The Use of SMAP-Reflectometry in Science Applications: Calibration and Capabilities

Abstract

The Soil Moisture Active Passive (SMAP) mission became one of the newest spaceborne Global Navigation Satellite System–Reflectometry (GNSS-R) missions collecting Global Positioning System (GPS) bistatic radar measurements when the band-pass center frequency of its radar receiver was switched to the GPS L2C band. SMAP-Reflectometry (SMAP-R) brings a set of unique capabilities, such as polarimetry and improved spatial resolution, that allow for the exploration of scientific applications that other GNSS-R missions cannot address. In order to leverage SMAP-R for scientific applications, a calibration must be performed to account for the characteristics of the SMAP radar receiver and each GPS transmitter. In this study, we analyze the unique characteristics of SMAP-R, as compared to other GNSS-R missions, and present a calibration method for the SMAP-R signals that enables the standardized use of these signals by the scientific community. There are two key calibration parameters that need to be corrected: The first is the GPS transmitted power and GPS antenna gain at the incidence angle of the measured reflections and the second is the convolution of the SMAP high gain antenna pattern and the glistening zone (Earth surface area from where GPS signals scatter). To account for the GPS transmitter variability, GPS instrument properties—transmitted power and antenna gain—are collocated with information collected from the CYclone Global Navigation Satellite System (CYGNSS) at SMAP’s range of incidence angles (37.3° to 42.7°). To account for the convolutional effect of the SMAP antenna gain, both the scattering area of the reflected GPS signal and the SMAP antenna footprint are mapped on the surface. We account for the size of the scattering area corresponding to each delay and Doppler bin of the SMAP-R measurements based off the SMAP antenna pattern, and normalize according to the size of a measurement representative to one obtained with an omnidirectional antenna. We have validated these calibration methods through an analysis of the coherency of the reflected signal over an extensive area of old sea ice having constant surface characteristics over a period of 3 months. By selecting a vicarious scattering surface with high coherency, we eliminated scene variability and complexity in order to avoid scene dependent aliases in the calibration. The calibration method reduced the dependence on the GPS transmitter power and gain from ~1.08 dB/dB to a residual error of about −0.2 dB/dB. Results also showed that the calibration method eliminates the effect of the high gain antenna filtering effect, thus reducing errors as high as 10 dB on angles furthest from SMAP’s constant 40° incidence angle.

The Polarimetric Sensitivity of SMAP-Reflectometry Signals to Crop Growth in the U.S. Corn Belt

“…To calibrate the SMAP-R DDMs, we applied the modified equation presented in [15]. The equation in [12] followed the CYclone Global Navigation Satellite System (CYGNSS) [23][24][25] mission calibration procedure presented in [26], but adds the filtering effect of the SMAP antenna pattern.…”

“…• B(τ, f d ) is the filtered effective surface scattering area. It is computed following the methodology described in [15], where the size of the area corresponding to each τ and f d bin filtered by the SMAP antenna is normalized to the size of the same τ and f d bin considering an omnidirectional antenna.…”

“…The calibration methodology developed in [15] and implemented in this study considers two corrections:…”

“…In August 2015, the SMAP mission started collecting GPS signals as they scatter off the Earth's surface [11][12][13][14][15]. These signals are measured by the SMAP radar receiver, whose band pass filter center frequency was switched to the GPS L2C band (1227.6 MHz).…”

“…The presence of vegetation also enlarges the spatial resolution as equally, it results in the scattering coming from a more extensive area. To compute the approximate spatial resolution of each measurement, we applied the methodology also explained in [15]. According to the results in [15], a threshold of 70% was selected, and the delay gathering the 70% of the power was transformed to an ellipse of constant delay on the surface (iso-delay line) [21].…”