{"id":{"repo_id":"ecu","oai_identifier":"oai:thescholarship.ecu.edu:10342/9716"},"canonical_url":"https://search.dev.ndltd.org/etd/ecu/oai:thescholarship.ecu.edu:10342/9716","repository":{"repo_id":"ecu","name":"East Carolina University","base_url":"https://thescholarship.ecu.edu/server/oai/request"},"display":{"title":"Using Random Sampling Consensus (RANSAC) to Detect Errors in Global Navigation Satellite Systems (GNSS) Signals and Data","abstract":"A positioning, navigation, and timing (PNT) signal can be used to estimate a user's position at an identified time. A global navigation satellite system (GNSS) uses the PNT signal to provide satellite-based navigation. Advanced receivers can track multiple GNSS constellations simultaneously. In order to have a robust and accurate solution, a user needs to detect any faulty measurements and data, and identify which satellite provided them so that faulty satellite can be excluded from a GNSS solution. Differencing techniques, such as time-differenced carrier phase (TDCP), provide for error reduction. The random sample consensus (RANSAC) method allows for the smoothing of data, even when there are a lot of gross errors present in the data set. The residuals from RANSAC and TDCP were studied to determine if they can be used to detect and identify error sources. A downsampling and thresholding method was able to identify first-order biases with slopes on the order of 10̄ ⁶ within minutes, while biases with slopes on the order of 10̄ ⁷ were identified on the order of one hour. The residuals from RANSAC and TDCP were ultimately able to detect and identify error sources.","abstract_html":"A positioning, navigation, and timing (PNT) signal can be used to estimate a user's position at an identified time. A global navigation satellite system (GNSS) uses the PNT signal to provide satellite-based navigation. Advanced receivers can track multiple GNSS constellations simultaneously. In order to have a robust and accurate solution, a user needs to detect any faulty measurements and data, and identify which satellite provided them so that faulty satellite can be excluded from a GNSS solution. Differencing techniques, such as time-differenced carrier phase (TDCP), provide for error reduction. The random sample consensus (RANSAC) method allows for the smoothing of data, even when there are a lot of gross errors present in the data set. The residuals from RANSAC and TDCP were studied to determine if they can be used to detect and identify error sources. A downsampling and thresholding method was able to identify first-order biases with slopes on the order of 10̄ ⁶ within minutes, while biases with slopes on the order of 10̄ ⁷ were identified on the order of one hour. The residuals from RANSAC and TDCP were ultimately able to detect and identify error sources.","abstract_has_math":false,"creators":["Shah, Nihar"],"institution":"East Carolina University","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Engineering","school":null,"contributors":[],"advisors":["Zhu, Zhen"],"committee_chairs":[],"committee_members":["Wasklewicz, Thad","Ryan, Teresa"],"year":2021,"date_issued":"2021-12-03","date_published":"2021-12-03","updated_at":"2026-07-24T02:13:51Z","subjects":["Time-differenced carrier phase","Random sample consensus","global navigation satellite system","positioning, navigation, and timing"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10342/9716","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Zhu, Zhen"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Wasklewicz, Thad","Ryan, Teresa"]},{"key":"dc:contributor.department","label":"Department","values":["Engineering"]},{"key":"dc:creator","label":"Author","values":["Shah, Nihar"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-02-10T14:57:58Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-02-10T14:57:58Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-12-03"]},{"key":"dc:publisher","label":"Institution","values":["East Carolina University"]},{"key":"dc:type","label":"Dc Type","values":["Master's Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Time-differenced carrier phase","Random sample consensus","global navigation satellite system","positioning, navigation, and timing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10342/9716"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["A positioning, navigation, and timing (PNT) signal can be used to estimate a user's position at an identified time. A global navigation satellite system (GNSS) uses the PNT signal to provide satellite-based navigation. Advanced receivers can track multiple GNSS constellations simultaneously. In order to have a robust and accurate solution, a user needs to detect any faulty measurements and data, and identify which satellite provided them so that faulty satellite can be excluded from a GNSS solution. Differencing techniques, such as time-differenced carrier phase (TDCP), provide for error reduction. The random sample consensus (RANSAC) method allows for the smoothing of data, even when there are a lot of gross errors present in the data set. The residuals from RANSAC and TDCP were studied to determine if they can be used to detect and identify error sources. A downsampling and thresholding method was able to identify first-order biases with slopes on the order of 10̄ ⁶ within minutes, while biases with slopes on the order of 10̄ ⁷ were identified on the order of one hour. The residuals from RANSAC and TDCP were ultimately able to detect and identify error sources."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Using Random Sampling Consensus (RANSAC) to Detect Errors in Global Navigation Satellite Systems (GNSS) Signals and Data"]}]}],"canonical_facts":{"dc:contributor.advisor":["Zhu, Zhen"],"dc:contributor.committeemember":["Wasklewicz, Thad","Ryan, Teresa"],"dc:contributor.department":["Engineering"],"dc:creator":["Shah, Nihar"],"dc:date.accessioned":["2022-02-10T14:57:58Z"],"dc:date.available":["2022-02-10T14:57:58Z"],"dc:date.issued":["2021-12-03"],"dc:description.abstract":["A positioning, navigation, and timing (PNT) signal can be used to estimate a user's position at an identified time. A global navigation satellite system (GNSS) uses the PNT signal to provide satellite-based navigation. Advanced receivers can track multiple GNSS constellations simultaneously. In order to have a robust and accurate solution, a user needs to detect any faulty measurements and data, and identify which satellite provided them so that faulty satellite can be excluded from a GNSS solution. Differencing techniques, such as time-differenced carrier phase (TDCP), provide for error reduction. The random sample consensus (RANSAC) method allows for the smoothing of data, even when there are a lot of gross errors present in the data set. The residuals from RANSAC and TDCP were studied to determine if they can be used to detect and identify error sources. A downsampling and thresholding method was able to identify first-order biases with slopes on the order of 10̄ ⁶ within minutes, while biases with slopes on the order of 10̄ ⁷ were identified on the order of one hour. The residuals from RANSAC and TDCP were ultimately able to detect and identify error sources."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/10342/9716"],"dc:language.iso":["en"],"dc:publisher":["East Carolina University"],"dc:subject":["Time-differenced carrier phase","Random sample consensus","global navigation satellite system","positioning, navigation, and timing"],"dc:title":["Using Random Sampling Consensus (RANSAC) to Detect Errors in Global Navigation Satellite Systems (GNSS) Signals and Data"],"dc:type":["Master's Thesis"]},"updated_at":"2026-07-24T02:13:51Z"}