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Simulation of Return Signal Spectrum of Wind Profile Radar
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摘要: 利用2008年1—9月北京延庆地区对流层CFL-08风廓线雷达和2009年7—12月广东东莞地区边界层CFL-03风廓线雷达晴空大气探测资料，对大气返回信号功率谱密度分布及雷达系统噪声幅度统计特征进行分析。基于大气返回信号的谱分布符合高斯分布的统计结果，采用高斯模型对大气返回信号谱进行模拟；雷达系统噪声是白噪声，其谱线幅度的统计特征呈高斯分布，在此基础上，通过生成高斯分布随机函数对雷达探测输出信号进行信号谱分布的仿真模拟，并采用雷达探测信号的谱参数对仿真模拟进行检验，效果较好。该文应用仿真模拟的数据，对风廓线雷达信息处理方法及其处理精度进行了初步试验和分析。Abstract: Wind profile radar uses coherent accumulation technology to improve sounding sensitivity, which can obtain high resolution spectral data and entire spectrum information of return signal compared to the Doppler weather radar, so it is applied in precipitation, cloud body structure detection and research aspects widely. The concrete implementing schemes of noise signal processing and spectrum parameters extraction leads to the differences in ability of extraction the useful signal from atmosphere return signal and estimation accuracy, so the method of signal processing and information extraction is the key technologies of signal process.The simulation of radar return signal is an important method to evaluate ability of extracted information. Based on the clear sky atmospheric detection data of different types of wind profile radars which are placed at Yanqing of Beijing and Dongguan of Guangdong, both the power spectral density distribution of atmospheric return signals and the statistical characteristics of radar system noise amplitude are analyzed. The distribution of atmospheric return signal is Gaussian distribution. Radar system noise is white noise, the noise amplitude statistical characteristics presents Gaussian distribution. Based on this, radar output signal is simulated by Gaussian random function generating method. Comparison is conducted between the detected and simulated signal spectrum parameters 1000 times, showing good accordance, the average relative error of the average signal power for CFL-08 wind profile radar is 2%, the error of average Doppler velocity is 3%, the average relative error of spectral width is 1%; the average relative error of the average signal power is 3% for CFL-03 wind profile radar, the error of average Doppler velocity of which is 2%, and the average relative error of spectral width of which is 2%. Furthermore, preliminary test and analysis for wind profile radar information processing method and its processing precision are carried out by using the simulation data.
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Key words:
- wind profile radar;
- atmospheric return signal;
- signal simulation
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图 1 大气返回信号功率谱密度谱分布和谱参数示意图
Fig. 1 Atmospheric return signal power spectral density distribution and spectrum parameters
图 2 CFL-08风廓线雷达 (a) 和CFL-03风廓线雷达 (b)5个距离库噪声特性统计
Fig. 2 Noise characteristics of five range bins of CFL-08(a) and CFL-03(b) wind profile radars
图 3 CFL-08风廓线雷达噪声模拟以及谱线幅度分布
(a) CFL-08风廓线雷达仿真噪声, (b) 噪声高斯拟合特性统计
Fig. 3 Noise simulation and spectrum amplitude distribution
(a) simulation of noise of CFL-08 wind profile radar, (b) spectrum amplitude distribution
图 4 CFL-03风廓线雷达噪声模拟以及谱线幅度分布
(a) CFL-03风廓线雷达仿真噪声，(b) 噪声高斯拟合特性统计
Fig. 4 Noise simulation and spectrum amplitude distribution of CFL-03 wind profile radar
(a) simulation of noise of CFL-03 wind profile radar, (b) spectrum amplitude distribution
图 5 晴空大气返回信号模拟 (a) 实测功率谱，(b) 模拟功率谱
Fig. 5 Simulation of return signal of the clear air
(a) the power spectrum of observation, (b) the power spectrum of simulation
图 6 风廓线雷达大气返回信号模拟流程图
Fig. 6 Flow chart of wind profile radar atmospheric return simulation signal
图 7 噪声电平估算误差与抽样谱线数关系图
Fig. 7 Relations between estimation relative error of noise level and numbers of spectral lines
图 8 谱宽计算误差随信噪比的变化情况
Fig. 8 Estimation relative error of spectral width with different SNR
图 9 随信噪比不同半功率点计算谱宽误差
Fig. 9 Relative error of spectral width with different SNR calculated by the method of half-power point
表 1 风廓线雷达系统参数表
Table 1 System parameters of wind profile radar
参数 对流层Ⅱ型 (CFL-08)
风廓线雷达边界层 (CFL-03)
风廓线雷达波长/mm 674 227 探测模式 低 高 低 高 脉冲宽度/μs 0.8 4 1 3 噪声系数/dB 2 2 1.8 1.8 谱变换数 256 512 256 512 谱平均数 6 12 6 6 相干积分次数 200 50 100 60 距离库长/m 120 240 50 100 Nyquist速度/(m·s-1) ±16.7 ±33.3 ±7.8 ±15.7 最小速度间隔/(m·s-1) 0.13 0.13 0.06 0.06 
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