Journals / Harita Dergisi / 2022 / Cilt: 88 - Sayı: 168

Accurate Lever Arm Determination via 3D Triangulation for Aided Inertial Navigation Systems

Destekli Ataletsel Navigasyon Sistemlerinde 3B Üçgenleme Yöntemi ile Kol Kaçıklığının Hassas Olarak Belirlenmesi

Pages
38–44
Publication Date
2022-10-18
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results reveal that lever arm accuracy of a few millimeters can be achieved with a total station of a medium quality.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:It is a well-known fact that the utilization of erroneous lever arm values in an aided inertial navigation system degrades the accuracy of the navigation solution.
📊
Key Findings & Data:This paper considers the accurate determination of lever arm vector via 3D triangulation, describes the methodology, and provides a MATLAB function for a quick implementation.
💡
Conclusion & Impact:The results reveal that lever arm accuracy of a few millimeters can be achieved with a total station of a medium quality.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

It is a well-known fact that the utilization of erroneous lever arm values in an aided inertial navigation system degrades the accuracy of the navigation solution. In practice, lever arm determination can be difficult, in particular when the displacement between the aiding sensors such as GNSS antenna, odometer, or a laser scanner and IMU is relatively large or the line of sight between them is blocked by the vehicle chassis. This paper considers the accurate determination of lever arm vector via 3D triangulation, describes the methodology, and provides a MATLAB function for a quick implementation. Slant distance, horizontal direction, and zenith angle measurements of a total station along with the fixed positions of the reference points on the IMU casing in an experimental setup are used to estimate the aiding sensor position in the inertial sensor coordinate frame by non-linear weighted least squares adjustment. The results reveal that lever arm accuracy of a few millimeters can be achieved with a total station of a medium quality.

Özet

Destekli ataletsel navigasyon sistemlerinde hatalı kol kaçıklığı değeri kullanımının, navigasyon sonuçları doğruluğunu düşürdüğü iyi bilinen bir gerçektir. Özellikle GNSS anteni, odometre veya lazer tarayıcı gibi destek sensörleri ile IMU arasındaki mesafenin göreceli olarak fazla olması veya birbirleri arasındaki görüş hattının araç gövdesi tarafından bloke edilmesi durumunda, pratikte kol kaçıklığı belirlemek zor bir durum haline gelebilir. Bu çalışma; kol kaçıklığı vektörünün 3B üçgenleme ile hassas bir şekilde belirlenmesini konu almakta, metodolojiyi tanımlamakta ve hızlı bir uygulama için bir MATLAB fonksiyonu sunmaktadır. Deneysel bir kurulum yapılarak bir total station ile elde edilen eğik mesafe, yatay doğrultu ve zenit açı ölçümleri ile birlikte IMU kasası üzerindeki referans noktalarının sabit konumları kullanılarak, destek sensörünün ataletsel sensör koordinat çerçevesindeki konumu, doğrusal-olmayan ağırlıklı en küçük kareler dengelemesi ile kestirilmiştir. Sonuçlar, orta kaliteli bir total station ile birkaç milimetre doğruluğunda kol kaçıklığının belirlenebileceğini göstermektedir.

🔖

Cite This Article

SİMAV, M., AKDOĞAN, Y. A. (2022). Accurate Lever Arm Determination via 3D Triangulation for Aided Inertial Navigation Systems. Harita Dergisi, Cilt: 88 - Sayı: 168, 38–44. https://ajindex.com/articles/533962

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (4)

  1. Alsadik, B. (2019). Adjustment models in 3D geomatics and computational geophysics with MATLAB examples. Elsevier, Amsterdam. Awange, J.L. and Grafarend, E.W. (2005). Solving algebraic computational problems in geodesy and geoinformatics. Springer, Berlin. Bell, T. (2000). Error analysis of attitude measurement in robotic ground vehicle position determination. Navigation, 47(4), 289-296. doi: 10.1002/j.2161-4296.2000.tb00222.x Borko, A., Klein, I. and Even-Tzur, G. (2018). GNSS/INS fusion with virtual lever-arm measurements. Sensors, 18(7), 2228. doi: 10.3390/s18072228 Farrell, J.A. (2008). Aided navigation: GPS with high rate sensors. McGraw-Hill, New York Grewal, M.S., Andrews, A.P. and Bartone, C.G. (2013). Global navigation satellite systems, inertial navigation and integration. John Wiley & Sons. Groves, P.D. (2013). Principles of GNSS, inertial, and multisensor integrated navigation systems. Artech House: Norwood, MA. He, X. and Jianye, L. (2002). Analysis of lever arm effects in GPS/IMU integration system. Trans. Nanjing Univ. Aeronaut. Astronaut, 19(1), 59-64.
  2. Hong, S., Chang, Y-S., Ha, S-K. and Lee, M-H. (2002). Estimation of alignment errors in GPS/INS integration. Proceedings of the 15th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 2002),
  3. Portland, OR, pp 527-534.
  4. Hong, S., Lee, M-H., Kwon, S-H. and Chun, H-H. (2004). A car test for the estimation of GPS/INS alignment errors. IEEE Transactions on Intelligent Transportation Systems, 5(3), 208-218. doi: 10.1109/TITS.2004.833771 Hong, S., Lee, M-H., Chun, H-H., Kwon, S-H. and Speyer, J.L. (2005). Observability of error states in GPS/INS integration. IEEE Transactions on Vehicular Technology, 54(2), 731-743. doi: 10.1109/TVT.2004.841540 Hong, S., Lee, M-H., Chun, H-H., Kwon, S-H. and Speyer, J.L. (2006). Experimental study on the estimation of lever arm in GPS/INS. IEEE Transactions on Vehicular Technology, 55(2), 431-448. doi: 10.1109/TVT.2005.863411 Jekeli, C. (2001). Inertial navigation systems with geodetic applications. Walter de Gruyter, Berlin. Lee, M.K., Hong, S., Lee, M-H., Kwon, S-H. and Chun, H-H. (2005). Observability analysis of alignment errors in GPS/INS. Journal of Mechanical Science and Technology, 19(6), 1253-1267. doi: 10.1007/BF02984046 Luhmann, T., Robson, S., Kyle, S. and Boehm, J. (2020). Close-range photogrammetry and 3D imaging. Walter de Gruyter, Berlin. Montalbano, N. and Humphreys, T. (2018). A comparison of methods for