星载W波段多普勒雷达云内大气风场探测信号仿真研究
doi: 10.11728/cjss2025.02.2024-0189 cstr: 32142.14.cjss.2024-0189
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叶晗 女, 1999年出生于安徽省黄山市, 现为中国科学院大学国家空间科学中心硕士研究生. 主要从事微波遥感探测技术等方面的研究. E-mail: yehan22@mails.ucas.ac.cn -
董晓龙 男, 1969年出生于陕西省渭南市, 现为中国科学院大学国家空间科学中心研究员, 博士生导师. 主要从事新型微波遥感探测与成像及微波遥感信息获取的方法与技术研究. E-mail: dongxiaolong@mirslab.cn
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Simulation Study on the Detection Signal of Atmospheric Wind Field within Clouds Using Spaceborne W-band Doppler Radar
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摘要: 全球三维大气风场探测对提升数值天气预报精度、增强气象灾害预警能力及保障航空航天安全具有关键作用. 本文建立了一套星载W波段多普勒雷达云内大气风场探测信号仿真系统, 通过输入实际场景的大气廓线数据, 仿真雷达回波信号, 进而利用回波信号估计径向风速, 并分析了信噪比和脉冲累积数对径向风速估计精度的影响. 结果表明, 对于星载W波段多普勒雷达, 当极化脉冲间隔不大于20 μs时, 极化分集脉冲对技术可实现0～40 m·s–1的风速探测范围, 有效获取云内高风速产品; 径向风速估计精度随脉冲累积数的增加和信噪比的增大而提升; 在本文雷达系统指标条件下, 当信噪比为0 dB, 脉冲累积数为64时, 径向风速估计精度为1.34 m·s–1, 能够满足数值天气预报2 m·s–1的测风精度要求.Abstract: The detection of the global three-dimensional atmospheric wind field plays a crucial role in improving the accuracy of numerical weather prediction, enhancing the ability of meteorological disaster early warning, and ensuring the safety of aerospace activities. At present, the main methods for detecting the atmospheric wind field include ground-based wind profile radars, spaceborne Doppler lidars, and millimeter-wave cloud radars, etc. Ground-based wind profile radars are difficult to deploy in oceanic and remote terrestrial areas, making it impossible to achieve global networked observations. Spaceborne Doppler Lidars can accurately detect the atmospheric wind field in clear-sky regions, but they are unable to obtain data on the wind field within clouds. Compared with lasers, millimeter waves have better penetration capabilities and possess unique advantages in the detection of the wind field within clouds. However, existing spaceborne millimeter-wave cloud radars cannot provide information on the horizontal wind field. Spaceborne millimeter-wave cloud radars with a conical scanning system can achieve the detection of the three-dimensional atmospheric wind field within clouds. In this paper, a signal simulation system for the atmospheric wind field detection within clouds by a spaceborne W-band Doppler radar was established, which provided a theoretical basis and technical reference for in-cloud wind field detection. The required elements of the signal simulation system include atmospheric profile data, reflectivity factor, attenuation coefficient, radar system parameters, spaceborne observation geometry, echo signal amplitude, echo signal frequency, echo signal phase, echo signals, and radial velocity. The system processes actual cloud profile data and simulates radar echo signals to estimate the radial wind speed. The effects of Signal-to-Noise Ratio (SNR) and pulse-pair cumulative number on the estimation accuracy of radial wind speed were systematically analyzed. The results show that for a spaceborne W-band Doppler radar, when the polarization pulse interval is not greater than 20 μs, the polarization diversity pulse-pair technique can achieve a wind speed detection range of 0 to 40 m·s–1, effectively obtaining high wind speed products within clouds. The estimation accuracy of radial wind velocity is positively correlated with the increase in SNR and the number of pulse-pair accumulations. Under the index conditions of the radar system described in this paper, when the SNR is 0 dB and the number of pulse-pair accumulations is 64, the estimation accuracy of the radial wind speed is 1.34 m·s–1, which can meet the wind measurement accuracy requirement of 2 m·s–1 for numerical weather prediction.
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图 2 云水反射率因子随云液水含量的变化
Figure 2. Variation of cloud water reflectivity factor with cloud liquid water content
图 3 云冰反射率因子随云冰水含量的变化
Figure 3. Variation of cloud ice reflectivity factor with cloud ice water content
图 4 云冰衰减系数随云冰水含量的变化
Figure 4. Variation of cloud ice attenuation coefficient with cloud ice water content
图 8 2019－2023年全球0～20 km高度上月平均水平风速
Figure 8. Global average monthly horizontal wind at 0～20 km height during 2019－2023
图 9 云反射率因子. (a)整体云场景, (b)局部放大图
Figure 9. Cloud reflectivity factor. (a) Full cloud scene, (b) enlarged view of the highlighted region
图 11 (a)整体云场景的径向风速误差, (b) 径向风速误差的局部放大, (c) 整体云场景的信噪比, (d) 信噪比的局部放大
Figure 11. (a) Radial wind speed error for full cloud scene, (b) enlarged view of the radial wind speed error for the highlighted region, (c) Signal-to-Noise ratio for full cloud scene, (d) enlarged view of the Signal-to-Noise ratio for highlighted region
图 10 (a)整体云场景的理论径向风速, (b)理论径向风速的局部放大, (c) 整体云场景的估计径向风速, (d)估计径向风速的局部放大
Figure 10. (a) Theoretical radial wind speed for full cloud scene, (b) enlarged view of the theoretical radial wind speed for the highlighted region, (c) estimated radial wind speed for full cloud scene, (d) enlarged view of the estimated radial wind speed for the highlighted region
图 12 径向风速估计误差随信噪比SNR和脉冲累积数M的变化
Figure 12. Variation of radial wind speed estimation error with Signal-to-Noise ratio and pulse accumulation M
图 13 径向风速估计误差的统计分析结果随信噪比SNR和脉冲累积数M的变化
Figure 13. Statistical analysis results of radial wind speed estimation error with respect to variations in Signal-to-Noise ratio and pulse accumulation M
表 1 星载W波段多普勒雷达系统参数
Table 1. System parameters of spaceborne W-band Doppler radar
参数及指标 数值 工作频率/ GHz 94 扫描方式 圆锥扫描 单程–3 dB波束宽度/(°) 0.08 天线尺寸/ m 3 天线增益/ dB 66.3 极化方式 H/V 发射峰值功率/ W 1800 脉冲宽度/ μs 3.3 脉冲重复频率/ kHz 4 信号形式 正交极化脉冲 极化脉冲时间间隔/ μs 20 系统损耗/ dB 2.5 接收机噪声系数/ dB 5 接收机带宽/ MHz 0.36 
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