A Software Engineering Approach on Developing a Real Time Radar Target Generator for Airborne Targets
DOI:
https://doi.org/10.5281/zenodo.10846637Keywords:
radar target generator, software engineering, airborne targets, radar systemAbstract
This paper presents a novel method of a radar system testing in a simulated environment using an artificial Target Generator. This work follows the software engineering approach into implementing the radar software system. Waterfall software development life cycle model if adopted for the Target Generator radar system implementation. The radar system can measure any type of radar target parameters supplied by a Radar Controller and can also transmit any radar signals generated by the Radar Target Generator. This work is essential for radar-related software development, testing, production, and maintenance. If radar targets are to be tested using real flights, though it would produce accurate performance testing results, it would consume increased amounts of time and would be prohibitively costly and complex. Additionally, there is no guaranteed method of flying multiple flights with the same velocity, acceleration, direction, azimuth (angle), altitude, etc. The slight change in every flight affects the accuracy of the final testing results. Hence, virtual radar targets are generated in real time via a virtual flight-testing environment to allow radar systems to be tested with flexible parameters’ settings and high accuracy results. To accomplish this, aircraft dynamics, aircraft’s Radar Cross Section (RCS), and other environmental effects are adjusted and customized in the virtual radar system testing environment. Then, the system will be ready to simulate as many flights as needed. This proposed software proved to be a faster and a more cost-effective solution. It is also programmable in any object-oriented programming language. In addition, due to the high modularity programming approach followed, this implementation is highly scalable and upgradable to any advanced deployment environment, such as governmental platforms.
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Sarkar, T. K., Palma, M. S., & Mokole, E. L. (2016). Echoing across the years: A history of early radar evolution. IEEE Microwave Magazine, 17(10), 46-60.
Graichen, C., Ashe, J., Ganesh, M., & Yu, L. (2012, December). Unobtrusive vital signs monitoring with range-controlled radar. In: 2012 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), pp. 1-6. IEEE.
Ly, H. D., & Liang, Q. (2007, October). Collaborative multi-target detection in radar sensor networks. In: MILCOM 2007-IEEE Military Communications Conference, pp. 1-7. IEEE.
Cataldo, D., Gentile, L., Ghio, S., Giusti, E., Tomei, S., & Martorella, M. (2020). Multibistatic radar for space surveillance and tracking. IEEE Aerospace and Electronic Systems Magazine, 35(8), 14-30.
Heuel, S., & McCarthy, D. (2015). Real time radar target generation. Microwave Journal, 92-106.
Vick, A., Zeigler, S., Brackup, J., Meyers, J. S., & Rand corporation. (2020). Air base defense: Rethinking army and air force roles and functions. RAND Corporation, pp. 0161.
Kavyashree.V, P.N. Madhu Chaitra, Prasad. A.Y, & Vinutha.H. (2017, May). A radar target generator for airborne targets. IJSTE - International Journal of Science Technology & Engineering, 3(11).
Fan, Y., Xiang, K., An, J., & Bu, X. (2013, April). A new method of multi-target detection for FMCW automotive radar. In: IET International Radar Conference, pp. 1-4. IET.
Moses, A. A. (2013). Radar based collision avoidance for unmanned aircraft systems. Doctoral Dissertation, University of Denver.
Goodman, R., Nagy, W., Wilhelm, J., & Crippen, S. (1994, March). A high-fidelity ground to air imaging radar system. In: Proceedings of 1994 IEEE National Radar Conference, pp. 29-34. IEEE.
Yanovsky, F. (2008). Millimeter-wave radar: principles and applications. In: Millimeter Wave Technology in Wireless PAN, LAN, and MAN, pp. 315-386. Auerbach Publications.
Bair, G. L. (1996). Airborne radar simulation. Camber Corporation, Dallas, Texas.
Prickett, M. J., & Chen, C. C. (1980). Principles of inverse synthetic aperture radar/ISAR/imaging. In: EASCON'80; Electronics and Aerospace Systems Conference, pp. 340-345.
Liu, J., Xie, J., Nie, Y., Wang, Y., & Cui, G. (2021, May). A new airborne radar target detection approach based on conditional generative adversarial nets. In: 2021 IEEE 4th International Conference on Electronics Technology (ICET), pp. 184-188. IEEE.
Moore, S. (2009, October). UK airborne AESA radar research. In: 2009 International Radar Conference" Surveillance for a Safer World"(RADAR 2009), pp. 1-7. IEEE.
Borkar, V. G., Ghosh, A., Singh, R. K., & Chourasia, N. K. (2010). Radar cross-section measurement techniques. Defence Science Journal, 60(2), 204.
Prcic, M. M. (1994). Flyable fiber-optic radar target generator. IEEE Aerospace and Electronic Systems Magazine, 9(1), 17-20.
Xiuwei, C., Yunhua, Z., & Xiangkun, Z. (2009, October). Radar echo simulation system with flexible configuration. In: 2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar, pp. 365-368. IEEE.
Berger, S. D. (2003). Digital radio frequency memory linear range gate stealer spectrum. IEEE Transactions on Aerospace and Electronic Systems, 39(2), 725-735.
Sagayaraj, M. J., Jithesh, V., Singh, J. B., Roshani, D., & Srinivasa, K. G. (2018). A hybrid approach to cognition in radars. Defence Science Journal, 68(2), 183.
Heuel, S. (2015, June). Radar target generation. In: 16th International Radar Symposium (IRS), pp. 1002-1009. IEEE.
Postel, J. (1980). User datagram protocol. The RFC Series. (No. rfc768).
You, H., Jianjuan, X., & Xin, G. (2016). Radar data processing with applications. John Wiley & Sons.
Williams, F. C., Howell, W. D., & Briggs, B. H. (1946). Plan-position indicator circuits. Journal of the Institution of Electrical Engineers-Part IIIA: Radiolocation, 93(7), 1219-1255.
Orman, A. J., Shahani, A. K., & Moore, A. R. (1998). Modelling for the control of a complex radar system. Computers & Operations Research, 25(3), 239-249.
Kedwan, F., & Sharma, C. (2019). Model-driven software development platforms reviews. International Journal of Computer Applications, 178(31), 24-33.
Lee, H. B. (2016). Efficient parameter estimation methods for automotive radar systems. Doctoral Dissertation, Department of Electrical and Computer Engineering, College of Engineering, Seoul National University.
Kedwan, F. (2023). Traffic light timer adjustment system using threshold edge detection for image processing: A software engineering approach. International Journal of Current Research in Multidisciplinary (IJCRM), 8(3), 09-36. doi:10.56581/IJCRM.8.3.09-36.
Kedwan, F., & Sharma, C. Twitter texts’ quality classification using data mining and neural networks. International Journal of Computer Applications, 975, 8887.
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