Low-cost navigation and guidance systems for Unmanned Aerial Vehicles. Part 2: Attitude determination and control

• Autorzy: Sabatini R. , Rodriguez L. , Kaharkar A. , Bartel C. , Shaid T. , Zammit-Mangion D.

Identyfikatory

DOI

10.2478/aon-2013-0008

• Języki publikacji: EN

Abstrakty

EN

This paper presents the second part of the research activity performed by Cranfield University to assess the potential of low-cost navigation sensors for Unmanned Aerial Vehicles (UAVs). This part focuses on carrier-phase Global Navigation Satellite Systems (GNSS) for attitude determination and control of small to medium size UAVs. Recursive optimal estimation algorithms were developed for combining multiple attitude measurements obtained from different observation points (i.e., antenna locations), and their efficiencies were tested in various dynamic conditions. The proposed algorithms converged rapidly and produced the required output even during high dynamics manoeuvres. Results of theoretical performance analysis and simulation activities are presented in this paper, with emphasis on the advantages of the GNSS interferometric approach in UAV applications (i.e., low cost, high data-rate, low volume/weight, low signal processing requirements, etc.). The simulation activities focussed on the AEROSONDE UAV platform and considered the possible augmentation provided by interferometric GNSS techniques to a low-cost and low-weight/volume integrated navigation system (presented in the first part of this series) which employed a Vision-Based Navigation (VBN) system, a Micro-Electro-Mechanical Sensor (MEMS) based Inertial Measurement Unit (IMU) and code-range GNSS (i.e., GPS and GALILEO) for position and velocity com-putations. The integrated VBN-IMU-GNSS (VIG) system was augmented using the intefero-metric GNSS Attitude Determination (GAD) sensor data and a comparison of the performance achieved with the VIG and VIG/GAD integrated Navigation and Guidance Systems (NGS) is presented in this paper. Finally, the data provided by these NGS are used to optimise the design of a hybrid controller employing Fuzzy Logic and Proportional-Integral-Derivative (PID) techniques for the AEROSONDE UAV.

PL

Artykuł przedstawia drugą część badań wykonanych na Uniwersytecie Cranfield dla oszacowania potencjalnych możliwości tanich czujników nawigacyjnych dla bezzałogowych obiektów latających (UAVs). Ta część skupia się na pomiarach fazowych w globalnych nawigacyjnych systemach satelitarnych (GNSS) dla określenia orientacji przestrzennej i sterowania małego lub średniego UAV. Zastosowano rekurencyjne algorytmy optymalnej estymacji dla łącznego przetwarzania różnorodnych pomiarów otrzymanych za pomocą systemu wielkoantenowego testowanego w różnorodnych warunkach wynikających z ruchu obiektu. Zaproponowane algorytmy okazały się zbieżne i zapewniły oczekiwane rezultaty nawet w warunkach bardzo dynamicznych manewrów. Przedstawiono wyniki analiz teoretycznych oraz symulacji, zwracając uwagę na zalety podejścia interferometrycznego w technice GNSS zastosowanej w warunkach wynikających z cech UAV (niski koszt, wysoka szybkość transmisji danych, niska waga i objętość, niewielkie wymagania odnośnie przetwarzania sygnału itd.). Symulacje odniesiono do UAV typu AEROSONDE z zamiarem poszerzenia możliwości systemu w efekcie zastosowania technik interferometrii GNSS, łącznie z tanimi i niewielkimi zintegrowanymi systemami nawigacyjnymi (przedstawionymi w pierwszej części badań w poprzednim artykule) zbudowanymi na systemach optycznych oraz systemie inercjalnym opartym na sensorach klasy MEMS, współpracującym z kodowym systemem GNSS. W artykule przedstawiono szczegółową analizę własności systemu zintegrowanego, łączącego techniki optyczne z GNSS i inercjalnymi, dodatkowo wspartego technikami interferometrycznymi GNSS dla określenia orientacji przestrzennej obiektu (GNSS Attitude Determination — GAD) oraz porównania z różnymi kombinacjami tych modułów. Ponadto podjęto próbę zastosowania danych dostarczonych przez opisany system NGS do zoptymalizowania mieszanego kontrolera wykorzystującego logikę rozmytą i klasyczny regulator PID do sterowania bezzałogowcem AEROSONDE.

Słowa kluczowe

EN

GNSS Attitude Determination; Attitude Determination and Control; unmanned aerial vehicle; Low-cost Navigation Sensors; Fuzzy Logic Controller; PID Controller

• Wydawca: Polskie Forum Nawigacyjne
• Czasopismo: Annual of Navigation
• Rocznik: 2013
• Tom: No. 20
• Strony: 97--126
• Opis fizyczny: Bibliogr. 34 poz., rys., tab.

Twórcy

autor

Sabatini R.

• Cranfield University Department of Aerospace Engineering Cranfield, Bedford MK43 0AL, United Kingdom

autor

Rodriguez L.

• Cranfield University Department of Aerospace Engineering Cranfield, Bedford MK43 0AL, United Kingdom

autor

Kaharkar A.

• Cranfield University Department of Aerospace Engineering Cranfield, Bedford MK43 0AL, United Kingdom

autor

Bartel C.

• Cranfield University Department of Aerospace Engineering Cranfield, Bedford MK43 0AL, United Kingdom

autor

Shaid T.

• Cranfield University Department of Aerospace Engineering Cranfield, Bedford MK43 0AL, United Kingdom

autor

Zammit-Mangion D.

• Cranfield University Department of Aerospace Engineering Cranfield, Bedford MK43 0AL, United Kingdom

Bibliografia

• [1] Angrisano A., GNSS/INS integration methods, Dottorato di ricerca (PhD) in Scienze Geodetiche e Topografiche Thesis, Universita’ degli Studi di Napoli PARTHENOPE, Naple 2010.
• [2] Brown A. K., et al., Interferometric Attitude Determination Using GPS, Pro-ceedings of the Third International Geodetic Symposium on Satellite Doppler Positioning, Las Cruces, NM, 1982, Vol. II, pp. 1289–1304.
• [3] Brunner F., et al., GPS Signal Diffraction Modelling: the Stochastic SIGMA-D Model, Journal of Geodesy, 1999, 73(5), pp. 259–267.
• [4] Chen Z., Birchfield S. T., Qualitative vision-based path following, IEEE Trans. on Robotics, 2009, Vol. 25, issue 3, pp. 749–754.
• [5] Cohen C. E., Attitude Determination Using GPS, PhD Thesis, Stanford Uni-versity, 1992.
• [6] Cohen C., et al., Flight Tests of Attitude Determination Using GPS Compared Against an Inertial Navigation Unit, Navigation (ION Journal), 1994, Vol. 41.
• [7] Gebre-Egziabher D., Hayward R., Powell. J, A Low-Cost GPS/Inertial Atti-tude Heading Reference System (AHRS) for General Aviation Applications, 1998 IEEE Position, Location and Navigation Symposium — PLANS ‘98, Palm Springs, California 1998.
• [8] Giorgi G., Teunissen P. J. G., Carrier phase GNSS attitude determination with the Multivariate Constrained LAMBDA method, Aerospace Conference, 2010 Available online at: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5446910&url=http%3A%2F%2Fieeexplore.ieee.org%2Fstamp%2Fstamp.jsp%3Ftp%3D%26arnumber%3D5446910 (website visited in 2012).
• [9] Giorgi G., Teunissen P. J. G., Gourlay T. P., Instantaneous Global Navigation Satellite System (GNSS)-Based Attitude Determination for Maritime Applica-tions, IEEE Journal of Oceanic Engineering Society, 2012, Vol. 37, No. 99, pp. 348–362.
• [10] Godha S., Performance Evaluation of Low Cost MEMS-Based IMU Integrated With GPS for Land Vehicle Navigation Application, UCGE Report No. 20239, University of Calgary, Department of Geomatics Engineering, Alberta, Canada, 2006.
• [11] Gong X., Abbott A. L., Fleming G. A., A Survey of Techniques for Detection and Tracking of Airport Runways, Collection of Technical Papers, 44th AIAA Aerospace Sciences Meeting and Exhibit, 2006, Vol. 23, pp. 1–14.
• [12] Hopfield H. S., Tropospheric effect on electromagnetically measured range: Prediction from surface weather data, In Radio Science, 1971, 6(3), pp. 357–367.
• [13] Keong J., Determining Heading and Pitch Using a Single Difference GPS/GLONASS Approach, PhD Thesis, Department of Geomatics Engineer-ing, University of Calgary, 2007.
• [14] Kleijer F., Troposphere Modeling and Filtering for Precise GPS Leveling, Ne-derlandse Commissie voor Geodesie (Netherlands Geodetic Commission), 2004.
• [15] Lau L., Cross P., A New Signal-to-Noise-Ratio Based Stochastic Model for GNSS High-Precision Carrier Phase Data Processing Algorithms in the Presence of Multipath Errors, Proceedings of the 19th International Technical Meeting of the Satellite Division of the Institute of Navigation, Fort Worth, TX, 2006, pp. 276–285.
• [16] Maurer J., Polar Remote Sensing Using an Unpiloted Aerial Vehicle (UAV), Seminar by Dr. James Maslanik, Colorado Center for Astrodynamics Re-search (CCAR), University of Colorado at Boulder, Available online at: http://www2.hawaii.edu/~jmaurer/uav/#specifications (website visited in 2012).
• [17] McGraw G.A., Tropospheric Error Modeling for High Integrity Airborne GNSS Navigation, IEEE/ION Position Location and Navigation Symposium, 2012.
• [18] Misra P., Enge P., Global Positioning System: Signal, Measurements, and Performance, Ganga-Jamuna Press, USA, 2001.
• [19] Molina P., Wis M., Pares M. E., Blazquez M., Tatjer J. C., Colomina I., New Approaches to IMU Modeling and INS/GPS Integration for UAV-Based Earth-Observation, Proceedings of the 21st International Technical Meeting of the Satellite Division of The Institute of Navigation, Savannah, GA, Sep-tember 2008, pp. 1335–1344.
• [20] Nassar S., Improving the Inertial Navigation System (INS) Error Model for INS and INS/DGPS Applications, UCGE Reports Number 20183, University of Calgary, Department of Geomatics Engineering, Alberta, Canada, 2003.
• [21] Nixon M. S., Aguado A. S., Feature Extraction and Image Processing, Newnes, 1st Edition, 2002.
• [22] Park C., et al., Error Analysis of 3-Dimensional GPS Attitude Determination System, International Journal of Control, Automation, and Systems, 2006, Vol. 4, No. 4, pp. 480–485.
• [23] Park C., Kim I., An Error Analysis of 2-Dimensional Attitude Determination System Using Global Positioning System, IEEE Transactions on Communica-tions, 2000, Vol. E83-B, No. 6, pp. 1370–1373.
• [24] Parkinson B. W., GPS error analysis, Global Positioning System: Theory and Applications, AIAA, 1996, Vol. 1, pp. 469–483.
• [25] Pinchin J., GNSS Based Attitude for Small Unmanned Aerial Vehicle, PhD Thesis, University of Cantenbury, 2011.
• [26] Sabatini R., Kaharkar A., Shaid T., Bartel C., Jia H., Zammit-Mangion D., Vision-based Sensors and Integrated Systems for Unmanned Aerial Vehicles Navigation and Guidance, Proceedings of the SPIE Conference Photonics Europe 2012, Brussels 2012.
• [27] Sabatini R., Kaharkar A., Shaid T., Bartel C., Jia H., Zammit-Mangion D., Low-cost Vision Sensors and Multisensor Systems for Small to Medium Size UAV Navigation and Guidance, Proceedings of the European Navigation Conference 2012, Gdansk 2012.
• [28] Sabatini R., Rodríguez L., Kaharkar A., Bartel C., Shaid T., GNSS Data Pro-cessing for Attitude Determination and Control of Unmanned Aerial Vehicles, Proceedings of the European Navigation Conference 2012, Gdansk 2012.
• [29] Sangyam T., Laohapiengsak P., Chongcharoen W., Nilkhamhang I., Path track-ing of UAV using self-tuning PID controller based on Fuzzy Logic, Proceed-ings of SICE Annual Conference, 2010, pp. 1265–1269.
• [30] Saripalli S., Montgomery J. F., Sukhatme G. S., Vision Based Autonomous Landing of an Unmanned Aerial Vehicle, Proceedings of International Con-ference of Robotics and Automation, ICRA2002, Washington DC, Virginia, 2002.
• [31] Teunissen P. J. G., The Least-Squares Ambiguity Decorrelation Adjustment: a Method for Fast GPS Integer Ambiguity Estimation, Journal of Geodesy, 1995, Vol. 70, pp. 65–82.
• [32] Unmanned Dynamics LLC, AeroSym Aeronatical Simulation Blockset User’s Manal, Available online at: http://people.rit.edu/pnveme/EMEM682n/Matlab_ 682/aerosim_ug.pdf (website visited in 2012).
• [33] Van Grass F., et al., GPS Interferometric Attitude and Heading Determina-tion: Initial Flight Test Results, Navigation (ION Journal), 1991, Vol. 38.
• [34] Wieser A., et al., Improved Positioning Accuracy with High Sensitivity GNSS Receivers and SNR Aided Integrity Monitoring of Pseudo-range Observa-tions, Proceedings of the 18th International Technical Meeting of the Satellite Division of Institute of Navigation, Long Beach, CA, 2005, pp. 13–16.