基于星载气象雷达的非线性调频信号优化设计

随着天气观测、研究和规划的进展，气象雷达技术的开发工作取得了重大进展。脉冲压缩使新一代低成本、紧凑型星载天气雷达系统成为可能。为了抑制脉压带来的距离旁瓣，目标探测雷达通常采用基于幅度调制和失配滤波的方法，但由于其存在主瓣扩展和功率损失等缺点，不适用于气象观测。非线性调频（NLFM）信号可以调整其功率谱密度，在明显不降低信噪比的情况下提供较低的旁瓣输出。本文设计了一种新的波形优化框架。该框架通过多目标粒子群优化算法（MOPOS）构造了一种针对气象粒子目标的非线性调频（NLFM）脉冲压缩波形，实现了极低的距离旁瓣电平和较高的多普勒容限，可以显著地缓解非常有限的卫星峰值功率的限制和卫星平台运动导致的多普勒对系统影响。仿真实验结果表明：改进的非线性调频波形具有良好的性能。

Optimal design of nonlinear frequency modulation signal based on spaceborne weather radar

Advances in weather observation, research, and planning have led to significant progress in the development of weather radar technology. Pulse compression enables a new generation of low-cost, compact spaceborne weather radar systems. In order to suppress the range side lobes caused by pulse pressure, target detection radar usually uses methods based on amplitude modulation and mismatch filtering. However, due to its shortcomings such as main lobe expansion and power loss, it is not suitable for meteorological observations. Nonlinear Frequency Modulation (NLFM) signals can adjust the power spectral density to provide lower sidelobe output without significantly reducing the signal-to-noise ratio. In this paper, a new waveform optimization framework is designed. This framework constructs a nonlinear frequency modulation (NLFM) pulse compression waveform for meteorological particle targets through the multi-objective particle swarm optimization algorithm (MOPOS), achieving extremely low range side lobe levels and high Doppler tolerance. The very limited satellite peak power limitations and Doppler effects on the system caused by satellite platform motion can be significantly mitigated. The simulation experiment results show that the improved nonlinear FM waveform has good performance.