Supplementary Files
Keywords
Ovals of Cassini
Radar Virtual Simulation Environment
Range Estimation
Radares Biestáticos
Óvalos de Cassini
Ambiente Virtual de Simulación de Radares
Estimación de la Zona de Visibilidad.
How to Cite
Abstract
A radar device is considered to be bistatic when the transmitter and receiver are placed on locations separated by a distance considerably greater than the distance from the target. One of the key aspects when working with radars is being able to assess the range prior to deployment. In this sense, the ZVR (Zona de Visibilidad del Radar, Radar Range) software is available in Cuba since 1993 for the estimation of the range of monostatic radars. In order to complement the functions of the ZVR, a MATLAB application, which allows the priori calculation of the coverage area, was developed by the authors for the bistatic case. The new BREM (Bistatic Range Estimation in Matlab) software has an intuitive graphical interface that allows the modification of simulation data and selection of specific geographic regions on a map from Cuban territory, while other maps may be also introduced. The tool uses the direct calculation method that requires the existence of direct visibility between the transmitter and receiver, and it will be used for evaluating and planning new bistatic radar deployments.
References
Meikle, H. Modern Radar Systems (2nd Edition): Artech House; 2008. 712 p.
Barton, D. K., & Leonov, S. A. Radar Technology Encyclopedia: Artech House; 1998. 536 p.
Bezousek, P., & Schejbal, V. Bistatic and Multistatic Radar Systems. Radioengineering. 2008;17(3).
Skolnik, M. I. Radar Handbook (3er ed.): McGraw-Hill. 2008. 1328p.
Gungor, A. Clutter Detection in Pulse-Doppler Radar Systems. 2010.
Mixon, D. G. Doppler-Only Multistatic Radar. (Master of Science). Ohio: Air Force Institute of Technology, Wright-Patterson Air Force Base. 2006.
D’Addio, E., Farina, A., Conte, E., & Longo, M. Multistatic Detection of Radar Signals for Swerling Models of the Target. Revista Técnica Selenia, v 9. 1985. 11-17 p.
Hanle, E. Survey of Bistatic and Multistatic Radar. IEE Proceedings. 1986;133(7). 587-595 p.
Sarabandi, K., & Nashashibi, A. A Novel Bistatic Scattering Matrix Measurment Technique using a Monostatic Radar. IEEE Transactions on Antennas and Propagation. 1996;44(1).
-50 p.
Palama, R., Greco, M., Stinco, P., & Gini, F. Statistical Analysis of Netrad High Resolution Sea Clutter. EUSIPCO. IEEE. 2013. 1-5 p.
Iannuzzelli, R. J., Schemm, C. E., & Marcotte, F. J. Aircraft Wake Detection using Bistatic Radar: Analysis of Experimental Results. Johns Hopkins APL Technical Digest. 1998;19(3). 299 p.
Masters, D. S. Surface Remote Sensing Applications of GNSS Bistatic Radar: Soil Moisture and Aircraft Altimetry. [Doctor of Philosophy]. [Colorado]: Faculty of the Graduate School of the University of Colorado. 2004.
Counts, T., Gurbuz, A. C., Scott, W. R., McClellan, J. H., & Kim, K. Multistatic Ground-Penetrating Radar Experiments. IEEE Transactions on Geoscience and Remote Sensing. 2007;45(8). 25544-2553 p.
Glennon, E. P., Dempster, A. G., & Rizos, C. Feasibility of Air Target Detection using GPS as a Bistatic Radar. Journal of Global Positioning Systems. 2006;5(1).
Krishnan, V., Swoboda, J., Yarman, C. E., & Yazici, B. Multistatic Synthetic Aperture Radar Image Formation. IEEE Transactions on Image Processing. 2010;19(5). 1290-1306 p.
Bruyere, D. P., & Goodman, N. A. Adaptive Detection and Diversity Order in Multistatic Radar. IEEE Transactions on Aerospace and Electronic Systems. 2008;44(4). 1615-1623 p.
Choi, S., Berger, C. R., Crouse, D., Willett, P., & Zhou, S. Target Tracking for Multistatic Radar with Transmitter Uncertainty. ECE Department, University of Connecticut. 2009.
M-74450M-12 p.
Liu, W., Yilong, L., & Fu, J. S. A Novel Threshold Optimization for Distributed OS-CFAR of Multistatic Radar Systems by Using the Genetic Algorithm. IEEE. 2001. 75-278 p.
Xu, S., Tang, C., Jing, P., & Chen, Z. Efficient Centralized Track Initiation Method for Multistatic Radar. 2011. 1-7 p.
Efe, M., & Soysal, G. Data Fusion in a Multistatic Radar Network using Covariance Intersection and Particle Filtering. Paper presented at the 14th International Conference on Information Fusion, Chicago. IEEE. 5-8 July 2011; Chicago, IL, USA: IEEE. 1-7 p.
Kay, S. Waveform Desing for Multistatic Radar Detection. Rhode Island: Dept. of Electrical, Computer, and Biomedical Engineering, University of Rhode Island. 2007; 45(3).
Liu, W., Lu, Y., & Fu, J. S. CFAR Data Fusion of Multistatic Radar System under Homogeneous and Nonhomogeneous Backgrounds. The Institution of Electrical Engineers. 2002. 248-252 p.
Bradaric, I., Caprarp, G. T., Weiner, D. D., & Wicks, M. C. A Framework for the Analysis of Multistatic Radar Systems with Multiple Transmitters. IEEE. 2007. 433-446 p.
Brooker, M. The Design and Implementation of a simulator for Multistatic Radar Systems. [Doctor of Philosophy]. [South Africa]: University of Cape Town. 2008.
Ling Lim, Y. The Modelling and Simulation of Passive Bistatic Radar. [Master of Philosophy]. [Australia]: The University of Adelaide. 2013.
Mahdi Naghsh, M., Modarres-Hashemi, M., ShahbazPanahi, S., Soltanalian, M., & Stoica,
P. Unified Optimization Framework for Multi-Static Radar Code Design using Information-Theoretic Criteria. IEEE Transactions on Signal Processing. 2013;61(21). 5401-5416 p.
Kumar Yadav, A., & Kant, L. Moving Target Detection using VI-CFAR Algorithm on MATLAB Platform. Paper presented at the International Journal of Advanced Research in Computer Science and Software Engineering. 2013;3(12) 915-918 p.
Santan, L. A. Análisis, estudio y simulación de los parámetros del radar en el programa MatLab. 2005.
Gibson, K. The Ovals of Cassini. Lecture Notes. 2007.