Soil moisture algorithm testing of interference signal inversion with GNSS linearly polarized antenna
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摘要:
利用全球导航卫星系统干涉信号（GNSS-IR）测量土壤湿度已成为热门的研究课题。搭载低成本线性极化天线的智能手机可以方便快捷采集干涉信号信噪比（SNR）。分别仿真垂直和水平线性极化天线采集的GNSS干涉信号，给出2种极化方式下干涉信号SNR波形和反射率随卫星高度角变化的结果。对于垂直极化分量，电磁波会在入射角65°～85°左右时发生全透射，导致干涉信号振荡效果消失，而水平极化不存在该现象。同时，分别仿真右旋圆极化(RHCP)直射和左旋圆极化(LHCP)反射天线采集的GNSS信号，并计算直反射信号的幅值比。在仿真基础上分别利用不同极化天线进行实验，结果表明：采用线性极化天线采集的GNSS干涉信号振荡效果几乎不受卫星高度角的限制，可以为土壤湿度反演提供更多的有效数据，并且反演得到的土壤湿度与同位数据具有良好的一致性，两者的相关性达到0.95。使用搭载圆极化天线的双通道接收机采集北斗系统卫星数据进行对比，相关性达到0.91。对于不同的设备，智能手机采集的GNSS数据占用空间相对比于双通道接收机降低1%，且反演结果相关性接近，由于干涉信号提取直反射信号需要一定的振荡周期，故反演结果的时间分辨率要低于双通道接收机。
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关键词:
- 全球导航卫星系统干涉信号 /
- 线性极化 /
- 信号幅值比 /
- 土壤湿度 /
- 圆极化
Abstract:Using global navigation satellite system Interferometric reflectometry (GNSS-IR) to measure soil moisture has become a prominent research topic. Smartphones equipped with low-cost linearly polarized antennas can easily and quickly acquire the signal noise ratio (SNR) of interference signals. The GNSS interference signals collected by the vertical and horizontal linearly polarized antennas are simulated separately, with the results of the SNR waveform and reflectivity of the interference signals changing with the satellite altitude angle under the two polarization modes. For the vertically polarized component, the electromagnetic wave is totally transmitted at the incident angle of about 65～85°, resulting in the disappearance of the oscillation effect of the interference signal. However, this phenomenon does not exist in the horizontal polarization. Then, the GNSS signals collected by the right-handed circle polarized (RHCP) direct and left-handed circle polarized (LHCP) reflective antennas are simulated separately, and the amplitude ratio of the direct reflection signal is calculated. Based on the simulation, experiments were carried out with different polarized antennas. Results show that the oscillation effect of the GNSS interference signal collected by the linearly polarized antenna is barely limited by the satellite altitude angle, providing more effective data for soil moisture inversion. The soil moisture obtained by the inversion is in good agreement with that of the isotopic data, and their correlation reaches 0.95. A dual-channel receiver equipped with a circularly polarized antenna is used to collect Beidou satellite data for comparison, revealing a correlation of 0.91. For different devices, the occupied space of the GNSS data collected by the smartphone is reduced to 1% compared with that of the dual-channel receiver, and the correlation of the inversion results is close. Since the interference signal needs a certain oscillation period to extract the direct reflection signal, the inversion results show a lower time resolution than that of a dual-channel receiver.
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图 3 MEO 卫星直反射信号原始 SNR 和趋势
Figure 3. Original SNR and its trend of direct reflection signal from MEO satellite
图 5 GEO 卫星直反射信号原始 SNR 和直反射幅值比
Figure 5. Original SNR of GEO satellite direct reflection signal, and direct reflection amplitude ratio
图 7 智能手机反演土壤湿度算法流程图
Figure 7. Flowchart of algorithm for soil moisture inversion by smartphone
图 10 EMD分解后的本征模式函数及对应的LSP谱估计结果
Figure 10. Intrinsic mode function EMD, and the corresponding LSP spectral estimation results
图 11 反演结果与同位数据趋势对比
Figure 11. Comparison of inversion results with in-suit data trends
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