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Implementation of MOIDS Algorithm for Optimal Parameter Selection of SFPT for Modern Radars
K. Ravi Kumar1, P. Rajesh Kumar2, Satish Kumar Injeti3
1Dr. K. Ravi Kumar, Department of ECE, N. S. Raju Institute of Technology, Sontyam, Visakhapatnam, Andhra Pradesh, India.
2Prof. P. Rajesh Kumar, Department of ECE, A U College of Engineering (A), Andhra University, Visakhapatnam, Andhra Pradesh, India.
3Dr. Satish Kumar Injeti, Department of Electrical Engineering, National Institute of Technology, Warangal, Telengana State, India.

Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 4093-4099 | Volume-8 Issue-5, January 2020. | Retrieval Number: D4515118419/2020©BEIESP | DOI: 10.35940/ijrte.D4515.018520

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Modern radars require signals of the large frequency range to attain relatively greater range resolution. Frequency stepping is the technique to convert the narrowband signal, i.e., a train of pulses into a wideband signal to achieve high accuracy in range resolution measurements. Due to the cause of constant step in frequency of successive pulses, grating lobes appeared when the period of pulse multiplied by step in frequency exceeds unity as is needed in modern radars. Hence to achieve the best resolution, grating lobes height, sidelobes level, and mainlobe width have to be minimum. In this paper an attempt has been made to diminish grating lobes, minimize sidelobes and reduce mainlobe width using MOIDSA to find the parameters of Stepped Frequency Pulse Train (SFPT) mechanism. The compromise between various lobes is obtained by using three dimensional Pareto fronts for different ranges of SFPT parameters.
Keywords: Stepped Frequency Pulse Train, Autocorrelation Function, Grating Lobes, Sidelobes, Mainlobe Width and Multioptimization Algorithms.
Scope of the Article: Parallel and Distributed Algorithms.