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This oral presentation discusses spacecraft Doppler tracking in which Doppler data recorded on the ground are linearly combined with Doppler measurements made on board a spacecraft. Methods are proposed to remove or reduce frequency fluctuations from the data that are caused by multiple circumstances. The resultant data from these proposed methods may have applicability in testing relativity theory.
The AWAKEN Dual-Doppler Lidar (ADDLidar) experiment was conducted as part of the larger AWAKEN field campaign (https://www.nrel.gov/wind/awaken.html). The American Wake Experiment (AWAKEN) is an international, multi-institutional wind energy field campaign that was conducted from May 2022 to 2024, in the vicinity of the King Plains wind farm in north central Oklahoma. The goal of AWAKEN was to provide observations to better understand interactions between wind turbines in a wind farm and the interactions between the wind farm as a whole and the atmosphere. The focus of the ADDLidar campaign was to provide height-resolved measurements of wind speed and direction at key locations upwind of the wind farm to characterize the inflow and possible blockage effects upwind of the farm. Specifically, dual-Doppler scanning methods were employed to create a number of so-called virtual towers (Calhoun et al 2006, Debnath et al. 2017, Fernando et al. 2019, Hill et al. 2010, Newman et al. 2016, Newsom et al. 2008, 2015) upwind of the farm. The ADDLidar campaign involved the deployment of two U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility scanning Doppler lidars (S/N 236 and 237) to AWAKEN sites A4 (36.361894°, -97.356352°) and A7 (36.347259°, -97.389968°). Both sites are located approximately 29 km south of the ARM Southern Great Plains (SGP) observatory C1 site, as shown in Figure 1. These sites were chosen for their close proximity to the most southerly row of turbines in the King Plains wind farm.
It is often useful to think of the Doppler resolution of a vertical synthetic aperture radar in terms of the distance spanned by a resolution cell on the ground in unit meters, yet Doppler shift is fundamentally a measure of frequency, so there is a disconnect. This memo derives relationships between frequently invoked Doppler resolution expressions when they are expressed in ground-projected units (meters), angular units (radians), range-rate units (meters/second), and frequency units (Hertz).
In this paper I attempt to document what I have learned and still remember about temperature effects, particularly Doppler broadening, on nuclear data, as it applies to ENDF formatted data. My focus is on the SIGMA1 method of Doppler broadening that I developed over 50 years ago. However, I do realize that there are currently many different methods used in computer codes, and I have tried to keep my discussion general as it applies to ALL of these methods. In particular, ALL of the MYTHS I describe below apply to all Doppler broadening methods: they all solve the parabolic diffusion equation in spherical geometry in (speed, reaction rate) versus temperature. These methods differ only in how the cross section is represented. So, at 85 years old here is what I still remember.
This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on ~30 m range gates, stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, below range, ran out of signal, cloud-topped). Cloud Base Height (Haar-gradient detection): 15 min estimates of cloud-base height (m) with a cloud-detection quality flag (0–3: none, low, moderate, high). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (2.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution, with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science
This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science
This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.1), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science
The structure of spacecraft tracking radar, and range and Doppler measurements, are discussed. Ranging can be used in conjunction with Doppler to determine the total number of charged particles on the radio path. Ranging can also be employed as the primary data type in determining certain kinds of orbits. The basic configuration of the ranging and Doppler system is considered. Inherent limitations on its accuracy with respect to the oscillator, transponder, ground equipment, signal to noise ratio, and general operation are noted.
The principal problem in the measurement of the Doppler reactivity effect is separating it from the thermal reactivity effects of the expansion of the heated sample. It is shown in this proposal that the thermal effects of sample expansion can be experimentally determined by making additional measurements with porous samples having the same mass and/or volume as the primary sample. By combining these results with independent measurements of the linear temperature coefficient and the computed temperature dependence of the Doppler coefficient the magnitude of the Doppler coefficient may be extracted from the data. These addiational measurements are also useful to experimentally determine the precision of the reactivity oscillator technique used to measure the reactivity effects of the heated sample.
The question of what resolution of the gravity field can be obtained from satellite-to-satellite Doppler tracking was investigated by performing least-squares adjustments of simulated Doppler data, solving for parameters describing the anomalous gravity field in various sized blocks. By examining the correlation between the adjusted parameters describing neighboring blocks, it was possible to judge whether a given set of data was capable of resolving blocks of a given size. Two concepts of satellite-to-satellite tracking are considered: the first involves two satellites near together in very low orbits, while the second uses geostationary satellites to track a single very low satellite. In either case, blocks 500 km on a side can be satisfactorily resolved from an orbital altitude of 700 km. From an altitude of 200 km, blocks 200 km on a side can be resolved. Because of the lower limit on altitude imposed by the presence of the earth's atmosphere, it does not appear that satellite-to-satellite Doppler tracking will be able to resolve features smaller than 200 km on a side.
A feasibility analysis and trade-offs for a one-way Doppler extractor using digital VCO techniques is presented. The method of Doppler measurement involves the use of a digital phase lock loop; once this loop is locked to the incoming signal, the precise frequency and hence the Doppler component can be determined directly from the contents of the digital control register. The only serious error source is due to internally generated noise. Techniques are presented for minimizing this error source and achieving an accuracy of 0.01 Hz in a one second averaging period. A number of digitally controlled oscillators were analyzed from a performance and complexity point of view. The most promising technique uses an arithmetic synthesizer as a digital waveform generator.
The integration of Doppler frequencies extracted from S-band communication and tracking signals received onboard an orbiting spacecraft provides a means of navigating on-orbit. This paper describes the one way Doppler tracking concept and two mechanizations which are being investigated by the Johnson Space Center to determine a suitable one way Doppler extraction technique for the Space Shuttle Orbiter and other advanced space systems. The designs of two breadboard models are outlined and measurement errors are discussed.
A Scanning Laser Doppler Velocimeter System (SLDVS) capable of detecting and monitoring atmospheric disturbances, including wake vortices of landing aircraft and vertical wind profiles in the atmosphere was developed. The SLDVS is a focused, continuous wave, CO2 system that determines the line-of-sight velocities of particles in the focal volume by measuring the Doppler shift created by these particles. At present, the SLDVS is designed to have a range coverage of approximately 2000 ft with a vertical angle coverage of approximately 60 deg. It is also designed to detect Doppler velocities of up to 200 ft/sec with a velocity resolution of approximately 1.8 ft/sec. A complete velocity spectrum is provided by the SLDVS at each point in space at which it is focused. The overall operation and performance of the system and the description of its individual components and data handling capabilities were given.
The hypothesis is advanced that observed Doppler noise during solar conjunctions is proportional to total columnar electron content along the signal path. This assumption leads directly to a geometrical model (ISED) for observed Doppler noise which is shown to be in very good agreement with Doppler noise data accumulated during the 1975 Pioneer 10, Pioneer 11 and Helios 1 solar conjunctions. An augmented model is constructed which quantitatively indicates correlation between earth observed sunspot activity and systematic, cyclical deviations from the ISED model.
Studies were made of (1) blood flow redistribution during lower body negative pressure (LBNP), (2) the profile of blood flow across the mitral annulus of the heart (both perpendicular and parallel to the commissures), (3) testing and evaluation of a number of pulsed Doppler systems, (4) acute calibration of perivascular Doppler transducers, (5) redesign of the mitral flow transducers to improve reliability and ease of construction, and (6) a frequency offset generator designed for use in distinguishing forward and reverse components of blood flow by producing frequencies above and below the offset frequency. Finally methodology was developed and initial results were obtained from a computer analysis of time-varying Doppler spectra.
The paper reports on a program undertaken to determine the feasibility of using a laser Doppler velocimeter (LDV) to measure smoke-stack gas exit velocity, particulate concentration, and mass flow. Measurements made with a CO2 laser Doppler radar system at a coal-burning power plant are compared with in-stack measurements made by a pitot tube. The operational principles of a LDV are briefly described along with the system employed in the present study. Data discussed include typical Doppler spectra from smoke-stack effluents at various laser elevation angles, the measured velocity profile across the stack exit, and the LDV-measured exit velocity as a function of the exit velocity measured by the in-stack instrument. The in-stack velocity is found to be about 14% higher than the LDV velocity, but this discrepancy is regarded as a systematic error. In general, linear relationships are observed between the laser data, the exit velocity, and the particulate concentration. It is concluded that an LDV has the capability of determining both the mass concentration and the mass flow from a power-plant smoke stack.
Doppler ultrasonic blood flowmeters are reviewed in detail. The importance of measurement accuracy for transcutaneous flowmeters and their clinical application is stressed. Doppler imaging was combined with conventional pulse echo imaging, and diagnostic information was extracted from flow signals. The range and extent of applications of Doppler instruments was also presented.
Doppler ultrasound has become the most useful and versatile noninvasive technique for objective evaluation of clinical vascular disease. Commercially available continuous-wave instruments provide qualitative and quantitative assessment of venous and arterial disease. Pulsed Doppler ultrasound was developed to provide longitudinal and transverse cross-sectional images of the arterial lumen with a resolution approaching that of conventional X-ray techniques. Application of Doppler ultrasound in venous, peripheral arterial, and cerebrovascular diseases is reviewed.