Supergeo Technologies, a provider of GIS software and solutions, has launched SuperSurv, a mobile GIS app, on the App Store and Google Play.
SuperSurv contains comprehensive GIS data-collection functions. Designed for both iOS and Android powered devices, it integrates with GIS and GPS technologies to provide functions in field survey, such as Map Display, Query, Measure, etc. With SuperSurv, the collected data can be saved as feature layer (point, line, polygon) in SHP or GEO format in offline mode. SuperSurv supports OpenStreetMap as the base map.
SuperSurv has been successfully applied in various industries worldwide, including environment protection, pollution prevention, and facility management. The free trial version is now available on Apple App Store and Google Play, allowing users to experience complete functions for seven days before purchase.
For users in North America, Supergeo has released the SuperSurv M3 version to provide easy-to-use and useful data collection and map display functions. SuperSurv M3 supports feature-layer display and offline editing functions. Furthermore, cached maps can be adopted as the base map to facilitate data capture tasks.
Geospatial Corporation has unveiled the company’s newest version of GeoUnderground, its proprietary cloud-based GIS platform custom designed around the Google Maps API and Google Maps Engine.
“The economic and social benefit gained through accurately locating, mapping and managing the world’s underground infrastructure assets in a systematic fashion is huge,” said Mark A. Smith, Geospatial CEO. “To accomplish this, Geospatial has developed a comprehensive suite of technologies capable of gathering accurate 3D positional data on most underground or underwater pipelines. The combination of these data acquisition technologies with our cloud-based GeoUnderground GIS platform provides our clients with a total solution to their underground asset management needs.”
Geospatial Corporation utilizes integrated technologies to determine the accurate location and position of underground pipelines, conduits and other underground infrastructure data, allowing Geospatial to create accurate three-dimensional digital maps and models of underground infrastructure.
The company manages the infrastructure data on its cloud-based GIS portal called GeoUnderground, its proprietary GIS platform custom designed around the Google Maps API and Google Maps Engine.
SPOT LLC, a wholly owned subsidiary of Globalstar, Inc., says its SPOT products have been used to initiate 3,000 rescues around the world since the technology’s launch in 2007. With more than 200,000 SPOT units in service, that averages to one rescue a day. SPOT delivers affordable and reliable satellite-based connectivity and real-time GPS tracking, completely independent of cellular coverage.
“Lifesaving rescues around the globe are now a daily occurrence for our SPOT products. SPOT is an absolute must for the outdoor recreation market and aviation, as well as an essential government and enterprise solution,” said Jay Monroe, CEO and Chairman of Globalstar. “With 3,000 confirmed rescues, saving lives continuously drives us to innovate, creating affordable satellite communications solutions that reach a market well beyond traditional mobile satellite users, including millions of people globally.”
SPOT products allow users to track their assets, use location-based messaging and emergency notification services, and make calls beyond the boundaries of cellular. SPOT products work around the world, including virtually all of the continental United States, Canada, Mexico, Europe and Australia, portions of South America, Northern Africa, North-Eastern Asia and thousands of miles offshore of these areas. Over the past seven years, boaters, hunters, recreational pilots, hikers, off-road travelers and outdoor enthusiasts have come to depend on the lifesaving capabilities of SPOT.
The 3,000th rescue occurred in the Hayman Fire area of Central Colorado. Two dirt bikers were outside of cell range when an accident occurred. One of the riders, Kevin, activated the SOS button on his SPOT Satellite GPS Messenger. The GEOS International Emergency Response Coordination Center was alerted and coordinated the rescue with local law enforcement. “SPOT worked really well. Without it, getting out would have been more difficult and time consuming and who knows what could have happened in that time. There were a lot of different variables involved,” Kevin said.
SPOT products and services include:
SPOT Gen3, a device that provides off-the-grid messaging, emergency alerts, extended battery life, and extreme GPS tracking at 2½-minute intervals.
SPOT Trace, a GPS tracking device that uses satellite technology to track anything, anytime, anywhere.
SPOT Global Phone, a satellite phone that allows users to make calls virtually anywhere beyond the boundaries of cellular.
The SPOT App, a web-based interface allowing users to view their SPOT messages, show their track points, and monitor their assets via smartphone or tablet.
TerraStar is offering GNSS manufacturers revenue sharing opportunities, including the possibility to launch their own precise GNSS augmentation services via endorsed rebranding of TerraStar services as a reseller. According to TerraStar, this will provide an attractive recurring service revenue stream to GNSS manufacturers that was not previously available in the industry.
TerraStar is a brand name of TerraStar GNSS Ltd., which is a wholly owned subsidiary of Veripos Ltd. Following the acquisition of its parent company by Hexagon AB in March, it will continue as a neutral and independent provider of satellite delivered precise positioning augmentation services for land and nearshore markets. It is already well advanced in plans to expand its service offering, the company said.
Gary Wilcock, general manager of TerraStar, renewed the company’s commitment to resellers, integrators and end customers at the Munich Satellite Navigation Summit, held in March. “TerraStar will remain an open system available to all current and future partners,” Wilcock said. “The TerraStar service will remain available to all partners who have a valid contract on a perpetual basis for as long as long as the services continue to be delivered. We intend to be a long-term partner for our customers.”
Walter Steedman, CEO of Veripos Ltd. Added, “All partners will be treated on a level playing field. Strict information firewalls will be maintained for all TerraStar dealings with different business partners so that all can be assured that market or other sensitive information remains confidential.”
GAINS-10 provides accurate inertial navigation in the presence of mechanical shock, transient platform vibrations and extreme magnetic interference. It features high speed, synchronous sampling of all inertial systems combined with high rate coning and sculling compensation and is fully calibrated across temperature.
“The GAINS-10 delivers precise performance in complex environments,” said Jim Lackemacher, Group vice president of Sparton’s Defense & Security Engineered Products. “Sparton’s GAINS-10 provides flexible integration options and platform customization.”
High-speed synchronous sampling of all inertial sensors
Customizable on-board high speed digital filtering
Sculling and coning compensation
High-speed data logging capability to off-board uSD card
Ruggedized, shockproof design, with proprietary seals that allow barometric pressure sensing combined with IP67 performance
Low power consumption with power management functionality (Sleep Mode)
Interface to external GPS receiver
External data interface via Multi-GPIO connectivity
Powerful user programmable customizations via NorthTek(TM) Forth interpreter
Sparton AUVSI 2014 Events Schedule: Sparton Navigation and Exploration will be featured at the “Beyond the Booth” showcase Wednesday, May 14th at 11:30am (EDT).
Throughout the AUVSI show, Sparton will host in-booth presentations along with live demonstrations.
Carrier Phase Compensates for Wind and Wave Motion
Limited landing area as well as interference due to wind disturbance and wave motion make shipboard landings of unmanned aerial vehicles (UAVs) extremely difficult. Use of UAVs at sea can enhance the efficiency of intelligence gathering and surveillance, and could also increase long-range air-strike capability. To successfully land aircraft in such a challenging environment requires a high-precision navigation system; this prototype applies RTK measurements.
By Chiu-Jung Huang and Shau-Shiun Jan
UAVs can perform functions such as surveying, imaging, detection, sensor work, rescue, and geographic information systems (GIS) data collection. The exploitation of UAVs with portable launching and recovery systems using an automatic guidance equipment can enhance their flexibility in many practical applications. In particular, UAVs can achieve great effectiveness from launch and recovery aboard ships at sea. However, the landing area is narrow on a ship, and interference related to the maritime environment due to wind disturbance and wave motions varies greatly, making maritime UAV landings quite difficult. Recovering these aircraft in such a rapid-dynamic environment requires a high-precision UAV navigation system.
Generally, UAVs use a differential GPS (DGPS) aiding station to continuously transmit positioning correction information during landing approach; this method can provide about 0.7 to 1-meter accuracy. However, shipboard landings require more stringent accuracy. According the Joint Precision Approach and Landing System (JPALS), the requirements of shipboard landing include vertical accuracy on the order of 0.3 meters, and the requirement for the vertical protection level is 1.1 meters. To fulfill these accuracy requirements, we have chosen the real-time kinematic (RTK) technique. Recently, researchers have studied the use of RTK satellite navigation. The Boeing Unmanned Little Bird program has been examining shipboard launch and recovery using related navigation techniques.
The accuracy of using RTK navigation is 1 centimeter + 1 part per million.
Figure 1. Flow chart for software-in-the-loop.
Since development of shipboard landing is costly in terms of time and many resources, including human resources, this research is an attempt to evolve a software-in-the-loop (SIL) simulation system to analyze the accuracy of using RTK for landing navigation. The SIL system uses the MATLAB Simulink interface becasue of its helpfulgraphic user interface and block diagrams. A flowchart of the SIL system is shown in Figure 1.
The simulated RTK message provides the navigational data used as the analysis results from the experiments. To ensure the stability of the landing process, the aircraft models were control by a linear quadratic Gaussian regulator (LQG), which is able to reject the environmental disturbances encountered in the landing process. The ship motions were simulated using the factors and the model formulated by the International Towing Tank Conference. A combined position error consisting of the aircraft controls and ship motions was calculated and then fed back to the RTK navigation message.
RTK Performance
RTK navigation provides high positioning performance in the range of a few centimeters; the technique can eliminate main errors, including ionospheric and tropospheric errors and satellite clock errors, among others. A base station and a rover station can cover a service area of about 10 to 20 square kilometers. The data transition should be in real time using a wireless VHF or Wi-Fi modem.
Because data for shipboard landings are difficult to acquire, the navigation message in the SIL was simulated using experiments involving a variety of conditions. In this article, four kinds of experiments were included to help verify the availability and reliability of using RTK information as a navigational message.
We started with a basic kinematic experiment, which was simply used to assess the RTK performance. Next, a relative positioning experiment was conducted to ensure the RTK relative positioning accuracy was adequate. After that, an antenna reversal experiment was designed in order to understand the ship’s swing effect in which aircraft altitude might cause a lack of common view satellites. Finally, an antenna forward flip experiment was conducted intended to show the different RTK positioning results for a variety of sea state effects.
All of the experimental data were collected by a workshop computer through a program data file. The analyses of the results included the mean, standard deviations of positioning error, unavailable RTK percentages and the positioning accuracy when RTK was unavailable. All of the analysis results were imported to the SIL simulation using the Gaussian random variable model.
Figure 2. Kinematic experimental setup.
Kinematic Experiment. The base station setup included an antenna, tripod, and receiver. The rover station setup included a portable vehicle with a battery, antenna, and receiver placed as shown in Figure 2. The data were transmitted and received using a wireless modem for which the transmitted rate was 115200 bps. The receiver was connected to a laptop used as a workshop to monitor satellite quality and collect the data. The region in which the experiment took place is shown in Figure 3: on the roof of the Aeronautics and Astronautics department building at National Cheng Kung University in Taiwan. The red star is the known position of the base station. The broken rectangular red line is 25 meters by 10 meters along which the moving rover station moved clockwise.
Figure 3. Kinematic experimental region.
However, it is difficult to show the true positions of the experiment. In this article, we tried to get the true position by using a linear regression method which used the time, t, as the explanatory variable and the position, y(t), as the dependent variable. The linear regression used the past five epoch positions as the dependent variables by which to obtain the linear polynomial, and the fifth position was put into the polynomial to get the position error. For example, in order to calculate an error at t=4, the position results from t=0 to t=4 must be taken into Equation (1) to form the second order polynomials with parameters P, Q, and R
(1)
The experimental results are shown in Figure 4, which is the ENU positioning error, and Table 1 shows the analysis error mean and standard deviations. The experimental results show that the horizontal positioning accuracy is 0.037 meters (95 percent).
Figure 4. ENU error results for the kinematic experiment.Table 1. Positioning results for the kinematic experiment.
Relative Experiment. This experiment had one base station as before and included two rover stations which were placed on a T-bar, the relative distance being known, on a portable cart as shown in Figure 5. The region of the experiment is shown in Figure 6, where the star marks the location of the base station, with the rover station moving along the black arrow.
The relative error was calculated using a known distance, 0.72 meters, to compare the two rover station positions. Figure 7 shows the relative results of the experiment for which the mean value and standard deviations were recorded in Table 2. In this experiment, only about 4.5 percent of the positioning results failed to meet the requirement of 0.3 meters.
Figure 7. Relative error results.Table 2. Positioning results for the relative experiment.
Common-View Satellite Experiment. Aircraft landing altitude and the ship’s swing motion caused by the state of the sea might affect GNSS information received by the antenna. This experiment had one base station and one rover station at fixed positions as before, but we attempted to flip the antenna of the base station toward the north by 80 degrees, as shown in Figure 8, and the rover station changed direction according to Table 3. The antenna directional change of 80 degrees were chosen for the extreme case that the base station and rover station could experience completely different satellites in view.
Table 3. Common view satellite experimental setup for antenna.Figure 8. Common view satellite experimental setup.
Results of the experiment are shown in Figure 9, in which the vertical lines indicate antenna directional changes. For this experiment, every change is 30 seconds. This experiment demonstrates that the position performance definitely varies. The position analysis is shown in Table 4, which shows a horizontal error of 0.116meters (95 percent).
Figure 9. ENU results of the common view satellite experiment.Table 4. Positioning results for the common view satellite experiment.
Sea-State Experiment. In this experiment, one base station and one rover station were required in a fixed position, but the rover station changed the direction of the antenna, as shown in Figure 10, where the angle of x is decided according to the sea state in Table 5. On the other hand, the antenna changing toward a different direction simulated the swing motion of the boat.
Figure 10. Swing experimental setup.Table 5. Antenna angle in the swing experiment.
The experimental results shown in Table 6 are the mean values, and Table 7 shows the standard deviations. The simulation provides the analysis results in order to authenticate the integration simulations. The results show that the sea state slightly influences RTK positioning.
UAV and Ship Motion Simulations
During shipboard landing processing, many complicated conditions must be taken into account, including crosswinds, an air-wake model, wind gusts, and deck motion. The ship deck motion and crosswind effects are two key factors that further increase the difficulty of ship-borne operations.
For this reason, the UAV controller must have anti- interference features. An LQG controller is able to reject the environmental disturbances encountered during landing in a lateral motion. For the ship deck motion, the chosen spectrum (the International Towing Tank Conference, or ITTC two-parameter spectrum) was used as the power spectrum of the sea waves to be simulated.
Aircraft Simulation. The aircraft was in the simulation, the SP.X-6, was designed by the Remotely Piloted Vehicle and Microsatellite Research Laboratory of National Cheng Kung University (see opening photo and cover). For the longitudinal motion, a combination of a linear quadratic integral (LQI) controller and a Kalman filter in the inner-loop system was used to control the vertical velocity and height mainly using an elevator. For the lateral motion, the LQG autopilots were designed with guaranteed robustness properties that allowed quick return to the designed point.
The SP.X-6 aircraft state functions are shown in Equation 2, in which the x, u, y, w, and v mean the system state vector, input, measurement, process error vector, and the measurement error, respectively. A, B, C, and K refer to the system state matrices, which can be evaluated by the system identifications that are derived by using the subspace identification to obtain an initial model. After that, the initial model will feed into the recursive prediction error method algorithm in order to arrive at further refined models.
(2)
Figure 11. Linear quadratic Gaussian regulator block diagram.
After obtaining the aircraft’s model, the LQG controller is used, a block diagram for which is shown in Figure 11 and for which the close-loop dynamic is given by Equation 3. The means the estimated states are feedback by which to form the optimal control law, u=−K. The y means the output command with the LQG variables F, G, K, and L.
(3)
The aircraft landing controls were divided into the longitudinal and lateral dynamics. For the longitudinal dynamics, the landing command was the vertical discrete height. In the case of the lateral dynamics, the stable condition was used when disturbances were encountered.
Up till now, navigation of SP.X-6 relied solely on the GPS signal. Using RTK technique for the landing process will enhance navigation accuracy. The navigation method is the point-to-point guidance law illustrated in Figure 12.
Figure 12. The point-to-point guidance law.
The basic concept of the point-to-point guidance law can be derived from the aircraft initial position A and the target position B in two-dimensional coordinate frame at every epoch. Desired heading angle θT and the distance between two points d can computed at each control loop via Equation 4.
(4)
The navigation signal used in the simulation is of 20 Hz.
Deck Motion Simulation. Variations in waves are formed by the wind, and waves do not propagate only in one direction; the other direction will also affect wave propagation. The wave always is set as a stationary random process for the purpose of processing. The Longuet-Higgins model assumes that random waves are composed of many different wavelengths and harmonic amplitude superposition. Assuming the wave travels in a fixed direction, the peaks and troughs of the wave lines are parallel to each other and perpendicular to the forward direction of the waves, which are called two irregular waves or crested waves. Crested waves cause greater ship motion. The crested wave model indicates that point a at t epoch on a random sea wave height can be expressed as Equation 5, where ai-th represents harmonic waves with ωi frequency and εi initial condition.
(5)
It can be seen that the wave function can be expressed as a superposition of individual harmonics, so as long as waves establishing harmonic amplitudes and harmonic frequencies can be simulated in order to create the wave model. In this research, the amplitudes and the initial conditions are obtained from the sea wave spectrum of the ITTC model:
(6)
Four different sea state conditions were designed, as shown in Table 8 in the integrated simulation. Using the parameters from the spectrum analysis and the frequency divide method, the sea wave simulation could be obtained. Figures 13 and 14 show the simulation results of sea state A. Figure 15 shows all four state spectrum simulations results, and Figure 16 shows the sea wave height.
Figure 13. Sea State A spectrum.Figure 14. Sea State A wave height.Figure 15. Wave spectrum simulation results.Figure 16. Wave height simulation results.
Integrated Simulations
In the integrated simulation, first the health of the RTK information was examined, and then, according the environment parameter settings, sea wave simulations were conducted. Subsequently, the aircraft landing process errors were presented using the experimental positioning analysis.
The integrated simulation system is shown in Figure 17; it can be divided into three parts. The first part is the sea state options shown in the black line region, and the sea wave change is displayed and the maximum changing rate is calculated after the sea state option is selected. The second part is shown in the green line region that is the landing analysis which includes RTK health status, ENU error size. The last part is the landing animation which is enclosed in the red line region.
Figure 17. Integrated simulations graphic user interface.
Four sea-wave height simulation statuses can be selected, and the chosen sea state can be used to determine the corresponding landing environment, as shown in Figure 18, which illustrates the ship motion simulated by the wave height.
Figure 18. Sea wave change.
RTK health information was simulated according to the experimental results in Table 9, in which the RTK information unavailability was 1.1 percent. A random Gaussian number was used to simulate the health of the RTK satellite information.
After the sea-wave simulation and the RTK health simulation, the second concern was the landing process simulation. The landing process simulation has two conditions, namely the “normal landing” condition and the “landing with common-view satellite problem” condition. The normal landing process errors were presented using the Sea State Experiment results, while the landing with common-view satellite problem process errors was simulated by the result of Common View Satellite Experiment positioning analysis.
For example, a ship was traveling at a velocity of 10 m/s in East, and an aircraft was cruising at a velocity of 20 m/s toward the East. The initial position of the ship was at (ES, NS, US) = (200, 0, 0) and the aircraft was at (EA, NA, UA) = (0,150,100). In the landing process, the desired heading angle and the distance to the waypoint were evaluated every epoch. The simulated landing process example is shown in Figure 19; the blue line is the ship’s trajectory and the red line indicates the aircraft’s trajectory.
Figure 19. The simulated landing process example.
The guidance accuracy includes the control accuracy and the navigation sensor measurement accuracy. In the simulation result, the control accuracy (that is, controller error) was neglected. Therefore, the error for the landing process becomes only the navigation sensor measurement error which was the RTK error in this article. Users have the options to add different controllers as well as the controller error in the simulations.
The landing positioning error was simulated using the imported analysis results in the correspondence sea state included in the RTK status shown in Figure 20 and the landing ENU errors are shown in Figure 21.
Figure 20. RTK state simulation results.Figure 21. The ENU errors of the simulated landing process example.
Red stars in Figure 20 indicate the warning window when the simulated RTK statuses were unhealthy. For example, the 114th, 126th, 169th and 240th epochs in Figure 21 indicate that RTK data is unavailable during this time simulation. The unhealthy RTK signal might cause interruptions in navigation service in the landing process, as shown as the red stars in Figure 21. For the epochs with red stars, the simulated position results were exceeding the performance requirement for RTK shipboard landing. When this situation happened, the monitoring system might raise a flag to the aircraft’s guidance system not to use the RTK signal for landing at this period of time. Excluding these unhealthy RTK epochs, the simulated landing errors were well met the performance requirement for RTK shipboard landing, as shown in Figure 22.
Figure 22. The ENU errors of the simulated landing process after excluding the unhealthy RTK results.
An overall simulation result is illustrated in Figure 23, when the successful landing message was shown in a pop-up window, the landing information of the whole landing process would be shown in the graphic user interface.
Figure 23. Example simulation result.
Conclusions
Experimental results showed that 99 percent of the horizontal positioning was in the range requirement of 0.3 meters. Using the common view satellite experiment and the sea state variation experiment conducted in this study, the limitations of RTK positioning can be understood. Monitoring the RTK status can provide high-quality accuracy with regard to guidance of the landing process. We hope that the results of this study will become a reference for building a shipboard landing system in Taiwan.
Manufacturers
All of the experimental data were collected by a workshop computer through a NovAtel (www.novatel.com) Connect program data file. The base station setup included a NovAtel GPS-703-GGG antenna with a Sokkia tripod and the NovAtel Propak-V3 RT2-G receiver. The rover station setup included a portable vehicle with a battery, a NovAtel GPS-703-GGG antenna and the NovAtel Propak-V3 RT2-G receiver.
Chiu-Jung Huang received her B.S. degree from National Cheng Kung University (NCKU) in Taiwan. She is currently studying for her M.S. degree in aeronautics and astronautics at NCKU.
Shau-Shiun Jan is an associate professor of aeronautics and astronautics at NCKU. He directs the NCKU Communication and Navigation Systems Laboratory (CNSL). His research focuses on GNSS augmentation system design, analysis, and application. He received his Ph.D. degree in aeronautics and astronautics from Stanford University.
Dave and Arnold Bansemer prepare the X100 for the survey.
Surveying an open-pit mine can be a hazardous undertaking. To obtain accurate volume measurements, it is necessary to pick up edges, known in the industry as “toes and crests,” as well as heaps. These are important features, since they provide a way to verify the current shape of a mine; but in light of increasingly stringent safety regulations and penalties, some companies refuse to let the surveyor get too close to such areas. Surveying the site from the air is an effective solution to this challenge.
It’s also a cost-effective solution. Namibian Mining Survey Services (NMSS) estimates that using an unmanned aerial system (UAS) can save more than 95 percent in mobilization costs, that is, bringing in resources from outside the country to conduct a lidar/photogrammetric survey. Believing UAS to be an important part of the future of surveying, NMSS had been investigating the technology for some time, and a recent project provided the perfect opportunity to try it out.
NMSS selected the Gatewing X100 for the job based on a demo at a platinum mine, where the results closely tracked those of a previous lidar survey.
The Project
The project was to survey a portion of Abenab Mine, a vanadium-lead mine owned by South West Africa Company and located just west of Tsumeb. The mine had been closed in the 1960s, but feasibility studies were underway to see if it would be viable to reopen the operation. Mine management needed to know volumes of all waste and tailings dumps, slimes, dams, and open-pit excavations. The main pit was roughly circular, about 60 meters deep and 120 meters across. Two smaller pits were covered in fairly thick vegetation but had enough ground showing to provide an accurate shape.
The survey area was approximately 100 hectares. The flying height was set at 150 meters in order to provide a ground separation distance of 5 centimeters. Ground control points (GCPs) were constructed from 1-meter lengths of masonite cut into 10-centimeter-wide strips; painted bright red, the strips were designed to provide 20 x 2 pixel coverage on the images. A total of 10 GCPs were set out in strategic positions covering a wide range of elevations, with points on top of the dumps, on undisturbed ground level, and in the pits. The points were fixed from existing control on the UTM34S coordinate system, by fast static techniques.
Launching the X100
The X100 prepares for flight.
Based on the Gatewing training received, basic photogrammetry principles and a few trials, NMSS determined that 9 a.m. to 3 p.m. was the best time to fly in order to avoid shadow. The flight area, including a previously surveyed area that would serve as a check, covered 140 hectares. Assuming favorable wind conditions, NMSS expected to cover the area on a single flight.
Arriving on site at 7 a.m., Dave Bansemer of NMSS started setting out the GCPs while his colleague performed the fast static survey. By 10 a.m., all GCPs had been placed and fixed. Having identified a suitable take-off and landing spot (a farm road), they proceeded through the pre-flight and flight checklist, and then launched the X100 at 11 a.m.. After completing the flight in around 35 minutes, with some turbulence at the 150-meter flying altitude, the X100 landed safely, albeit short of the goal, in an open area.
Once the data was downloaded, the team returned to Tsumeb to begin the processing. They started with the post-processing of the GCPs, and then moved to the coordinates obtained in the photo-control identification process. NMSS used Gatewing Stretchout Pro software for the photogrammetrical processing.
After specifying the coordinate system and identifying the GCPs, number-crunching began; the processing ran for around seven hours before the final point cloud and orthomosaics were created. The mean horizontal error was 3 centimeters and the vertical error was 9 centimeters, well within the error budget.
Results
Aerial image of the X100 survey.
The first check was to see if all areas had been covered. NMSS then checked the point cloud against the previous survey. The tie-in was perfect. Some gaps in the point cloud seemed to correspond with tree canopy areas; to ensure complete accuracy, the team resurveyed a few areas using a spatial station.
NMSS learned some important lessons from using UAV technology for survey, which Bansemer lists for the benefit of future users:
Make sure you have enough control. It is sometimes difficult to place your control points exactly in the corners of your flight and one in the center, as the actual flight is influenced by wind direction and the shape of the flight may change accordingly. Put down more points than recommended.
Make sure that your ground control point size is relevant to your flying height. You will not be able to identify a 10-centimeter wide strip if you fly at 300 meters.
Check the completeness of the job before you leave the area.
Make sure there is sufficient area for a safe landing. Bansemer recommends at least a 300-meter strip, taking obstacles into account in the event of a short landing.)
Manufacturers
The fast static techniques described were carried out with Trimble R6 GPS systems. Re-survey was done with the Trimble VX spatial station. The Gateway X100 is manufactured by Trimble.
Raven Industries, Inc. announces that its Applied Technology Division (ATD) has acquired SBG Innovatie BV and its affiliate, Navtronics BVBA. Headquartered in Middenmeer, Netherlands, SBG manufactures advanced GPS steering systems for a variety of agricultural applications. The acquisition broadens Raven’s guided steering system product line by adding high-accuracy implement steering applications. Additionally, SBG’s headquarters will become the new home office for Raven in Europe, expanding the company’s global presence and reach into key European markets. The purchase is not expected to have a material impact on Raven’s fiscal 2015 results.
“SBG specializes in very precise, real time kinematic, or RTK, GPS steering systems with a focus on high-value crops. Their highly accurate implement steering technology broadens Raven’s existing product line and integrates well into the Raven product portfolio.” said Matt Burkhart, ATD’s Division Vice President and General Manager. “We are proud to welcome the SBG organization into the Raven family. Our innovative cultures align very well, and SBG’s leading technology and strong team members will be a great compliment to further Raven’s position as a leader in the precision ag market.”
“Our priorities within ATD are to drive growth through international market expansion, new products and broadening OEM relationships,” said Daniel A. Rykhus, Raven’s president and chief executive officer. “We believe SBG can help further these strategies and position us for success in new markets.”
“We’re excited to join Raven so that, together, we can expand Raven’s footprint in key geographies and augment their expertise and product line,” said Rik van Bruggen, managing director of SBG. “In turn, Raven’s scale and resources will allow SBG to realize our dream of growing the business and helping customers increase yields and efficiencies. Raven is a good partner for us because they are committed to increasing their presence in Europe and providing additional opportunities for our team.”
Effective immediately, SBG’s products will be offered as a part of Raven’s lineup of precision ag products. Sales team members from both companies will be offering the combined product lines.
Trimble is making available the Trimble Irrigate-IQ precision irrigation solution in North America. Along with the North American launch, Trimble also introduced the Connected Farm Irrigate app, which provides farmers with real-time status and control of their pivot irrigation systems using a smartphone or tablet.
The Irrigate-IQ GPS-controlled solution, which is installed on the pivot, enables farmers to remotely control their irrigators via the Internet, including performing variable rate irrigation, and receive reports about where water or fertilizer has been applied. With the solution, farmers can apply the optimal amount of water, fertigation or effluent where needed, which can improve crop quality and yield, while minimizing nutrient and chemical runoff. The solution enables farmers to conserve water use and improve efficiency, reduce energy costs for fuel and electricity, minimize input costs, comply with environmental regulations, and safely dispose of effluent. In addition, Trimble’s brand-agnostic strategy allows farmers to use the solution with most irrigator makes and models. Irrigate-IQ is also available in New Zealand.
In addition, Trimble introduced the Connected Farm Irrigate app for use on an iPhone, iPad, Android smartphone or tablet. The app allows farmers to see the status of their pivots, including whether they are operating or not operating, in which direction they are traveling, the heading, pump pressure, pivot voltage and type of material being dispersed (water, fertigation, or effluent). It also gives farmers the ability to remotely start or stop their pivots, choose the direction (forward or reverse), turn the pump on or off or switch the type of material being dispersed. This new functionality comes in addition to farmers’ ability to remotely control their irrigators by accessing the Irrigate-IQ software on a desktop or laptop computer, rugged mobile computer or tablet.
“Now that Trimble has expanded availability of its Irrigate-IQ solution, and launched the Connected Farm Irrigate app, farmers across North America and New Zealand will be able to monitor and control their irrigators from virtually any location,” said David Fitzpatrick, business area director of Trimble’s Agriculture Division. “Irrigate-IQ allows farmers to be more strategic with their irrigation planning, while the app creates time savings and increased efficiencies by allowing farmers to respond to weather changes or faulty equipment on the fly without being on site.”
The Irrigate-IQ solution and Connected Farm Irrigate app are both part of Trimble’s Connected Farm solution, which includes a robust suite of recently announced features including soil analysis, rainfall totals, weather forecasts, commodity tracking, and now irrigation monitoring and control.
The Trax personal tracker for children and pets uses a u-blox receiver.
Swedish WTS (Wonder Technology Solutions) has launched Trax, a personal tracking device for children and pets. Based on a u-blox GNSS receiver module with integrated antenna and cellular module, the tiny tracker can be located anywhere, anytime via a free Android or iPhone mobile phone app.
In addition to real time tracking, Trax provides flexible geofence alerts, and can monitor how fast your teenager is driving. It also works indoors, thanks to a proprietary dead-reckoning algorithm that delivers a position even when satellites are out of sight. Accurate down to 1.5 meters, the robust, water resistant device also provides an “augmented reality” mode that helps users locate their trackers using a smartphone’s built-in camera view.
To achieve the smallest possible size, Trax uses a u-blox’ CAM-M8Q GNSS receiver module with a built-in antenna. CAM-M8Q (chip antenna module) provides both small size (9.6 x 14.0 x 1.95 mm) and multi-GNSS capability. It is based on a u-blox M8 chip and includes an integrated chip antenna plus SAW filter, LNA, TCXO, RTC crystal and passives. The surface-mount module is also extremely low in height making very thin customer designs possible.
“Trax is the world’s smallest and most versatile personal tracking device available, packed with features designed to provide peace of mind to parents and pet owners almost anywhere in the world,” said Fredrik Danelius, Managing Director at WTS, “By combining the leading GNSS and cellular technologies from u blox, we have designed a tiny, reliable, low-cost device that protects our most valuable family members: children and pets.”
Trax comes with an integrated SIM-card and two years of free data and roaming in 33 countries. It is charged via USB and typically lasts between two and four days on a full battery. For wireless connectivity, device integrates a u blox SARA-G3 GSM/GPRS module which is footprint compatible with the SARA-U2 UMTS/HSPA module for easy 2G to 3G upgrade.
“Trax is an elegant and sophisticated example of our embedded GNSS and cellular modules combined to protect people’s loved ones,” said Pasi Alajoki, Area Sales Manager at u-blox, “It is an extremely important application of our mobile communications and global positioning technology where performance, size and power consumption play a critical role. We are proud WTS chose u-blox for Trax.”
deCarta, Inc., an independent LBS platform company, has expanded coverage of its advanced local search technology, the L2 Geospatial Search Engine, to 120 countries including Europe, North America, and most major countries around the world.
L2 is a high-performance, scalable local search engine with single line input to enable a more intuitive user interface, the company said. deCarta sources and indexes premium map and POI (Points of Interest) content but also enables customers to index and control their own content using the L2 Index tools.
deCarta’s L2 has advantages over most other search engines in that it can be used as a pure geocoder for address search, or for POI search….or simultaneously as a combination of the two mixed in a single line search query – with the additional ability to tune this behavior at runtime. This gives developers maximum flexibility and creativity in producing their mobile and desktop applications. The new expanded country coverage now enables deCarta customers to offer truly global services.
The L2 Search engine is an integral component of deCarta’s LBS platform which provides specialized geospatial technologies for maps, routing, navigation, geocoding, local search and geo-data integration and processing. deCarta offers two deployment models for its LBS platform: a Hosted LBS Platform Service (PaaS) or, alternatively, customers can self-host the platform either on-premise or in a cloud service such as Amazon’s AWS. Both approaches utilize deCarta’s advanced REST API architecture and can scale to support billions of maps and searches and millions of users per month.
L2 enables deCarta’s customers to offer flexible, advanced local search capabilities that are on par with Google Maps but beyond other search engines, deCarta said. Examples include:
Single line entry of POI or address or both
Fast typeahead, predictive entry – ideal for mobile devices and web interfaces
High tolerance for misspellings and partial entries
Random ordering of address parameters
Search for a POI near a POI, such as:
“Coffee near XYZ company”
“Restaurants on Main Street”
“ATMs near AMC Theater”
Search for POI near a specific address, such as “Parking near 1234 Main Street”
Furthermore, the ability to integrate L2 with deCarta’s patented “Search Along A Route” technology gives automotive OEMs and Telematics Service Providers the ability to offer more advanced and helpful “driver-centric” connected car services.
“We are excited by the market reaction to L2 since its introduction last year,” said J. Kim Fennell, CEO of deCarta. “We’re winning business competing with, and in some cases replacing, major local search engines such as Google Maps based on the merits of L2’s technology advantages, customization capabilities, flexible content offerings, less restrictive license terms and our superior customer service – all of which creates a more satisfied customer experience.”
deCarta offers a “house blend” of premium map and POI content with L2. It works closely with worldwide and regional map data providers including TomTom, Nokia/HERE, OpenStreetMap (OSM), AND, Sensis, IPC, Nav2 and eMapgo; as well as leading POI providers and other content sources (traffic, parking, weather, speed cameras, etc). deCarta integrates and de-duplicates multiple content sources for optimum search results.
deCarta provides the tools to let companies index and search on their own content for maximum control and commercial advantage. This content can stand alone or be merged with industry map and POI content. Customers can “boost” content and control rankings to suit their needs. These capabilities provide huge benefits for local search companies, Automotive OEMs and telematics service providers seeking to offer their users the best customer care and connected car services.
For more information on L2, please visit deCarta’s web site at www.decarta.com or go straight to the demo. Developers can find more technical details at deCarta’s DevZone.
Geotab, a telematics engineering company, is announcing its J1939 integration launch with Mobileye’s Advanced Driver Assistance System — the Mobileye 560. In combining these two solutions, businesses with heavy-duty fleets will be able to use advanced warning alerts to reduce the likelihood of vehicle crashes from occurring.
In addition to the reports provided by Mobileye and Geotab that target unsafe driving practices, the solution also provides lane departure warnings, forward collision warnings, pedestrian and bicyclist warnings, distance keeping (headway) warnings, and speeding alerts. The ultimate goal is to give drivers added visibility and insight in the unexpected moments they need it most.
Edward Kulperger, VP of Business Development for Geotab, commented on the cooperation by explaining that “fleet management technology has evolved to include proactive and dynamic solutions that incorporate real time data in the vehicle and in a fleet’s operations to predict and alert both safety and efficiency elements of fleets.” Isaac Litman, Mobileye Inc.’s CEO, Mobileye Aftermarket, said, “With Geotab, we have provided businesses with an unbeatable driver monitoring and evaluation system. It is the one of the most effective risk management tools available in the marketplace today.” This enthusiasm was also mirrored by Neil Cawse, Geotab’s CEO, “The ease in which businesses can adopt this technology makes it possible for fleet managers to show real savings that make an impact on the bottom line.”
According to Mobileye, fleets using this collision avoidance technology typically realize a return on their investment in about 6-8 months. The benefits are abundant: Safe driving habits are significantly improved, costs associated with accidents are reduced or completely avoided, smooth driving patterns are reinforced on a continuous basis, and fuel and maintenance costs are minimized. Geotab and Mobileye are working together to bring the solution to the global market.
Supergeo Technologies, a provider of GIS software and solutions, has launched SuperSurv, a mobile GIS app, on the App Store and Google Play.
For users in North America, Supergeo has released the SuperSurv M3 version to provide easy-to-use and useful data collection and map display functions. SuperSurv M3 supports feature-layer display and offline editing functions. Furthermore, cached maps can be adopted as the base map to facilitate data capture tasks.
