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Soil moisture estimation based on BeiDou B1 interference signal analysis

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Abstract

BeiDou Navigation Satellite System reflectometry (BDS-R) is an emerging area of BD (BeiDou) applications that uses multipath reflected signals in microwave remote sensing. Soil moisture estimation is one of the potential important applications of BDS-R. This study aims to investigate the feasibility of soil moisture estimation based on BD B1 band interference signals, which are composed of direct and reflected BD signals and can be readily captured using low-cost commercial BDS receivers. In this paper, a theoretical background for soil estimation from interference signals was introduced, and an analysis of field experimental data was conducted. First, a cosine model for the interference signal power was built, and a non-uniform power spectrum analysis was performed on the received interference signals to determine its main frequency. Then, a least squares curve fitting was applied on the interference signal power to extract its phase. The relationship between the soil moisture and the phase was then determined. Two months of experimental data were collected at BaoXie, Wuhan and analyzed for further inversion. Experimental results show that the phase of the interference signals increases with the increase of soil moisture. The correlation coefficient between the phase and the in-situ soil moisture value is approximately 0.8. Finally, the relationship between the phase and soil moisture is employed to estimate soil moisture. Results show that using BDS-R to measure soil moisture is feasible, which demonstrates a great potential of new application of the BD system.

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References

  • Blu T, Thevenaz P, Unser M. 2004. Linear interpolation revitalized. IEEE T Image Process, 13: 710–719

    Article  Google Scholar 

  • Chew C C, Small E E, Larson K M, Zavorotny V U. 2014. Effects of near-surface soil moisture on GPS SNR data: Development of a retrieval algorithm for soil moisture. IEEE Trans Geosci Remote Sens, 52: 537–543

    Article  Google Scholar 

  • China Satellite Navigation Office. 2013. BeiDou Navigation Satellite System Open Service Performance Standard (Version 1.0)

  • Guo J, Zhao Q L, Guo X, Liu X L, Liu J N, Zhou Q. 2015. Quality assessment of onboard GPS receiver and its combination with DORIS and SLR for Haiyang 2A precise orbit determination. Sci China Earth Sci, 58: 138–150

    Article  Google Scholar 

  • Guo P, Shi J, Du J, Liu Q. 2012. A new method for estimation of bare surface soil moisture with L-band radiometer. In: Geoscience and Remote Sensing Symposium (IGARSS). IEEE International. 658–661

    Google Scholar 

  • Hajj G A, Zuffada C. 2003. Theoretical description of a bistatic system for ocean altimetry using the GPS signal. Radio Sci, 38: 1089

    Article  Google Scholar 

  • He L N, Ge M R, Wang J X, Wickert J, Schuh H. 2013. Experimental study on the precise orbit determination of the BeiDou navigation satellite system. Sensors, 13: 2911–2928

    Article  Google Scholar 

  • ITU C I R C. 1986. Report 1008. Reflection From the Surface of the Earth

  • Jacobson M D. 2010. Snow-covered lake ice in GPS multipath reception—Theory and measurement. Adv Space Res, 46: 221–227

    Article  Google Scholar 

  • Jin S G, Feng G P, Gleason S. 2011. Remote sensing using GNSS signals: Current status and future directions. Adv Space Res, 47: 1645–1653

    Article  Google Scholar 

  • Larson K M, Small E E, Gutmann E, Bilich A, Axelrad P, Braun J. 2008. Using GPS multipath to measure soil moisture fluctuations: Initial results. GPS Solut, 12: 173–177

    Article  Google Scholar 

  • Larson K M, Braun J J, Small E E, Zavorotny V U, Gutmann E D, Bilich A L. 2010. GPS multipath and its relation to near-surface soil moisture content. IEEE J Sel Top Appl Earth Observations Remote Sens, 3: 91–99

    Article  Google Scholar 

  • Li W Q, Yang D K, Fabra F, Cao Y C, Yang W. 2014. Typhoon Wind Speed Observation Utilizing Reflected Signals from Bei Dou GEO Satellites. In: China Satellite Navigation Conference (CSNC) 2014 Proceedings. Vol I. 191–200

    Chapter  Google Scholar 

  • Mitra S K. 2005. Digital Signal Processing: A Computer-Based Approach. New York: McGraw-Hill Higher Education, 4. 1558–1559

    Google Scholar 

  • Montenbruck O, Hauschild A, Steigenberger P, Hugentobler U, Teunissen P, Nakamura S. 2013. Initial assessment of the COMPASS/BeiDou-2 regional navigation satellite system. GPS Solut, 17: 211–222

    Article  Google Scholar 

  • Nievinski F G, Larson K M. 2014. Forward modeling of GPS multipath for near-surface reflectometry and positioning applications. GPS Solut, 18: 309–322

    Article  Google Scholar 

  • Njoku E G, Entekhabi D. 1996. Passive microwave remote sensing of soil moisture. J Hydrol, 184: 101–129

    Article  Google Scholar 

  • Oppenheim A V, Schafer R W, Buck J R. 1989. Discrete-Time Signal Processing. Upper Saddle River: Prentice Hall

    Google Scholar 

  • Pardo-Iguzquiza E, Rodríguez-Tovar F J. 2011. Implemented Lomb-Scargle periodogram: A valuable tool for improving cyclostratigraphic research on unevenly sampled deep-sea stratigraphic sequences. Geo-Mar Lett, 31: 537–545

    Article  Google Scholar 

  • Qu B, Wei J L, Zhang S N, Bi L. 2013. Analysis of multipath and CW interference effects on GNSS receivers with EMLP discriminator. Commun Network, 5: 80–85

    Article  Google Scholar 

  • Shi C, Zhao Q L, Li M, Tang W M, Hu Z G, Lou Y D, Zhang H P, Niu X J, Liu J N. 2012. Precise orbit determination of Beidou Satellites with precise positioning. Sci China Earth Sci, 55: 1079–1086

    Article  Google Scholar 

  • Steven M K. 1993. Fundamentals of Statistical Signal Processing. Upper Saddle River: Prentice Hall. 83–182

    Google Scholar 

  • Tsang L, Kong J A, Ding K H. 2000. Scattering of Electromagnetic Waves. Vol 1. Theory and Applications. New York: Wiley Interscience

    Book  Google Scholar 

  • Wang X Y, Wang X L, Dai Z Q, Ke F Y, Cao Y C, Wang F F, Song L C. 2014. Tropospheric wet refractivity tomography based on the BeiDou satellite system. Adv Atmos Sci, 31: 355–362

    Article  Google Scholar 

  • Xu A G, Xu Z Q, Ge M R, Xu X C, Zhu H Z, Sui X. 2013. Estimating zenith tropospheric delays from BeiDou navigation satellite system observations. Sensors, 13: 4514–4526

    Article  Google Scholar 

  • Yan S H, Gong J Y, Li H W. 2010. Research on soil moisture sensor nodes and their placement in distributed sensor networks. Hong Kong: 2010 Ninth International Symposium on Distributed Computing and Applications to Business Engineering and Science (DCABES). 165–168

    Google Scholar 

  • Yan S H, Li Z Y, Yu K G, Zhang K F. 2014. GPS-R L1 interference signal processing for soil moisture estimation: An experimental study. Eurasip J Adv Signal Process, 2014: 107

    Article  Google Scholar 

  • Yang Y X, Li J L, Wang A B, Xu J Y, He H B, Guo H R, Shen J F, Dai X. 2014. Preliminary assessment of the navigation and positioning performance of BeiDou regional navigation satellite system. Sci China Earth Sci, 57: 144–152

    Article  Google Scholar 

  • Zavorotny V U, Larson K M, Braun J J, Small E E, Gutmann E D, Bilich A L. 2010. A physical model for GPS multipath caused by land reflections: Toward bare soil moisture retrievals. IEEE J Sel Top Appl Earth Observations Remote Sens, 3: 100–110

    Article  Google Scholar 

  • Zhang E H, Cao Y C, Zhu B. 2013. Developing of Beidou radiosonde system and analysis on its wind measuring performance. J Appl Meteorol Sci, 24: 464–471

    Google Scholar 

  • Zhang T, Zhang L X, Jiang L M, Zhao S J, Zhao T J, Li Y Q. 2012. Effects of spatial distribution of soil parameters on soil moisture retrieval from passive microwave remote sensing. Sci China Earth Sci, 55: 1313–1322

    Article  Google Scholar 

  • Zhang X, Chen N, Chen Z. 2014. Spatial pattern and temporal variation law-based multi-sensor collaboration method for improving regional soil moisture monitoring capabilities. Remote Sens, 6: 12309–12333

    Article  Google Scholar 

Download references

Acknowledgements

The work was supported by the National Natural Science Foundation of China (Grant No. 41571420) and LIESMARS Special Research Funding.

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Authors and Affiliations

  1. School of Electronic Information, Wuhan University, Wuhan, 430079, China

    SongHua Yan & Fen Zhao

  2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China

    NengCheng Chen & JianYa Gong

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  1. SongHua Yan
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  2. Fen Zhao
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  3. NengCheng Chen
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  4. JianYa Gong
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Correspondence to SongHua Yan.

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Yan, S., Zhao, F., Chen, N. et al. Soil moisture estimation based on BeiDou B1 interference signal analysis. Sci. China Earth Sci. 59, 2427–2440 (2016). https://doi.org/10.1007/s11430-015-0013-7

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  • DOI: https://doi.org/10.1007/s11430-015-0013-7

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