Flowfinity Wireless, Inc., a provider of enterprise mobile applications, has announced a solution that enables businesses to quickly create and deploy mobile surveys for offline data collection and submission to a centralized database. Flowfinity’s survey customization and integration features help businesses improve productivity through better management of information collected in the field, the company said.
Survey data can be captured anywhere, even in locations without network coverage such as job sites, retail store stock rooms, or manufacturing plants. Feedback submitted in real time to a Flowfinity database provides actionable insights that allow businesses to improve efficiency and identify issues that require immediate attention, the company said. Information stored in the database such as survey results, locations, or customer data can also be easily retrieved on mobile devices.
Flowfinity mobile surveys configured using a point-and-click web-based editor can include dynamic fields such as checklists, drop-down menus, photos, signature capture, and GPS locations. Conditional field visibility allows users to be guided through the survey form based on previous answers. As soon as surveys are created, they can be immediately published to different user groups based on user permissions.
“Flowfinity helps businesses collect and access the information they need in the field, so that they can eliminate inefficient paper and spreadsheet processes,” says Larry Wilson, VP of Sales and Marketing, Flowfinity. “While many mobile survey solutions offer simple one-way data submission, Flowfinity provides two-way access to survey data from a centralized database, allowing feedback to be viewed or submitted anytime, anywhere.”
Flowfinity mobile survey software is available as a fully cloud-hosted or on-premise deployed solution.
Photo: TrimbleTrimble has introduced the Trimble MX2 mobile spatial imaging data capture system. The MX2 extends the capabilities of geospatial professionals, allowing them to safely and effectively address complex projects by collecting spatial data from a mobile scanning platform, the company said. The Trimble MX2 provides a versatile and complimentary addition to Trimble’s family of mobile data capture systems.
Designed for mapping, surveying and engineering environments, the MX2 is rugged, lightweight and portable. It is also easily deployed and redeployed on projects similar to conventional surveying equipment. A precise laser scanner, along with an embedded Trimble-Applanix GNSS/Inertial positioning system, allows geospatial professionals to create the point cloud accuracies necessary for many spatial imaging projects. Accompanied by Trimble Trident software to capture, process and analyze point data, the MX2 offers a ready-to-use workflow for surveyors and professionals in mapping, engineering, planning, oil and gas, utilities, mining, environmental, public safety and more. The system is available in single and dual-laser versions.
In conjunction with the MX2 system, Trimble also announced new features for its Trident Software 6.0. The software developed for rapid transformation of point clouds and imagery into geospatial intelligence has been significantly enhanced to provide a scalable software suite for a wide range of users. Additions include the incorporation of direct trajectory import and the Trimble Coordinate System Manager. The Trimble Trident software suite is ideal for the analysis of mobile laser scanner data and geo-referenced imagery.
“The Trimble MX2 provides survey companies with the opportunity to enter the world of mobile scanning at a time when it is becoming a desired service within their solution portfolios,” said Katherine Sandford, general manager of Trimble’s Imaging Division. “The MX2 offers a simple and highly productive mobile data collection capability and a 3D point cloud workflow for a wide range of users.”
Septentrio NV, the Belgian manufacturer of high-end GNSS receivers, and Esri BeLux, the regional distributor of Esri software, have joined forces to offer a user-friendly mobile solution that is accurate up to 1 centimeter. The combination of Esri software and the AsteRx-m GeoPod operates seamlessly using standard, open interfaces on any professional tablet. Used today by a major utility company, the new bundled solution allows anyone in the organization to accurately locate field assets and record geo-referenced data on the spot, Septentrio said.
The AsteRx-m GeoPod upgrades professional tablet PCs with a high accuracy GNSS receiver, giving the user access to sub-meter, or even centimeter, accurate positions without needing specialized equipment. Using a standard USB connection, the AsteRx-m GeoPod can be connected to any professional tablet, giving the user free choice to select a device.
The receiver uses satellites from the GPS and GLONASS constellations to increase the availability of a high-quality position solution, even in areas with bad satellite visibility. In addition, the receiver offers innovative tracking and positioning algorithms designed for demanding professional environments.
The included RxAssitant software takes care of configuring the receiver and connecting to NTRIP-capable RTK or DGNSS networks, allowing a seamless integration with existing software applications like esri ArcGIS for mobile.
Applications for the AsteRx-m GeoPod include construction, field service, utility mapping, highway maintenance, government mapping and emergency services.
Trimble has introduced its next-generation Unmanned Aircraft System (UAS) — the Trimble UX5 aerial imaging rover with the Trimble Access aerial imaging application. The new solution builds upon the strengths of its predecessor, the Trimble Gatewing X100, to offer enhanced image quality and intuitive workflows. Combined with the Trimble Business Center photogrammetry office software module, the Trimble UX5 is the a complete UAS photogrammetric mapping solution specifically designed for surveyors and geospatial professionals.
Trimble’s UAS for photogrammetric aerial mapping allows surveyors and geospatial professionals to collect data with an unmanned aircraft for large projects. A wide variety of traditional surveying applications such as topographic surveying, site and route planning, progress monitoring, volume calculations, disaster analysis and as-builts in industries such as surveying, oil and gas, mining, environmental services, and agriculture can now benefit from aerial imaging by allowing professionals to safely collect large amounts of accurate data in a short time.
“With the recent introduction of the Trimble Business Center photogrammetry module and now the Trimble UX5 and Trimble Access aerial imaging application, Trimble continues to pioneer the development of UAS photogrammetry data collection and integration for geospatial professionals,” said Erik Arvesen, vice president of Trimble’s Survey Division. “The complete solution represents a significant leap in efficiency, transforming traditional workflows with faster data collection, easier processing and enhanced deliverables.”
The new Trimble Access aerial imaging application is field software for planning UAS missions, performing flight checks and monitoring flights — all with intuitive workflows. The imaging application is used to define the project area, avoidance zones, and flight parameters as well as take-off and landing locations. In the field, it is used to perform pre- and post-flight checks and download the flight data and images after landing. The new wizard-like digital checklists give the operator a complete “to-do list” so critical steps are not bypassed or missed in the field that can enhance reliable and safe flights. The software also includes fixed post-flight procedures to ensure that operators do not leave the field with a dataset that is incomplete or inconsistent.
The Trimble UX5 can provide a safer method to collect data compared to traditional surveying methods, Trimble said. Flights are fully automated, from launch to landing, and require no piloting skills. The operator facilitates the aircraft’s operation and built-in safety procedures can ensure safe and successful launches. Data collection can be performed remotely without exposing individuals to hazardous terrain, environmental contaminants or heavy equipment and machinery.
The Trimble UX5 unmanned system in use at a construction site. Photo: Trimble
The Trimble UX5 aerial imaging rover has been designed to follow the latest developments in the “prosumer” camera market, providing optimal image quality along with maximum photogrammetric accuracy.
Incorporating a mirrorless 16-megapixel camera with a fixed focal-length external lens, the Trimble UX5 provides high-resolution imagery and accurate deliverables. The large field of view from the camera allows the UX5 to cover 50-75 percent more area to enhance efficiency and reduce operational costs. In addition to the increase in flight efficiency, the Trimble UX5 is capable of producing 3D surface deliverables with a ground sampling distance of approximately 2.4 centimeters (approximately 1.0 inch).
Designed to operate in real-world conditions, the Trimble UX5 is capable of flights between 75 and 750 meters (approximately 246 and 2,460 feet) above ground level and can be flown in light rain and windy conditions, up to 65 kph (approximately 40 mph).
The Trimble UX5 airframe is comprised of a carbon frame inside expanded polypropylene. Impact-resistant plastics and composite fibers are used for the aircraft components, including winglets and belly plate. This design and choice of materials results in a rigid aircraft with strong torsional stability and the ability to withstand rough landings.
Performance enhancements also include the ability to execute steep landing approaches and thrust reversal for accurate and repeatable landings. The landing procedure starts 300 meters (approximately 984 feet) from the landing location allowing the UX5 to be used for jobs that have site restrictions such as buildings, towers or trees.
Orthophotos, contour maps, point clouds, digital surface models (DSMs) and feature maps can easily be created from aerial images using the Trimble Business Center photogrammetry module. Single-click processing for stitching images streamlines the office process for generating powerful deliverables, Trimble said.
The Trimble Business Center allows surveyors and other geospatial professionals to combine aerial photography with data collected from GNSS receivers, total stations, 3D laser scanners and more. By combining imagery from the Trimble UX5 and any Trimble VISION instruments, users can visualize their project from both aerial and terrestrial perspectives, measure points within the images and create 3D models of the infrastructure and terrain.
The conference GeoGathering: GIS for Gathering and Production Lines will be held Colorado Springs at the Cheyenne Mountain Resort on August 21-22, 2013. With the theme of “Developing a Data Strategy: Data Collection and Sharing,” the conference focuses on how operators collect and share information about their assets to increase operational safety and improve pipeline decision-making.
“Today, acquisitions and fast growth in the gathering industry are forcing operators to develop a data strategy and look deeper at all aspects of their pipeline asset data – from how it is collected, to making it available to decision makers,” said Victoria Skogman, is the conference manager. “Currently, gathering systems are unregulated, but trends in the industry show this is likely to change in the future. Preparing for this impending change is crucial, hence the theme of the conference.”
The goal of the GeoGathering Conference is to provide valuable information to gathering system and upstream operators who want to create efficient, accurate, and collaborative data strategies that work for their organizations. Presenters will demonstrate how GIS technology allows attendees to collect and share data between the field and the office, enabling their organization to make well-informed decisions. The versatile agenda focuses on real-world experiences — everything from integrity management and data requirements to data security and making GIS technology more accessible to stakeholders, Skogman said.
The GeoGathering Conference committee estimates that close to 150 GIS professionals and top-level management from leading oil and gas companies will attend this year. Attendees will be able to attend sessions that include:
Developing a Data Strategy
Data Collection Methods to Meet Requirements
Data Security and the Cloud
Data Sharing: GIS as an Enterprise
Organizing Data for Decision-Makers
PHMSA MAOP Strategies
Web-enabled Data Sharing Technologies & Portals
Collecting & Sharing Data to Enhance Safety
This year, attendees will experience the new, audience-focused format that offers two simultaneous tracks giving attendees the chance to tailor their own conference schedule. Plus, two of the biggest improvements are the addition of “structured networking” sessions and a “GIS Think Tank.”
Structured Networking facilitates a small group setting, in which attendees have the opportunity to meet people with common interests, share practical ideas, and network with individuals who might possibly help your organization. When attendees leave the networking session, they will have a solid list of new business contacts, Skogman said. The networking sessions are strategically placed at the beginning of the conference to help you build new relationships over the duration of the conference.
The GIS Think Tank session is also a unique addition to the agenda. It will feature five to seven GIS managers from a variety of gathering operators around the country. This is not a typical Q&A panel session; instead, it will allow the participating GIS managers to converse among themselves as the audience listens in. This will be mostly an unstructured session so that managers can spend more or less time on topics as they choose, Skogman said. It will be facilitated with questions from the audience. The purpose is to lead an informal discussion on some of the successes that each manager has had along with their opinions on pressing issues that gathering operators are facing.
This year’s conference has a seven-person steering committee with pipeline gathering background. Members include Trisha Menasco of DCP Midstream, Tom Coolidge of Esri, Ellen Nodwell of Hess, Cameron Collins of Williams, Rob McElroy of McElroy Consulting, Ron Brush of New Century Software and Victoria Skogman of New Century Software.
“The conference topics are very timely,” said Menasco. “Just when I thought I had all the data requirements figured out, it feels like we are starting over. I look forward to helping build an agenda that will be useful to the gathering community.”
Early bird registration is open. The conference committee welcomes senior management, project managers, integrity management specialists, GIS professionals, field operations managers, regulatory compliance personnel, and engineers.
Topcon Positioning Systems has released the MR-1 Heading System, an OEM GNSS solution for high-performance positioning and heading.
Using the MR-1 receiver and Topcon’s MG-A8 antenna, the system provides “centimeter-accurate RTK positioning and better than 1/10 of a degree heading accuracy in challenging environments,” said Doug Langen, TPS GNSS product manager. “The rugged MR-1 receiver is water and dustproof and operates at a robust operational temperature range of -40°C to 75°C.”
When combined with Topcon’s Quartz Lock Loop technology, the MR-1 offers continuous operation during “extreme vibration and shock, typical of intense dynamic environments,” he said.
The MG-A8 antenna of the MR-1 Heading System is designed for moving platforms and provides multipath rejection. It also offers increased resistance to near-band interference from satellite communications systems commonly found in marine applications.
Applanix has introduced the POS LV 120, the latest version of its positioning and orientation systems for land vehicles. Using commercial Micro-Electro-Mechanical (MEMS) inertial measurement unit (IMU) technology, the Applanix POS LV 120 is a small, lightweight system and provides an economical solution for any continuous positioning and orientation application.
POS LV 120 is a fully integrated, turnkey position and orientation system, using integrated inertial technology to generate stable, reliable and repeatable positioning solutions for land-based vehicle applications, Applanix said. Redesigned to be smaller and lighter, it maintains identical data interfaces and software compatibility with the established POS LV line of products.
“With a MEMS IMU and a 220 channel, dual-antenna GNSS receiver integrated into a single enclosure, the POS LV 120 is a cost-effective GNSS-Inertial solution designed to support many types of land-based mobile mapping projects,” said Kevin Andrews, product manager for Land Products at Applanix. “The integrated system is smaller than the standard POS LV computer system (PCS), making it ideal for use in lightweight applications such as robotics, autonomous vehicles, centerline mapping, asset mapping and short-range direct georeferencing.”
POS LV 120 is available now through the Applanix sales network.
The Earth’s surface is constantly shifting, being deformed as earthquake faults accumulate strain, and slip or slowly creep over time. Not long ago, scientists relied solely on seismometers to monitor the earth’s movements. Today, GPS has taken prominence as an indispensible tool.
PANGA, the monitoring network covering the Pacific Northwest, uses GPS to monitor this movement by measuring the precise position (within 5 millimeters or less) of stations near active faults relative to each other. By determining how the stations have moved, ground deformation can be determined.
If the plates near the coast or the Cascade Mountains move even a few centimeters, the scientists at PANGA know within seconds. The network is still being built, but eventually it’s expected that PANGA will be able to sense earthquakes faster and more accurately than traditional seismometers, and issue alerts to warn citizens of impending activity.
“GPS is helpful in distinguishing magnitude 8 from M9 earthquakes quickly,” explained Rex Flake, PANGA. “By design, seismometers only record high-frequency energy that becomes saturated during strong ground motion. Moreover, seismic data ‘clip’ at high magnitudes whereas GPS become more accurate. Seismographs are mainly intended to detect very small to moderately large earthquakes. GPS gives actual ground motions that in theory could be incorporated very quickly into tsunami models and warning systems. That is one of the things we are working on now.”
Volcano Watch. “A more speculative application is that some (not all by any measure) large earthquakes are preceded by slow creep events,” said Andrew Miner, PANGA. “While not really good enough to predict an earthquake, I think if we saw a very large transient creep event it would at least ring alarm bells. Unfortunately though, earthquakes are by their nature just not very predictable, at least to the level of a day or week that people could reasonably act on. On the bright side, volcanoes are reasonably predictable, and GPS is also an important tool in monitoring them. We work with the Cascade Volcano Observatory on several monitoring projects.”
PANGA is one of a series of earthquake monitoring networks stretching along the West Coast. The Pacific Northwest Geodetic Array is run by the PANGA Geodesy Laboratory at Central Washington University (CWU) in Ellensburg, and includes 300 continuously operating, high-precision GPS receivers located throughout the Pacific Northwest. Sixty more stations are expected to be installed this year. Trimble, Leica, Topcon, and Javad are the main receivers used in the region.
Data from these receivers is continuously downloaded, analyzed, archived, and disseminated. About one third of PANGA’s GPS stations are telemetered in real-time back to CWU, where the data are processed using NASA’s Jet Propulsion Laboratory’s GIPSY/OASIS II software for high-precision data analysis, and Trimble’s RTKNet Integrity Manager software for real-time analysis. The data provide relative positioning of several millimeters across the Cascadia subduction zone and its metropolitan regions. These real-time data are used to monitor and mitigate natural hazards arising from earthquakes, volcanic eruptions, landslides, and coastal sea-level hazards.
Sagging Bridges. The data are also used to monitor man-made structures such as Seattle’s sagging Alaska Way Viaduct, the State Route 520 and Interstate 90 floating bridges, and dams throughout the Cascadia subduction zone, including those along the Columbia River. For instance, for the S.R. 520 bridge, PANGA teamed up with Washington State Department of Transportation (WSDOT) to monitor movement of the 520 bridges during wind storms and seismic events.
The receivers continuously monitor and record structural deformation with about a millimeter precision. Raw GNSS satellite phase and pseudorange estimates are acquired and processed continuously into receiver positions estimated every 5 seconds and delivered with 10 and 30-second latencies. Daily-averaged receiver positions computed with predicted and post-processed satellite orbit and clock corrections are provided with 1-6 day latencies.
Seattle’s aging Alaska Way viaduct is one of several major man-made structures being monitored by PANGA’s GPS Network. (photos courtesty of CWU Geodesy Lab.)
Tremor Slips. The Northwest is at the forefront of earthquake-related GPS research, in large part because the area provides a lot to learn from GPS monitoring, Flake said. “For example, when we started it was strongly suspected but not definitely known that the Cascadia subduction zone was locked over parts of its surface and a major earthquake threat. Thanks to GPS monitoring we now have a pretty good idea not only exactly where it is locked, but also when parts of it do slip or creep.
“One important discovery made with GPS data, along this line, was that of the Episodic Tremor Slip (ETS) events that occur here in the Northwest U.S.,” Flake said. “Since the time duration of ETS motion takes place on the scale of days to weeks, these earthquake events were unrealized by traditional seismic detection methods.”
GPS data shed light on this peculiarly predictable earthquake phenomenon. “With these GPS data we can measure strain accumulation within the continental crust (where people live) and calculate the residual that can be expected to rebound in a large subduction zone earthquake,” Flake said.
“Even more detailed than that, we can use GPS data from past ETS events to constrain the locked zone of the subducting crustal plate by inferring the amount of slip at depth that best reproduces the observed GPS recordings — important in determining possible magnitude and location of the megathrust earthquakes (Mw = 8 to 9) that will someday occur. This is of obvious concern to society and is a major reason that we lead the geodetic applications of GPS research.”
Data Online. PANGA maintains a website that integrates daily GPS measurements from about 1,500 stations along the Pacific/North American plate boundary, ranging from Alaska to the U.S-Mexico border. Cleaned, network solutions from several arrays are merged and grouped into regional clusters.
Arrow on a Velocity Field Map of Oregon and Washington represent ground motion as measured by GPS at each particular location. The grey circles are 2 sigma error ellipses (click to enlarge.) (photos courtesty of CWU Geodesy Lab.)The PANGA team constructs a bedrock drill-brace geodetic monument at Howard Hanson Dam east of Auburn, Washington. (photos courtesty of CWU Geodesy Lab.)
The field at Commonwealth Stadium in Edmonton, Alberta, recently received a CDN $2 million renovation. The old natural-grass field had become expensive to maintain properly, and the Grey Cup game, Canada’s Super Bowl, will be played at Commonwealth Stadium this year. The stage needed to be re-set.
Renovation required total removal of the existing medium and subgrade materials to a 1.2-meter depth. Wilco Contractors Northwest replaced the subgrade to a planarity or flatness tolerance of 3 millimeters over a 3-meter length. To achieve this precision, Wilco used a machine automation system on a Volvo G-960 motor grader fitted with a GPS receiver, and base station nearby. A second grader carried a robotic total station.
“We probably have a quarter-million dollars invested in this,” said Wilco President Art Maat. “The machine-control equipment pays for itself on an annual basis. It enables us to construct projects to tolerances that other contractors cannot match, even though they have the same big iron capabilities we do.”
Work began with removal of existing soil mixes, drainage rock, and subgrade clay. A bulldozer and the two motorgraders graded the subgrade to a 0.5 percent slope on both sides of the field’s center spine. The work included the D-shaped zone behind each goal post, created by a running track encircling the field. In all areas, the slope must be constant. “The problem is, how do you grade that half-circle?” said Maat. “Grader operators and surveyors want to work in straight lines or on rectangular grids. We use the geo-tracker, or robotic total station, to control the grader blade three-dimensionally. It is one step more accurate than a GPS system.”
Using the robotic total station involves entering a digital terrain model, called a TIN-file, into the grader’s onboard computer. The grader is fitted with a mast and prism, which has a fixed relation to the grader blade. The robotic total station can see the prism, read its 3D location, and communicate it back to the grader. The computer processes the differences between the actual blade location and the digital terrain model to control the blade.
The GPS-equipped grader did the rough grading at 20-millimeter accuracy, and the prism-equipped grader handled the fine grading at sub-centimeter accuracy. With final subgrade complete, Wilco dug trenches to install a drainage system, covered with a geotextile. Working in four lifts of 300 millimeters each, Wilco filled the excavation with coal bottom ash, a gritty product like playground sand. “We took the TIN file and offset the elevation by 300 millimeters at a time.”
Savings. The machine-control equipment saved Wilco $15,000–$20,000 on surveying, for 100 hours or more at $150 an hour for a crew. “The systems make our equipment 25 percent more efficient on low-tolerance sites such as fields and running tracks where grades are critical,” Maat added.
To test planarity, Wilco stretched a stringline over a 3-meter distance at many points on the field and measured with a Canadian dollar coin, a looney. If they could fit a couple of loonies under the string, they had found a low spot. If they could fit only one, the 3-millimeter tolerance had been met. “Our feedback from the consultants was that they had never seen a field prepared this well, with very little adjustment required. The slope of the field had to be 0.25 percent from the centerline spine to the sides. And the slope of the D-shaped areas behind the goal posts was exactly the same.”
Manufacturers
Wilco uses a Leica PowerGrade GPS/GNSS receiver, Leica Redline base station, Redline Power Tracker robotic total station, and Geo-Tracker.
By Ana P. C. Larocca, Ricardo E. Schaal, and Augusto C. B. Barbosa, University of São Paulo
Multipath makes it difficult to detect very low-frequency structural vibrations, ranging from 0.05 to 1 Hz, important in characterizing dynamic loads and determining safe structural lifetimes. The authors have developed a phase-residual method for use with very high-frequency data to distinguish receiver noise, multipath, and the periodic displacements that are most structurally significant. The methodology can apply to bridges, tall buildings, and towers.
Civil engineers continuously seek reliable methods and tools to improve the quality and lifetime of large structures. Most studies in this field have been based on static loading. Nowadays, dynamic loading has become a particular concern, and GPS offers direct measures of dynamic displacements of large structures induced by traffic, wind, and earthquakes.
Precisely characterizing the vibrations that are a common behavior of large structures such as bridges, tall buildings, and towers undergoing dynamic loads facilitates structural analysis studies. It is feasible to detect structural vibrations using a computational model and GPS sensors. The critical vibration frequencies of bridges detectable with different GPS positioning techniques (real-time kinematic, static, quasi-static) range from 0 to 0.3 Hz.
However, the unavoidable presence of multipath signals in the same frequency range makes it difficult to detect very low-frequency vibrations, mostly ranging from 0.05 up to 1 Hz, for short- to medium-span bridges.
Our preliminary results show that the structural vibration measurements, mixed with random amplitude and frequency signals generated by electronics and the ionosphere, together with slowly varying signals generated by multipath, can be better detected with an oversampled GPS data set. This hypothesis relies on fact that the structure oscillation is reasonably stable during the data-collecting period.
The analyses of GPS time series used were done by mathematical addition of well-known sine waves in the raw phase of a 100-Hz data set collected from a short baseline. This strategy simulates the antenna vibrating vertically on a structure, for example at the deck’s midpoint of a bridge.
Methodology
The methodology used to collect and analyze GPS data was developed for providing low-cost high-accuracy monitoring with single-frequency GPS receivers. The technique is the interferometry method based on the analysis of the L1 double-difference phase residuals of regular static observations. In this data-processing, one satellite is considered as a reference, and its selection is according to the direction of the vibration to be measured. The satellite not taken as a reference — located in the same direction as the vibration movement — has the residual values that contain information about bridge deckvibrations (phase changes). In 2001, we named this the phase-residual method (PRM); see “Millimeters in Motion” in GPS World, January 2005.
The residuals incorporate all phase deviations from the adjusted double-difference position during the observation. These phase deviations are due to electronic receiver noise, multipath, small dynamic antenna movements, and other error sources. Converting the residuals to the frequency domain by the fast Fourier transform (FFT) associated with a continuous wavelet transform (CWT), it is possible to see the different behaviors of the receiver phase noise,
multipath, and periodic vibration, enabling the distinction between them. The periodic displacement presents a peak due to the fundamental vibration mode, while the receiver noise presents a white-noise spectrum, and the multipath presents a broad spectrum close to zero frequency. The last feature is very dependent on how the antennas “see” their vicinity. As PRM does not need well-known coordinates epoch-by-epoch to determine the amplitude and the frequency values of the oscillations, it is possible to get reliability.
The spectrum analyses were done by FFT, which provides a design of the vibration’s peak amplitude values; the CWT was used to detect the variation of the frequency value during the timespan of observations, and for validating the results.
Simulation and Filtering
The preliminary investigation was done by the mathematical addition of sine waves on satellite signals close to zenith, which are the most affected by a vertical amplitude vibration in a real situation. The double-difference phase was calculated, taking as reference the lowest satellite.
The mathematically generated sine wave had peak-to-peak amplitude of 1 millimeter and frequency values ranging from 0.06 Hz up to 1 Hz. The analyses for sine-wave detection were done by applying the FFT and the CWT with the Morlet Wavelet, which deserves a short description.
The CWT was used because structural vibration signals with small peak-to-peak amplitudes in the low frequency region are not well represented in time and frequency by the FFT methods. A particular wavelet, Morlet, was used and is defined as
(1)
where wo is dimensionless frequency and η is dimensionless time. When using wavelets for feature extraction purposes, the Morlet wavelet is a good choice, because it provides a good balance between time and frequency localization.
The idea behind the CWT is to apply the wavelet as a band-pass filter to the time series. The CWT of a time series (f (t),t = 1,…,N) with uniform time steps dt, is defined as the convolution of f (t) with the complex combination of the mother wavelet scaled and normalized, as:
(2)
where Wj,k(t) represents the similarity between wavelet function and the analyzed time series f (t); that is, the higher the value of Wj,k(t), the greater the similarity between the analyzed function and the mother wavelet function that modulates the analyzed signal. The CWT was implemented in MATLAB software.
100-Hz Phase Data
Regarding the detection of low frequencies due to a small peak-to-peak amplitude vibration, it is important to show the L1 double-difference residuals of a 100-Hz data rate (Figure 1) and its spectrum before mathematically adding the sine-wave signal due to periodic vibrations. The figure shows the raw phase residuals of 20 seconds of data between two satellites, SV05 (lowest) and SV20 (highest).
FIGURE 1. Raw L1 double-difference phase residuals from a time series at a 100-Hz data rate.
Figure 2 presents a 1-second data span for better visualization of peak-to-peak amplitude of the raw double-difference phase residuals, which is lower than 3 millimeters.
FIGURE 2. Residuals from L1 double-difference phase residual.
Figure 3 was produced to verify the variability of 100-Hz residuals and the probability of errors in the signal that can contribute to degrading the identification of the sine-wave vibration peaks. The resulting histogram is close to a bell curve of a Gaussian distribution, demonstrating the good quality of the 100-Hz data. Figure 4 shows the Morlet CWT computed to identify the low-frequency bias term and a high-frequency noise term. The 5-percent significance (95-percent confidence) level of significant signal-wave information is delimited by a thick contour. The signal information of double-difference phase residuals was used as a reference for supporting a better distinction between noise and sine-wave signals.
FIGURE 3. The Gaussian distribution of 100-Hz data rate residuals.FIGURE 4. Continuous Wavelet Transform of the residual time series. The 5-percent significance level of sine wave detection is shown as a thick contour.
Zero-Baseline Test
A zero-baseline test was performed to determine the correct operation of a GPS receiver, associated antennas, and cabling. The objective was to verify the precision of the receiver. A 1-minute data sample was collected. Figure 5 shows the residuals of L1 double-difference phase.
FIGURE 5. Zero baseline 100-Hz data rate residuals of L1 double-difference phase.
Figure 6 shows 5 seconds of the zero-baseline data; the peak-to-peak amplitude of residuals is very small, close to 2.0 millimeters. This information leads us to expect detection of very low-frequency vibrations, ranging up to 0.3 Hz with a 1-millimeter amplitude displacement peak-to-peak.
FIGURE 6. Residuals from a zero baseline with 100-Hz data.
Figure 7 shows the spectrum of the zero-baseline residuals; it is possible to observe the region close to zero strongly affected by multipath. This makes the detection of very low frequencies difficult.
FIGURE 7. Power spectrum of a zero-baseline residual.
The CWT was applied to decomposing the zero-baseline double-differenced residuals into a low-frequency bias term and a low-frequency noise term. Figure 8 shows the behavior of the residuals of the 100-Hz phase data, where red regions represent the most suggestive energy level of the measurement noise term.
FIGURE 8. Morlet CWT of zero-baseline residual time series. The 5-percent significance level of sine-wave detection is shown as a thick contour.
Preliminary Simulation Results
Figure 9 illustrates the raw L1 double-difference phase residuals with a periodic sine wave of 1 millimeter peak-to-peak amplitude mathematically added to the time series. It is possible to observe the presence of the periodic signal.
FIGURE 9. Raw L1 residual time series with a sine wave of 1-Hz frequency and 1-millimeter amplitude.
Figure 10 shows that the stronger energy is close to 1 Hz due to the 1-Hz sine wave, as expected. The resulting well-defined peak is due to the high sampling rate provided by 100-Hz receivers. Figure 11 shows details of the peak due to the sine wave of 1 Hz added to the residuals.
FIGURE 10. Spectrum of L1 double-difference phase residuals with a sine wave of 1 Hz and 1 millimeter.FIGURE 11. Close-up of region with the most power at 1 Hz.
We analyzed these data with the Morlet CWT to find events to compared when other low frequencies had been simulated, helping separate noise from signal. Figure 12 presents the standardized time-series residuals, showing a region with highest power level. The continuous red region corresponds to a 1-Hz sine wave, and the spread-out red-orange regions may be due to electronic noise and multipath. The region outside the cone, delimited by the thick contour, indicates the detection of significant signal information but without the 95-percent confidence.
FIGURE 12. Morlet CWT of time series of residuals with 1-Hz sine wave with 1 millimeter amplitude. The 5-percent significance level of sine-wave detection is shown as a thick contour.
0.5-Hz Sine Wave. The second sine wave generated had the same peak-to-peak amplitude, 1 millimeter, and the frequency value of 0.5 Hz. Figure 13 illustrates the raw L1 double-difference phase residuals with a periodic 0.5-Hz sine wave mathematically added to the time series.
FIGURE 13. Raw L1 double-difference phase residuals with a sine wave of 0.5 Hz.
Figure 14 shows an energy peak at a frequency of approximately 0.5 Hz, also with a well defined peak.
FIGURE 14. Spectrum of L1 double-difference phase residuals with a sine wave of 0.5 Hz.
Figure 15 shows details of the peak.
FIGURE 15. Close-up of region with the most power at 0.5 Hz.
The CWT in Figure 16 shows that the intensity energy level represented by the red continuous region and the spread-out red-orange regions are quite similar to those of the CWT of the 1-Hz sine wave (Figure 12). Note a decrease in energy intensity (orange-yellow) that occurs due to decreased signal sampling of the 0.5-Hz signal (10 cycles) in 20 seconds of data, compared to 1 Hz (12 cycles) in the same 20 seconds.
FIGURE 16. Morlet CWT of time series of residuals with 0.5 Hz sine wave with 1 mm amplitude. The 5-percent significance level of sine wave detection is shown as a thick contour.
0.1-Hz Sine Wave. The third sine wave mathematically generated had the same peak-to-peak amplitude, 1 millimeter, and a frequency of 0.1 Hz. Figure 17 illustrates the raw L1 double-difference phase residuals with the periodic 0.1-Hz sine wave mathematically added to the time series. Figure 18 shows the power at one frequency, approximately 0.10 Hz, still with a well-defined peak.
FIGURE 17. Raw L1 double-difference phase residuals with a sine wave of 0.10 Hz.FIGURE 18. Close-up of region with the most power at 0.10 Hz.
Figure 19 presents identification of the 0.1-Hz sine wave by CWT with the 5-percent significance level shown as a thick contour. A decrease of energy intensity (orange-yellow) occurs due to decreased signal sampling of 0.1 Hz (2.5 cycles) in 20 seconds of data compared to 0.5 Hz (10 cycles) in the same 20 seconds.
FIGURE 19. Morlet CWT of time series of residuals with 0.1-Hz sine wave with 1-millimeter amplitude; 5-percent significance level of sine wave detection shown as a thick contour.
0.08-Hz Sine Wave. We simulated a sine wave of this frequency (Figure 20). Figure 21 presents identification of the 0.08-Hz sine wave by CWT through the 5-percent significance level shown as a thick contour. A decrease in energy intensity (orange-yellow) occurs due to decreased signal sampling of 0.08 Hz (almost two cycles) in 20 seconds of data compared to 0.5 Hz (ten cycles) in the same 20 seconds.
FIGURE 20. Close-up of region with most power at 0.08 Hz.FIGURE 21. Morlet CWT of time series of residuals with 0.08 Hz sine wave with 1-millimeter amplitude; 5-percent level of sine-wave detection shown as a thick contour.
0.06-Hz Sine Wave. Finally, a 0.06-Hz sine wave was simulated and added to the residuals, but the FFT spectral analysis did not present the power peak. This can be attributed due to the sine-wave period providing only 1.5 cycles during 20 seconds and did not generate enough power to be detected by FFT.
Figure 22 presents a close-up view of 0.06-Hz sine-wave power spectrum of the residuals not indicating a significant peak close to the expected frequency region.
FIGURE 22. Power spectrum of double-difference phase residuals with 0.06-Hz sine-wave signal.
The investigation continued with a Morlet CWT. In Figure 23 it is possible to verify the presence of a faded red region close to the period corresponding to 0.06 Hz — at the bottom of figure and under the cone’s thick contour — signalling that the wavelet was able to detect a very low frequency even with a small sampling. However, due to small signal sampling, the detection is not within a 95-percent confidence. Otherwise, if the time series had lasted more than 20 seconds, certainly the sine wave would have been detected.
FIGURE 23. Morlet CWT of time series of residuals with 0.06 Hz sine wave with 1-millimeter amplitude.
These analyses suggest that longer time-series data would enable detection of very low frequencies with 95-percent confidence.
Conclusions
The lack of amplitude accuracy does not constitute a significant restriction in large structure monitoring, as the exactness of its natural oscillating frequency, harmonics, and response to external dynamic forces are more important for identification of a structural problem.
Using 100-Hz receivers to detect very low-frequency vibrations, the combination of 100-Hz data with filtering techiniques enables detection of signal vibrations of very low frequencies. The tests were conducted using a mathematical simulation of sine waves added to raw residuals of L1 double-difference phase.
The results of simulations and filtering techniques indicate that very low frequency vibrations can be detected when the sampling rate of GPS data and the sampling frequency of an embedded sine wave is large.
Additionally, zero baseline and static short baseline trials have been conducted to assess the noise of the receivers that is close to 2.5 millimeters — extremely low and contributing to detection of vibrations with low peak-to-peak amplitude.
Spectral analysis is a fundamental tool for engineering development. Despite such new analysis concepts as FFT and CWT used here, as well as higher-order spectra, basic frequency domain analysis will remain the practical analysis tool in the foreseeable future.
Future tests will be carried out collecting 100-Hz data, sufficient for having oversampling of sine-wave frequencies due to structural vibrations, and using a new methodology with just one GPS receiver.
Acknowledgments
Thanks to the JAVAD GNSS Moscow Research and Development team for providing a Triumph receiver and 100-Hz data through Michael Glutting, whom we also thank. The researchers received a sponsorship from the National Counsel of Technological and Scientific Development Government (CNPq) of the Brazil Federal Government to purchase a pair of 100-Hz data-rate GPS receivers.
Manufacturers
The 20 seconds of data were kindly provided by JAVAD GNSS Moscow Research and Development team and were collected using Javad GNSS Triumph receivers with JNS choke-ring antennas.
Ana P.C. LaRocca is a lecturer in the Department of Transportation Engineering of the Polytechnic School at the University of São Paulo (USP) and holds a Ph.D from that same institution.
Ricardo E. Schaal is an associate professor with a Ph.D. from USP.
Augusto C. B. Barbosa is a Ph.D candidate at the Institute of Astronomy, Geophysics and Atmospheric Sciences, at USP.
By Steven M. Di Naso, Vincent P. Gutowski, Harvey Henson, and Ryan Leonard
During the winter of 1838–39, the great Native American Cherokee Nation trekked across southern Illinois, in a forced removal by the U.S. government from their ancestral homeland in Tennessee. Harried, unequipped, and unsupported by their captors, thousands died on the Trail of Tears. Burial records were not kept, and burial locations remain lost to this day. Local history suggests that some Illinois settlers allowed the Cherokee to bury their dead on small plots of land adjacent to their own family cemeteries. One such plot, the Campground Presbyterian Church cemetery near Anna, Illinois, may contain unmarked Cherokee graves.
Researchers from Southern Illinois University and Eastern Illinois University used GPS to navigate and precisely map probes of a ground-penetrating radar (GPR) instrument in the cemetery. We monumented the geophysical survey grids using real-time kinematic (RTK) DGPS. Site topography was also mapped using GPS, as were the individual cemetery headstones. Adding geographic information systems (GIS) software to our mix to map cemetery headstone distribution and record headstone attributes (dates of death, names), we could determine chronological gaps within the cemetery that coincide with the probable emigration of the Cherokee.
GPR and electromagnetic conductivity produced contour plots of high-resolution magnetic gradient data. Small dipolar anomalies detected are typically related to disruptions within near-surface soil horizons and may correspond to locations of shallow graves: the lost final resting places of many Cherokee.
By close examination of the geophysical survey data and the anomalies produced from them, we were able to present plausible if not possible locations of several gravesites. However, at this time, and for obvious reasons, the actual location must remain secure and cannot be published.
The figure below shows a mosaic of amplitude depth slices at .30–.70 meter intervals from processed interpolated 250-MHz GPR profile data. White rectangles denote known graves. Most marked graves were imaged, although some were represented as more subtle anomalies on this display. Some possible unmarked graves were interpreted at UTM coordinates xxxx, yyyy.
The cemetery is within working distance of CORS station ILCB at Southern Illinois University. Two RTK GPS units communicating with the station via CDMA cellular radio used real-time differential corrections along a variable baseline length of approximately 28.5 kilometers, enabling mapping of the site at centimeter-accuracy resolution.
Survey data were edited, mapped, and analyzed with a GIS. Family genealogy polygons were generated using last names, to produce family distribution plots throughout the cemetery.
Manufacturers
The study, supported by a National Park Service grant with Southern Illinois University at Carbondale, used two Leica 1250 RTK GPS units, a Leica TC802 robotic total station, and Esri ArcGIS ArcInfo. Equipment was provided by Kara Company of Countryside, Illinois.
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