We present the first-light airborne measurements of a new W-band atmospheric radar, part of the CloudCube instrument. CloudCube is a multifrequency, ultra-compact, low-cost, modular radar system for vertical profiling of clouds, convection, and precipitation structures and dynamics from space. The instrument employs a novel radar architecture that directly upconverts the baseband signal to the RF band, eliminating the need for intermediate frequencies or further multiplication schemes. This architecture, combined with pulse compression techniques, offers a straightforward and effective solution while achieving the necessary performance and robustness for airborne or spaceborne radar instruments. The W-band channel was installed and operated aboard NASA’s DC-8 Airborne Laboratory, completing two test flights over the coast of California and operated as a technology demonstration during science flights as part of the CPEX field deployment. A detailed pulse compression validation and comparison of reflectivity profiles across multiple frequency bands demonstrate the instrument’s performance for atmospheric profiling.

The development of radar systems operating at G-band (110 - 300 GHz) with small size, weight, and power requirements can offer new possibilities for probing clouds and precipitation from space and lead to novel mission concepts. To advance the technology needed to achieve such objective, a ground-based G-band Doppler radar prototype for atmospheric profiling has been developed and demonstrated with different targets. This article describes the radar architecture and discusses the instrument calibration and reflectivity and Doppler velocity measurements of clouds and precipitation.

Studies of sea level rise, ice sheet mass loss, and other glacial processes are hindered by the sparsity of observational measurements. Orbital radar sounding of the Martian ice caps has been successfully conducted, showing the promise for orbital sounding of terrestrial glaciers for improved coverage. Concepts for terrestrial orbital radar sounders, such as the Distributed Element Beamformer Radar for Ice and Subsurface Sounding (DEBRIS) mission concept, use an array of CubeSats to obtain narrow beam patterns and reduce cross-track clutter. To loosen wireless synchronization requirements, we investigate the application of orthogonal wave beamforming to DEBRIS. We compare orthogonal wave beamforming to traditional phased arrays and investigate Sinusoidal Frequency Modulated Continuous Waves (SFMCW) as an orthogonality scheme for beamforming.

The innovations in high-performance, low-power electronics and low-cost space access are unlocking affordable distributed radar systems and new remote sensing opportunities. The Distributed Element Beamformer Radar for Ice and Subsurface sounding (DEBRIS) is a concept to implement a 2D sparse radar aperture to improve the radar's spatial resolution and sounding investigation depth through the reduction of surface clutter. Here, we introduce this system and highlight its applications, orbital configurations, and the implementation considerations to achieve state-of-the-art performance for spaceborne radar sounders.

Pulse compression has enabled a new generation of low-cost and compact spaceborne weather radar systems. To successfully utilize pulse compression techniques for cloud and precipitation applications, the effects of Doppler-range migration must be considered during the design and operation of the radar. Pulse compression for spaceborne weather applications introduces additional interdependence between the radar system and the operations when compared with traditional pulsed radar systems, primarily as a result of the large platform velocities. Pulse compression signals for weather radar can be simulated with high fidelity to predict and optimize the radar's performance. In this article, we evaluate the pulse compression performance of RainCube, a Ka-band precipitation radar in a CubeSat, through analysis and comparison of observations and radar simulations. Through these comparisons, design and operational considerations for pulse compression weather radar are discussed. This work shows that the optimal pointing angle for RainCube to achieve the finest vertical resolution is not at nadir, but when pointing forward approximately 2.25°, in the direction of the spacecraft's orbit.

The NASA dual-frequency, dual-polarization, Doppler radar (D3R) [1] was conceived and developed to support ground validation (GV) operations of the Global Precipitation Measurement (GPM) mission [2]. The D3R operates in the same frequencies bands, Ku- and Ka-band, as GPM's dual-frequency precipitation radar enabling direct comparisons of microphysical observations of precipitation. The D3R radar is shown in Figure 1. To support the GPM GV mission, D3R substantively participated in four field campaigns in North America with diverse geographic features covering both winter and summer conditions.

The operating state of a wind turbine determines the characteristics of its time-varying radar signature. We demonstrate this using high-rate state telemetry from the NREL CART3 wind turbine to suppress its radar signature. We also consider the update frequency and accuracy requirements that are necessary to directly use state telemetry for the estimation or suppression of the radar signature of a wind turbine.

The NASA dual-frequency, dual-polarization, Doppler radar (D3R) is a weather radar operating at 13.91 GHz (Ku-band) and 35.56 GHz (Ka-band). The operational range of the D3R is 40 km, this relatively short operating range, along with the high sensitivity of D3R, are susceptible to increased observation of range ambiguous echoes, also referred to as “second-trip echoes”. In this work, by leveraging a staggered pulse repetition period and random transmitted phase codes, two methods are developed to detect and dealias the second trip contamination for the operational use with the D3R. Using these methods, the overlapping echoes are separated, and unambiguous range of the D3R is increased. Weather signals are simulated and used to quantitatively characterize the performance of moment estimator over a wide range of realistic weather scenarios. The D3R's Ku-band observations are presented to demonstrate the performance of algorithm with and without overlapping echoes from different ranges.

The NASA dual-frequency, dual-polarization, Doppler radar (D3R) is an important ground validation tool for the global precipitation measurement (GPM) missions dual-frequency precipitation radar (DPR). In this work, we start with the hardware modifications done to accomplish this upgrade, although the focus is not much on the hardware modifications. Overall system architecture is presented. The focus is more on the system sensitivity and spatial resolution. Also, the performance of the pulse compression waveforms is presented and compared with simulated results. Various trade-offs are discussed in context of range resolution, sensitivity and side lobe performance of these waveforms.

Unwanted radar echoes, colloquially referred to as “clutter,” impede the mission effectiveness of radar systems. Depending on radar's application, clutter examples can include weather, buildings, vegetation, and more. Techniques to mitigate clutter and improve the performance of radar systems are continuously being developed and refined. In this paper, wind turbines used for commercial power generation, which present a Doppler velocity signature that is time-varying, are considered a source of radar clutter. A wind turbine clutter mitigation technique is developed for fixed-pointing weather radar applications, approximating the turbine's radar signature as a cyclostationary process. The cyclostationary model for the wind turbine and the suppression technique is then validated using observations of wind turbines and precipitation.

Wind turbine observations and characterization efforts have treated the wind turbine as a noncooperative target. Similarly, suppression of the turbine's radar signature has been considered without the aid of state information from the wind turbine under observation. In this paper, X-band radar observations of a utility-scale wind turbine, with detailed turbine state telemetry, are investigated. From scattering theory, the wind turbine's physical structure has a deterministic radar cross section for a given observation geometry. Using the telemetry, the variation in the turbine's signature is considered over a range of operating states. The deterministic nature of a turbine's signature is demonstrated from radar observations, and a model is developed to isolate it. The turbine's radar signature, as it relates to changes in the operating state, is discussed with the intent of enabling future suppression techniques.

The optimal design of pulse compression waveform/filter pairs for use with near-nadir spaceborne radar in low earth orbit for the observation of clouds and precipitation is discussed. An optimization technique is introduced that considers performance metrics specific to the remote sensing of clouds and precipitation from such platforms. Specifically, the sensitivity of the radar to precipitation and clouds is maximized as close to the ground as required. The sensitivity of the radar near the surface is typically limited by the pulse compression range sidelobes from the surface's echo. Optimization of the waveform/filter pair's performance is facilitated by a time-domain radar scattering model to simulate radar reflectivity range profiles. The presented radar-scattering model accounts for the radar's configuration constraints and platform motion, as well as the spatial distribution and relative motion of the scatterers. In this paper, the optimization of both linear frequency modulation (LFM) and nonlinear frequency modulation (NLFM) waveforms is considered. It is demonstrated that the LFM waveforms provide superior performance over NLFM waveforms for application subject to unmitigated Doppler shifts.

The NASA D3R was successfully deployed and operated throughout the NASA OLYMPEx field campaign. A differential phase based attenuation correction technique has been implemented for D3R observations. Hydrometeor classification has been demonstrated for five distinct classes using Ku-band observations of both convection and stratiform rain. The stratiform rain hydrometeor classification is compared against LDR observations and shows good agreement in identification of mixed-phase hydrometeors in the melting layer.

Weather radar signals at high frequencies such as Ku-band are attenuated along the propagation path through rainfall. Hence, reflectivity and differential reflectivity measurements at such frequencies should be corrected for attenuation before any quantitative applications such as the retrieval of raindrop size distribution (DSD), which is a fundamental descriptor of rainfall microphysics. This paper presents the attenuation correction algorithm implemented for NASA Dual-frequency Dual-polarized Doppler Radar (D3R) Ku-band observations. The dual-polarization based correction performance is evaluated with the self-consistency criterion. In addition, the DSD parameters are estimated with the attenuation corrected observations, and the preliminary results are shown.

Linear depolarization ratio (LDR) is often difficult to measure in low and moderate signal-to-noise ratio conditions because the cross-polar echo power is typically two to three orders of magnitude weaker than the copolar echo power. For radars operating at attenuating frequencies such as X-, Ku-, and Ka-bands, differential attenuation must be accounted for to accurately estimate the LDR. A method for robust estimation of the LDR is introduced and evaluated that addresses both of these issues. In practice, the “enhanced” LDR offers robust LDR estimation over current estimation methods. The enhanced LDR is insensitive to noise, radar calibration error, and path-integrated attenuation. The proposed estimator is experimentally validated using Ku-band observations from the National Aeronautics and Space Administration dual-frequency dual-polarization Doppler radar (D3R).

The demand for renewable power production has fostered an exponential increase in the size and number of wind turbines. This expanding source of power generation is sometimes at odds with maintaining the effective operation of radar systems in air traffic control, defense, weather prediction, and severe-storm-tracking applications. With the recent upgrade of the NEXRAD weather radar system to enable dual-polarization observations, a dual-polarization characterization effort of wind turbines is warranted. Focusing on weather radar applications, a characterization of ground clutter, precipitation, and wind turbines is presented here using a consistent unified treatment. This characterization effort directly compares the dual-polarization radar signatures of these three classes of scatterers. The physical characteristics of wind turbines (particularly their cyclostationary behavior) are exploited to identify unique dual-polarization radar signatures.

Vertical profiles of vertical air motion and raindrop size distributions (DSDs) within stratiform rain are estimated using two collocated vertically pointing radars (VPRs) operating at 3 and 35 GHz. Different raindrop backscattering cross sections occur at 3 and 35 GHz with Rayleigh scattering occurring for all raindrops at 3 GHz and Mie scattering occurring for larger raindrops at 35 GHz. This frequency-dependent backscattering cross section causes differently shaped reflectivity-weighted Doppler velocity spectra leading to radar transmit frequency-dependent radar moments of intrinsic reflectivity factor, mean Doppler velocity, and spectrum variance. The retrieval method described herein uses four radar moments as inputs to retrieve four outputs at each height within a precipitation column. The inputs include 3-GHz VPR mean Doppler velocity and unattenuated reflectivity factor and 35-GHz VPR mean Doppler velocity and spectrum variance. The outputs include vertical air motion and three parameters of a gamma-shaped DSD. To account for different VPR sample volumes, radar observations were accumulated over 45 s and over several range gates to represent time-space scales larger than either VPR sample volumes. Observed variability over this common time-space scale is used to estimate retrieval uncertainties. The retrieved air motions and DSD parameters compare well against retrievals from a collocated 449-MHz VPR that estimated air motions from Bragg scattering signals and DSD parameters from Rayleigh scattering signals.

The polarimetric radar parameter, linear depolarization ratio (LDR), provides microphysical insight into a scattering volume, particularly for mixed-phase and ice particles. A new estimator for improved estimation of LDR is presented. The NASA dual-frequency, dual-polarization, Doppler radar (D3R), which was recently upgraded to support operational linear depolarization ratio observations, was used as a testbed for evaluation of the new estimator. With D3R's Ku-band observations, the new LDR estimator is compared to conventional estimators and it is demonstrated that the new estimator is insensitive to attenuation, a number of radar system biases, and has increased immunity to noise for low SNR observations.

In order to investigate how well observations from precipitation-monitoring satellites match up to the best estimate of the true precipitation measured at ground level and how to use the collected precipitation data to evaluate models that describe and predict the hydrology, the Integrated Precipitation and Hydrology Experiment (IPHEx) was conducted in the southern Appalachian Mountains in the eastern United States from May 1 to June 15, 2014. The NASA dual-frequency dual-polarization Doppler radar (D3R), co-located with NASA NPOL radar, was deployed as part of the IPHEx field campaign to characterize precipitation properties at Ku- and Ka-band frequencies. This paper presents the deployment and performance of D3R during the IPHEx field experiment. Sample observations will be presented, with particular attention paid to cross-comparison between D3R and NPOL.

Accurate noise-power estimation in dual-polarization weather radar is necessary for the correction of all power-based moments in low signal-to-noise ratio environments. A method of real-time noise-power estimation for dual-polarization radar systems using copolar correlation and receiver power is introduced. This real-time noise-power estimation algorithm is implemented in the NASA dual-frequency dual-polarization Doppler radar, and the performance results are presented.

Radar observed differential Doppler velocity can be a proxy for the dual-frequency ratio for vertical pointing observations. Vertical pointing dual-frequency data was collected with the NASA D3R and the relationship between Ku- and Ka-band velocity measurements is discussed. It is shown that the differential Doppler velocity between frequencies provides insight into the microphysical properties of rain. The differential Doppler velocity can be used to estimate the median volume diameter, D0.

The Iowa Flood Studies (IFloodS) field experiment was conducted to better understand the strengths and limitations of Global Precipitation Measurement (GPM) mission satellite products in the context of hydrologic applications. The NASA dual-frequency dual-polarization Doppler radar (D3R), designed as part of the GPM ground validation program, participated in the IFloodS field campaign to characterize precipitation properties at Ku- and Ka-band frequencies. This paper presents the deployment of the D3R and summarizes the D3R observations during the IFloodS field campaign. The quality of the D3R measurements is evaluated by comparing with the NASA NPOL S-band radar observations. In addition, the capability for rainfall estimation using the D3R is also described and validated using ground gauge measurements.