Abstract

ABSTRACT The global navigation satellite system interferometric reflectometry (GNSS-IR) technique for collecting corn height has the limitation of not accounting for changes in the corn canopy reflector. A model that uses the corn canopy reflection coefficient to account for changes in the canopy’s reflector and the power attenuation of the signal reflected by the soil surface is proposed. This letter proposes a method to solve the overcompensation problem of traditional GNSS-IR vegetation height measurement. Considering the decrease in GNSS signal penetration depth and the upward shift of the actual reflecting surface caused by changes in corn leaf water content (LWC), this letter provides a calibration model for the GNSS-IR corn height measurement. The GNSS signals reflected from the corn canopy were separated using empirical mode decomposition (EMD), and the height measurement was then calibrated using the directed and reflected signal ratios. The results of the experiments show that the model proposed in this letter can effectively improve the accuracy of corn height measurement, and the root mean square error (RMSE) is reduced to 0.17 m . Compared with the current study, the model proposed in this study reduces the influence of the actual reflective surface variation of the corn canopy on the height measurement using GNSS-IR.

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