A Study on Integrity Monitoring Improvement of the DGPS Reference Station

Cho, Deuk-Jae; Park, Sang‐Hyun; Choi, Jin-Kyu; Suh, Sang-Hyun

doi:10.5394/kinpr.2007.31.6.509

Cited by 4 publications

(3 citation statements)

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“…Such an imbalanced network error can effect on the other network solutions or rover solutions including maritime DGPS (Ahn, 2006;Ahn, 2007;Seo, 2009;Shin, 2013). There have been several studies on how to detect GNSS faults and improve the positioning performance for DGPS applications (Cho, 2007;Kim, 2010;Zhang, 2005;Zheng, 2004). The network errors caused by localized troposphere anomaly can degrade the correction message to the rover.…”

Section: Introductionmentioning

confidence: 99%

Tropospheric Anomaly Detection in Multi-reference Stations Environment during Localized Atmosphere Conditions-(1) : Basic Concept of Anomaly Detection Algorithm

Yoo¹

2016

JNPR

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Extreme tropospheric anomalies such as typhoons or regional torrential rain can degrade positioning accuracy of the GPS signal. It becomes one of the main error terms affecting high-precision positioning solutions in network RTK. This paper proposed a detection algorithm to be used during atmospheric anomalies in order to detect the tropospheric irregularities that can degrade the quality of correction data due to network errors caused by inhomogeneous atmospheric conditions between multi-reference stations. It uses an atmospheric grid that consists of four meteorological stations and estimates the troposphere zenith total delay difference at a low performance point in an atmospheric grid. AWS (automatic weather station) meteorological data can be applied to the proposed tropospheric anomaly detection algorithm when there are different atmospheric conditions between the stations. The concept of probability density distribution of the delta troposphere slant delay was proposed for the threshold determination.

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Section: Introductionmentioning

confidence: 99%

Tropospheric Anomaly Detection in Multi-reference Stations Environment during Localized Atmosphere Conditions-(1) : Basic Concept of Anomaly Detection Algorithm

Yoo¹

2016

JNPR

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“…There were more than 13 times of unscheduled outages from NANU (Notice Advisory to Navstar User) every year during 2000∼2009 on an average [3]. GPS users could be exposed in those error-occurred situation when GPS anomaly started, and the receiver sometimes tracks the anomaly satellite even though it was set unhealthy by GPS control station.…”

Section: Introductionmentioning

confidence: 99%

GPS Anomaly Analysis and Pseudorange Accuracy Improvement by Anomalous Satellite Elimination

Yoo¹,

Cho²,

Park³

2010

Journal of Navigation and Port Research

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“…Inhomogeneous atmospheric conditions can affect the network solution and an imbalanced network error can degrade the correction message to rover station. It has been studied for the integrity monitoring and correction technique of high performance DGPS solution during tropospheric delay anomaly caused by localized atmospheric conditions (Cho, 2007;Kim, 2012;Seo, 2009;Shin, 2013;Yoo, 2011), and it is critical issue to detect an anomalous satellite that can degrade the correction accuracy during inhomogeneous atmosphere conditions in network RTK environment.…”

Section: Introductionmentioning

confidence: 99%

Tropospheric Anomaly Detection in Multi-Reference Stations Environment during Localized Atmospheric Conditions-(2) : Analytic Results of Anomaly Detection Algorithm

Yoo¹

2016

JNPR

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: Localized atmospheric conditions between multi-reference stations can bring the tropospheric delay irregularity that becomes an error terms affecting positioning accuracy in network RTK environment. Imbalanced network error can affect the network solutions and it can corrupt the entire network solution and degrade the correction accuracy. If an anomaly could be detected before the correction message was generated, it is possible to eliminate the anomalous satellite that can cause degradation of the network solution during the tropospheric delay anomaly. An atmospheric grid that consists of four meteorological stations was used to detect an inhomogeneous weather conditions and tropospheric anomaly applied AWSs (automatic weather stations) meteorological data. The threshold of anomaly detection algorithm was determined based on the statistical weather data of AWSs for 5 years in an atmospheric grid. From the analytic results of anomaly detection algorithm it showed that the proposed algorithm can detect an anomalous satellite with an anomaly flag generation caused tropospheric delay anomaly during localized atmospheric conditions between stations. It was shown that the different precipitation condition between stations is the main factor affecting tropospheric anomalies.

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A Study on Integrity Monitoring Improvement of the DGPS Reference Station

Cited by 4 publications

References 0 publications

Tropospheric Anomaly Detection in Multi-reference Stations Environment during Localized Atmosphere Conditions-(1) : Basic Concept of Anomaly Detection Algorithm

Tropospheric Anomaly Detection in Multi-reference Stations Environment during Localized Atmosphere Conditions-(1) : Basic Concept of Anomaly Detection Algorithm

GPS Anomaly Analysis and Pseudorange Accuracy Improvement by Anomalous Satellite Elimination

Tropospheric Anomaly Detection in Multi-Reference Stations Environment during Localized Atmospheric Conditions-(2) : Analytic Results of Anomaly Detection Algorithm

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