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Improving radar visualization system
Keywords:
Radar, Data Visualization, Signal Processing, Signal Pattern RecognitionAbstract
This work develops a system to visualize the information for radar systems interfaces. It is a flexible, portable software system that allows to be used for radars that have different technologies and that is able to be adapted to the specific needs of each aplication domain in an eficient way. Replacing the visualization and processing units on existing radar platforms by this new system, a practical and inexpensive improvement is achieved.
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References
[1] Hovanessian, S. A., Radar Detection and Tracking Systems. Artech House, Inc. 1973.
[2] Sha, L. et al., Evolving Dependable Real-Time Systems. Technical Report CMS/SEI95 -TR-005, CMU, Software Engineering Institute. 1995.
[3] Perry, R. et al., Trellis Structure Approach to Multitarget Tracking. Adaptive Sensor Array Processing Workshop, Marzo de 1999. MIT Lincoln Laboratory.
[4] Johnson, J. R. y Johnson, R. W., Challenges of Computing the Fast Fourier Transform. Optimized Portable Application Libraries (OPAL) Workshop, Kansas City. Junio de 1997.
[5] Xilinx Ltd., Virtex 4 Family Overview, DS112 (V2.0), January 23, 2007.
[6] Ken Chapman, Pico Blaze – Amplifier and A/D converter control for Spartan-3E Starter Kit, Xilinx Ltd, February 23, 2006.
[7] Solanki Gautam V., Neural network and its application in pattern recognition, Seminar Report, Indian Institute of Technology, 2004.
[8] Yihua Liao, Neural networks in hardware: a survey, Department of Computer Science, University of California, 2001.
[9] Silicon Recognition, 1150 Industrial Avenue, Suite C, Petaluma, CA 94952, URL: www.silirec.com.
[10] Noone, G., Radar pulse train parameter estimation and tracking using neural networks, In Proc. IEEE ANNES'95, IEEE, November 1995.
[11] Mingolla E., Ross W., Grossberg S., A neural network for enhancing boundaries and surfaces in synthetic aperture radar images, Neural Networks 1999; 12 499—511
[12] Krishnamohan Rao C. and Mmoharir, P. S., Radar signal design problem with neural network processing, Sadhana, Vol. 26, Part 3, June 2001, pp. 237–241.
[13] Acosta et. al., Desarrollo de un Visualizador de Señales de Radar, CACIC, October 2006, San Luis, Argentina.
[2] Sha, L. et al., Evolving Dependable Real-Time Systems. Technical Report CMS/SEI95 -TR-005, CMU, Software Engineering Institute. 1995.
[3] Perry, R. et al., Trellis Structure Approach to Multitarget Tracking. Adaptive Sensor Array Processing Workshop, Marzo de 1999. MIT Lincoln Laboratory.
[4] Johnson, J. R. y Johnson, R. W., Challenges of Computing the Fast Fourier Transform. Optimized Portable Application Libraries (OPAL) Workshop, Kansas City. Junio de 1997.
[5] Xilinx Ltd., Virtex 4 Family Overview, DS112 (V2.0), January 23, 2007.
[6] Ken Chapman, Pico Blaze – Amplifier and A/D converter control for Spartan-3E Starter Kit, Xilinx Ltd, February 23, 2006.
[7] Solanki Gautam V., Neural network and its application in pattern recognition, Seminar Report, Indian Institute of Technology, 2004.
[8] Yihua Liao, Neural networks in hardware: a survey, Department of Computer Science, University of California, 2001.
[9] Silicon Recognition, 1150 Industrial Avenue, Suite C, Petaluma, CA 94952, URL: www.silirec.com.
[10] Noone, G., Radar pulse train parameter estimation and tracking using neural networks, In Proc. IEEE ANNES'95, IEEE, November 1995.
[11] Mingolla E., Ross W., Grossberg S., A neural network for enhancing boundaries and surfaces in synthetic aperture radar images, Neural Networks 1999; 12 499—511
[12] Krishnamohan Rao C. and Mmoharir, P. S., Radar signal design problem with neural network processing, Sadhana, Vol. 26, Part 3, June 2001, pp. 237–241.
[13] Acosta et. al., Desarrollo de un Visualizador de Señales de Radar, CACIC, October 2006, San Luis, Argentina.
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Published
2007-03-01
How to Cite
Acosta, N., Tosini, M. A., Mezzanotte, M. F., & Tommasi, M. C. (2007). Improving radar visualization system. Journal of Computer Science and Technology, 7(01), p. 1–7. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/795
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