Progress In Electromagnetics Research
ISSN: 1070-4698, E-ISSN: 1559-8985
Home | Search | Notification | Authors | Submission | PIERS Home | EM Academy
Home > Vol. 145 > pp. 11-18


By H. Wu and T. Zwick

Full Article PDF (575 KB)

The major difficulty of realizing a micro-air-vehicle-borne (MAV-borne) synthetic aperture radar (SAR) is the motion errors that need to be precisely measured and compensated. This paper presents two novel motion measuring algorithms specifically for near-range applications. These algorithms use only low-cost micro-electronicmechanical system (MEMS) inertial measurement units (IMU). A MAV-borne SAR system was built equipped with a commercial off-the-shelf (COTS) motion sensing board. Several MAV-borne SAR measurements were performed for the first time in a hall with a realistic scene. SAR images were generated with proposed motion measuring algorithms in off-line mode. Obvious improvements in SAR image quality in terms of focusing have been observed after motion compensation with the proposed motion measuring algorithms. These results show that MAV-borne SAR together with low-cost IMU can yield very useful images.

H. Wu and T. Zwick, "Micro-Air-Vehicle-Borne Near-Range SAR with Motion Compensation," Progress In Electromagnetics Research, Vol. 145, 11-18, 2014.

1. Meta, A., P. Hoogeboom, and L. P. Ligthart, "Signal processing for FMCW SAR," IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, No. 11, 3519-3532, 2007.

2. IMSAR, "NanoSAR C data and specification sheet,", 2013.
doi:http://www.imsar.com/uploads/files/46 NanoSAR C Data Sheet.pdf.

3. Roke Manor Research Limited, "Miniature radar altimeter MRA type 2,", 2012.

4. Moses, A., M. J. Rutherford, and K. P. Valavanis, "Radar-based detection and identification for miniature air vehicles," IEEE International Conference on Control Applications (CCA) ,", 933-940, 2011.

5. Seibold, J., N. Frietsch, J. Gut, O. Meister, and G. Trommer, "Cooperative UAV-navigation-aiding based on UGV vision systems," Symposium Gyro Technology, 2010.

6. Weiss, S., M. W. Achtelik, S. Lynen, M. Chli, and R. Siegwart, "Real-time onboard visual-inertial state estimation and self-calibration of MAVs in unknown environments," IEEE International Conference on Robotics and Automation (ICRA), 2012.

7. Ackerman, E., "Quadrotor + kinect = one weird looking robot," IEEE Spectrum, 2010.

8. Martinelli, A., "Vision and IMU data fusion: Closed-form solutions for attitude, speed, absolute scale, and bias determination ," IEEE Transactions on Robotics, Vol. 28, No. 1, 44-60, 2012.

9. Cumming, I. G. and F. H. Wong, Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation, Artech House, 2005.

10. Wu, H. and T. Zwick, "Octave division motion compensation algorithm for near-range wide-beam SAR applications," Progress In Electromagnetics Research, Vol. 144, 115-122, 2014.

11. Titterton, D. H. and J. L. Weston, Strapdown Inertial Navigation Technology, 2nd Ed., Institution of Electrical Engineers, 2004.

12. Wu, H. and T. Zwick, "A novel motion compensation method for automotive SAR: Simulations and experiments," Proceedings of German Microwave Conference, 2010.

© Copyright 2014 EMW Publishing. All Rights Reserved