A Hybridized Particle Swarm – Grey Wolf Optimization (PS-GWO) Mechanism for the Design of OFDM-LFM Signals in MIMO Systems
Keywords:
Multiple inputs and outputs (MIMO), Radar Communication, Spatial Synthesis Signals, Orthogonal Frequency Division Multiplexing (OFDM), Particle Swarm Integrated Grey Wolf Optimization (PS-GWO), Linear Frequency Modulation (LFM)Abstract
The Orthogonal Frequency Division Multiplexing (OFDM) linear frequency modulation (LFM) waveform has become the focus of much research due to its possible usage in Multiple-Input, Multiple-Output (MIMO) radar; nonetheless, its efficient design remains a hurdle. The OFDM-LFM signals are utilized to extensively examine the pulse compression feature of dynamically generated signals. In the most recent research, several coupled optimization methodologies have been developed to improve radar communication systems’ overall efficiency. However, it comes with shortcomings such as calculations that are hard to understand, a substantial miss rate, and decreased efficacy. To enhance the pulse compression qualities and suppress grating sidelobes, the suggested study aims to develop a hybrid Particle Swarm integrated Grey Wolf Optimization (PS-GWO) mechanism for generating OFDM-LFM signals with suppressed grating side lobes. In this case, the intended LFM waveform is modified to enhance its periodic frequency steps whilst retaining orthogonal and sidelobe properties that are symmetrical. Through simulation research, the performance and results of the proposed PS-GWO based joint optimization model have been evaluated and compared using various pulses compression features. When compared to the most recent methods already in use, the findings of the investigation demonstrate that the suggested optimization model provides more effective results.
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