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At least 1,171 records · Page 65

GPS/Magnetometer Based Satellite Navigation and Attitude Determination

In recent years algorithms were developed for orbit, attitude and angular-rate determination of Low Earth Orbiting (LEO) satellites. Those algorithms rely on measurements of magnetometers, which are standard, relatively inexpensive, sensors that are normally installed on every LEO satellite. Although magnetometers alone are sufficient for obtaining the desired information, the convergence of the algorithms to the correct values of the satellite orbital parameters, position, attitude and angular velocity is very slow. The addition of sun sensors reduces the convergence time considerably. However, for many LEO satellites the sun data is not available during portions of the orbit when the spacecraft (SC) is in the earth shadow. It is here where the GPS space vehicles (SV) can provide valuable support. This is clearly demonstrated in the present paper. Although GPS measurements alone can be used to obtain SC position, velocity, attitude and angular-rate, the use of magnetometers improve the results due to the synergistic effect of sensor fusion. Moreover, it is possible to obtain these results with less than three SVs. In this paper we introduce an estimation algorithm, which is a combination of an Extended Kalman Filter (EKF) and a Pseudo Linear Kalman Filter (PSELIKA).

Deutschmann, Julie↗

Teaching About the Sun-Earth Connection

This talk will be about the Sun: how it changes with time, its magnetic cycle, flares, and the solar wind. The solar wind and what space is like between the Sun and Earth will be presented. Also, the Earth, its magnetic field, how the solar wind interacts with the Earth, Aurora, and how these affect human systems will be discussed. These interactions dictate how we build our systems in space (communications satellites, GPS, etc), and some of our ground systems (power grids). Some simple classroom activities will be presented that can be done using new data from space that is available daily on the internet, and how you can use the internet to get space questions answered within about 1 day. Finally, some career opportunities for jobs related to space for the future will be discussed.

Poland, Arthur I.↗

Use of IRI to Model the Effect of Ionosphere Emission on Earth Remote Sensing at L-Band

Microwave remote sensing in the window at 1.413 GHz (L-band) set aside for passive use only is important for monitoring sea surface salinity and soil moisture. These parameters are important for understanding ocean dynamics and energy exchange between the surface and atmosphere, and both NASA and ESA plan to launch satellite sensors to monitor these parameters at L-band (Aquarius, Hydros and SMOS). The ionosphere is an important source of error for passive remote sensing at this frequency. In addition to Faraday rotation, emission from the ionosphere is also a potential source of error at L-band. As an aid for correcting for emission, a regression model is presented that relates ionosphere emission to the integrated electron density (TEC). The goal is to use TEC from sources such as TOPEX, JASON or GPS to obtain estimates of emission over the oceans where the electron density profiles needed to compute emission are not available. In addition, data will also be presented to evaluate the use of the IRI for computing emission over the ocean.

Abraham, Saji↗

New Applications for the Testing and Visualization of Wireless Networks

Traditional techniques for examining wireless networks use physical link characteristics such as Signal-to-Noise (SNR) ratios to assess the performance of wireless networks. Such measurements may not be reliable indicators of available bandwidth. This work describes two new software applications developed at NASA Glenn Research Center for the investigation of wireless networks. GPSIPerf combines measurements of Transmission Control Protocol (TCP) throughput with Global Positioning System (GPS) coordinates to give users a map of wireless bandwidth for outdoor environments where a wireless infrastructure has been deployed. GPSIPerfView combines the data provided by GPSIPerf with high-resolution digital elevation maps (DEM) to help users visualize and assess the impact of elevation features on wireless networks in a given sample area. These applications were used to examine TCP throughput in several wireless network configurations at desert field sites near Hanksville, Utah during May of 2004. Use of GPSIPerf and GPSIPerfView provides a geographically referenced picture of the extent and deterioration of TCP throughput in tested wireless network configurations. GPSIPerf results from field-testing in Utah suggest that it can be useful in assessing other wireless network architectures, and may be useful to future human-robotic exploration missions.

Griffin, Robert I.↗

Guidance, Navigation, and Control Performance for the GOES-R Spacecraft

The Geostationary Operational Environmental Satellite-R Series (GOES-R) is the first of the next generation geostationary weather satellites. The series represents a dramatic increase in Earth observation capabilities, with 4 times the resolution, 5 times the observation rate, and 3 times the number of spectral bands. GOES-R also provides unprecedented availability, with less than 120 minutes per year of lost observation time. This paper presents the Guidance Navigation & Control (GN&C) requirements necessary to realize the ambitious pointing, knowledge, and Image Navigation and Registration (INR) objectives of GOES-R. Because the suite of instruments is sensitive to disturbances over a broad spectral range, a high fidelity simulation of the vehicle has been created with modal content over 500 Hz to assess the pointing stability requirements. Simulation results are presented showing acceleration, shock response spectra (SRS), and line of sight (LOS) responses for various disturbances from 0 Hz to 512 Hz. Simulation results demonstrate excellent performance relative to the pointing and pointing stability requirements, with LOS jitter for the isolated instrument platform of approximately 1 micro-rad. Attitude and attitude rate knowledge are provided directly to the instrument with an accuracy defined by the Integrated Rate Error (IRE) requirements. The data are used internally for motion compensation. The final piece of the INR performance is orbit knowledge, which GOES-R achieves with GPS navigation. Performance results are shown demonstrating compliance with the 50 to 75 m orbit position accuracy requirements. As presented in this paper, the GN&C performance supports the challenging mission objectives of GOES-R.

Control↗

Spinoff 2015

Topics covered include: 3D Endoscope to Boost Safety, Cut Cost of Surgery; Audio App Brings a Better Night's Sleep Liquid Cooling Technology Increases Exercise Efficiency; Algae-Derived Dietary Ingredients Nourish Animals; Space Grant Research Launches Rehabilitation Chair; Vision Trainer Teaches Focusing Techniques at Home; Aircraft Geared Architecture Reduces Fuel Cost and Noise; Ubiquitous Supercritical Wing Design Cuts Billions in Fuel Costs; Flight Controller Software Protects Lightweight Flexible Aircraft; Cabin Pressure Monitors Notify Pilots to Save Lives; Ionospheric Mapping Software Ensures Accuracy of Pilots' GPS; Water Mapping Technology Rebuilds Lives in Arid Regions; Shock Absorbers Save Structures and Lives during Earthquakes; Software Facilitates Sharing of Water Quality Data Worldwide; Underwater Adhesives Retrofit Pipelines with Advanced Sensors; Laser Imaging Video Camera Sees through Fire, Fog, Smoke; 3D Lasers Increase Efficiency, Safety of Moving Machines; Air Revitalization System Enables Excursions to the Stratosphere; Magnetic Fluids Deliver Better Speaker Sound Quality; Bioreactor Yields Extracts for Skin Cream; Private Astronaut Training Prepares Commercial Crews of Tomorrow; Activity Monitors Help Users Get Optimum Sun Exposure; LEDs Illuminate Bulbs for Better Sleep, Wake Cycles; Charged Particles Kill Pathogens and Round Up Dust; Balance Devices Train Golfers for a Consistent Swing; Landsat Imagery Enables Global Studies of Surface Trends; Ruggedized Spectrometers Are Built for Tough Jobs; Gas Conversion Systems Reclaim Fuel for Industry; Remote Sensing Technologies Mitigate Drought; Satellite Data Inform Forecasts of Crop Growth; Probes Measure Gases for Environmental Research; Cloud Computing Technologies Facilitate Earth Research; Software Cuts Homebuilding Costs, Increases Energy Efficiency; Portable Planetariums Teach Science; Schedule Analysis Software Saves Time for Project Planners; Sound Modeling Simplifies Vehicle Noise Management; Custom 3D Printers Revolutionize Space Supply Chain; Improved Calibration Shows Images' True Colors; Micromachined Parts Advance Medicine, Astrophysics, and More; Metalworking Techniques Unlock a Unique Alloy; Low-Cost Sensors Deliver Nanometer-Accurate Measurements; Electrical Monitoring Devices Save on Time and Cost; Dry Lubricant Smooths the Way for Space Travel, Industry; and Compact Vapor Chamber Cools Critical Components.

Source record↗

First results of GPS time transfer to Australia

A Global Positioning System time transfer unit built by NBS under contract to JPL was installed at Tidbinbilla Deep Space Communications Complex of the NASA Deep Space Network in June 1983. It has been used to estimate the relationship to UTC(USNO MC) of the Tidbinbilla frequency and time system TID(FTS) based on a hydrogen maser, and thence to estimate the performance of the Australian free-running time scale UTC(AUS). Data from the first three months has been analyzed three ways: by two-hop common view using JPL as intermediary; by long-arc interpolation of measurements against space vehicle clocks; and by long-arc interpolation of GPS-Time results. Residuals from a single quadratic fit through three months of UTC(USNO MC) - TID (FTS) results were white noise with standard error 15 ns, and a flying clock measurement gave 70 ns agreement. A straight line fit through results UTC(USNO MC) - UTC (AUS) gave 90 ns standard error and 120 bns agreement. It is proposed to use the GPS measurements to steer UTS(AUS) to UTC(BIH), and to rename the existing time scale TA(AUS).

Luck, J. M.↗

Survey Parameters and Availability of Low-level Aeromagnetic Data for Geomagnetic Field Modelling

Since aeromagnetic surveying started immediately after World War II, a considerable area of the earth's surface both onshore (in excess of 25 million sq. km) has been magnetically surveyed. For about the first 15 years or so, fluxgate magnetometers were employed in aeromagnetic surveys, but the introduction of proton free-precession magnetometers resulted in absolute readings being recorded. Proton precession magnetometers have now been replaced to a large extent by the more sensitive optical absorption magnetometers. Some care has to be taken to calibrate aeromagnetic survey systems and this is best done using a calibration range tied to a magnetic observatory so that accuracies of 10nT or better are achieved for the total field values recorded. Survey navigation has always posed a problem for aeromagnetic surveys, especially offshore. Over land, vertically pointed 35 mm cameras were initially used to recover the aircraft track using a combination of aerial photos and topographic maps. Over featureless areas, it was necessary to utilize existing electronic positioning systems such as Loran C or set up special navigation systems. The advent of the satellite-based Global Positioning Systems (GPS) has to a larger extent solved the navigational problem because there is now almost continuous worldwide coverage to 10 m accuracy in the differential mode. The resultant aeromagnetic data is normally compiled into contour maps in which the diurnal variation and aircraft heading effects are removed. The resultant digital data are normally made publicly available both in gridded and profile form along with the published contour maps. Most aeromagnetic coverage has been obtained in the developed western countries, but elsewhere a considerable amount of surveying has been carried out; as an example, some 80 percent of Africa has been surveyed mostly as a result of aid programs. The data is usually held by the national geological survey or equivalent organizations, but in a number of cases the data (e.g., for the Magnetic Anomaly Map of North America) is also held by the World Data Centres.

Hood, Peter↗

Temperature, Humidity, and Time-Lapse Video Data from the East River Watershed, Water Year 2024

A new version of this dataset is available at doi:10.15485/3001338 and is the first citation in the 'Related References' section. It is expands on this dataset by appending another water year of data collection and additional logger sites.This dataset contains time-lapse imagery and distributed measurements of air temperature, relative humidity, dew point, and soil temperature across the East River basin from 3 October 2023 to 12 August 2024. Instruments were deployed at 14 sites as part of the DOE Grant: Seasonal Cycles Unravel Mysteries of Missing Mountain Water organized by Jessica Lundquist (University of Washington), Rosemary Carroll (Desert Research Institute), and Ethan Gutmann (National Center for Atmospheric Research). The data are published to support studies of surface climate or hydrologic processes in complex terrain. Measurements were collected with low-cost data loggers installed 2 m high on evergreen trees or buried just below the soil surface. Time-lapse cameras were deployed at three sites. Imagery from sites AP BONUS and AP5 provides insight into large-scale seasonal snow cover variability. Imagery from site EL2 shows smaller-scale snow patterns across a nearby meadow.Dataset files are organized by site and variable (air measurements, ground measurements, or time-lapse video). Air and ground measurements are packaged in LoggerData.zip, and time-lapse imagery is compiled into short videos stored in TimelapseVideos.zip. File-level metadata contains details for each file included in the dataset. A data dictionary provides units and descriptions for column or row names in all files. The locations metadata file describes site characteristics, locations, and associated GPS methods.Dataset update 2025-03-03: Resolved header and datetime formatting inconsistencies within LoggerData.zip files KP1_Air, KP3_Air, KP3_Ground, KP6_Ground, AP3_Ground, AP4_Air, and AP6_Air.Dataset update 2025-11-18: Modified abstract and related references sections to include new version of dataset.

54 ENVIRONMENTAL SCIENCES↗

Temperature, Humidity, and Time-Lapse Video Data from Yosemite National Park, Water Year 2024

This dataset contains time-lapse imagery and distributed measurements of air temperature, relative humidity, dew point, and soil temperature across Yosemite National Park from October 2023 to September 2024. Instruments were deployed at 10 sites in two cross-valley transects as part of the DOE Grant: Seasonal Cycles Unravel Mysteries of Missing Mountain Water organized by Jessica Lundquist (University of Washington), Rosemary Carroll (Desert Research Institute), and Ethan Gutmann (National Center for Atmospheric Research). The data are intended to support hydrologic modeling efforts to better resolve the fate of mountain water, and are published to support studies of surface climate or hydrologic processes in complex terrain. Measurements were collected with low-cost data loggers installed 2 m high on evergreen trees or buried just below the soil surface. A time-lapse camera at one site captures valley-scale seasonal snow cover variability.Dataset files are organized by site and variable (air measurements, ground measurements, or time-lapse video). Air and ground measurements are packaged in LoggerData.zip, and time-lapse imagery is compiled into a short video stored in TimelapseVideos.zip. File-level metadata contains details for each file included in the dataset. A data dictionary provides units and descriptions for column or row names in all files. The locations metadata file describes site characteristics, locations, and associated GPS methods.

54 ENVIRONMENTAL SCIENCES↗

Temperature, Humidity, and Time-Lapse Video Data from the East River Watershed, Water Years 2024 and 2025

This dataset contains time-lapse imagery and distributed measurements of air temperature, relative humidity, dew point, and soil temperature across the East River basin from 3 October 2023 to 8 August 2025. Instruments were deployed at 19 sites as part of the DOE Grant: Seasonal Cycles Unravel Mysteries of Missing Mountain Water organized by Jessica Lundquist (University of Washington), Rosemary Carroll (Desert Research Institute), and Ethan Gutmann (National Center for Atmospheric Research). The data are published to support studies of surface climate or hydrologic processes in complex terrain. Measurements were collected with low-cost data loggers installed 2 m high on evergreen trees or buried just below the soil surface. Time-lapse cameras were deployed at three sites. Imagery from sites AP BONUS and AP5 (Avery Picnic) provides insight into large-scale seasonal snow cover variability. Imagery from site EL2 (Emerald Lake) shows smaller-scale snow patterns across a nearby meadow. Dataset files are organized by site and variable (air measurements, ground measurements, or time-lapse video). Air and ground measurements are packaged in LoggerData.zip, and time-lapse imagery is compiled into short videos stored in TimelapseVideos.zip. File-level metadata contains details for each file included in the dataset. A data dictionary provides units and descriptions for column or row names in all files. The locations metadata file describes site characteristics, locations, and associated GPS methods.

54 ENVIRONMENTAL SCIENCES↗

Improved treatment of global positioning system force parameters in precise orbit determination applications

Data collected from a worldwide 1992 experiment have been processed at JPL to determine precise orbits for the satellites of the Global Positioning System (GPS). A filtering technique has been tested to improve modeling of solar-radiation pressure force parameters for GPS satellites. The new approach improves orbit quality for eclipsing satellites by a factor of two, with typical results in the 25- to 50-cm range. The resultant GPS-based estimates for geocentric coordinates of the tracking sites, which include the three DSN sites, are accurate to 2 to 8 cm, roughly equivalent to 3 to 10 nrad of angular measure.

Y Vigue↗

Precision orbit determination using TOPEX/Poseidon TDRSS observations

The TOPEX/Poseidon (T/P) Mission carries a variety of packages to support experimental, precision and operational orbit determination. Included are a GPS transponder, laser retro-reflectors, the French-developed Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) Doppler tracking system and a Tracking Data Relay Satellite System (TDRSS) transponder. Presently, TDRSS tracking is used for operational orbit support and is processed with force and measurement modeling consistent with this purpose. However, the low noise and extensive geographical coverage of the TDRSS/TOPEX data allows an assessment of TDRSS Precision Orbit Determination (POD) capabilities by comparison to the T/P precision orbit determination. The Geodynamics (GEODYN) Orbit Determination System is used to process laser and DORIS data to produce the precision orbits for the T/P Project. GEODYN has been modified recently to support the TDRSS observations. TDRSS data analysis can now benefit from the extensive force modeling and reference frame stability needed to meet the orbit determination (OD) goals of the T/P Mission. This analysis has concentrated on the strongest of the TDRSS measurement types, its two-way average range rate. Both the TDRSS and T/P orbits have been assessed in combination with the global satellite laser ranging (SLR) data and by themselves. These results indicate that significant improvement in the TDRSS ephemerides is obtained when the T/P orbit is well determined by SLR, and the TDRSS/TOPEX Doppler link is used to position TDRSS. Meter-level TDRSS positioning uncertainty is achieved using this approach. When the TDRSS orbit location is provided by this approach, the two-way range rate from a single TDRSS (i.e. West only) can provide T/P orbits with sub-meter radial accuracies and two meter RMS total position agreement with SLR defined orbits. These preliminary results indicate improved modeling of the TDRSS measurement through the elimination of heretofore neglected effects like the motion of the T/P TDRSS antenna and improved modeling of ionospheric and atmospheric refractive effects, and the inclusion of TDRSS East in the analysis are warranted. Through these improvements, TDRSS can make a significant contribution to geopotential recovery and precision OD.

Teles, Jerome↗

Trajectory Reconstruction and Measurement Techniques

The filter/smoother combination provides the most accurate means of trajectory reconstruction. Not all parameters of interest can be determined from a given flight test data set: need to check observability. A variety of ground & onboard sensors may be used; trend appears to be toward increasing reliance on onboard GPS.

Carpenter, J. Russell↗

Coastal Changes in Temperature and Salinity Observed during Hurricane Isaac Recorded and Downloaded by NASA DRIFTERs Moored in Heron Bay and at Half Moon Island, Louisiana

Major changes in salinity (approx.14 ppt.) and temperature (approx.40C) were continuously registered by two prototype NASA DRIFTERs, surface moored floaters, that NASA's Applied Science and Technology Project Office (ASTPO) has developed. The DRIFTER floating sensor module is equipped with an Arduino open-source electronics prototyping platform and programming language (http://www.arduino.cc), a GPS (Global Positioning System) module with antenna, a cell phone SIM (Subscriber Identity Module) card and a cellular antenna which is used to transmit data, and a probe to measure temperature and conductivity (from which salinity can be derived). The DRIFTER is powered by a solar cell panel and all the electronic components are mounted and sealed in [ waterproof encasement. Position and measurement data are transmitted via short message service (SMS) messaging to a Twitter site (DRIFTER 002@NASADRIFTER_002 and DRIFTER 004@NASADRIFTER_004), which provides a live feed. These data are the imported into a Google spreadsheet where conductivity is converted to salinity, and graphed in real-time. The spreadsheet data will be imported into a webpage maintained by ASTPO, where it will be displayed available for dO\\1lload.

Kalcic, Maria↗

Continuous snow depth and temperature measurements from dense network of above-ground distributed temperature profiling systems from 2021-09-23 to 2024-08-23, Seward Peninsula, Alaska

The dataset contains temperature measurements from distributed temperature profiling (DTP) systems (Dafflon et al., 2022; Wielandt et al., 2022; Wang et al., 2024a; Fiolleau et al., 2024) deployed vertically above the ground surface at a large number of locations from 2021 to 2024. The research is designed to improve understanding of the local heterogeneity in snow depth and snow thermal insulation dynamics, as well as their interactions in a discontinuous permafrost region (Wang et al., 2025). The DTP systems were deployed at 96 locations in a watershed along the Nome-Teller road at mile marker 27 (T27) and at 54 locations on a hillslope along the Kougarok road at mile marker 64 (K64) in the Seward Peninsula, Alaska. The probe location information is stored in Probe_locations_T27.csv and Probe_locations_K64.csv. Temperature measurements were recorded at 15-minute intervals using high-precision digital sensors (accuracy: ±0.1°C, resolution: 0.0078°C). The temperature probes, either 1.4 m or 1.6 m long, contain sensors spaced every 5 cm or 10 cm along their length. The temperature data are stored in compressed files following the format: DTP_snow_air_temperature_(site)_(start)_(end).zip, where site is either T27 or K64, and start and end represent the time series period. Within each ZIP file, individual CSV files are named by probe ID and contain temperature records at different heights above the ground surface.This dataset also includes derived snow depth time series over three snow seasons, estimated from temperature measurements. Snow depth was estimated by identifying the consecutive sensor pair that exhibited the largest drop in high-frequency temperature fluctuations (detailed in the methods). These data are stored in: Snow_depths_flags_(site)_(start)_(end).csv, which includes snow depth time series and corresponding quality flags (defined in the methods) from different probes. Additionally, the dataset includes derived metrics and supporting measurements at selected locations over two snow seasons, contributing to the manuscript of Wang et al., 2025. These locations were chosen based on the availability of high-quality snow depth time series during both seasons. The additional data include: (1) Air temperature proxies measured from the top sensors on the pole when they were not buried by snow, stored in Air_temperature_proxies_(site)_(start)_(end).csv (2) Ground interface temperature, recorded at 3 cm above the ground, stored in Ground_interface_temperature_(site)_(start)_(end).csv (3) Site characteristics, including vegetation height, elevation, and the topographic position index (TPI) within a 50 m radius, stored in Selected_probe_locations_gps_vegheight_tpi_elevation_(site).csv. These metrics were derived from 1 m resolution summer LiDAR-based digital elevation models and digital surface models from Singhania et al., 2023, DOI:10.5440/1832016. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv.This dataset is an updated version of a previous archive (Wang et al., 2024b, DOI: 10.15485/2475020), incorporating multiple seasons and improved snow depth estimation. Please note that due to large amount of information present in this dataset, many specificities associated with the acquisition of snow temperature, air temperature proxy and estimation of snow depth, and the future archiving of additional datasets on the soil temperature, thaw depth and soil characteristics at these locations, the author would welcome being contacted by people planning to use this dataset.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Differentially Private Map Matching (DPMM) v1.0

Human mobility trajectories provide valuable information for developing mobility applications, as they contain diverse and rich information about the users. User mobility data is valuable for various applications such as intelligent transportation systems (ITS), commercial business models, and disease-spread models. However, such spatio-temporal traces may pose a threat to user privacy. GPS trajectories in their raw form are not suitable for transportation studies, as they require matching locations with nearest road links — a process called map-matching. This software implements a differential privacy (DP)-based map-matching algorithm, called DPMM, that generates link-level location trajectories in a privacy-preserving manner to protect users' origin destinations (OD) and travel paths. OD privacy is achieved by injecting Planar Laplace noise to the user OD GPS points. Travel-path privacy is provided with randomized travel path construction using exponential DP mechanism. The injected noise level is selected adaptively, by considering the link density of the location and the functional category of the localized links. For path privacy, our mechanism samples waypoints and selects candidate paths between waypoints. DPMM provides privacy effectively with respect to link density instead of other trajectory samples in the database compared to other privacy mechanisms. Compared to the different baseline models our DP-based privacy model offers closer query responses to the raw data in terms of individual and aggregate trajectory-level statistics with an average at absolute deviation from the baseline for individual statistics on ϵ = 1.0. Beyond individual trajectory statistics, the DPMM outperforms the other benchmark DP-based mechanisms on different aggregate statistics with up to 8x improvement in utility.

Peisert, Sean [Lawrence Berkeley National Laborato↗

Efficient detection and signal parameter estimation with application to high dynamic GPS receiver

In a system for deriving position, velocity, and acceleration information from a received signal emitted from an object to be tracked wherein the signal comprises a carrier signal phase modulated by unknown binary data and experiencing very high Doppler and Doppler rate, this invention provides combined estimation/detection apparatus for simultaneously detecting data bits and obtaining estimates of signal parameters such as carrier phase and frequency related to receiver dynamics in a sequential manner. There is a first stage for obtaining estimates of the signal parameters related to phase and frequency in the vicinity of possible data transitions on the basis of measurements obtained within a current data bit. A second stage uses the estimates from the first stage to decide whether or not a data transition has actually occurred. There is a third stage for removing data modulation from the received signal when a data transition has occurred and a fourth stage for using the received signal with data modulation removed therefrom to update global parameters which are dependent only upon receiver dynamics and independent of data modulation. Finally, there is a fifth stage for using the global parameters to determine the position, velocity, and acceleration of the object.

Kumar, Rajendra↗