GNSS Reflectometry for land surface monitoring and buried object detection

Global Navigation Satellite System Reflectometry (GNSS-R) is attracting growing interest nowadays for several remote sensing applications. As a bistatic radar, the transmitter and the receiver are not co-located and in the special case of GNSS-R, the GNSS satellites are acting as transmitters and the receiver can be mounted either in a static position or onboard a aircraft or low orbit satellite. Various information about the surface from where the GNSS signals are reflected or scattered can be extracted by means of reflected signal strength, code delay, carrier phase delay, interference with direct GNSS signals and so on. Possible applications cover soil moisture retrieval, ice topography and thickness detection, snow depth estimation, vegetation coverage, sea state monitoring such as sea wind and surface roughness, sea salinity… In this work, soil moisture retrieval was mostly focused on. Hardware including antennas and receivers was studied and designed. Our first strategy of soil moisture retrieval is to apply a single Left Hand Circular Polarization (LHCP) antenna for reflected signal reception. Therefore multiple types of antennas such as the helix antenna, the patch antenna and several commercial antennas were designed, simulated or tested in the anechoic chamber. Two receiver solutions were used in our group and both of them apply the SiGe GPS frontend. The first solution is a PC based one: the collection and store of the raw incoming reflected GPS signals were done by the NGrab software (designed by NAVSAS Group of Politecnico di Torino) installed in a standard PC. The other solution was developed in our group and it is operated by a single Hackberry board, which consists of power supply, storage subsystem and customized Linux Debian operating system. The light weight and small size enable this compact receiver to perform flight measurement onboard UAVs. Both of the above mentioned receivers only store raw sampled data and no real time signal processing is performed on board. Post processing is done by Matlab program which makes correlations in both time and frequency domain with incoming signals using the local generated GPS C/A code replica. The so-called Delay Doppler Map (DDM) is therefore generated through this correlation. Signal to Noise Ratio (SNR) can be calculated through Delay Waveform (DW) which is extracted from DDM at the Doppler frequency where the correlation peak exists. Received signal power can be obtained knowing the noise power which is given in a standard equation. In order to better plan a static measurement and to georeference specular points on the surface, programs for georeferencing specular points on either Google Maps or an x-y plane centered at the receiver position were developed. Fly dynamics in terms of roll, pitch and yaw influencing the antenna gain due to the variation of incident angles were also studied in order to compensate the gain to the received signal. Two soil moisture retrieval algorithms were derived corresponding to two receiving schemes. The first one is for the receiving of only LHCP reflected signals. In this case, the surface is assumed to be perfectly smooth and the received signal is seen to consist of only coherent component caused by specular reflection. Dielectric constant can be retrieved from the processed SNR. Two measurement campaigns were carried out using this single LHCP system. The first campaign is a flight measurement overflown a big portion of rice fields when most of the fields were flooded. It was a test measurement on the SNR sensitivity to water/no-water surfaces and an attempt of dielectric constant retrieval was also performed. SNR showed good sensitivity to the surface water content and dielectric constant was also checked to be reasonable. The second campaign is in static positions and it includes two experiments. This campaign initially aimed at testing the sensitivity of the compact receiver to different surface moisture. Results of both SNR and retrieved dielectric constant showed to be coherent with the surface moisture changes. The other retrieval algorithm is for the receiving of both LHCP and RHCP reflected signals concurrently. The cross polarization power ratio (LHCP/RHCP) is believed to be independent of surface roughness by several previous studies and this idea was also verified during the deriving process for either specular reflection case (only coherent component) or diffuse scattering condition (incoherent component). For diffuse scattering, three well known models were applied which are the Kirchhoff Approximation in stationary-phase approximation (Kirchhoff Geometrical Optics, KGO), Kirchhoff Approximation in Physical Optics Approximation (KPO) and Small Perturbation Method (SPM). These three models cover different roughness surfaces from very rough (KGO) to slightly rough surfaces (SPM). All the derived results of cross polarization ratio for the three models were verified to be independent of surface properties and depend on only dielectric constant of soil and incident angle. A new application of GNSS-R technique for the possibility of detection of buried objects was firstly investigated by our group. It has the potential use for man-made mines detection in the military field. Two measurement campaigns were carried out and the variation of the SNR level due to the presence of a metallic object was investigated. The first measurement campaign was performed in a static condition on a sandy terrain to check the functionality of the system. And the presence of the metallic object was detected also in the case of wet terrain. In the second measurement campaign, the antenna was moving along a given path and the possibility of detecting the object dimensions was highlighted. The results show the possibility of adopting this technique on board a remotely controlled UAV for metal object and even its dimension detection. A measurement of snow depth attempting to relate it to reflected LHCP SNR is briefly presented and discussed in Chapter 7

Remote Sensing in Land Applications by Using GNSS-Reflectometry

Global navigation satellite system-reflectometry (GNSS-R) as an efficient tool for remote sensing has gained increasing interests in the last two decades, due to its unique characteristics. It uses GNSS signals as sources of opportunity, providing precise, continuous, all-weather, and 24 hours’ detections, which play a key role in many land applications. The fundamental theoretical part of GNSS-R technique is examined at first. Then, GNSS-R methodologies applied in the soil moisture content, vegetation biomass sensing, and altimetry applications are also detailed. One retrieval method uses only RH (right-hand) reflected data. Another retrieval method for soil moisture content (SMC) aimed to calibrate the measurement by using water reflections, based on the bistatic equations with LH (left-hand) reflected and RH direct signals. The other method for SMC retrieval is related to the polarimetric ratio (PR), the ratio of LH/RH reflected signals can reveal the fluctuations of the SMC. Another vital parameter vegetation biomass was observed by using the variation of reflectivity of the LH and RH reflected components. Finally, the C/A code method was used for exploring the possibility to the altimetry estimation. The features of GNSS-R technique made it a promising remote sensing technique in hydrology, climatology carbon cycles, and other potential applications

Explicit Complex Solutions to the Fresnel Coefficients

Global Navigation Satellite System Reflectometry (GNSS-R) is a microwave remote sensing technique which can be used to derive information about the composition or the properties of ground surfaces. The received power of the GPS signals reflected by the ground is proportional to the magnitude of the reflection Fresnel coefficients In particular, it depends on the incidence angle $\theta$ and on the ground's permittivity $\epsilon$. The knowledge of $\epsilon$ is important for determining various conditions and characteristics of the surface (e.g., soil moisture, salinity, freeze-thaw transitions). The value of $\epsilon$ can be found from the Fresnel reflection coefficients, for a given incidence angle $\theta$. For dispersive media, $\epsilon$ is a complex quantity; we present explicit formulas, which express both $\Re(\varepsilon)$ and $\Im(\varepsilon)$ as a function of the incident angle $\theta$ and of the magnitude of the linearly polarized Fresnel reflection coefficients

Detection of buried objects using reflected GNSS signals

The use of reflected Global Navigation Satellite System (GNSS) signals for sensing the Earth has been growing rapidly in recent years. This technique is founded on the basic principle of detecting GNSS signals after they have been reflected off the Earth's surface and using them to determine the properties of the reflecting surface remotely. This is the so-called GNSS reflectometry (GNSS-R) technique. In this paper, a new application regarding the detection of metallic buried objects is analyzed and it is validated through several experimental campaigns. Although the penetration depth of GNSS signals into the ground is not optimal and depends on the soil moisture, GNSS signals can likely interact approximately with the first 10 cm of the ground and therefore can be reflected back by any metallic object buried on the first terrain layer. A very light and low-cost GNSS receiver prototype based on a software-defined radio approach was developed. This receiver can be used as a payload on board small drones or unmanned aerial systems to detect metallic objects (mines or other explosive devices). A signal processing tool based on an open-loop GNSS signal acquisition strategy was developed. The results of two experiments which show the possibility of using GNSS-R signals to detect buried metallic objects and to provide an estimate of their dimensions are discussed

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

GNSS-R SIGNAL STRENGTH SENSITIVITY TO SOIL MOISTURE

GNSS Reflectometry is an emerging technique used for the remote sensing of soil surface. In this work, a bi-static radar equation method was implemented for remote sensing of soil. A portable GNSS-R receiver was used during various in situ measurements campaign. Left Hand Circularly Polarized (LH) reflected signals were processed to extract Delay Doppler Maps (DDMs) and corresponding Delay Waveforms (DWs) by means of an open-loop approach. Signal to Noise Ratios (SNRs) time series were estimated from non-coherent integrated Delay Waveforms. The signal strength sensitivity to different soil moisture levels, i.e. different SNRs levels in input, was verifie

A Fully Software GNSS-R Receiver for Soil Dielectric Constant Monitoring

GNSS Reflectometry is an emerging technique used for the remote sensing of soil surfaces. In this contribution an application of dielectric constant retrieval is presented. Both direct and reflected GPS signals were collected by a fully software receiver mounted on-board an aircraft. The reflected signal was processed with an open loop approach, obtaining Delay Doppler Maps (DDMs) and corresponding Delay Waveforms. Signal to Noise Ratios (SNRs) time series were estimated from (non coherently) integrated Delay Waveforms. To take into account variations of system parameters from nominal values, a calibration was performed considering signals reflected from a water lake. Finally, the retrieval process able to estimate dielectric constant of soil surface fromevaluated SNR was applied and the results showed good correlation with fields' flooding stat

Soil moisture retrieval from GNSS-R signals

Signals transmitted from Global Navigation Satellite System (GNSS) can be used for soil moisture monitoring after reflection from the Earth’s surface. In this paper, the data collected by a GNSS receiver prototype installed on a small aircraft were analyzed. A conventional GNSS L1 patch antenna up-looking with right-hand circular polarization was used to receive the direct signals, while a dual polarized RHCP/LHCP GPS antenna by ANTCOM Corporation was use to received the reflected signals. The system was calibrated considering the signals reflected from water surface. Soil moisture was retrieved from the power ratio of LH reflected SNR over direct RH SNR regardless of the surface roughness and incoherent components. Results showed good correlation with the types of underlying terrain