin Farinaccio, B. Donahue, Y. Mireault, M. A. Goudarzi, P. Collins, R. Ghoddousi-Fard, Omid Kamali
{"title":"Enabling ambiguity resolution in CSRS‐PPP","authors":"S. Banville, Elyes Hassen, Philippe Lamothe, Justin Farinaccio, B. Donahue, Y. Mireault, M. A. Goudarzi, P. Collins, R. Ghoddousi-Fard, Omid Kamali","doi":"10.1002/NAVI.423","DOIUrl":"https://doi.org/10.1002/NAVI.423","url":null,"abstract":"","PeriodicalId":30601,"journal":{"name":"Annual of Navigation","volume":"68 1","pages":"433-451"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/NAVI.423","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45018088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"GNSS spoofing detection through spatial processing","authors":"F. Rothmaier, Yu‐Hsuan Chen, S. Lo, T. Walter","doi":"10.1002/NAVI.420","DOIUrl":"https://doi.org/10.1002/NAVI.420","url":null,"abstract":"","PeriodicalId":30601,"journal":{"name":"Annual of Navigation","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/NAVI.420","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48949833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The advent of assisted GPS/GNSS can reduce the time to first fix (TTFF) dramatically and still provide sufficient positioning accuracy. However, many applications utilize GNSS for timing and assisted GPS/GNSS does not always provide the accurate nanosecond synchronization. Accurate timing is challenging for assisted GNSS due to the lack of diversity in the solution over short time periods. The relatively short ambiguities of the GPS L1 C/A code signal, one millisecond and twenty milliseconds, are too coarse to resolve accurate time reliably. In this paper, the impact of different ambiguity times has been derived/computed and validated. Experimental results show that when the ambiguity time is 200 milliseconds or longer, the least squares process will reliably converge and the typical nanosecond-level timing can be achieved. An example shows how the GPS L1 C/A data parity word (provided every 600 milliseconds) can be used, demonstrating nanosecond-level timing from assisted GPS.
{"title":"Deriving Accurate Time from Assisted GNSS Using Extended Ambiguity Resolution","authors":"Ryan Blay, Boyi Wang*, D. Akos","doi":"10.1002/NAVI.412","DOIUrl":"https://doi.org/10.1002/NAVI.412","url":null,"abstract":"The advent of assisted GPS/GNSS can reduce the time to first fix (TTFF) dramatically and still provide sufficient positioning accuracy. However, many applications utilize GNSS for timing and assisted GPS/GNSS does not always provide the accurate nanosecond synchronization. Accurate timing is challenging for assisted GNSS due to the lack of diversity in the solution over short time periods. The relatively short ambiguities of the GPS L1 C/A code signal, one millisecond and twenty milliseconds, are too coarse to resolve accurate time reliably. In this paper, the impact of different ambiguity times has been derived/computed and validated. Experimental results show that when the ambiguity time is 200 milliseconds or longer, the least squares process will reliably converge and the typical nanosecond-level timing can be achieved. An example shows how the GPS L1 C/A data parity word (provided every 600 milliseconds) can be used, demonstrating nanosecond-level timing from assisted GPS.","PeriodicalId":30601,"journal":{"name":"Annual of Navigation","volume":"68 1","pages":"217-229"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/NAVI.412","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47786816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GNSS positioning relies on orbit and clock information, which is predicted on the ground and transmitted by the individual satellites as part of their broadcast navigation message. For an increased autonomy of either the space or user segment, the capability to predict a GNSS satellite orbit over extended periods of up to two weeks is studied. A tailored force model for numerical orbit propagation is proposed that offers high accuracy but can still be used in real-time environments. Using the Galileo constellation with its high-grade hydrogenmaser clocks as an example, global average signal-in-space range errors of less than 25mRMS and 3D position errors of less than about 50 m are demonstrated after two-week predictions in 95% of all test cases over a half-year period. The autonomous orbit prediction model thus enables adequate quality for a rapid first fix or contingency navigation in case of lacking ground segment updates.
{"title":"A long‐term broadcast ephemeris model for extended operation of GNSS satellites","authors":"O. Montenbruck, P. Steigenberger, Moritz Aicher","doi":"10.1002/navi.404","DOIUrl":"https://doi.org/10.1002/navi.404","url":null,"abstract":"GNSS positioning relies on orbit and clock information, which is predicted on the ground and transmitted by the individual satellites as part of their broadcast navigation message. For an increased autonomy of either the space or user segment, the capability to predict a GNSS satellite orbit over extended periods of up to two weeks is studied. A tailored force model for numerical orbit propagation is proposed that offers high accuracy but can still be used in real-time environments. Using the Galileo constellation with its high-grade hydrogenmaser clocks as an example, global average signal-in-space range errors of less than 25mRMS and 3D position errors of less than about 50 m are demonstrated after two-week predictions in 95% of all test cases over a half-year period. The autonomous orbit prediction model thus enables adequate quality for a rapid first fix or contingency navigation in case of lacking ground segment updates.","PeriodicalId":30601,"journal":{"name":"Annual of Navigation","volume":"68 1","pages":"199-215"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/navi.404","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45325101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A low complexity smoothing algorithm for improved GPS point solutions on board LEO spacecraft","authors":"Damon Van Buren, P. Axelrad, S. Palo","doi":"10.1002/NAVI.410","DOIUrl":"https://doi.org/10.1002/NAVI.410","url":null,"abstract":"","PeriodicalId":30601,"journal":{"name":"Annual of Navigation","volume":"68 1","pages":"185-198"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/NAVI.410","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45958024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The past several years have seen a proliferation of software-defined radio (SDR) data collection systems and processing platforms designed for or applicable to satellite navigation (satnav) applications. These systems necessarily produce datasets in a wide range of different formats. To correctly interpret this SDR data, essential information such as the packed sample format and sampling rate is needed. Communicating this metadata between creators and users has historically been an ad-hoc, cumbersome, and error-prone process. To address this issue, the satnav SDR community developed a metadata standard and normative software library to automate this process, thus simplifying the exchange of datasets and promoting the interoperability of satnav SDR systems. The standard was ratified and formally accepted as an Institute of Navigation Standard in January 2020. This article describes the ION GNSS SDR metadata standard and associated open-source software project. All content associated with the standard is available on sdr.ion.org.
{"title":"ION GNSS software‐defined radio metadata standard","authors":"S. Gunawardena, T. Pany, J. Curran","doi":"10.1002/NAVI.407","DOIUrl":"https://doi.org/10.1002/NAVI.407","url":null,"abstract":"The past several years have seen a proliferation of software-defined radio (SDR) data collection systems and processing platforms designed for or applicable to satellite navigation (satnav) applications. These systems necessarily produce datasets in a wide range of different formats. To correctly interpret this SDR data, essential information such as the packed sample format and sampling rate is needed. Communicating this metadata between creators and users has historically been an ad-hoc, cumbersome, and error-prone process. To address this issue, the satnav SDR community developed a metadata standard and normative software library to automate this process, thus simplifying the exchange of datasets and promoting the interoperability of satnav SDR systems. The standard was ratified and formally accepted as an Institute of Navigation Standard in January 2020. This article describes the ION GNSS SDR metadata standard and associated open-source software project. All content associated with the standard is available on sdr.ion.org.","PeriodicalId":30601,"journal":{"name":"Annual of Navigation","volume":"68 1","pages":"11-20"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/NAVI.407","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44535742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The benefits of GNSS have created dependencies on navigation in modern day aviation systems. Many of these systems operate with no backup navigation source. This makes the capabilities supported by precise navigation vulnerable. This paper investigates a contemporary approach to terrain-referenced navigation (TRN), used to preserve an aircraft’s navigation solution during periods of GNSS denial. Traditionally, TRN has been accomplished using a single measurement sensor pointed nadir to an aircraft. Although shown to be effective, this approach limits the achievable navigation accuracy by restricting the measurable terrain gradients to those below an aircraft. This paper explores an alternative approach to TRN that maximizes navigation information through optimal steering of a gimbaled laser. A Cramer-Rao lower bound analysis as well as a high-fidelity simulation establishes the utility of optimal steering while employing TRN. This original approach to TRN shows the order of magnitude improvements in navigation performance over existing methods.
{"title":"Terrain‐referenced navigation using a steerable‐laser measurement sensor","authors":"Jason D. Carroll, A. Canciani","doi":"10.1002/NAVI.406","DOIUrl":"https://doi.org/10.1002/NAVI.406","url":null,"abstract":"The benefits of GNSS have created dependencies on navigation in modern day aviation systems. Many of these systems operate with no backup navigation source. This makes the capabilities supported by precise navigation vulnerable. This paper investigates a contemporary approach to terrain-referenced navigation (TRN), used to preserve an aircraft’s navigation solution during periods of GNSS denial. Traditionally, TRN has been accomplished using a single measurement sensor pointed nadir to an aircraft. Although shown to be effective, this approach limits the achievable navigation accuracy by restricting the measurable terrain gradients to those below an aircraft. This paper explores an alternative approach to TRN that maximizes navigation information through optimal steering of a gimbaled laser. A Cramer-Rao lower bound analysis as well as a high-fidelity simulation establishes the utility of optimal steering while employing TRN. This original approach to TRN shows the order of magnitude improvements in navigation performance over existing methods.","PeriodicalId":30601,"journal":{"name":"Annual of Navigation","volume":"68 1","pages":"115-134"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/NAVI.406","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46197018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The full deployment of China’s BeiDou navigation satellite system (BDS) was finalized in June 2020. To support safety-critical applications, the system must provide assured signal-in-space (SIS) performance. As one of the key steps forward for BDS, this paper characterizes the SIS range errors (SISREs) for both the regional (BDS-2) and the global (BDS-3) systems from the integrity perspective. Following the safety standards in aviation, a data-driven SISRE evaluation scheme is presented in this work. This scheme evaluates the overbounding user range accuracy (URA) and the prior fault probability to respectively capture the nominal and anomalous SIS behaviors. By processing the 4.5-year ephemerides starting from 2016 for BDS-2 and the recent 1.5-year data from2019 for BDS-3, we preliminarily provide an overall picture of the BDS SIS characteristics and reveal the significant performance variation among different satellites.
{"title":"Characterizing BDS signal‐in‐space performance from integrity perspective","authors":"Shizhuang Wang, Y. Zhai, X. Zhan","doi":"10.1002/NAVI.409","DOIUrl":"https://doi.org/10.1002/NAVI.409","url":null,"abstract":"The full deployment of China’s BeiDou navigation satellite system (BDS) was finalized in June 2020. To support safety-critical applications, the system must provide assured signal-in-space (SIS) performance. As one of the key steps forward for BDS, this paper characterizes the SIS range errors (SISREs) for both the regional (BDS-2) and the global (BDS-3) systems from the integrity perspective. Following the safety standards in aviation, a data-driven SISRE evaluation scheme is presented in this work. This scheme evaluates the overbounding user range accuracy (URA) and the prior fault probability to respectively capture the nominal and anomalous SIS behaviors. By processing the 4.5-year ephemerides starting from 2016 for BDS-2 and the recent 1.5-year data from2019 for BDS-3, we preliminarily provide an overall picture of the BDS SIS characteristics and reveal the significant performance variation among different satellites.","PeriodicalId":30601,"journal":{"name":"Annual of Navigation","volume":"68 1","pages":"157-183"},"PeriodicalIF":0.0,"publicationDate":"2021-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/NAVI.409","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42318395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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