• Axford, D. N., 1968: On the accuracy of wind measurements using an inertial platform in an aircraft, and an example of a measurement of the vertical mesostructure of the atmosphere. J. Appl. Meteor., 7 , 645666.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bange, J., and Roth R. , 1999: Helicopter-borne flux measurements in the nocturnal boundary layer over land—A case study. Bound.-Layer Meteor., 92 , 295325.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bange, J., Beyrich F. , and Engelbart D. A. M. , 2002: Airborne measurements of turbulent fluxes during LITFASS-98: A case study about method and significance. Theor. Appl. Climatol., 73 , 3551.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Beyrich, F., and Mengelkamp H-T. , 2006: Evaporation over a heterogeneous land surface: EVA_GRIPS and the LITFASS-2003 experiment—An overview. Bound.-Layer Meteor., 121 , 532.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bohn, D., and Simon H. , 1975: Mehrparametrige approximation der Eichraume und Eichflächen von Unterschall- bzw. Uberschall-5-Loch-Sonden. Archiv fur Technisches Messen and Meßtechnische Praxis Vol. 470 (3), 31–37.

    • Crossref
    • Export Citation
  • Boiffier, J-L., 1998: The Dynamics of Flight. : The Equations. Wiley, 353 pp.

  • Brown, E. N., Friehe C. A. , and Lenschow D. H. , 1983: The use of pressure fluctuations on the nose of an aircraft for measuring air motion. J. Appl. Meteor., 22 , 171180.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Buschmann, M., Bange J. , and Vörsmann P. , 2004: MMAV—A miniature unmanned aerial vehicle (mini-UAV) for meteorological purposes. Preprints, 16th Symp. on Boundary Layers and Turbulence, Portland, ME, Amer. Meteor. Soc., 6.7. [Available online at http://ams.confex.com/ams/pdfpapers/77875.pdf.].

  • Buschmann, M., Heindorf A. , Winkler S. , and Vörsmann P. , 2006: MINC: A miniature integrated guidance, navigation and control system enables in-flight GPS/INS data fusion aboard a micro aerial vehicle. Proc. 25th Congress of the Int. Council of the Aeronautical Sciences, Hamburg, Germany, ICAS.

  • Crawford, T. L., and Dobosy R. J. , 1992: A sensitive fast-response probe to measure turbulence and heat flux from any airplane. Bound.-Layer Meteor., 59 , 257278.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Egger, J., and Coauthors, 2002: Diurnal winds in the Himalayan Kali Gandaki Valley. Part III: Remotely piloted aircraft soundings. Mon. Wea. Rev., 130 , 20422058.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Farrell, J. L., 2001: Carrier phase processing without integers. Proc. ION 57th Annual Meeting, Albuquerque, NM, Institute of Navigation, 423–428.

  • Gelb, A. H., 1989: Applied Optimal Estimation. MIT Press, 374 pp.

  • Grossman, R. L., 1977: A procedure for the correction of biases in winds measured from aircraft. J. Appl. Meteor., 16 , 654658.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haering, E. A., 1990: Airdata calibration of a high-performance aircraft for measuring atmospheric wind profiles. NASA Tech. Memo. 101774, 24 pp.

    • Crossref
    • Export Citation
  • Hobbs, S., Dyer D. , Courault D. , Olioso A. , Lagouarde J-P. , Kerr Y. , McAneney J. , and Bonnefond J. , 2002: Surface layer profiles of air temperature and humidity measured from unmanned aircraft. Agron. J., 22 , 635640.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holland, G. J., and Coauthors, 2001: The aerosonde robotic aircraft: A new paradigm for environmental observations. Bull. Amer. Meteor. Soc., 82 , 889901.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kálmán, R. E., 1960: A new approach to linear filtering and prediction problems. Trans. AMSE, J. Basic Eng., 82D , 3545.

  • Khelif, D., Burns S. P. , and Friehe C. A. , 1999: Improved wind measurements on research aircraft. J. Atmos. Oceanic Technol., 16 , 860875.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Leach, B. W., and MacPherson J. I. , 1991: An application of Kalman filtering to airborne wind measurements. J. Atmos. Oceanic Technol., 8 , 5165.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Leise, J. A., and Masters J. M. , 1993: Wind measurements from aircraft. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Aircraft Operation Center, 166 pp.

  • Lenschow, D. E., 1986: Probing the Atmospheric Boundary Layer. Amer. Meteor. Soc., 269 pp.

  • Ma, S., Chen H. , Wang G. , Pan Y. , and Li Q. , 2004: A miniature robotic plane meteorological sounding system. Adv. Atmos. Sci., 21 , 890896.

  • Press, W., Flannery B. , Teukolsky S. , and Vetterling W. , 1992: Numerical Recipes in C: The Art of Scientific Computing. 2nd ed. Cambridge University Press, 994 pp.

    • Search Google Scholar
    • Export Citation
  • Sasongko, H., 1997: Rand- und Spaltströmungen in Stark Gestaffelten Verdichtergittern aus Schwach Gewölbten Profilen. Technische Universität Braunschweig, 167 pp.

    • Search Google Scholar
    • Export Citation
  • Scott, S. G., Bui T. P. , Chan K. R. , and Bowen S. W. , 1990: The meteorological measurement system on the NASA ER-2 aircraft. J. Atmos. Oceanic Technol., 7 , 525540.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Soddell, J. R., McGuffie K. , and Holland G. J. , 2004: Intercomparison of atmospheric soundings from the aerosonde and radiosonde. J. Appl. Meteor., 43 , 12601269.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Spieß, T., Bange J. , Buschmann M. , and Vörsmann P. , 2007: First application of the meteorological mini-UAV “M2AV”. Meteor. Z., 16 , 159169.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tjernström, M., and Friehe C. A. , 1991: Analyses of radome air-motion system on a twin-jet aircraft for boundary-layer research. J. Atmos. Oceanic Technol., 8 , 1940.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Van Graas, F., and Farrell J. L. , 2001: GPS/INS—A very different way. Proc. ION 57th Annual Meeting, Albuquerque, NM, Institute of Navigation, 715–721.

  • Vörsmann, P., 1985: Ein Beitrag zur bordautonomen Windmessung. Ph.D. dissertation, Technische Universität Braunschweig, 117 pp.

  • Wendel, J., and Trommer G. F. , 2004: Tightly coupled GPS/INS integration for missile applications. Aerosp. Sci. Technol., 8 , 627634.

  • Winkler, S., and Vörsmann P. , 2007: Multi-sensor data fusion for small autonomous unmanned aircraft. Eur. J. Navig., 5 , 3241.

  • Wood, R., Stromberg I. M. , Jonas P. R. , and Mill C. S. , 1997: Analysis of an air motion system on a light aircraft for boundary layer research. J. Atmos. Oceanic Technol., 14 , 960968.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1153 313 22
PDF Downloads 781 247 20

Measuring the Wind Vector Using the Autonomous Mini Aerial Vehicle M2AV

Aline van den KroonenbergInstitute of Aerospace Systems, Technical University of Braunschweig, Braunschweig, Germany

Search for other papers by Aline van den Kroonenberg in
Current site
Google Scholar
PubMed
Close
,
Tim MartinInstitute of Aerospace Systems, Technical University of Braunschweig, Braunschweig, Germany

Search for other papers by Tim Martin in
Current site
Google Scholar
PubMed
Close
,
Marco BuschmannMavionics GmbH, Braunschweig, Germany

Search for other papers by Marco Buschmann in
Current site
Google Scholar
PubMed
Close
,
Jens BangeInstitute of Aerospace Systems, Technical University of Braunschweig, Braunschweig, Germany

Search for other papers by Jens Bange in
Current site
Google Scholar
PubMed
Close
, and
Peter VörsmannInstitute of Aerospace Systems, Technical University of Braunschweig, Braunschweig, Germany

Search for other papers by Peter Vörsmann in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The meteorological mini unmanned aerial vehicle (M2AV) was used for measuring the meteorological wind. The wind is the vector difference between the aircraft speed relative to the earth (inertial velocity) and relative to the airflow (true airspeed). The latter was computed from five-hole-probe pressure measurements in combination with calibration–coefficient polynomials obtained during wind tunnel calibration. The aircraft inertial velocity, position, and attitude were calculated using a Kalman filter that combined data from a global positioning system (GPS) and an inertial navigation system (INS). The temporal (and spatial) resolution of the M2AV wind measurement is remarkably fine. An inertial subrange of locally isotropic turbulence can be measured up to 40 Hz (or 0.55 m at 22 m s−1 airspeed).

The first M2AV wind estimation showed some systematic deviations compared to the expected values (like a constant mean wind in every flight direction). Therefore, an in-flight wind calibration technique was developed that corrects for the inaccuracy of the true heading, the constant offset of the pitch angle, and the underestimation of the true airspeed. The final adjusted wind measurements were verified during a field experiment at the measurement field of the German Meteorological Service, southeast of Berlin. The mean horizontal and vertical wind measured by the M2AV agreed well with simultaneous sodar and tower measurements.

Corresponding author address: Aline van den Kroonenberg, Institut fur Luft- und Raumfahrtsysteme, TU Braunschweig, 38108 Braunschweig, Germany. Email: a.kroonenberg@tu-bs.de

Abstract

The meteorological mini unmanned aerial vehicle (M2AV) was used for measuring the meteorological wind. The wind is the vector difference between the aircraft speed relative to the earth (inertial velocity) and relative to the airflow (true airspeed). The latter was computed from five-hole-probe pressure measurements in combination with calibration–coefficient polynomials obtained during wind tunnel calibration. The aircraft inertial velocity, position, and attitude were calculated using a Kalman filter that combined data from a global positioning system (GPS) and an inertial navigation system (INS). The temporal (and spatial) resolution of the M2AV wind measurement is remarkably fine. An inertial subrange of locally isotropic turbulence can be measured up to 40 Hz (or 0.55 m at 22 m s−1 airspeed).

The first M2AV wind estimation showed some systematic deviations compared to the expected values (like a constant mean wind in every flight direction). Therefore, an in-flight wind calibration technique was developed that corrects for the inaccuracy of the true heading, the constant offset of the pitch angle, and the underestimation of the true airspeed. The final adjusted wind measurements were verified during a field experiment at the measurement field of the German Meteorological Service, southeast of Berlin. The mean horizontal and vertical wind measured by the M2AV agreed well with simultaneous sodar and tower measurements.

Corresponding author address: Aline van den Kroonenberg, Institut fur Luft- und Raumfahrtsysteme, TU Braunschweig, 38108 Braunschweig, Germany. Email: a.kroonenberg@tu-bs.de

Save