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.

A ground-based distributed sensing network is described in this work that leverages elements of wireless sensor networks (WSN) and uncrewed areal vehicles (UAVs) with software-defined radar payloads. Hardware and software advancements are made towards combining the operations of WSNs and UAVs for dynamic spatiotemporal monitoring of surface to subsurface soil moisture at kilometer scales. The multi-agent and distributed sensing approach demonstrates coordination, collaboration, and parallel operation of discrete assets for optimal soil moisture monitoring. Results from the first field experiment showing this coordinated operation are reported.

This paper aims to retrieve the soil moisture profile above the water table using ground penetrating radar. For the forward model, the Van Genuchten soil saturation model and the generalized refractive mixing dielectric model are used to parameterize the soil saturation profile. The finite-difference time-domain method was used to simulate the electromagnetic signal. The soil moisture profile retrieval was carried out using a look-up table. We demonstrate successful retrieval of soil moisture profile in the presence of noise.

Recent innovations in small satellite, ultra-wideband direct RF sampling, and synchronization technologies have made multistatic and MIMO coherent SAR constellations a feasible concept for future missions. The Distributed Aperture Radar Tomographic Sensors (DARTS) mission concept at NASA JPL aims to measure Earth's surface topography and vege-tation using TomoSAR techniques. This paper describes the development of an embedded ultra-wideband next generation software defined radar (SDRadar) testbed capable of multi-band operation implemented with the Xilinx RF System on Chip (RFSoC) architecture, which features 8x 6.4 GSPS DACs and 8x 4 GSPS ADCs. The RFSoC SDRadar repre-sents a state of the art testbed for rapid prototyping of radio, radar, and synchronization technologies. We provide preliminary testing results for airborne monostatic radar imaging from a small uninhabited aerial system (sUAS), successfully demonstrating multi-band operation using first and second Nyquist zone direct RF sampling.

Adaptive and targeted allocation of mobile sensing agents, in the form of unmanned aerial vehicles (UAVs) with software defined radar (UAV-SDRadar) payloads, enable mapping of surface soil moisture in regions wherein situwireless sensor networks (WSNs) undersample soil moisture or upscaling models perform poorly. This work presents an optimization-based UAV path planning methodology that seeks to maximize UAV flight coverage over areas where a complementing WSN yields upscaled soil moisture estimates with high uncertainty. By recursively mapping soil moisture over such areas, the combined UAV and WSN instrumentation can gradually capture the domain’s true mean soil moisture. A series of numerical simulations are presented to demonstrate the algorithm’s basic function while considering real-world and feasible operational scenarios.

We present results from a field campaign to measure seasonal snow depth at Cameron Pass, Colorado, using a synthetic ultrawideband software-defined radar (SDRadar) implemented in commercially available Universal Software Radio Peripheral (USRP) software-defined radio hardware and flown on a small hexacopter unmanned aerial vehicle (UAV). We coherently synthesize an ultrawideband signal from stepped frequency 50-MHz subpulses across 600–2100-MHz frequency bands using a novel nonuniform nonlinear synthetic wideband waveform reconstruction technique that minimizes sweep time and completely eliminates problematic grating lobes and other processing artifacts traditionally seen in stepped waveform synthesis. We image seasonal snow across two transects: a 400-m open Meadow Transect and a 380-m forested transect. We present a surface detection algorithm that fuses data from LiDAR, global navigation satellite system (GNSS)/global positioning system (GPS), and features in the radargram itself to obtain high precision estimates of both snow and ground surface reflections, and thus total snow depth, represented as two-way travel time. The measurements are validated against independent ground-based ground-penetrating radar measurements with correlations coefficients as high as$\rho = 0.9$demonstrated. Finally, we compare backscattered radar data collected by the UAV-SDRadar while hovering proximal to a known snow pit within situmeasured snow dielectric profiles and demonstrate imaging of snow stratigraphy.

The advent of smaller SAR satellites and cheaper access to space is bringing the notion of a multistatic SAR constellation into the realm of feasibility. Researchers at JPL are studying a Distributed Aperture Radar Tomographic Sensors (DARTS) mission concept intended to measure Earth's surface topography and vegetation using TomoSAR techniques. This paper describes progress on the airborne testbed for the DARTS study. The testbed is the union of a software-defined radio that implements a radar and synchronization link together with a small uninhabited aerial system (sUAS) that serves as a platform with precise control of the observation geometry. Initial experiments have demonstrated successful multi-sensor synchronization as well as acquisition and processing of monostatic SAR imagery.

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.

We present analytic expressions for the clock phase error power spectral density (PSD) resulting from a previously reported decentralized distributed wireless synchronization protocol acting on independent sensor oscillators. We provide an overview of oscillator phase noise error modelling and examine the effects of the wireless synchronization protocol and the resulting synchronized clock phase noise PSDs. We present results from both simulation and experiment to validate the expressions derived.

In this paper we describe the development of new wireless sensor network technologies to coordinate among different ground-based and unmanned aerial vehicle (UAV)-based sensors as “Agents” who, when coordinated, deliver ground-truth at varying temporal and spatial sampling scales for NASA remote sensing science products, as well as for other potential users that may have different application requirements.

In this work, we explore efficient ultra-wideband radar waveforms and signal processing techniques for achieving high performance radar systems in low-cost hardware. This paper describes the generation of nonlinear constant-amplitude frequency modulated (FM) waveforms with autocorrelation functions that resemble linear FM waveforms that are amplitude-apodized by an arbitrary window function. The principle of stationary phase is used to solve for a time-frequency curve that produces a waveform with a power spectral density (PSD) that is similar to a desired PSD but dependent only on waveform phase. This method is extended to nonlinear (NL) synthetic wideband waveforms (SWWs), wherein an ultra-wideband nonlinear waveform having arbitrary spectral weighting is synthesized from non-uniform stepped-frequency nonlinear frequency modulated (NLFM) sub-pulses. A novel reconstruction algorithm, Non-Uniform Frequency Stitching (NUFS) is presented for obtaining high range resolution performance from such non-uniform nonlinear SWW (NUNL-SWW) waveforms with minimal grating lobe contamination.

In this paper we demonstrate the capability of an ultra-wideband software defined radar (SDRadar) implemented in commercial USRP SDR hardware to produce high-resolution images of sub-surface landmine-like targets. We formulate a half-space back-projection focusing algorithm for low-altitude nadir-looking airborne altimetric ground-penetrating SAR that accounts for dispersive and refractive effects of the air-ground interface. Performance of the SDRadar and focusing algorithm are shown in experimental results. This work has applications in the development of low-cost high-resolution UAV-based radar systems for landmine detection and other sub-surface imaging tasks.