{"title":"A Novel Constrained Filter Integrated with an Extended Kalman Filter in Underground Pipeline Navigation Using MEMS IMU","authors":"I. H. Afshar, M. R. Delavar, B. Moshiri","doi":"10.1134/s2075108722010023","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">\n<b>Abstract</b>—</h3><p>To produce a 3D map of the Tehran’s first gas transfer pipeline (Tehran—Kuhnamak), a methodology has been developed in this research, in which a strapdown inertial navigation system (SINS) based on micro-electro-mechanical system (MEMS) and inertial measurement unit (IMU) is applied on pipeline inspection gauges (PIGs) to sense data every 4 millimeters of 111 kilometers of the whole pipeline. The navigation solution is based on an extended Kalman filter (EKF) using Allan variance (AVAR) to analyze and tune the EKF initial inputs. A new constrained PIG filter (CPF) is proposed in this paper in integration with EKF, in which two Euler angles (pitch and yaw) of the PIG are updated due to non-holonomic state constraints between pipe junctions. Besides, 98 magnetic control points have been used to increase robustness about every kilometer, which is coordinated by GPS. Furthermore, odometer measurements have been employed as measurements in the EKF. The results show that using such a hybrid approach has improved the PIG positioning accuracy by about 81% compared with that of the Basic EKF. In addition, positioning accuracy in comparison with the latest methods like EKF/pipeline junctions (PLJ) has increased by 32%. Furthermore, the proposed method is 55% better than EKF/PLJ in the algorithm runtime.</p>","PeriodicalId":38999,"journal":{"name":"Gyroscopy and Navigation","volume":"36 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gyroscopy and Navigation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1134/s2075108722010023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract—
To produce a 3D map of the Tehran’s first gas transfer pipeline (Tehran—Kuhnamak), a methodology has been developed in this research, in which a strapdown inertial navigation system (SINS) based on micro-electro-mechanical system (MEMS) and inertial measurement unit (IMU) is applied on pipeline inspection gauges (PIGs) to sense data every 4 millimeters of 111 kilometers of the whole pipeline. The navigation solution is based on an extended Kalman filter (EKF) using Allan variance (AVAR) to analyze and tune the EKF initial inputs. A new constrained PIG filter (CPF) is proposed in this paper in integration with EKF, in which two Euler angles (pitch and yaw) of the PIG are updated due to non-holonomic state constraints between pipe junctions. Besides, 98 magnetic control points have been used to increase robustness about every kilometer, which is coordinated by GPS. Furthermore, odometer measurements have been employed as measurements in the EKF. The results show that using such a hybrid approach has improved the PIG positioning accuracy by about 81% compared with that of the Basic EKF. In addition, positioning accuracy in comparison with the latest methods like EKF/pipeline junctions (PLJ) has increased by 32%. Furthermore, the proposed method is 55% better than EKF/PLJ in the algorithm runtime.
期刊介绍:
Gyroscopy and Navigation is an international peer reviewed journal that covers the following subjects: inertial sensors, navigation and orientation systems; global satellite navigation systems; integrated INS/GNSS navigation systems; navigation in GNSS-degraded environments and indoor navigation; gravimetric systems and map-aided navigation; hydroacoustic navigation systems; navigation devices and sensors (logs, echo sounders, magnetic compasses); navigation and sonar data processing algorithms. The journal welcomes manuscripts from all countries in the English or Russian language.