Abstract
Frequency shift keying-phase shift keying (FSK-PSK) waveforms are recognized for their superior resolution and signal detectability. However, the optimization of FSK-PSK parameters, particularly frequency hopping control, remains challenging and can lead to increased sidelobe levels. This paper develops an optimization model to substantially enhance the controllability of hopping frequency in FSK-PSK waveforms for radar systems. By harnessing the Karush-Kuhn-Tucker (KKT) conditions, the model strategically minimizes the autocorrelation integrated sidelobe level (ISL), thereby sharpening radar target discrimination and bolstering anti-jamming capabilities. An iterative algorithm specifically addresses the model’s optimal subproblems, optimizing frequency agility and stability. Simulation results show that our FSK-PSK waveform outperforms the waveform optimized by the Multi-Objective Quantum Genetic Algorithm (MoQGA) with a 4.93 dB sidelobe suppression gain, enhancing detection accuracy and anti-jamming performance in disturbed environments.
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