IEEE Geoscience and Remote Sensing Letters | 2019

A Random Model and Simulation for Generating GNSS Ocean Reflected Signals

 
 
 
 
 
 
 

Abstract


In recent years, Global Navigation Satellite System Reflectometry (GNSS-R) has been studied as a new technique for ocean remote sensing, and the simulation of GNSS-R signals has played a very important role. In this letter, a random model for ocean reflected signal simulation of GNSS-R is presented to provide a useful method for generating reflected signals. The study is conducted by means of a superimposed result of multiple random reflected signals based on a previous fixed model. Reflected signals are randomly selected with different delay bins and different random amplitudes. To generate GNSS-R signals, a software GNSS-R simulator based on the proposed random model is developed. A receiver is also used to process the simulated signals to demonstrate the availability of the proposed model and developed simulator. The analysis shows good agreement between the produced and theoretical delay waveforms with the correlation coefficient of 0.998. To further verify the significance of the random model, the simulated reflected signals are compared with the airborne experimental data collected in Yantai, China. The comparative results show that the random model has better statistical and stochastic characteristics.

Volume 16
Pages 1036-1040
DOI 10.1109/LGRS.2018.2890011
Language English
Journal IEEE Geoscience and Remote Sensing Letters

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