KEYWORDS: Particles, Radar, Particle swarm optimization, Signal to noise ratio, Fluctuations and noise, Doppler effect, Detection and tracking algorithms, Computer simulations, Signal processing, Motion models
Signals from Costas-coded frequency-hopped radars exhibit an approximate “thumbtack” ambiguity function and prevent range-Doppler coupling. Therefore, these radars provide high-resolution range and velocity performance. However, the radar signals are highly sensitive to Doppler frequency shifts, and peak divergence arises due to Doppler mismatches when the target is moving. To solve these problems, we thoroughly analyze the effect of velocity on range profiles. Then, we propose a method of motion compensation based on particle swarm optimization using improved waveform entropy as the objective function. The target velocity is accurately determined through an iterative search. After motion compensation, the focus of the target range profile is notably improved. Simulation results confirm that the proposed method has a low computational complexity and retrieves accurate velocity estimates even under low signal-to-noise ratio and high target speeds, suggesting its adaptability and robustness for real-world applications.
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