Title: ImpDAR: an open-source impulse radar processor
Abstract Despite widespread use of radio-echo sounding (RES) in glaciology and broad distribution of processed radar products, the glaciological community has no standard software for processing impulse RES data. Dependable, fast and collection-system/platform-independent processing flows could facilitate comparison between datasets and allow full utilization of large impulse RES data archives and new data. Here, we present ImpDAR, an open-source, cross-platform, impulse radar processor and interpreter, written primarily in Python. The utility of this software lies in its collection of established tools into a single, open-source framework. ImpDAR aims to provide a versatile standard that is accessible to radar-processing novices and useful to specialists. It can read data from common commercial ground-penetrating radars (GPRs) and some custom-built RES systems. It performs all the standard processing steps, including bandpass and horizontal filtering, time correction for antenna spacing, geolocation and migration. After processing data, ImpDAR's interpreter includes several plotting functions, digitization of reflecting horizons, calculation of reflector strength and export of interpreted layers. We demonstrate these capabilities on two datasets: deep (~3000 m depth) data collected with a custom (3 MHz) system in northeast Greenland and shallow (<100 m depth, 500 MHz) data collected with a commercial GPR on South Cascade Glacier in Washington. more »« less
Crosby, C. J.; Arrowsmith, J R.; Nandigam, V.
(, Developments in earth surface processes)
Tarolli, P.; Mudd, S.
(Ed.)
High-resolution topography (HRT) is a powerful observational tool for studying the Earth's surface, vegetation, and urban landscapes, with broad scientific, engineering, and education-based applications. Submeter resolution imaging is possible when collected with laser and photogrammetric techniques using the ground, air, and space-based platforms. Open access to these data and a cyberinfrastructure platform that enables users to discover, manage, share, and process then increases the impact of investments in data collection and catalyzes scientific discovery. Furthermore, open and online access to data enables broad interdisciplinary use of HRT across academia and in communities such as education, public agencies, and the commercial sector. OpenTopography, supported by the US National Science Foundation, aims to democratize access to Earth science-oriented, HRT data and processing tools. We utilize cyberinfrastructure, including large-scale data management, high-performance computing, and service-oriented architectures to provide efficient web-based visualization and access to large, HRT datasets. OT colocates data with processing tools to enable users to quickly access custom data and derived products for their application, with the ultimate goal of making these powerful data easier to use. OT's rapidly growing data holdings currently include 283 lidar and photogrammetric, point cloud datasets (>1.2 trillion points) covering 236,364km2. As a testament to OT's success, more than 86,000 users have processed over 5 trillion lidar points. This use has resulted in more than 290 peer-reviewed publications across numerous academic domains including Earth science, geography, computer science, and ecology.
We present an open-source wireless network and data management system for collecting and storing indoor environmental measurements and perceived comfort via participatory sensing in commercial buildings. The system, called a personal comfort and indoor environment measurement (PCIEM) platform, consists of several devices placed in office occupants’ work areas, a wireless network, and a remote database to store the data. Each device, called a PCFN (personal comfort feedback node), contains a touchscreen through which the occupant can provide feedback on their perceived comfort on-demand, and several sensors to collect environmental data. The platform is designed to be part of an indoor climate control system that can enable personalized comfort control in real-time. We describe the design, prototyping, and initial deployment of a small number of PCFNs in a commercial building. We also provide lessons learned from these steps. Application of the data collected from the PCFNs for modeling and real-time control will be reported in future work. We use hardware components that are commercial and off-the-shelf, and our software design is based on open-source tools that are freely and publicly available to enable repeatability.
Young, Duncan; Greenbaum, Jamin S; Kerr, Megan E; Singh, Shivangini; Chan, Kristian; Buhl, Dillon P; Ng, Gregory C; Kempf, Scott D; Echeverry, Gonzalo; Blankenship, Donald D
(, Texas Data Repository)
These transect organized radargrams were collected as part of the Center for Oldest Ice Exploration (COLDEX) Science and Technology Center (https://www.coldex.org) in the 2022/23 (CXA1) airborne reconnaissance field season. The raw 3 TB data is deposited at the USAP data center at https://doi.org/10.15784/601768. Flight organized data with additional processing by the University of Kansas to remove electromagnetic interference can be found at the Open Polar Radar server (https://www.openpolarradar.org). The science goal was to characterize the ice sheet between Antarctica's Dome A and Amundsen Scott South Pole Station, to locate sites of interest for the drilling of an ice core with ages spanning the mid-Pleistocene. The radar was deployed on Balser C-FMKB, and flown at ranges of up to 800 km from South Pole Station at velocities of 90 m/s and typical altitude above ground of 600 m. Other instruments included a UHF array system provided by the University of Kansas, a gravity meter, a magnetometer, a laser altimeter, and multiple global navigation satellite systems receivers. The radar data is used for finding ice thickness, bed character, englacial structure and surface assessment. Dataset organization Transects are provided a P/S/T nomenclature, organized by the Project they are flying in, the acquisition System (typically named after the aircraft) and the Transect within the Project. Transects were collected in preplanned systems with the following parameters: CLX radials (CLX/MKB##/R###), attempting to emulate flow lines from Dome A and radiating (in the EPSG:3031 polar stereographic projection) from easting 965 km northing 385 km, with a separation of 0.25 degrees. CLX corridor (CLX/MKB##/X###) rotated from the EPSG:3031 polar stereographic projection at -150 degrees and separated by 10 km in the Y direction and 3.75 km in the X direction CLX2 corridor (CLX2/MKB##/X###) rotated from the EPSG:3031 polar stereographic projection at -150 degrees and separated by 2.5 km in its Y direction and 2.5 km in its X direction SAD corridor (SAD/MKB##/X###|Y####) designed to characterize the Saddle region near South Pole approximately perpendicular to the flow lines, rooted from the EPSG:3031 polar stereographic projection at -73.8 degrees and separated by 2.5 km in its Y direction and 2.5 km in the its X direction Untargeted transit lines used the name of the expedition (CXA1) as the project, and used the flight and the increment within the flight to name the Transect (eg (CXA1/MKB2n/F10T02a). Processing These data represent range compressed VHF radargrams as collected and analyzed in the field. The data are from the MARFA radar system, a 60 MHz ice penetrating radar system that has operated in several different guises over the years. MARFA operates with a 1 microsecond chirp with a design bandwidth of 15 MHz, allowing for ~8 range resolution. The record rate after onboard stacking is 200 Hz. High and low gain channels are collected from antennas on each side of the aircraft. In ground processing, the data were stacked 10x coherently to reduce range delayed incoherent surface scattering, and then stacked 5 times incoherently to improve image quality. In this preliminary processing, the effective resolution of deep scattering is several hundred meters due to range ambiguities at depth. Data format These data collection represents georeferenced, time registered instrument measurements (L1B data) converted to SI units. The data format are netCDF3 files, following the formats used for NASA/AAD/UTIG's ICECAP/OIB project at NASA's NSIDC DAAC (10.5067/0I7PFBVQOGO5). Metadata fields can be accessed using the open source ncdump tool, or c, python or matlab modules. A Keyhole Metadata Language (KML) file with geolocation for all transects is also provided. See https://www.loc.gov/preservation/digital/formats/fdd/fdd000330.shtml for resources on NetCDF-3, and https://nsidc.org/data/IR2HI1B/versions/1 for a description of the similar OIB dataset. Acknowledgements This work was supported by the Center for Oldest Ice Exploration, an NSF Science and Technology Center (NSF 2019719). We thank the NSF Office of Polar Programs, the NSF Office of Integrative Activities, and Oregon State University for financial and infrastructure support, and the NSF Antarctic Infrastructure and Logistics Program, and the Antarctic Support Contractor for logistical support. Additional support was provided by the G. Unger Vetlesen Foundation.
These transect organized radargrams were collected as part of the Center for Oldest Ice Exploration (COLDEX) Science and Technology Center (https://www.coldex.org) in the 2023/24 (CXA2) airborne reconnaissance field season. The raw 3 TB data is deposited at the USAP data center at https://doi.org/10.15784/601768. Flight organized data with additional processing by the University of Kansas to remove electromagnetic interference can be found at the Open Polar Radar server (https://www.openpolarradar.org). The science goal was to characterize the ice sheet between Antarctica's Dome A and Amundsen Scott South Pole Station, to locate sites of interest for the drilling of an ice core with ages spanning the mid-Pleistocene. The radar was deployed on Balser C-FMKB, and flown at ranges of up to 800 km from South Pole Station at velocities of 90 m/s and typical altitude above ground of 600 m. Other instruments included a UHF array system provided by the University of Kansas, a gravity meter, a magnetometer, a laser altimeter, and multiple global navigation satellite systems receivers. The radar data is used for finding ice thickness, bed character, englacial structure and surface assessment. Dataset organization Transects are provided a P/S/T nomenclature, organized by the Project they are flying in, the acquisition System (typically named after the aircraft) and the Transect within the Project. Transects were collected in preplanned systems with the following parameters: CLX radials (CLX/MKB##/R###), attempting to emulate flow lines from Dome A and radiating (in the EPSG:3031 polar stereographic projection) from easting 965 km northing 385 km, with a separation of 0.25 degrees. CLX corridor (CLX/MKB##/X###) rotated from the EPSG:3031 polar stereographic projection at -150 degrees and separated by 10 km in the Y direction and 3.75 km in the X direction CLX2 corridor (CLX2/MKB##/X###) rotated from the EPSG:3031 polar stereographic projection at -150 degrees and separated by 2.5 km in its Y direction and 2.5 km in its X direction NPXE radials (NPXE/MKB##/R####) primarily designed to survey the Upper Byrd Glacier Catchment, constitute spokes radiating from South Pole separated by 2 degrees, in the EPSG:3031 polar stereographic projection Untargeted transit lines used the name of the expedition (CXA2) as the project, and used the flight and the increment within the flight to name the Transect (eg (CXA2/MKB2n/F10T02a). Processing These data represent range compressed VHF radargrams as collected and analyzed in the field. The data are from the MARFA radar system, a 60 MHz ice penetrating radar system that has operated in several different guises over the years. MARFA operates with a 1 microsecond chirp with a design bandwidth of 15 MHz, allowing for ~8 meter range resolution. The record rate after onboard stacking is 200 Hz. High and low gain channels are collected from antennas on each side of the aircraft. In ground processing, the data were stacked 10x coherently to reduce range delayed incoherent surface scattering, and then stacked 5 times incoherently to improve image quality. In this preliminary processing, the effective resolution of deep scattering is several hundred meters due to range ambiguities at depth. Data format These data collection represents georeferenced, time registered instrument measurements (L1B data) converted to SI units. The data format are netCDF3 files, following the formats used for NASA/AAD/UTIG's ICECAP/OIB project at NASA's NSIDC DAAC (10.5067/0I7PFBVQOGO5). Metadata fields can be accessed using the open source ncdump tool, or c, python or matlab modules. A Keyhole Metadata Language (KML) file with geolocation for all transects is also provided. See https://www.loc.gov/preservation/digital/formats/fdd/fdd000330.shtml for resources on NetCDF-3, and https://nsidc.org/data/IR2HI1B/versions/1 for a description of the similar OIB dataset. Acknowledgements This work was supported by the Center for Oldest Ice Exploration, an NSF Science and Technology Center (NSF 2019719). We thank the NSF Office of Polar Programs, the NSF Office of Integrative Activities, and Oregon State University for financial and infrastructure support, and the NSF Antarctic Infrastructure and Logistics Program, and the Antarctic Support Contractor for logistical support. Additional support was provided by the G. Unger Vetlesen Foundation.
We present the design and field test results for a 600 to 900 MHz polarimetric ice penetrating radar that can be operated on the ground or from an airborne platform. This system is part of a development to build a dual band (VHF/UHF) polarimetric ice sounding radar suite. The VHF radar operates over 140-215 MHz and is essentially a modified version of the multi-channel 3D imaging system reported in [1]. The UHF radar, the focus of this work, is an adaptation of the CReSIS Accumulation Radar, which operates from 600 to 900 MHz [2]. The radar system uses a custom-designed, dual-polarized 4x4 antenna array with increased peak and average transmit power levels, which together provide additional sensitivity with respect to prior system renditions. The UHF radar incorporates a new receiver [3] that uses controlled analog compression via RF limiters to increase the instantaneous dynamic range. We designed the instrument setup to be towed by snowmobiles and operated at nominal speeds of 4 to 8 m/s. The relatively slow motion helps improve SNR through an increase in coherent averaging due to the longer dwell time. Although the focus of the field test is on ground-based work, the electronics are designed to also support airborne operation.
Lilien, David A., Hills, Benjamin H., Driscol, Joshua, Jacobel, Robert, and Christianson, Knut. ImpDAR: an open-source impulse radar processor. Retrieved from https://par.nsf.gov/biblio/10173862. Annals of Glaciology . Web. doi:10.1017/aog.2020.44.
Lilien, David A., Hills, Benjamin H., Driscol, Joshua, Jacobel, Robert, & Christianson, Knut. ImpDAR: an open-source impulse radar processor. Annals of Glaciology, (). Retrieved from https://par.nsf.gov/biblio/10173862. https://doi.org/10.1017/aog.2020.44
@article{osti_10173862,
place = {Country unknown/Code not available},
title = {ImpDAR: an open-source impulse radar processor},
url = {https://par.nsf.gov/biblio/10173862},
DOI = {10.1017/aog.2020.44},
abstractNote = {Abstract Despite widespread use of radio-echo sounding (RES) in glaciology and broad distribution of processed radar products, the glaciological community has no standard software for processing impulse RES data. Dependable, fast and collection-system/platform-independent processing flows could facilitate comparison between datasets and allow full utilization of large impulse RES data archives and new data. Here, we present ImpDAR, an open-source, cross-platform, impulse radar processor and interpreter, written primarily in Python. The utility of this software lies in its collection of established tools into a single, open-source framework. ImpDAR aims to provide a versatile standard that is accessible to radar-processing novices and useful to specialists. It can read data from common commercial ground-penetrating radars (GPRs) and some custom-built RES systems. It performs all the standard processing steps, including bandpass and horizontal filtering, time correction for antenna spacing, geolocation and migration. After processing data, ImpDAR's interpreter includes several plotting functions, digitization of reflecting horizons, calculation of reflector strength and export of interpreted layers. We demonstrate these capabilities on two datasets: deep (~3000 m depth) data collected with a custom (3 MHz) system in northeast Greenland and shallow (<100 m depth, 500 MHz) data collected with a commercial GPR on South Cascade Glacier in Washington.},
journal = {Annals of Glaciology},
author = {Lilien, David A. and Hills, Benjamin H. and Driscol, Joshua and Jacobel, Robert and Christianson, Knut},
}
Warning: Leaving National Science Foundation Website
You are now leaving the National Science Foundation website to go to a non-government website.
Website:
NSF takes no responsibility for and exercises no control over the views expressed or the accuracy of
the information contained on this site. Also be aware that NSF's privacy policy does not apply to this site.
An official website of the United States government
