XXII ISPRS Congress 2012: Technical Commission VII

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Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/7, III/2, V/1, V/3, ICWG V/I: LOW-COST UAVS (UVSS) AND MOBILE MAPPING SYSTEMS]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: THE PERFORMANCE ANALYSIS OF AN AKF BASED TIGHTLY-COUPLED INS/GPS INTEGRATED POSITIONING AND ORIENTATION SCHEME WITH ODOMETER AND NON-HOLONOMIC CONSTRAINTS Kun-Yao Peng, Cheng-An Lin, Kai-Wei Chiang

Document type:: Multivolume work

Structure type:: Chapter

Table 6. RMS values of the second test integrated system RMS (m) KE E N U EKF 67.214 30.703 43.888 EKF-NHC 36.088 16.557 37.725 AKF 14.169 16.019 28.464 AKF+NHC 11.222 10.963 22.721 4.4 Analysis The first test integrated system implements AKF with NHC can achieve 25% in horizontal position error and 25% in vertical position error in comparison with AKF based algorithm. The second test integrated system implements AKF with NHC can achieve 26% in horizontal position error and 20% in vertical position error from AKF based algorithm. Comparing to the results of the first test integrated system (geodetic GPS receiver) and the second test integrated system (low-cost GPS receiver), similar improvement ration can be obtained. In the case of EKF based INS/GPS tightly-coupled integration with non-holonomic constraints, all the results in this field scenario have 40% up improvement in horizontal position error and 30% averaged improvement in 3D position error from EKF to EKF with non-holonomic constraints. In the other case of AKF based INS/GPS tightly-coupled integration with non-holonomic constraints; the results show the 25% averaged improvement in 3D position error. From the results of EKF, EKF with NHC, AKF and AKF with NHC applied in the integrated systems, the non-holonomic constraints can improve the EKF and AKF based integration algorithms. Therefore, the aid of non-holonomic constraints to the Kalman filters applied in land vehicles can be reveal here, especially during no GPS signals. 5. CONCLUSION The objective of this study 1s to implement EKF and AKF based tightly-coupled INS/GPS integrated system with non-holonomic constraints for land vehicles. 17-state EKF and 17-state AKF with non-holonomic constraints can raise the position accuracy especially during GPS signal obstructions for land vehicles. The case of the 17-state EKF based tightly-coupled INS/GPS integrated system can reach 30% averaged improvement in 3D position error with non-holonomic constraints. The other case of 17-state AKF based tightly-coupled INS/GPS integrated system can reach 25% averaged improvement in 3D position error with non-holonomic constraints. Especially, the non- holonomic constraints can be the aid for the stand-alone INS to decrease the position drift during the GPS obstructions over 1 minute in those two cases of the INS integrated with the geodetic GPS receiver and the low-cost GPS receiver. Therefore, the AKF based INS/GPS tightly-coupled integrated algorithm with non-holonomic constraints can provide more stable navigation solutions than EKF and AKF based integration algorithms applied in a hostile environment. 6. REFERENCE Brown, R.G. and Hwang, P.Y.C., 1992. Introduction to random signals, John Wiley and Sons, New York. Chiang, K.W.; Noureldin, A.; El-Sheimy, N., 2003. A New Weight Updating Method for INS/GPS Integration Architectures Based on Neural Networks. Measurement Science and Technology, 15(10), pp. 2053-2061. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia Chiang, K.W. and Huang, Y.W., 2008. An Intelligent Navigator for Seamless INS/GPS Integrated Land Vehicle Navigation Applications. Applied Soft Computing, Vol. 8, Issue 1, pp. 722- 733. Gelb, A., 1974. Applied Optimal Estimation. MIT Press, Cambridge, England. Genin, F., 1970. Further comments on the derivation of Kalman filters, section II: Gaussian estimates and Kalman filtering. In: Leondes CT (ed) Theory and applications of Kalman filtering, AGARDOgraph 139, NATO Advanced Groups for Aerospace R&D. Kailath, T., 1972. A note on least squares estimation by the innovation method. Soc Ind Appl Math 10(3), pp. 477-486. Kailath, T., 1981. Lectures on Wiener and Kalman filtering, CISM courses and lectures no. 140. Springer, Berlin Heidelberg New York. Lewantowicz, Z.H., 1992. Architectures and GPS/INS integration: impact onmission accomplishment, IEEE Aerospace and Electronics Systems Magazine; 7 (6) 16. Schwarz, K.P. and Mohamed, A.H., 1999. Adaptive Kalman Filtering for INS/GPS, Journal of Geodesy 73, pp. 193-203. Wendel, J. and Trommer, G.F., 2004. Tightly coupled GPS/INS integration for missile applications, Aerospace Science and Technology 8, pp. 627—634. Barbour, N. and Schmidt, G., 2001. Inertial Sensor Technology Trends, IEEE Sensors Journal, Vol. 1, No. 4, pp. 332-339.

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