The ongoing Distributed Aperture Radar Tomographic Sensors (DARTS) project at NASA Jet Propulsion Laboratory aims to mature and demonstrate multi-static SAR measurements for fine-scale 3D imaging of surface topography, vegetation, and surface deformation and change. The project explores the use of drones as SAR platforms and integrates software-defined radar on RF system-on-chip for compact and flexible radar instruments. This paper highlights the progress in DARTS hardware development, experiments, and data processing. The recent experiments have successfully demonstrated monostatic interferometry as well as acquisition and processing of bi-static SAR imagery. By leveraging the advantages of multi-static SAR and drone-based platforms, the project aims to build a testbed for future missions design and enhanced SAR imaging capabilities for scientific applications.

Recent results have highlighted the potential ability of bistatic and multistatic synthetic aperture radar (SAR) tomographers to measure vegetation structure and surface topography. However, the quality of SAR tomographic measurements with multiple platforms is impacted by the phase instability in each platform’s oscillator. The phase noise, if uncompensated, may lead to degradation in the SAR data products such as increased sidelobe levels, reduced peak amplitude of the impulse response, and low-frequency phase modulation, among others. In this work, we model and examine the effects of oscillator phase noise on tomographic SAR signals for spaceborne missions flying in formation. A synchronization process is also adopted to help mitigate oscillator phase errors by measuring and predicting relative phase offsets at prescribed temporal intervals. A simulation tool was developed to examine the point target response (PTR) as seen by realistic satellite constellations in low Earth orbit using different quality oscillators, radar configurations, and synchronization configurations. A first analysis of a multiplatform tomographic SAR mission suggests that a system without a dedicated physical link with minimal effects on the PTR may be achievable using current oscillators. Our analysis also shows that phase noise has differing effects on multistatic radar modes. Tomograms formed with a system operating in single-input–multiple-output (SIMO) mode are the most affected by an oscillator phase noise error, followed by multiple-input–multiple-output (MIMO), with negligible effects on the single-input single-output (SAR-SISO) mode. These trade studies and the simulation tool can be used to help inform the design of future multistatic radar missions.

When GNSS signals reflect off of the surfaces of lakes, rivers, wetlands, and other inland water bodies, the surfaces are often sufficiently smooth to produce coherent reflections. The observable produced from coherent reflections made by GNSS Reflectometry (GNSS-R) instruments exhibits particular features with respect to diffusely scattered signals by rough land and wind-driven oceans allowing detection of such smooth bodies. Several different GNSS-R coherence detection approaches have been reported in the literature and developed among the GNSS-R community over the last several years; however, the merits of each approach are difficult to compare because they are often applied to different scenarios and quantified in different ways, independently of each other. This paper provides a unified comparison of a wide variety of different GNSS-R coherence detection approaches, which is the most extensive published to date. The approaches are applied to a common data set from the NASA CYGNSS satellites that includes both the standard Level-1 DDM science product as well as raw baseband signal recordings. Additionally, simulated observables are generated with varying coherent and non-coherent reflection components to exercise algorithms over a wide range of SNRs and relative powers. Objective measures of accuracy are used to quantify the performance of each approach in the context of relative implementation complexity. Conclusions are presented on the pros/cons of the various methods as they relate to various applications such as real-time in-orbit coherence detection or post-processing on the ground.

GNSS-R measurements from inland waters and wetlands show strong coherent reflections. These measurements can be utilized to detect the presence of surface water and to measure its extent; however, there are numerous geophysical phenomena may affect the received signal properties, such as wind induced waves and vegetation attenuation of both the electromagnetic signal and the surface water waves. Under-standing the impact of each of these geophysical effects in the inland water scene is useful for developing and assessing the capabilities of GNSS- R retrieval algorithms for detection and monitoring of dynamically changing inland water scenes. This paper proposes a combination of models to characterize these effects on the coherent GNSS reflection to a first order.

GNSS-R is a technique that has demonstrated sensitivity to inland water bodies. Observations from CYGNSS can be used to map inland water bodies and extracting information from CYGNSS observations is the subject of many ongoing investigations. While the information in CYGNSS observations is useful, we are exploring methods to leverage the strengths of CYGNSS together with the strengths of other observations. This work is driven by the development of a Bayesian approach for combining synergistic observations together with those from CYGNSS. To support this approach, we developed methods for representing information from CYGNSS observations probabilistically. In this paper, we develop a logistic regression model to estimate surface water probability from CYGNSS observations. Understanding how to use CYGNSS to estimate surface water is the necessary first step in the development of a data fusion approach to surface water mapping. Although this work focuses on utilizing the GNSS-R data from CYGNSS, the data fusion approach we develop will serve as the preparatory framework for utilization of all GNSS-R constellations in hydrological data fusion in the future.

Distributed Aperture Radar Tomographic Sensors (DARTS) is a mission concept being studied at the NASA Jet Propulsion Laboratory in collaboration with the California Institute of Technology to enable global and repeated imaging of surface topography and three-dimensional vegetation structure using single-pass tomographic SAR technique. The observing system consists of a distributed formation of multiple small synthetic aperture radar platforms deployed in space with variable distances to achieve look angle diversity and sensitivity to the vertical distribution of vegetation components. Our goal is to identify the optimal system configuration starting from documented community needs and mature the critical technologies that lead to a viable implementation of DARTS. Here, we provide an overview of DARTS and describe our approach for designing and demonstrating single-pass SAR tomographic systems as part of an on-going funded NASA Instrument Incubator Program effort.

Recent results from CYGNSS have highlighted the importance of coherent GNSS reflections for measuring and mapping surface water. However, the GNSS-R instrument aboard CYGNSS was intended for measuring diffuse scattering from the ocean, and the way in which it processes measurements is not optimal for coherent reflections. The goal of this work is to review recent investigations into how on-board algorithms in future instruments can take full advantage of coherent GNSS-R measurements, especially with how they apply to observation of inland water. It is understood that the proper utilization of coherent reflections will open the door to a number of new and interesting science applications for GNSS-R. Several algorithms are proposed.

Spaceborne GNSS reflectometry allows for the production of maps of rivers, wetlands and inundations using a significant change in the reflected signal while the ground track transects those inland water basins. We performed modeling of both coherent and non-coherent DDMs from Okeechobee Lake in Florida for overpasses by CYGNSS observatories under various wind conditions. To obtain the same level of quantitative matchup one needs to scale the modeled SNR curve by several dBs. Modeled results showed a good qualitative matchup with CYGNSS data over lake's open water. Potentially, vegetation of wetlands in the western part of Okeechobee Lake can attenuate the DDM coherent component. Water covered by vegetation and open water might produce comparable reflected powers, however, due to different mechanisms. The level of the reflected signal from rough open water is governed by both the wind speed and wind direction, representing confounding variables for determining vegetation height and boundaries in wetlands. In this paper we demonstrate implicating effects of the wind generated roughness of open water, while demonstrating modeling work to examine the effect of wetlands vegetation on the GNSS reflected signal is in progress.

GNSS Reflectometry (GNSS-R) measurements are very sensitive to the presence of inland waters such as wetlands, floods, rivers and lakes. This paper reviews the basic characteristics of a GNSS-R ‘water detection’ research product, including resolution and temporal sampling of wetlands, and discusses the main known sources of errors. Additionally, a summary of GNSS-R applicability to the study of lakes is provided.

An algorithm for detecting coherence in Cyclone Global Navigation Satellite System (CYGNSS) mission delay-Doppler maps (DDMs) is presented. Because CYGNSS DDMs report only the observed power without phase information, the algorithm uses estimates of power “spread” within the DDM to flag coherency. Since the estimate used is a ratio of the powers in differing portions of the DDM, it is less sensitive to absolute power calibration and to the GPS C/A code type observed, and is applied to CYGNSS Level-1 uncalibrated DDMs. The basic detector formulation is described along with modifications to improve performance in lower signal-to-noise ratio (SNR) situations. The required detection thresholds are determined using matchups with CYGNSS “Raw I/F” mode measurements for which the DDM phase can be computed and used to identify coherence more precisely. Application of the final detector over a large CYGNSS data set suggests that approximately 8.9% of all inland returns are coherent. Inland regions persistently identified as coherent were found largely to be associated with the presence of water bodies. A smaller set of desert locations apparently having very low surface roughness were also found to be associated with persistent coherence. The detector was also applied to a set of ocean measurements, with the results showing that persistent coherence is limited to areas with sheltered waters. Ocean tests avoiding such regions indicate that the detector's false-alarm rate is approximately 0.0012% for the detection threshold used.

The accuracy of spaceborne ocean surface altimetry depends on precise knowledge of the altimeter satellite orbit. Previous studies of the potential utility of CYGNSS GNSS Reflectometry (GNSS-R) measurements for ocean altimetry have identified its orbit error as a limiting factor. To address this, a recent firmware upgrade to the CYGNSS satellites has enabled the downlink of additional GPS raw measurements from the navigation receiver and increased numerical precision of open-loop GNSS-R tracking information. In this paper, we present improvements to the accuracy of both the orbit determination and the ocean surface height retrievals as a result of these recent upgrades. JPL's GipsyX software is used to process 170 days of GPS navigation measurements for one of the 8 CYGNSS satellites. Incorporating high fidelity dynamic models and antenna group delay corrections, daily orbit overlaps throughout the period show mean RMS differences of 2.5 cm in height, 5.9 cm in cross-track, and 10 cm in along-track. Applying these new orbits reduced the standard deviation of retrieved sea surface height anomalies from 2.2 m to 1.9 m using 4 second smoothed measurements. Further improvements are expected using new ionospheric corrections and re-tracking methods currently in development.

The Cyclone Global Navigation Satellite System (CYGNSS) has recently shown exciting potential for GNSS reflectometry (GNSS-R) to resolve small-scale and dynamic hydrological features over land (such as rivers, lakes, wetlands, and urban flooding), even when obstructed by dense vegetation. Since CYGNSS is a small satellite constellation, sub-daily measurement frequencies provide a unique opportunity to observe short timescale changes. However, since CYGNSS observations occur in sparse, quasi-random tracks, it is more difficult to understand the true observability of events as compared to imaging instruments. Changes in SNR that would indicate a dynamic change in the scene are confounded by inherent variability due to other sources, including vegetation, geometry changes, instrument gain calibration, and surface roughness due to wind. While the literature does detail the use of CYGNSS measurements to map surface water changes, the lack of valid ground data makes it difficult to quantify the true accuracy. Here, we present results from a simulation study currently underway that utilizes a GNSS-R coherent scattering model to understand the observability and accuracy of CYGNSS measurements of dynamic changes in inland water bodies. The goal is to quantify the sensitivity and resolution of observations of dynamic spatial and temporal variations of inland water bodies.

Current GNSS-R instruments, such as those used aboard the CYGNSS and TDS-1 satellites, form delay-Doppler maps (DDMs) using fixed integration schemes. The reflected GNSS signal is coherently integrated with a local replica signal and then non-coherently integrated to form a DDM measurement. For scenes dominated by diffuse scattering (i.e. most land and ocean surfaces at typical incidence angles), this approach works well given the short reflected signal coherence time that does not vary significantly over the typical range of incidence angles. However, the coherence properties of the reflected signal change significantly in some circumstances, such as over inland water bodies, coastal areas, wetlands, and at grazing incidence angles over the ocean and land. In this study, we investigate the possible benefits of a receiver adapting its coherent integration time to the instantaneous properties of the reflected signal. The algorithm proposed uses the complex DDM samples to estimate the coherence time efficiently on-the-fly. These estimations are then used to adapt the coherent integration time in the receiver to form DDM measurements. Example results using raw signal data collected from CYGNSS will be presented.

Spaceborne GNSS Reflectometry (GNSS-R) measurements over inland waters have exhibited strong coherent scattering. The strong reflected signal from a relatively small spatial extent (several km) is highly sensitive to surface waves. This sensitivity can be leveraged to estimate wave height profiles across inland waters. Coupled with a wind wave model, retrievals of wind vector can be performed using a forward model approach. The surface waves play a significant role in nearshore ecosystems, affecting sediment resuspension, biomass production, and fish habitat, among others. This paper details a novel approach to estimating surface wave profiles and wind vectors using the passive, bistatic radar receiver aboard CYGNSS. The first ever retrieval of wind vector and wave height of an inland water body using spaceborne GNSS-R will be shown using raw signals recorded onboard CYGNSS.

The science payload on each spacecraft in the CYGNSS constellation is a GNSS-R receiver and antennas designed to receive GPS L1 signals scattered from the Earth surface. The constellation was launched on 15 Dec 2016 and the GNSS-R instruments continue to operate successfully. A next generation version of the receivers and antennas is in development which adds significant measurement capabilities that are expected to enhance the resolution, precision and coverage of current CYGNSS science data products as well as enable some new ones.

Spaceborne GNSS reflectometry has shown ability to observe the global inland water distribution. It allows generating dynamic maps of rivers, wetlands and inundations using the large variation in the received power while the ground track crosses those objects. Here, we analyze the change of the reflected signal's power and coherence due to surface roughness and cover (ice) observed in the CYGNSS delay-Doppler maps for Qinghai Lake, China. It is shown that a significant attenuation of the reflected coherent signal and emergence of the diffuse component occurs due to wind-generated surface waves. The comparable attenuation effect of the coherent component is observed in the case of the frozen lake. It takes place due to the lower value of the average Fresnel reflection coefficient of ice. A similar effect may occur for reflections from wetlands, when open water and water covered by vegetation could produce comparable reflected powers, however, due to different mechanisms. Understanding the relative scattering characteristics of wetlands in contrast with rougher bodies such as lakes is important for the development of algorithms to detect their dynamic changes.

Ocean surface altimetry with GNSS reflectometry (GNSS-R) has the potential to improve the observation and retrieval of mesoscale ocean current flows by increasing the spatial density of ocean surface observations. The leading challenges in current GNSS-R altimetry investigations include precise delay retracking, correction of ionospheric effects, and spacecraft receiver positioning. Here, we present improved methods to account for these challenges. A reflection-model-based approach is presented for delay retracking that uses simulated delay-Doppler maps (DDMs) to retrieve the specular delay from measured DDMs. Global ionosphere maps are used to estimate the group delay effect along the direct and reflection paths. Precise orbit determination techniques are used to improve estimates of the receiving spacecraft position and reduce systematic intersatellite biases. We analyze altimetric height retrievals from two cases, strongly coherent or diffuse reflections. We study the residual systematic error signals with a focus on understanding the errors identified above. The strong coherent observations have narrow, symmetric delay waveforms and provide higher than average signal-to-noise ratio. The DDMs of diffuse observations, originate from relatively rough ocean surfaces and have the characteristic horse-shoe shape. Only measurements from the ocean and seas surrounding Indonesia are considered as this area provides a significant number of strongly coherent reflections. More than 50 000 single-point observations and week-long averaged results are presented to quantify the noise and systematic characteristics of the retrieved surface heights.

This paper presents recent work being done to produce a new GNSS Reflectometry (GNSS-R) ocean altimetry product using data from NASA's CYGNSS Mission, a constellation of 8 small satellites that measure reflected GPS signals off of the surface of the ocean. Although CYGNSS is not intended or optimized for altimetry, creation of a research product will allow assessment at the synoptic level over the life of the CYGNSS mission. The algorithms being developed here are for generation of large-scale production runs, unlike previous reports that have have examined limited sets of data. The CYGNSS Level 1 data is processed using a modified CYGNSS End-to-end Simulator (E2ES) which provides a full-forward-model waveform fit (along both delay and Doppler space) and precise delay retrieval. The delay is converted into estimated sea surface height (SSH) using auxiliary data sources for corrections, such as ionospheric, tropospheric, tidal, orbital and instrument. The resulting data product will enable thorough characterization of altimetry accuracy and remaining error sources.

Spaceborne GNSS Reflectometry (GNSS-R) measurements have shown strong coherent scattering over inland waters. It has been recognized that GNSS-R could be utilized for monitoring the global surface water distribution by making dynamic maps of wetlands as well as rapid response to flood events. Using the strength of the reflected signals, one can make maps that reveal the presence of water over land. In this paper, we used simulations to analyze the accuracy of these maps. The CYGNSS End-to-end Simulator (E2ES) was extended to include coherent scattering in the heterogeneous scenes where the region around the specular point is composed of both land and water in complex geometries. The simulation is then used to evaluate the accuracy of a simple fractional water in footprint approach to mapping wetland extent. We find that scattering from outside the first Fresnel zone and CYGNSS measurement processing effects significantly impact the accuracy of this approach. However, the accuracy can be improved by combining multiple measurements into a gridded map.

Recent results from CYGNSS measurements over land show the importance of coherent scattering. It is envisioned that future GNSS-R instruments will have the ability to separate and detect coherent scattering and downlink complex-valued coherent DDM measurements. This additional information will allow carrier phase altimetry, the separation of coherent and non-coherent scattered power, and the evaluation of geo-physical phenomena at along-track resolutions 10x greater than current spaceborne instruments, such as TDS-1 or CYGNSS. In this paper, we will present a prospective design for the on-board detection of coherent reflections. We also investigate how to achieve enhanced along-track resolution.

The current generation of spaceborne GNSS-R instruments, such as CYGNSS, utilize only narrowband GPS Ll CIA-coded signals at a 1575.42 MHz center frequency. A next-generation instrument being developed will also support Galileo E1bc signals as well as wideband GPS L5 and Galileo E5 signals. The additional bandwidth in the L5/E5 band should significantly improve the spatial resolution and range accuracy of measured reflections and the corresponding scientific products. In the proposed implementation, these reflection measurements will be made using a locally generated reference signal (i.e. conventional GNSS-R). However, the use of wideband, high-spatial-resolution, high-range-accuracy measurements are often cited as a benefit of the interferometric GNSS-R approach. In this work, we develop a simulator to compare the performance of the two approaches, both in terms of measurement quality and implementation complexity.