Mapping of the environment with a high resolution ground-based radar imager

The aim of this paper is to present the potential of microwave radar as a high resolution ground-based imager, in order to build radar maps in environmental applications. A new radar sensor named K2Pi, based on the principle of frequency-modulated continuous wave (FM-CW) is described. In order to build the radar maps, the R-SLAM algorithm has been developed. It is based on simultaneous localization and mapping (SLAM) principles. The global radar map is constructed through a data merging process, using scan matching of radar image sequences. First results obtained in different environments are presented, which show the ability of the microwave radar to deal with unstructured and extended environments, and to build consistent maps.

[1]  Sen Zhang,et al.  An Efficient Data Association Approach to Simultaneous Localization and Map Building , 2005, Int. J. Robotics Res..

[2]  Hugh F. Durrant-Whyte,et al.  High‐resolution millimeter‐wave radar systems for visualization of unstructured outdoor environments , 2006, J. Field Robotics.

[3]  P. Faure,et al.  Multiple targets detection with a FMCW radar dedicated to mobile robotics , 2004 .

[4]  Hugh F. Durrant-Whyte,et al.  A solution to the simultaneous localization and map building (SLAM) problem , 2001, IEEE Trans. Robotics Autom..

[5]  Jussi Suomela,et al.  Millimetre Wave Radar for Close Terrain Mapping of an Intelligent Autonomous Vehicle , 1995 .

[6]  N. Baghdadi,et al.  Potential of ERS and Radarsat data for surface roughness monitoring over bare agricultural fields: Application to catchments in Northern France , 2002 .

[7]  S.K. Boehmke,et al.  A high speed 3D radar scanner for automation , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[8]  Paul Newman,et al.  Detecting Loop Closure with Scene Sequences , 2007, International Journal of Computer Vision.

[9]  Alex Foessel-Bunting Radar sensor model for three-dimensional map building , 2001, SPIE Optics East.

[10]  Jagath Samarabandu,et al.  Recent advances in simultaneous localization and map-building using computer vision , 2007, Adv. Robotics.

[11]  Hugh F. Durrant-Whyte,et al.  Autonomous land vehicle navigation using millimeter wave radar , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[12]  Eric F. Lambin,et al.  Land-use and land-cover change : local processes and global impacts , 2010 .

[13]  Hans P. Moravec,et al.  Robot Evidence Grids. , 1996 .

[14]  Hugh F. Durrant-Whyte,et al.  The design of a radar-based navigation system for large outdoor vehicles , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[15]  Martin David Adams,et al.  Millimetre Wave RADAR spectra simulation and interpretation for outdoor SLAM , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[16]  Merril I. Skolnik,et al.  Introduction to radar systems /2nd edition/ , 1980 .

[17]  Hermann Rohling,et al.  Radar CFAR Thresholding in Clutter and Multiple Target Situations , 1983, IEEE Transactions on Aerospace and Electronic Systems.

[18]  Graham M. Brooker,et al.  Application of Millimetre Wave Radar Sensor to Environment Mapping in Surface Mining , 2006, 2006 9th International Conference on Control, Automation, Robotics and Vision.

[19]  G.M. Brooker,et al.  W-band airborne interrupted frequency modulated CW imaging radar , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[20]  Ramakrishna R. Nemani,et al.  Satellite monitoring of global land cover changes and their impact on climate , 1995 .