Vol. 77
Latest Volume
All Volumes
PIERM 130 [2024] PIERM 129 [2024] PIERM 128 [2024] PIERM 127 [2024] PIERM 126 [2024] PIERM 125 [2024] PIERM 124 [2024] PIERM 123 [2024] PIERM 122 [2023] PIERM 121 [2023] PIERM 120 [2023] PIERM 119 [2023] PIERM 118 [2023] PIERM 117 [2023] PIERM 116 [2023] PIERM 115 [2023] PIERM 114 [2022] PIERM 113 [2022] PIERM 112 [2022] PIERM 111 [2022] PIERM 110 [2022] PIERM 109 [2022] PIERM 108 [2022] PIERM 107 [2022] PIERM 106 [2021] PIERM 105 [2021] PIERM 104 [2021] PIERM 103 [2021] PIERM 102 [2021] PIERM 101 [2021] PIERM 100 [2021] PIERM 99 [2021] PIERM 98 [2020] PIERM 97 [2020] PIERM 96 [2020] PIERM 95 [2020] PIERM 94 [2020] PIERM 93 [2020] PIERM 92 [2020] PIERM 91 [2020] PIERM 90 [2020] PIERM 89 [2020] PIERM 88 [2020] PIERM 87 [2019] PIERM 86 [2019] PIERM 85 [2019] PIERM 84 [2019] PIERM 83 [2019] PIERM 82 [2019] PIERM 81 [2019] PIERM 80 [2019] PIERM 79 [2019] PIERM 78 [2019] PIERM 77 [2019] PIERM 76 [2018] PIERM 75 [2018] PIERM 74 [2018] PIERM 73 [2018] PIERM 72 [2018] PIERM 71 [2018] PIERM 70 [2018] PIERM 69 [2018] PIERM 68 [2018] PIERM 67 [2018] PIERM 66 [2018] PIERM 65 [2018] PIERM 64 [2018] PIERM 63 [2018] PIERM 62 [2017] PIERM 61 [2017] PIERM 60 [2017] PIERM 59 [2017] PIERM 58 [2017] PIERM 57 [2017] PIERM 56 [2017] PIERM 55 [2017] PIERM 54 [2017] PIERM 53 [2017] PIERM 52 [2016] PIERM 51 [2016] PIERM 50 [2016] PIERM 49 [2016] PIERM 48 [2016] PIERM 47 [2016] PIERM 46 [2016] PIERM 45 [2016] PIERM 44 [2015] PIERM 43 [2015] PIERM 42 [2015] PIERM 41 [2015] PIERM 40 [2014] PIERM 39 [2014] PIERM 38 [2014] PIERM 37 [2014] PIERM 36 [2014] PIERM 35 [2014] PIERM 34 [2014] PIERM 33 [2013] PIERM 32 [2013] PIERM 31 [2013] PIERM 30 [2013] PIERM 29 [2013] PIERM 28 [2013] PIERM 27 [2012] PIERM 26 [2012] PIERM 25 [2012] PIERM 24 [2012] PIERM 23 [2012] PIERM 22 [2012] PIERM 21 [2011] PIERM 20 [2011] PIERM 19 [2011] PIERM 18 [2011] PIERM 17 [2011] PIERM 16 [2011] PIERM 14 [2010] PIERM 13 [2010] PIERM 12 [2010] PIERM 11 [2010] PIERM 10 [2009] PIERM 9 [2009] PIERM 8 [2009] PIERM 7 [2009] PIERM 6 [2009] PIERM 5 [2008] PIERM 4 [2008] PIERM 3 [2008] PIERM 2 [2008] PIERM 1 [2008]
2018-12-21
The Influence of the Terrain on Height Measurement Using the GNSS Interference Signal
By
Progress In Electromagnetics Research M, Vol. 77, 73-82, 2019
Abstract
Global Navigation Satellite System (GNSS) reflectometry is a promising technology used to estimate soil moisture, sea surface height, ice properties, etc. Interference signal technique is an important method to estimate these geophysical parameters. The effect of this method is closely related to the terrain and the receiving antenna placement. This study aims to investigate the effects of terrain and antenna placement on height measurement through simulation and field experiments. In this paper, we first simulated the interference signal in different types of terrain by parabolic equation method and analyzed the influence of terrain on the height measurement. Then we conducted three typical field experiments and processed experimental data. The simulated and experimental results indicate that the interference signal is affected by the terrain and the receiving antenna placement. Height measurement result is correct by both horizontal-looking and zenith-looking antenna when the ground is flat. However when the ground is not flat, the soil block near the receiving antenna leads to estimation errors. A more accurate estimation is obtained by using zenith-looking antenna to suppress the influence from the near terrain than horizontal-looking antenna. When a slope is near the receiving antenna, the signal with a high elevation may achieve an obvious interference effect if high elevation minus slope is equivalent to a low elevation. In this situation, the measurement height is the distance between the antenna and slope surface.
Citation
Nan Zhang, Songhua Yan, Wenwei Wang, and Jianya Gong, "The Influence of the Terrain on Height Measurement Using the GNSS Interference Signal," Progress In Electromagnetics Research M, Vol. 77, 73-82, 2019.
doi:10.2528/PIERM18101402
References

1. Li, W., et al. "First spaceborne phase altimetry over sea ice using TechDemoSat-1 GNSS-R signals," Geophysical Research Letters, Vol. 44, No. 16, 8369-8376, 2017.
doi:10.1002/2017GL074513

2. Han, M., et al. "A semi-empirical SNR model for soil moisture retrieval using GNSS SNR data," Remote Sensing, Vol. 10, No. 2, 280, 2018.
doi:10.3390/rs10020280

3. Yan, Q. and W. Huang, "Sea ice sensing from GNSS-R data using convolutional neural networks," IEEE Geoscience and Remote Sensing Letters, Vol. 99, 1-5, 2018.

4. Zhang, S., et al. "Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop," Hydrology and Earth System Sciences, Vol. 21, No. 9, 4767-4784, 2017.
doi:10.5194/hess-21-4767-2017

5. Yan, S., et al. "Feasibility of using signal strength indicator data to estimate soil moisture based on GNSS interference signal analysis," Remote Sensing Letters, Vol. 9, No. 1, 61-70, 2018.
doi:10.1080/2150704X.2017.1384587

6. Rodriguez-Alvarez, N., et al. "Snow thickness monitoring using GNSS measurements," IEEE Geoscience and Remote Sensing Letters, Vol. 9, No. 6, 1109-1113, 2012.
doi:10.1109/LGRS.2012.2190379

7. Arroyo, A. A., et al. "Dual-polarization GNSS-R interference pattern technique for soil moisture mapping," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 7, No. 5, 1533-1544, 2014.
doi:10.1109/JSTARS.2014.2320792

8. Zavorotny, V. U., et al. "A physical model for GPS multipath caused by land reflections: Toward bare soil moisture retrievals," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 3, No. 1, 100-110, 2010.
doi:10.1109/JSTARS.2009.2033608

9. Hannah, B. M., K. Kubik, and R. A. Walker, "Propagation modelling of GPS signals," IFP, 137, 1999.

10. Sevgi, L., C. Uluisik, and F. Akleman, "A matlab-based two-dimensional parabolic equation radiowave propagation package," IEEE Antennas and Propagation Magazine, Vol. 47, No. 4, 164-175, 2005.
doi:10.1109/MAP.2005.1589923

11. Hannah, B. M., Modelling and simulation of GPS multipath propagation, 2001.

12. Apaydin, G. and L. Sevgi, "The split-step-fourier and finite-element-based parabolic-equation propagation-prediction tools: Canonical tests, systematic comparisons, and calibration," IEEE Antennas and Propagation Magazine, Vol. 52, No. 3, 66-79, 2010.
doi:10.1109/MAP.2010.5586576

13. Pardo-Iguzquiza, E. and F. J. Rodríguez-Tovar, "Implemented Lomb-Scargle periodogram: A valuable tool for improving cyclostratigraphic research on unevenly sampled deep-sea stratigraphic sequences," Geo-Marine Letters, Vol. 31, No. 5-6, 537-545, 2011.
doi:10.1007/s00367-011-0247-x