Abstract
Images usually refer to video images which capture the density of light in each pixels. Instead of density of light, there are many other measurements we can use to sense the objects. For example, radar can sense the intensity of the reflected microwave or acoustic signal at each location. In this chapter, we review and describe new methods for using airborne beamforming radar to create images. By using radar technology, the images so created can have new information, such as velocity and distance. In this paper, we first review the characteristic of optical imaging. Then we proposed an image construction method using low cost airborne beamforming and compare the relationship between optical image and the created radar image. The performance of this method is also investigated. This kind of radar image can be used as a supplement of optical imaging to increase processing speed and accuracy.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ausherman, D.A., Kozma, A., Walker, J.L., Jones, H.M., Poggio, E.C.: Developments in radar imaging. IEEE Trans. Aerosp. Electron. Syst. 20(4), 363–400 (1984)
Axelsson, S.R.J.: Noise radar for range/Doppler processing and digital beamforming using low-bit ADC. IEEE Trans. Geosci. Remote Sens. 41(12), 2703–2720 (2003)
Çetin, M., Karl, W.C.: Feature-enhanced synthetic aperture radar image formation based on nonquadratic regularization. IEEE Trans. Image Process. 10(4), 623–631 (2001)
Cole, C.R., Maslak, S.H., Petrofsky, J.G.: Method and apparatus for Doppler receive beamformer system (1996)
Fujisaka, T., Kirimoto, T., Ohashi, Y.: Digital beam forming radar system (1991)
Hasselmann, K., Hasselmann, S.: On the nonlinear mapping of an ocean wave spectrum into a synthetic aperture radar image spectrum and its inversion. J. Geophys. Res.: Oceans (1978–2012) 96(C6), 10713–10729 (1991)
Hasselmann, S., Brüning, C., Hasselmann, K., Heimbach, P.: An improved algorithm for the retrieval of ocean wave spectra from synthetic aperture radar image spectra. J. Geophys. Res.: Oceans (1978–2012) 101(C7), 16615–16629 (1996)
Ji, Z., Prokhorov, D.: Radar-vision fusion for object classification. In: 2008 11th International Conference on Information Fusion, pp. 1–7 (2008)
Kažys, R., Jakevičius, L., Mažeika, L.: Beamforming by means of 2D phased ultrasonic arrays. Ultragarsas (Ultrasound), Kaunas, Technologija 1(29), 12–15 (1998)
Krieger, G., Gebert, N., Moreira, A.: Multidimensional waveform encoding: a new digital beamforming technique for synthetic aperture radar remote sensing. IEEE Trans. Geosci. Remote Sens. 46(1), 31–46 (2008)
Read, P., Meyer, M.P.: Restoration of Motion Picture Film. Butterworth-Heinemann, London (2000)
Roy, A., Gale, N., Hong, L.: Fusion of Doppler radar and video information for automated traffic surveillance. In: 12th International Conference on Information Fusion. FUSION’09, pp. 1989–1996 (2009)
Shi, J., Braun, R.: Image construction using beam forming. In: Proceedings of the 2nd Asia-Pacific Conference on Computer-Aided System Engineering, APCASE 2014, p. 121 (2004)
Skolnik, M.I.: Radar Handbook. McGraw-Hill, New York (1970)
Ulaby, F.T., Kouyate, F., Brisco, B., Williams, T.H.L.: Textural information in SAR images. IEEE Trans. Geosci. Remote Sens. 24(2), 235–245 (1986)
Waldteufel, P., Corbin, H.: On the analysis of single-Doppler radar data. J. Appl. Meteorol. 18(4), 532–542 (1979)
Xu, L., Li, J., Stoica, P.: Adaptive techniques for MIMO radar. In: Fourth IEEE Workshop on Sensor Array and Multichannel Processing, pp. 258–262. IEEE (2006)
Zebker, H.A., Goldstein, R.M.: Topographic mapping from interferometric synthetic aperture radar observations. J. Geophys. Res.: Solid Earth (1978–2012) 91(B5), 4993–4999 (1986)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Shi, J., Braun, R. (2015). Image Construction Using Low Cost Airborne Beamforming. In: Borowik, G., Chaczko, Z., Jacak, W., Łuba, T. (eds) Computational Intelligence and Efficiency in Engineering Systems. Studies in Computational Intelligence, vol 595. Springer, Cham. https://doi.org/10.1007/978-3-319-15720-7_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-15720-7_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-15719-1
Online ISBN: 978-3-319-15720-7
eBook Packages: EngineeringEngineering (R0)