Experimental Analysis of Radar Odometry by Commercial Ultralight Radar Sensor for Miniaturized UAS

  • Antonio Fulvio Scannapieco
  • Alfredo Renga
  • Giancarmine Fasano
  • Antonio Moccia


Autonomous navigation of miniaturized Unmanned Aircraft Systems (UAS) in complex environments, when Global Positioning System is unreliable or not available, is still an open issue. This paper contributes to that topic exploring the use of radar-only odometry by existing commercial ultralight radars. The focus is set on an end-to-end Multiple-Target Tracking strategy compliant with desired sensor and platform, which exploits both range and bearing measurements provided by the radar. A two-dimensional odometry approach is then implemented. Main results show real-time capabilities and standard deviation of errors in Forward and Cross-range directions smaller than 1.50 m and 3.00 m, respectively. Field test data are also used to discuss the potential of this technique, challenging issues, and future improvements.


UAS Radar Odometry 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



The authors want to thank Roberto Opromolla and Amedeo R. Vetrella for their valuable support during experimental campaign.


  1. 1.
    De Wagter, C., Tijmons, S., Remes, B.D.W., de Croon, G.C.H.E.: Autonomous flight of a 20-gram Flapping Wing MAV with a 4-gram onboard stereo vision system. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 4982–4987 (2014)Google Scholar
  2. 2.
    Vetrella, A., Fasano, G., Renga, A., Accardo, D.: Cooperative UAV navigation based on distributed multi-antenna GNSS, vision, and MEMS sensors. In: 2015 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1128–1137 (2015)Google Scholar
  3. 3.
    Weiss, S., Scaramuzza, D., Siegwart, R.: Vision based MAV navigation in unknown and unstructured environments. In: 2010 IEEE International Conference on Robotics and Automation (ICRA), pp. 21–28 (2010)Google Scholar
  4. 4.
    Achtelik, M., Achtelik, M., Weiss, S., Siegwart, R.: Onboard IMU and monocular vision based control for MAVs in unknown in- and outdoor environments. In: 2011 IEEE International Conference on Robotics and Automation (ICRA), pp. 3056–3063 (2011)Google Scholar
  5. 5.
    Vetrella, A.R., Savvaris, A., Fasano, G., Accardo, D.: RGB-D camera-based quadrotor navigation in GPS-denied and low light environments using known 3D markers. In: 2015 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 185–192 (2015)Google Scholar
  6. 6.
    Accardo, D., Fasano, G., Forlenza, L., Moccia, A.: A.rispoli Flight test of a radar-based tracking system for UAS sense and avoid. IEEE Trans. Aerosp. Electron. Syst. 49, 1139–1160 (2013)CrossRefGoogle Scholar
  7. 7.
    Moses, A.A., Rutherford, M.J., Kontitsis, M., Valavanis, K.P.: UAV-Borne X-band radar for MAV collision avoidance. In: Proceedings of the SPIE 8045, Unmanned Systems Technology XIII 80450U (2011)Google Scholar
  8. 8.
    Caris, M., et al.: SARApe - Synthetic aperture radar for all weather penetrating UAV application. In: 2013 14th International Radar Symposium (IRS), pp. 41–46 (2013)Google Scholar
  9. 9.
    Itcia, E., Wasselin, J.-P., Mazuel, S., Otten, M., Huizing, A.: FMCW Radar for the sense function of sense and avoid systems onboard UAVs. In: Proceedings of the SPIE 8899, Emerging Technologies in Security and Defence; and Quantum Security II; and Unmanned Sensor Systems X 889914 (2013)Google Scholar
  10. 10.
  11. 11.
    Scannapieco, A.F., Renga, A., Fasano, G., Moccia, A.: Ultralight radar sensor for autonomous operations by micro-UAS. In: 2016 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 727–735 (2016)Google Scholar
  12. 12.
    Kopardekar, P.: Safely Enabling Low-Altitude Airspace Operations: Unmanned Aerial System Traffic Management (UTM). Online: (2015)
  13. 13.
    Quist, E.B.: UAV Navigation and Radar Odometry, All theses and dissertations. Paper 4439 (2015)Google Scholar
  14. 14.
    Zhang, J., Singh, S.: Low-drift and real-time lidar odometry and mapping, Autonomous Robots (2017)Google Scholar
  15. 15.
    Nister, D., Naroditsky, O., Bergen, J.: Visual odometry. In: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004, 1, pp. I-652-I-659 (2004)Google Scholar
  16. 16.
    Knott, E.F.: “Radar Cross Section” in Radar Handbook. McGraw Hill, New York (1990)Google Scholar
  17. 17.
    Kauffman, K., Raquet, J., Morton, Y.T.J., Garmatyuk, D.: Real-time UWB-OFDM radar-based navigation in unknown terrain. IEEE Trans. Aerosp. Electron. Syst. 49(3), 1453–1466 (2013)CrossRefGoogle Scholar
  18. 18.
    Quist, E., Beard, R.: Radar odometry on Fixed-Wing small unmanned aircraft. IEEE Trans. Aerosp. Electron. Syst. 52(1), 396–410 (2016)CrossRefGoogle Scholar
  19. 19.
    Quist, E., Niedfeldt, P., Beard, R.: Radar Odometry with recursive-RANSAC. IEEE Trans. Aerosp. Electron. Syst. 52(4), 1618–1630 (2016)CrossRefGoogle Scholar
  20. 20.
    Scaramuzza, D., Fraundorfer, F.: Visual odometry part I: the 1st 30 years and fundamentals. IEEE Robot. Autom. Magazine 18(4), 80–92 (2011)CrossRefGoogle Scholar
  21. 21.
    Scannapieco, A.F., Renga, A., Moccia, A.: Preliminary Study of a Millimeter Wave FMCW inSAR for UAS Indoor Navigation. Sensors 15(2), 2309–2335 (2015)CrossRefGoogle Scholar
  22. 22.
    Howland, P.E., Griffiths, H.D., Baker, C.J.: Passive bistatic radar systems. In: Bistatic Radars: Emerging Technology. Wiley, New York (2008)Google Scholar
  23. 23.
    Scannapieco, A.F., Renga, A., Moccia, A.: Investigation on radar-based applications for mini-UAS and MAVs. In: 2016 17th International Radar Symposium (IRS), pp. 1–6 (2016)Google Scholar
  24. 24.
    Kohlbrecher, S., von Stryk, O., Meyer, J., Klingauf, U.: A flexible and scalable slam system with full 3d motion estimation. In: 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics, pp. 155–160 (2011)Google Scholar
  25. 25.
    Steinbrücker, F., Sturm, J., Cremers, D.: Real-Time Visual Odometry from Dense RGB-D Images. In: 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp. 719–722 (2011)Google Scholar
  26. 26.
    De Lellis, E., Corraro, F., Greco, G., Fasano, G., Accardo, D.: Exploiting Forward Looking Radar Measurements and Digital Map Data Fusion for Altimetry Estimation during Low-altitude Flight Infotech@Aerospace (2011)Google Scholar
  27. 27.
    Cook, C.E., Bernfeld, M.: Radar Signals, An Introduction to Theory and Application, Artech House (1993)Google Scholar
  28. 28.
    Ulaby, F.T., Moore, R.K., Fung, A.K.: Microwave Remote Sensing: Active and Passive, Vol. II – Radar Remote Sensing and Surface Scattering and Emission Theory. Addison-Wesley, Reading (1982)Google Scholar
  29. 29.
    Moccia, A.: Synthetic Aperture Radar. In: Encyclopedia of Aerospace Engineering, pp. 1–13. Wiley, Chichester (2010)Google Scholar
  30. 30.
    Oppenheim, A.V., Willsky, A.S., Nawab, S.H.: Signals and systems. Prentice-Hall, Englewood Cliffs (1983)Google Scholar
  31. 31.
    Blackman, S., Popoli, R.: Design and analysis of modem tracking systems, artech house boston (1999)Google Scholar
  32. 32.
    Rohling, H.: Radar CFAR thresholding in clutter and multiple target situations. IEEE Trans. Aerosp. Electron. Syst. AES-19(4), 608–621 (1983)CrossRefGoogle Scholar
  33. 33.
    Rohling, H.: Some radar topics: Waveform Design, Range CFAR and Target Recognition. In: Advances in Sensing with Security Applications, pp. 293–322. Springer, Netherlands (2006)Google Scholar
  34. 34.
    Novak, L.M.: Radar target detection and map-matching algorithm studies. IEEE Trans. Aerosp. Electron. Syst. AES-16, 620–625 (1980)MathSciNetCrossRefGoogle Scholar
  35. 35.
    Hansent, V.C., Sawyers, J.H.: Detectability loss due to ’greatest of’ selection in a cell-averaging CFAR. IEEE Trans. Aerosp. Electron. Syst. AES-16, 115–118 (1980)CrossRefGoogle Scholar
  36. 36.
    Moore, J.D., Lawrence, N.B.: Comparison of Two CFAR Methods Used with Square Law Detection of Swerling I Targets. IEEE International Radar Conference. Washington, D.C (1980)Google Scholar
  37. 37.
    Weiss, M.: Analysis of some modified cell averaging CFAR processors in multiple-target situations. IEEE Trans. Aerosp. Electron. Syst. AES-18, 102–114 (1982)CrossRefGoogle Scholar
  38. 38.
    Trunk, G.V.: Range resolution of targets using automatic detectors. IEEE Trans. Aerosp. Electron. Syst. AES-14, 750–755 (1978)CrossRefGoogle Scholar
  39. 39.
    Rickard, J.T., Dillard, G.M.: Adaptive detection algorithms for multiple-target situations. IEEE Trans. Aerosp. Electron. Syst. AES-13, 338–343 (1977)CrossRefGoogle Scholar
  40. 40.
    Dillard, G.M., Rickard, J.T.: A distribution-free Doppler processor. IEEE Trans. Aerosp. Electron. Syst. 26, 479–486 (1974)CrossRefGoogle Scholar
  41. 41.
    Blackman, S.: Multiple hypothesis tracking for multiple target tracking. IEEE Aerosp. Electron. Syst. Mag. 19(1), 5–18 (2004)CrossRefGoogle Scholar
  42. 42.
    Bar-Shalom, Y., Li, X.-R.: Estimation and tracking: principles, Techniques and Software. Artech House, Dedham (1993)zbMATHGoogle Scholar
  43. 43.
    Munkres, J.: Algorithms for the assignment and transportation problems. Journal of the Society of Industrial and Applied Mathematics 5, 32–38 (1957)MathSciNetCrossRefzbMATHGoogle Scholar
  44. 44.
    Bourgeois, F., Lassalle, J.-C.: An extension of the munkres algorithm for the assignment problem to rectangular matrices. Commun. ACM 14(12), 802–804 (1971)MathSciNetCrossRefzbMATHGoogle Scholar
  45. 45.
    Bucy, R.S., Joseph, P.D.: Filtering for Stochastic Processes with Applications to Guidance. Interscience Publishers, New York (1968)zbMATHGoogle Scholar
  46. 46.
    Simon, W., Klein, T., Litschke, O.: Small and light 24 GHz multi-channel radar, pp. 987–988 (2014)Google Scholar
  47. 47.
    Kaplan, E.D., Hegarty, C.: Understanding GPS: Principles and Applications. Artech House, Norwood (2005)Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  • Antonio Fulvio Scannapieco
    • 1
  • Alfredo Renga
    • 1
  • Giancarmine Fasano
    • 1
  • Antonio Moccia
    • 1
  1. 1.Department of Industrial EngineeringUniversity of Naples “Federico II”NaplesItaly

Personalised recommendations