NVS Technologies has released updated firmware for its NV08C receiver series. Firmware v0206 is compatible with current and preceding hardware revisions of the NV08C receiver series. Firmware v0206 can be downloaded free of charge.
Firmware v0206 offers:
Stabilized raw data output for output rates up to 10 Hz
Extended $POUTC NMEA message, including current LEAP SECONDS value, flags for expected UTC correction, and PPS edge shift relative to UTC (sawtooth correction SW).
Stabilized sleep mode operation ($POPWR,1111*66) for all NV08C series HW versions
Increased position accuracy and stability in urban canyon conditions with poor SV visibility
Cold start initialized to LEAP SECOND 16 (LEAP SECOND 16 came into effect July 1, 2012)
Benefits include:
Obtain initial receiver coordinates more quickly, in cold starts, low satellite signal (foliage/canopy) and loss of satellite signal conditions (indoor, garages, tunnels…).
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.
Emerging GNSS applications in automobiles support regulation, security, safety, and financial transactions, as well as navigation, guidance, traffic information, and entertainment. The GNSS sub-systems and onboard applications must demonstrate robustness under a range of environments and varying threats. A dedicated automotive GNSS test center enables engineers to design their own GNSS test scenarios including urban canyons, tunnels, and jamming sources at a controlled test site.
By Mark Dumville, William Roberts, Dave Lowe, Ben Wales, NSL, Phil Pettitt, Steven Warner, and Catherine Ferris, innovITS
Satellite navigation is a core component within most intelligent transport systems (ITS) applications. However, the performance of GNSS-based systems deteriorates when the direct signals from the satellites are blocked, reflected, and when they are subjected to interference. As a result, the ability to simulate signal blockage via urban canyons and tunnels, and signal interference via jamming and spoofing, has grown fundamental in testing applications.
The UK Center of Excellence for ITS (innovITS), in association with MIRA, Transport Research Laboratory (TRL), and Advantage West Midlands, has constructed Advance, a futuristic automotive research and development, and test and approvals center. It provides a safe, comprehensive, and fully controllable purpose-built road environment, which enables clients to test, validate and demonstrate ITS. The extensive track layout, configurable to represent virtually any urban environment, enables the precise specification of road conditions and access to infrastructure for the development of ITS innovations without the usual constraints of excessive set up costs and development time.
As such, innovITS Advance has the requirement to provide cityscape GNSS reception conditions to its clients; a decidedly nontrivial requirement as the test track has been built in an open sky, green-field environment (Figure 1).
Figure 1. innovITS Advance test circuit (right) and the environment it represents (left).
NSL, a GNSS applications and development company, was commissioned by innovITS to develop Skyclone in response to this need. The Skyclone tool is located between the raw GNSS signals and the in-vehicle system. As the vehicle travels around the Advance track, Skyclone modifies the GNSS signals to simulate their reception characteristics had they been received in a city environment and/or under a jamming attack. Skyclone combines the best parts of real signals, simulated scenarios, and record-and-replay capabilities, all in one box. It provides an advanced GNSS signal-processing tool for automotive testing, and has been specifically developed to be operated and understood by automotive testing engineers rather than GNSS experts.
Skyclone Concept
Simulating and recreating the signal-reception environment is achieved through a mix of software and hardware approaches. Figure 2 illustrates the basic Skyclone concept, in which the following operations are performed.
In the office, the automotive engineer designs a test scenario representative of a real-world test route, using a 3D modelling tool to select building types, and add tunnels/underpasses, and jammer sources. The test scenario is saved onto an SD card for upload onto the Skyclone system.
The 3D model in Skyclone contains all of the required information to condition the received GNSS signals to appear to have been received in the 3D environment.
The Skyclone system is installed in a test vehicle that receives the open-air GNSS signals while it is driven around the Advance track circuit.
The open-air GNSS signals are also received at a mobile GNSS reference receiver, based on commercial off-the-shelf GNSS technology, on the test vehicle. It determines the accurate location of the vehicle using RTK GNSS. The RTK base station is located on the test site.
The vehicle’s location is used to access the 3D model to extract the local reception conditions (surrounding building obstructions, tunnels attenuations, jamming, and interference sources) associated with the test scenario.
Skyclone applies satellite masking, attenuation, and interference models to condition/manipulate raw GNSS signals received at a second software receiver in the onboard system. The software receiver removes any signals that would have been obstructed by buildings and other structures, and adds attenuation and delays to the remaining signals to represent real-world reception conditions. Furthermore, the receiver can apply variable interference and/or jamming signatures to the GNSS signals.
The conditioned signals are then transmitted to the onbaord unit (OBU) under test either via direct antenna cable, or through the air under an antenna hood (acting as an anechoic chamber on top of the test vehicle). Finally, the GNSS signals produced by Skyclone are processed by the OBU, producing a position fix to be fed into the application software.
Figure 2. Skyclone system concept.
The Skyclone output is a commercial OBU application that has been tested using only those GNSS signals that the OBU receiver would have had available if it was operating in a real-world replica environment to that which was simulated within the Skyclone test scenario.
Skyclone Architecture
The Skyclone system architecture (Figure 3) consists of five principal subsystems.
Office Subsystem Denial Scenario Manager. This software has been designed to allow users to readily design a cityscape for use within the Skyclone system. The software allows the users to select different building heights and styles, add GNSS jamming and interference, and select different road areas to be treated as tunnels.
Figure 3. Baseline Skyclone system architecture.
City Buildings. The Advance test site and surrounding area have been divided into 14 separate zones, each of which can be assigned a different city model. Ten of the zones fall inside of the test road circuit and four are external to the test site. Each zone is color-coded for ease of identification (Figure 4).
Figure 4. Skyclone city zones.
The Skyclone system uses the city models to determine GNSS signal blockage and multipath for all positions on the innovITS Advance test site. The following city models, ordered in decreasing building height and density, can be assigned to all zones: high rise, city, semi urban, residential, and parkland.
Interference and Jamming. GNSS jamming and interference can be applied to the received GNSS signals. Jamming is set by specifying a jamming origin, power, and radius. The power is described by the percentage of denied GNSS signal at the jamming origin and can be set in increments of 20 percent. The denied signal then decreases linearly to the jammer perimeter, outside of which there is no denial.
The user can select the location, radius, and strength of the jammer, can select multiple jammers, and can drag and drop the jammers around the site.
Tunnels. Tunnels can be applied to the cityscape to completely deny GNSS signals on sections of road. The user is able to allocate “tunnels” to a pre-defined series of roads within the test site. The effect of a tunnel is to completely mask the sky from all satellites.
Visualization. The visualization display interface (Figure 5) provides a graphical representation of the scenario under development, including track layout, buildings, locations, and effects of interference/jammers and tunnels. Interface/jammer locations are shown as hemispherical objects located and sized according to user definition. Tunnels appear as half-cylinder pipes covering selected roads.
Figure 5. 3D visualisation display.
Reference Subsystem
The reference subsystem obtains the precise location of the test vehicle within the test site. The reference location is used to extract relevant vehicle-location data, which is used to condition the GNSS signals.
The reference subsystem is based on a commercial off-the-shelf real-time kinematic GPS RTK system, capable of computing an accurate trajectory of the vehicle to approximately 10 centimeters. This position fix is used to compute the local environmental parameters that need to be applied to the raw GNSS signals to simulate the city scenario.
A dedicated RTK GNSS static reference system (and UHF communications links) is provided within the Skyclone system. RTK vehicle positions of the vehicles are also communicated to the 4G mesh network on the Advance test site for tracking operational progress from the control center.
Vehicle Subsystem
The vehicle subsystem acquires the GNSS signals, removes those that would be blocked due to the city environment (buildings/tunnels), conditions remaining signals, applies interference/jammer models, and re-transmits resulting the GNSS signals for use by the OBU subsystem.
The solution is based on the use of software GNSS receiver technology developed at NSL. In simple terms, the process involves capturing and digitizing the raw GNSS signals with a hardware RF front end. Figure 6 shows the system architecture, and Figure 7 shows the equipment in the innovITS demonstration vehicle.
Figure 6. Skyclone hardware architecture.
The digitized signals are then processed in NSL’s software receiver running on a standard commercial PC motherboard. The software receiver includes routines for signal acquisition and tracking, data demodulation and position determination.
In the Skyclone system, the raw GNSS signals are captured and digitized using the NSL stereo software receiver. The software receiver determines which signals are to be removed (denied), which signals require conditioning, and which signals can pass through unaffected. The subsystem does this through accurate knowledge of the vehicle’s location (from the reference subsystem), knowledge of the environment (from the office subsystem), and knowledge of the satellite locations (from the vehicle subsystem itself).
The Skyclone vehicle subsystem applies various filters and produces a digital output stream. This stream is converted to analog and upconverted to GNSS L1 frequency, and is sent to the transmitter module located on the same board.
The Skyclone transmitter module feeds the analog RF signal to the OBU subsystem within the confines of a shielded GPS hood, which is attached to the vehicle on a roof rack. An alternative to the hood is to integrate directly with the cable of the OBU antenna or through the use of an external antenna port into the OBU. The vehicle subsystem performs these tasks in near real-time allowing the OBU to continue to incorporate non-GNSS navigation sensors if applicable.
Onboard Unit Subsystem
The OBU subsystem, typically a third-party device to be tested, could be a nomadic device or an OEM fitted device, or a smartphone. It typically includes a GNSS receiver, an interface, and a software application. Examples include:
Navigation system
Intelligent speed adaptation system
eCall
Stolen-vehicle recovery system
Telematics (fleet management) unit
Road-user charging onboard unit
Pay-as-you-drive black-box
Vehicle-control applications
Cooperative active safety applications
Vehicle-to-vehicle and vehicle-to-infrastructure systems.
Tools Subsystem Signal Monitor
The Skyclone Monitor tool provides a continuous monitoring service of GNSS performance at the test site during tests, monitoring the L1 frequency and analyzing the RF singal received at the reference antenna. The tool generates a performance report to provide evidence of the open-sky GNSS conditions. This is necessary in the event of poor GNSS performance that may affect the outcome of the automotive tests. The Skyclone Monitor (Figure 8) is also used to detect any spurious leaked signals which will highlight the need to check the vehicle subsystem. If any spurious signals are detected, the Skyclone system is shut down so as to avoid an impact on other GNSS users at the test site. A visualization tool (Visor) is used for post-test analysis displaying the OBU-determined position alongside the RTK position within the 3D environment.
Figure 8. GNSS signal and positioning monitor.Figure 9. 3D model of city.
Performance
Commissioning of the Skyclone system produced the following initial results. A test vehicle was installed with the Skyclone and RTK equipment and associated antennas.. The antennas were linked to the Skyclone system which was installed in the vehicle and powered from a 12V invertor connected to the car power supply. The output from the RTK GPS reference system was logged alongside the output of a commercial third-party GNSS receiver (acting as the OBU) interfaced to the Skyclone system. Skyclone was tested under three scenarios to provide an initial indication of behavior: city, tunnel, and jammer.
The three test cenarios were generated using the GNSS Denial Scenario Manager tool and the resulting models stored on three SD cards. The SD cards were separately installed in the Skyclone system within the vehicle before driving around the test site.
City Test. The city scenario consisted of setting all of the internal zones to “city” and setting the external zones to “high-rise.”
Figure 10A represents the points as provided by the RTK GPS reference system installed on the test vehicle. Figure 10B includes the positions generated by the COTS GPS OBU receiver after being injected with the Skyclone output. The effect of including the city scenario model is immediately apparent. The effects of the satellite masking and multipath model generate noise within the position tracks.
Figure 10A. City scenario: no Skyclone.Figure 10B. City scenario: withSkyclone.
Tunnel Test. The tunnel scenario consists of setting all zones to open sky. A tunnel is then inserted along the central carriageway (Figure 11). A viewer location (depicted by the red line) has been located inside the tunnel, hence the satellite masking plot in the bottom right of Figure 11 is pure red, indicating complete masking of satellite coverage. The output of the tunnel scenario is presented in Figure 12. Inclusion of the tunnel model has resulted in the removal of all satellite signals in the area of track where the tunnel was located in the city model. The color shading represents signal-to-noise ratio (SNR), an indication of those instances where the output of the test OBU receiver has generated a position fix with zero (black) signal strength, hence the output was a prediction. Thus confirming the tunnel scenario is working correctly.
Figure 11. 3D model of tunnel.Figure 12. Results.
Jammer Test. The jammer test considered the placement of a single jammer at a road intersection (Figure 13). Two tests were performed, covering low-power jammer and a high-power jammer. Figure 14A shows results from the low-power jammer. The color shading relates to the SNR as received within the NMEA output from the OBU, which continued to provide an output regardless of the jammer. However, the shading indicates that the jammer had an impact on signal reception.
Figure 13. Jammer scenario.Figure 14A. Jammer test results: low power interference.Figure 14B. Jammer test results: high-power interference.
In contrast the results of the high-power jammer (Figure 14B) show the effect of a jammer on the OBU output. The jammer denies access to GNSS signals and generates the desired result in denying GNSS signals to the OBU. Furthermore, the results exhibit features that the team witnessed during real GNSS jamming trials, most notably the wavering patterns that are output from GNSS receivers after they have regained tracking following jamming, before their internal filtering stabilizes to nominal behaviors.
The Future
The Advance test site is now available for commercial testing of GNSS based applications. Current activity involves integrating real-world GNSS jammer signatures into the Skyclone design tool and the inclusion of other GNSS threats and vulnerabilities.
Skyclone offers the potential to operate with a range of platforms other than automotive. Unmanned aerial systems platforms are under investigation. NSL is examining the integration of Skyclone features within both GNSS simulators as well as an add-on to record-and-replay tools. This would enable trajectories to be captured in open-sky conditions and then replayed within urban environments.
Having access to GNSS signal-denial capability has an immediate commercial interest within the automotive sector for testing applications without the need to invest in extensive field trials. Other domains can now benefit from such developments. The technology has been developed and validated and is available for other applications and user communities.
Downtown Seattle, a typical test-case environment.
Multi-Constellations Working in a Dense Urban Future
GNSS receivers in cell phones will soon support four or more satellite constellations and derive additional location measurements from other sources: cellular location, MEMS sensors, Wi-Fi, and others. The authors propose test standards covering these sources, meeting industry requirements for repeatable testing while considering the user experience.
By Peter Anderson, Esther Anyaegbu, and Richard Catmur
Cellular location test standards include well-defined and widely used standards for GPS-based systems in both the 3rd Generation Partnership Program cellular technologies of GSM/WCDMA/LTE, typically referenced as the 3GPP standards, and for CDMA technologies in the 3GPP2 standards. These standards provide a reference benchmark for location performance in the laboratory, when the unit under test is directly connected to the test system via a coax connection. In addition, standards are being rolled out, such as the CTIA — The Wireless Association total isotropic sensitivity (TIS) requirement, for over-the-air (OTA) testing and developed further with LTE A-GPS OTA using SUPL 2.0. These tests are typically performed in an anechoic chamber and allow the performance of the antenna to be included.
Recently developed standards such as the 3GPP Technical Specification (TS) 37.571-1 cover multi-constellation systems, typically GPS and GLONASS for a two-constellation system, or GPS, GLONASS and Galileo for a three-constellation system, with options for additionally supporting QZSS and space-based augmentation system (SBAS) satellites. During 2014, the standards will encompass additional constellations such as the BeiDou satellite system.
Figure 1A. GNSS systems available in the 2015-2020 timescale.Figure 1B. GNSS systems available in the 2015-2020 timescale.
Significant change is also happening with the additional technologies such as cellular location, Wi-Fi, and micro-electromechanical systems (MEMS) sensors providing location information. Hybrid solutions using all/any available location information from these multiple technologies present significant challenges to both the test environment and the related test standards.
The acceptance levels required for the platform integrators and their customers are becoming much more stringent, as the use cases of the location become more diverse. These present further challenges to the performance requirements for test standards for cellular location.
Measuring Performance
The rapid growth in the GNSS applications market has driven users to demand improvements in the performance and reliability of GNSS receivers. The test standards currently employed by cellular phone and network manufacturers to evaluate the performance of GNSS receivers are even more stringent than the regulatory mandates for positioning of emergency callers and other location-based services. Emergency-call positioning is an example of a service that must provide a position fix in both outdoor and indoor environments.
A user’s experience with a GNSS receiver begins when he switches on the device. The quality of his experience defines the basic performance criteria used to assess the performance of a GNSS receiver.
How long did it take to get a position fix?
How accurate is the position fix?
When the fix is lost, how long did it take the device to reacquire satellites and re-compute the fix?
These expectations define the performance of the GNSS receiver. Manufacturers use these performance metrics to compare the performance of different GNSS receivers.
The receiver’s time-to-first-fix (TTFF) depends on the initial conditions; that is, the type of acquisition aiding data (almanac data, ephemerides, knowledge of time and frequency, and so on) available to the receiver when it is switched on.
Users now expect location-based applications to work regardless of where they are and whether they are in a fixed location or on the move. They expect the same level of performance when they are indoors at home or at work, as outdoors in a rural or urban environment. This has led to an increased demand for accurate and reliable outdoor and indoor positioning.
Reacquisition time — how quickly a receiver recovers when the user goes through a pedestrian underpass or under a tunnel or a bridge, for instance — is not tested in any of the existing test standards discussed here.
The useable sensitivity of any GNSS receiver is key to its performance. It defines the availability of a GNSS positioning fix. The acquisition sensitivity defines the minimum received power level at which the receiver can acquire satellites and compute a position fix, while the tracking sensitivity of a receiver defines the minimum received power level at which a GNSS receiver is still able to track and maintain a position fix.
Different applications use different criteria to characterize the performance of a GNSS receiver. In an E911 scenario, for instance, position accuracy and response time are critical, whereas for navigation while driving, accuracy and tracking sensitivity are important. The test criteria employed by different manufacturers are intended to verify the suitability of a particular device for the required application.
The initial test conditions are defined by the manufacturers to ensure that the different devices are tested in the same way. These conditions describe how the test sessions are started, and what acquisition aiding data are available at the start of the test session.
The main divisions among performance tests are:
Laboratory-based tests, either conducted versus OTA RF testing, or simulated versus record-and-playback signal testing.
Real-world testing (field testing). This can be difficult because the test conditions are never the same. Fortunately, it is possible to record these scenarios using an RF data recorder. This allows the same real-world scenario (with the same test conditions) to be tested repeatedly in the lab.
Static scenario testing versus moving scenario testing.
Comparison tests — relative testing (comparing one receiver against another): for reported signal-to-noise ratio (SNR), reported accuracy, and repeatability tests.
Current GNSS Test Standards
Varying performance requirements test the TTFF, accuracy, multipath tolerance, acquisition, and tracking sensitivity of the GNSS receiver. The first three following are industry-defined test standards:
3GPP2 CDMA Performance Standards. The 3GPP2 CDMA test standards (C.S0036-A) are similar to the 3GPP test standards. The 3GPP2 is for CDMA cellular systems, which are synchronized to GPS time.
3GPP GNSS Performance Standards. The latest 3GPP TS 37.571-1 test standard describes the tests for the minimum performance requirements for GNSS receivers that support multi-constellations. It is slightly more stringent than the original 3GPP TS 34.171 test standard. In the 3GPP TS 37.571-1 coarse-time sensitivity test case, signals for only six satellites are generated, whereas in the TS 34.171 coarse-time sensitivity scenario, signals for eight satellites are generated.
Table 1 shows the power levels and satellite allocation for a multi-constellation 3GPP TS 37.571-1 coarse-time sensitivity test case. In this scenario, the pilot signal will always be GPS, if GPS is supported. The signal level of the pilot signal for GPS and GLONASS have been set as –142 dBm, while the non-pilot signal level for GPS and GLONASS have been set as –147 dBm.
Table 1. 3GPP TS 37.571-1 Satellite allocation.
For the 3GPP TS 37.571-1 fine-time assistance test case, six satellites are generated. For the dual-constellation fine-time test, the split is 3+3, and for a triple-constellation test case, the split is 2+2+2, as shown in Table 2.
OTA Requirements. Testing standards have been rolled out for OTA testing, where the testing is typically performed in an anechoic chamber, allowing antenna performance to be included, with tests for the receive sensitivity referenced to an isotropic antenna and over partial summations such as the upper hemisphere. They measure the TIS of the final receiver, and operator requirements typically require OTA acquisition sensitivity of –140 dBm and tracking sensitivity of –145 dBm or lower.
Other modified test standards used by manufacturers to assess the performance of the GNSS receiver include:
Nominal Accuracy Margin Test. This test is based on the 3GPP nominal accuracy test case. All signals are reduced in steps of 1 dB till the test fails to achieve a fix in 20 seconds.
Dynamic Range Margin Test. This test is based on the 3GPP dynamic range test case. All signals are reduced in steps of 1 dB till the test fails to achieve a fix in 20 seconds.
Sensitivity Coarse-Time Margin Test. This test is based on the 3GPP sensitivity coarse-time test case. Both the pilot and non-pilot signals are reduced in steps of 1dB till the test fails to achieve a fix in 20 seconds.
Pilot Sensitivity Coarse-Time Margin Test. This test is based on the 3GPP coarse-time sensitivity test case. The non-pilot signals are always kept at –152 dBm while the signal level of the pilot signal is reduced in steps of 1 dB till the test fails to achieve a fix in 20 seconds.
Non-Pilot Sensitivity Coarse-Time Margin Test. This test is based on the 3GPP coarse-time sensitivity test case. In this test, the pilot signal is always kept at –142 dBm while the signal levels of the other seven non-pilot signals are reduced in steps of 1 dB till the test fails to achieve a fix in 20 seconds.
These modified performance tests are used because they map directly to the end-user’s experience in the real world, measuring the position accuracy, response time, and sensitivity of the GNSS receiver.
Current Equipment. The equipment required for the current test standards are all GNSS multi-satellite simulator-based, either using a single constellation (for GPS), or a multi-constellation GNSS simulator as a component of a larger cellular test system.
Limitation of Current Standards
So far, tests for GNSS in cellular devices have been very much customer/manufacturer specific, starting with 3GPP-type tests, but adding to them. Each will have its own preferred type of tests, with different configurations and types of tests. They have included primarily GNSS simulator tests, either directly connected to the device under test or using radiated signals, together with some corner cases. With chips such as the ST-Ericsson CG1960 GNSS IC, this means that different tests need to be performed for each customer.
Typically the tests are focused on cold or hot TTFF type tests, or sensitivity type tests. Live signal tests have typically been used for drive tests, with a receiver being driven around an appropriate test route, normally in an urban environment. More recently RF replays have become much more widely used, but do require truth data to give validity. RF replay tests are typically used for specific difficult routes for urban drive tests or pedestrian tests.
The 3GPP types of test standards were developed to provide a simple set of repeatable tests. However, they are idealistic, and they do not relate closely to any real-world scenario, and the test connection is defined to be at the antenna port of the system. In reality, different manufacturers and network operator standards take these tests as a given, and define margins on the tests to allow for typical losses due to antennas and implementation on a platform. These margins might be as much as 8 or 10 dB. In addition, manufacturers and network operators define their own variants of the 3GPP tests to match typical real-world usage cases, such as deep indoor.
Challenges
Current location test specifications assume that the key input to the location calculation is always the GPS constellation. With the rise of additional constellations and alternative location sources, and the challenges of the urban environment, GPS will be one of many different inputs to the location position. The key for the future will be for standards focused on testing location performance, irrespective of which constellations are visible, and also being able to fully test the system performance. Tests will be suggested that allow the basic functionality of a system to be checked, but can be enhanced to stress-test the performance of a receiver. As future location systems will use all available inputs to produce a location, there will be challenges to the supporting test standards and test equipment to handle all of these in parallel.
The initial challenge for location test standards has been the use of GNSS constellations in addition to GPS. Current leading GNSS receivers in cellular devices make use of GPS, GLONASS, SBAS, and QZSS, and network-aiding information for A-GLONASS is being rolled out in the cellular networks. The 3GPP TS 37.571-1 specification has been derived from the original GPS-only specification TS 34.171, with the addition of GLONASS and Galileo constellation options. These allow single-, dual-, or triple-constellation tests to be performed. If there is GPS in the system, then GPS is viewed as the primary constellation, and tests like the sensitivity coarse-time assistance test would have a satellite from the GPS constellation with the highest signal level. The test standards also accommodate the use of some satellites from SBAS such as WAAS and QZSS. These tests require that the performance shall be met without the use of any data coming from sensors that can aid the positioning.
This is only the first stage in the rollout of new GNSS constellations, and in the near future, GNSS receivers in cellular phones will support four or more constellations, and possibly also on frequencies additional to the L1 band, covering some or all of: GPS, GLONASS, Galileo, BeiDou Phase 2, BeiDou Phase 3, QZSS, SBAS, and IRNSS.
Table 3. Suggested four-constellation mix (Pilot signal to rotate round constellations).
The challenge for the minimum-performance specifications is to accommodate these different constellations as they become fully available. For the new constellations, this will initially be purely simulator-based, but could be extended to use of live data for certain test cases as the constellations are built up. A further challenge for the test specifications is that some of the systems are regionally based, so a performance specification based on a global approach is not applicable.
Further, tests must be severe enough to stress the receiver. With multiple constellations, it can be simple to pass a test without using all available satellites or constellations.
Other Location Sources (Hybrid Solution). Within the cellular platform, location can be provided by a number of different technologies, either separately or compositely, to provide a location to the accuracy required by the user. Technologies currently available include:
Cellular network: cell ID and cell network triangulation
LTE Positioning Protocol
Fine time assistance (for aiding)
Wi-Fi network name (service set identifier, or SSID)
Wi-Fi ranging
MEMS sensors
Near-field communication
Bluetooth
Pseudolites, other beacons, coded LED lights, and so on.
Real-World Environments. Measuring performance in a real environment is becoming much more important, as the user experience becomes much more key. The product must not only pass particular specifications, but must also meet customer expectations. In the age of the blog, negative customer feedback can damage a product’s reputation. But with the various GNSS constellations and other sources of location information, performance testing is growing significantly in complexity, and test standards needed to cover this complexity will also become more complex. The simple user criteria could be stated as “I want the system to provide a rapid, accurate position wherever I am.” But how accurate?
The end-user of a location system does not use a GNSS simulator with clean signals, but a location device with live signals, often in difficult environments. This has been recognized by platform integrators, and live test routes for both urban drive and urban pedestrian routes are now required. The performance required of the receiver in these locations has also changed, from “just need to get a fix of limited accuracy” to getting accurate location information, both from a fix (even from a cold start in a built-up area), to continuous navigation (better than 30-meter accuracy 99 percent of the time) throughout a test run.
Typical environments for these test cases include locales in many major cities, such as the environment in the OPENING PHOTO of Seattle and one shown here of Seoul, Korea.
Seoul, Korea, a typical test-case environment.
Coexistence and Interference. Recent controversies have raised the profile of GNSS interference from other wireless technologies. However, within the cellular platform, significant coexistence and potential interference issues are already present. These can occur due to adjacent channel interference, or from harmonics of cellular frequencies on the platform, for example, the second harmonic of the uplink channel for LTE Band 13 overlays the BeiDou-2 frequency of 1561MHz, and the second harmonics of both Bands 13 and 14 create out-of-band emissions in the GPS band (Figures 2 and 3).
Figure 2. BeiDou and LTE bands 13/14.Figure 3. GPS and LTE bands 13/14.
Test Proliferation. The increase in the number of GNSS constellations together with the use of other location sources to provide a hybrid solution could increase the number of tests to be performed exponentially. When this is then combined with the need to test over a range of simulated and real-world locations, together with customer specific requirements, a set of tests could easily take weeks to run. It is therefore important to ensure that the cellular location test standards are carefully constructed to not significantly proliferate the number and time for tests to be performed.
Future Test Equipment
A new generation of test equipment is emerging to meet the new challenges and requirements of multi-constellation GNSS and hybrid location systems. These include:
GNSS Simulators. Simulators currently provide up to three GNSS constellations, together with augmentation systems. With the roll-out of BeiDou-2, four-constellation simulators will now be required. Currently all GNSS devices integrated in cellular platforms use the L1 band. This will also potentially change to multi-frequency use. The appropriate GNSS simulator will need to be included in the cellular test system.
New Hybrid Test Systems. As the need for testing hybrid positioning systems in cellular devices emerges, hybrid location test systems (HLTS) are becoming available that can simulate and test hybrids of A-GNSS, Wi-Fi, MEMS sensors, and cellular positioning technologies, all in one system.
Today, these test systems use separate simulators for the different individual technologies (like GNSS, Wi-Fi, and so on), but these are now being merged into multi-system simulators that combine a number of different technologies into one device (see Figure 4).
RF Replay. The use of RF replay units for replicating live trials is already widespread. This will extend with further constellations and further frequency bands.
The advantages of using RF recorded data include:
Gives real-world data, which if the location is chosen carefully will stress the device under test;
Allows use of recorded test data from several/many urban locations;
Good for drive and pedestrian test applications;
Will be integrated in the HLTS type of test system.
The disadvantages of using RF recorded data include:
Results not deterministic;
Taken at one point in time, do not allow for future development of satellite constellations;
Proprietary recording devices, difficult to define a standard;
Need to include an inertial measurement unit (IMU) to get accurate truth data.
The difficulties of using RF replays include:
Successfully integrating all the signal environment (cellular, Wi-Fi, MEMS, and so on);
Multiple runs required to give reliable data (for example, 13 runs at different times of day to give a range of satellite geometry and user speed, between rush hour and middle of night);
Multiple locations required to stress the system;
Test time can be up to a day of real-time testing to re-run tests on one location.
Proposal for Hybrid Positioning
Tests should include a mixture of simulator-based tests, RF-replay-based tests, and live tests. This would comprise the following suite:
GNSS Performance Tests. The 3GPP type of tests (TS 37.571-1) are a good starting point for a minimum performance test, but they rely on the person running the test to define the number of constellations. To automate this, there could be a single test at the start of each test sequence to identify which constellations are supported (one to four), and then the formal test run for that mix of constellations. The constellations supported should be reported as part of the test report.
An option should be provided to allow margin tests for specific tests to be run, and these should again be reported in a standard method in the test report, specifying how far the device under test exceeds the 3GPP test. The typical margins expected for a GPS-only test would be between 8 and 10 dB in the 2014 timeframe. For a multi-constellation test, it will depend on the specific constellations used, but could be between 5 and 8 dB margin.
Ideally, a multipath scenario should be created that more closely matches the environment seen in a real urban environment.
Hybrid Location Tests. The main purpose of the hybrid location test is to prove that the different components of a cellular platform providing location are all operating correctly. A basic test would provide a sequence where the different combinations providing location are tested for correct operation separately, and then together. This would not be envisaged as a complete stress test, but each technology should be running in a mode where a location solution is not simple.
A simple example sequence of tests would be:
GNSS performance test;
Cell ID static test;
Wi-Fi SSID static test
Cell ID and Wi-Fi SSID static test
Cell ID and GNSS static test (GNSS –142 dBm)
Wi-Fi SSID and GNSS static test (GNSS –142 dBm)
Cell ID, Wi-Fi SSID, and GNSS static test (GNSS –142 dBm)
Cell ID, Wi-Fi SSID, GNSS, and sensors moving test.
See how easily tests can proliferate!
A more stringent test could then be performed to stress-test the performance if required, and if required a playback test could be performed (see RF Replay test below).
The additional location sources can also aid in providing initial states and information for the position-determination system, in addition to the common assisted-GNSS information provided by the network. This will be particularly important in indoor and other environments where GNSS performance is compromised.
Further developments such as the LTE Positioning Protocol Extensions (LPPe) from the Open Mobile Alliance will also allow the sending of additional information to the device to improve the accuracy of the position. This additional information could include accurate time, altitude information, and other parameters. Future assistance standards should enhance the use of this information, and test standards should verify the correct use of this information.
RF Replay (or Playback) Tests. GNSS performance is statistical, and it is important to ensure that any tests have sufficient breadth and repetition to ensure statistical reliability. This applies to the more normal standard simulator tests, as well as to the uses of tests in the urban environment. For example, performance in the urban environment can vary significantly between two closely spaced runs, and can also be very dependent on the time of the day. A test done in the daytime may hit rush-hour traffic, whereas tests done at night will have relatively free flow, and hence faster average speeds. Additionally, the space-vehicle constellation geometry is constantly changing, which can enhance or degrade the GNSS performance. These factors need to be considered in generating any test routes.
For RF replay tests, a number of specific locations for urban driving and pedestrian routes should be specified. These locations should be based on network-operator test requirements, and include a mixture of suburban and deep urban environments (such as Tehran Street, Seoul). For each location, ten different data sets should be used, captured at different times, including peak rush hour at a specified hour. The data set should also include separate high-performance IMU data to provide truth data. To provide test consistency, a golden-standard data set should be used. But with different suppliers this would be difficult.
For pedestrian tests, a similar number of different routes should be defined, and data captured similarly. Ideally, all data useable for a hybrid solution should be captured, and available for replay. The test criteria analyzed for this could include: yield; horizontal position error, along-track error, across-track error, heading error, and speed error.
Interference Tests with Different Cellular Bands. It is important to have a standard test to demonstrate that the device under test does not have performance degradation due to interference from particular cellular subsystems interfering with the GNSS. For this test, the device should be tested in an OTA environment to ensure that all interference coupling mechanisms are present. Two tests should be performed: first, a tracking test. In this the A-GPS performance is tested by measuring the GNSS carrier-to-noise ratio for each GNSS band, while all the wireless channels on the platform are exercised sequentially. The test result would indicate the maximum number of dBs degradation that occurs.
Second, a cold-start test at –140 dBm should be performed separately while each wireless channel on the platform is exercised. Any extension in cold-start TTFF should be noted.
Conclusions
The challenges for cellular location test standards have increased significantly with the availability of new GNSS constellations, and the use of all available technologies within the cellular platform to provide the best appropriate location for the required use case. For test standards to be relevant, and also able to be run in an appropriate time, they must consider both the requirements to prove that the appropriate technology is operating correctly, and also bear a relationship to the final system performance required. This means, for example, that a multi-constellation GNSS receiver is really using all the constellations appropriately, and also that the end-user performance requirement is considered.
Existing cellular test standards are minimum performance requirements, but future standards should encapsulate the minimum performance requirements while also allowing standard extension to provide a consistent performance description.
Further to this, platform performance must be proved in all standing operating modes, which means, for example, that the cellular system be checked when operating in all supported bands.
Test equipment to support future cellular test standards is in development, but the significant challenges will be in providing equipment to fully support urban drive and pedestrian performance requirements.
In conclusion, the ability to appropriately test a hybrid location system, comprising multi-constellation GNSS and additional location technologies, presents almost as many challenges as generating the hybrid solution in the first place.
Acknowledgments
Many thanks to the GNSS team at ST-Ericsson, and at Spirent, and also to our customers for the challenges that they have presented as the required location performances have changed and increased.
Manufacturers
Figure 4 is taken from a Spirent Hybrid Location Test System (HLTS).
Peter Anderson received master’s degrees in electrical sciences from Cambridge University and in microelectronics from Durham University. Until recently, he was a GPS systems manager and the GNSS Fellow at ST-Ericsson; he is now a consultant with PZA Systems Ltd.
Esther Anyaegbu is a senior systems architect at ST-Ericsson. She earned her Ph.D. in data communications systems from the University of Leeds, where she focused on the processing of GNSS signals in the frequency domain.
Richard Catmur is head of standards development at Spirent Communications. He holds an M.A. in engineering science from Oxford University. He has served as rapporteur, editor, or major contributor to all 3GPP and OMA standards on the testing of positioning in wireless devices.
Mappt has introduced an Android app for technical and professional staff who need to record data in the field and then seamlessly integrate it with desktop GIS systems.
According to the announcement, the concept — developed by Perth-based remote sensing company Scantherma for Mappt — was born in the dusty outback of Western Australia.
“We were on a field trip into the bush as part of a client project and the tools we had were just not good enough,” said Amir Farhand, Scantherma’s CEO.
“We needed something more flexible that would be easier to use with a better battery life than a laptop. That’s where Mappt started, aimed at shifting GIS and mapping tools to a tablet without relying on other proprietary technology.”
The company reports that while it will not replace the desktop applications necessary for the storage and analysis of large volumes of data, Mappt will create a faster, simpler, lower cost and more flexible method for accurate field data processing and collection. Users range from geologists and environmental officers, field workers, through to outdoor enthusiasts and travellers.
After extensive testing and development, Mappt is available for the Android operating system. Android was chosen as the key development platform because of the closed nature of the Apple iOS. “Apple has some great features, but some big drawbacks as well,” said Mr Farhand.
“The locked file system really prevented us from doing what is needed in iOS, so we chose Android because it was able to do what the market needed. Our Beta tests have gathered some very positive feedback from users and we plan to continue developing the scope and flexibility of Mappt.”
Mappt reports that the software is compatible with a number of different GIS formats, Mappt provides an application layer for both amateurs and professionals to integrate information gathered in the field into their existing GIS information databases. It can import and export a variety of different commercial and free-to-use vector and raster image file formats for the recording of information useful to technicians and professionals who need accurate geo-located information. One important feature is the use of real-time tracking which can be exported to a GIS system. By including this, field workers who are off the beaten track can easily find their way to and from previously visited locations without having to make or repeat mistakes, a feature very useful for mining exploration. In addition, this feature has applications in other industries and can be turned on and off as required.
Mappt is now available for download via the Google Play store. For more information, visit the Mappt website at www.mappt.com.au
A small device the size of a flash drive brings a new level of accountability to fleet drivers, providing a tool for timekeeping that will help the back office by verifying driver time sheet information, according to GPSTrackIt.
“The device itself is simple,” explained Eddie Ramirez, GPSTrackIt’s product manager. “Each device is an electromagnetic ‘key’. The driver must seat the face of the key in a receptacle wired into the vehicle’s electrical system so that it can be read.”
The device has a 16-digit code, or hex number, associated with it. The number is embossed across the face of the device. That number is the device’s electronic signature.
“When the key fob is seated in the reader the system checks the hex number encoded on it,” Bermudez continued. “It uses the key number to identify the driver. This enables fleet managers to have multiple drivers assigned to the same vehicle, optimizing their use of fleet resources. And it increases driver accountability — reports can be run to evaluate the behaviors of specific drivers.”
It also helps out in the back office when it comes to verifying time cards, according to the company. When the driver uses the key fob to identify himself, it also registers a “clock in” on the system’s time clock. Drivers use the key fob at the end of their shift to clock out. If a driver forgets to clock out, the clock-in by the next driver automatically clocks the previous driver out.
It isn’t the same old news that the portable or personal navigation device, PND, has lost a lot of ground to mobile applications found on smartphones. The reason it isn’t old news is that the drop in sales is being measured by the millions — from a high of 33 million in 2011 — to a little more than half of that amount. While consumers’ tastes are shifting, often to automobiles equipped with connected features, a smartphone is still the device of choice for quick navigation, location-based services and other features.
While stand-alone portable navigation systems seem to be a fading market driver, connected units seem to be the rage at trade shows and other venues. One example is the recent partnership of Audi of America and T-Mobile USA, who announced a data plan that includes real-time news, weather and fuel prices, Google Earth access and Google Voice Local Search.
The marriage of usually two distinct industries the past three or so years has generated new interest in telematics, which has always been a catch-all term for an automobile’s mobile information features.
While not exactly an eye-opening finding, Berg Insight says sales of PNDs are set to significantly decrease in coming years as consumers choose alternatives. The company says that PND sales will fall to 17 million units, down from the more than 28 million sold last year — and 33 million in 2011.
Berg says PNDs will face stiff competition from lower-cost embedded systems. The company says 150 million people use smartphone navigation apps, compared to 105 million in 2011.
Such companies as Dutch PND manufacturer TomTom said it posted a 13 percent fall, to $262 million, in first-quarter sales. The company is diversifying its product line to counter the loss of revenue from falling PND sales.
To diversify, TomTom rolled out a GPS watch recently to compete with rival Garmin, which has similar products on the market. According to published reports, the company said it is competing with mobile phones for the navigation market.
To echo the Berg findings, TomTom said about 2.1 million navigation units were sold in Europe last year, but in the United States, the drop was even more significant. The company’s PND products fell from 1.5 million units in 2012 to 1.1 million in 2011.
The competition to PNDs is coming from a number of areas. In the recent Audi and T-Mobile deal, users can retrieve information over Wi-Fi for $15 a month (the company says new and existing owners can receive full data services for 30 months for $30 a month). Through the Audi Connect system, users can get connectivity for as many as eight devices.
Audi Connect, which first went on the market in 2011, allows users to gain access to real-time localized weather, news and fuel prices.
Apple Buys Indoor Navigation Company WiFiSLAM
Say what you want about the recent surge in interest of indoor navigation. Some call it an over-hyped fad — or not technically ready for market. The bottom line is that Apple thinks enough of the market to have spent $20 million for Silicon Valley start-up WiFiSLAM in late March.
According to published reports, WiFiSLAM can pinpoint a user’s indoor location to within 8 feet, using Wi-Fi.
Apple has made several inroads to enhance its location portfolio since its Apple Maps debacle in 2012 when users complained about inaccurate directions.
The problems were so acute for Apple Maps that its CEO told potential customers to buy navigation from its rivals, including Waze.
Apple rival Google already has been in the indoor positioning and navigation market, mapping shopping malls, airports and sports venues in several countries.
DeCarta Launches Local Search Engine
DeCarta has launched the L2 Local Search Engine. L2 offers companies the ability to index their own data and make it searchable via a sophisticated single-line search, said Kim Fennell, deCarta president and CEO. Those companies might include local search, vertical search (hotels, restaurants), classifieds, newspapers, Internet yellow pages and others.
“Single-line search is the standard for most web search and for the big mapping portals, but is oddly missing from most local search sites,” Fennell said. “They still use a two-line entry, first specifying what you want and then where you want it. The main reason for that disconnect is that the technology to do good single-line geo-search requires a pretty deep understanding of geospatial data and technology, and is hard to do well. L2 solves that problem. We provide a fully featured local search engine with baseline map and POI data,” he said.
“The local site can clean and index their proprietary data using our tools and then host the search engine in the cloud,” Fennell said. “They get the control of the data and the user interface that the big map portals use.”
Some examples of a deCarta Local Search Engine point of interest entry may be, “coffee near XYZ company,” “restaurants on Main Street,” and “parking near AMC Theater.”
In other LBS news:
Telenav introduced its embedded product for the Scout for Cars product line. The embedded product features in-dash navigation with mobile and cloud services for real-time, personalized information, the company said. Marketed to automakers, the company said installers can connect Scout for Phones service in their cars for real-time services and personalization. The company said the unit comes with flexible branding so OEMs can offer embedded navigation in their vehicles through their own brands.
Audiovox’ $169.99 Car Connection kit tracks vehicles and monitors the driver with a built-in GPS unit and a two-way cellular data connection, without a smartphone, the company said. Once an account is established, and the unit is recognized by the Car Connection service, owners can track their cars’ movements and receive e-mail or text alerts in the event the car is stolen or used without permission. An interesting feature is a free app that allows users to find the car via a smartphone. Car Connection costs $10 a month, or $90 per year, and has a $20 activation fee.
Send your LBS news and announcements to Kevin Dennehy at [email protected].
Houston’s George Bush Intercontinental Airport (IAH) became fully operational with the first precision approach flown by a United Airlines aircraft using Honeywell’s SmartPath Ground Based Augmentation System (GBAS) on April 22. IAH is one of two airports in the country participating in a pilot program, in partnership with the Federal Aviation Administration (FAA), United Airlines and Honeywell to demonstrate the use of GBAS. This new system delivers a cost-effective solution to increase airport capacity, decrease air traffic noise and reduce weather-related delays.
“The Houston Airports are among the most innovative and progressive in the nation when it comes to safety and efficiently connecting passengers to destinations around the world,” said Mario Diaz, director of the Houston Airports. “It is imperative that we continue to invest in new technology that enhances the aviation sector.”
Honeywell’s SmartPath GBAS system augments GPS signals so they can be used for precision navigation in the approach and landing phases of flight. The flexible approaches provided by GBAS may produce a significant reduction in aircraft delays and carbon emissions at airports. The project is a component of the Federal Aviation Administration (FAA) Next Generation Air Transportation System (NextGen). It’s a migration from what is considered to be a ground-based air navigation system to a satellite-based navigation system which uses the same GPS that you use in your cars today.
“There is a great opportunity for SmartPath to modernize the flight experience for airline passengers,” said Pat Reines, senior manager, SmartPath Ground Based Augmentation Systems at Honeywell Aerospace. “We’re looking forward to helping Houston passengers and visitors’ experience more flights that depart and arrive on time.”
United Airlines will operate the flights with a Boeing 737 aircraft equipped with global navigation satellite system (GNSS) landing system (GLS) technology to receive the GBAS landing approach data. United was an early leader in NextGen technology, taking delivery of GLS-equipped aircraft since 2009.
“We believe that GBAS is the air carrier precision landing system of the future,” said Captain Joe Burns, United’s managing director of technology and flight test. “We continue to work closely with the FAA and our industry partners on GBAS and other NextGen initiatives.”
GBAS can provide aircraft with guidance to as low as 200 feet above the surface of the runway, referred to as a Category I approach. The FAA is currently validating the requirements for a GBAS to support Category II and Category III precision approach operations which would guide an aircraft to the surface of the runway. GBAS represents the only currently feasible satellite-based navigation solution for Category II/III precision approach operations, according to the Houston Airport System.
Applanix has introduced POSPac MMS v6.2, its latest generation of software for directly georeferencing mobile mapping sensors using GNSS and inertial technology. Featuring new Applanix IN-Fusion Multi-Single-Base Processing, POSPac MMS V6.2 is designed to improve the productivity and accuracy of mapping from mobile platforms in the air, on land or at sea, the company said.
IN-Fusion Multi-Single-Base Processing is designed for customers who need the highest level of differential GNSS position accuracy and perform long, linear projects such as power-line corridors, long highways or stretches of coastline. During these projects, a GNSS base station network may not be available, or the geometry of the network so weak that an Applanix SmartBase solution — which uses existing reference stations to achieve high accuracy over longer distances — is not viable. In these cases, IN-Fusion Multi-Single-Base Processing allows base stations to be established along the full length of the travel path and makes optimal use of the nearest base station at all times.
Customers can now take advantage of robust tightly coupled in-fusion processing without the need to break the project up into multiple segments for each base station to attain the highest accuracy, Applanix said.
“In addition to IN-Fusion Multi-Single-Base Processing, POSPac MMS V6.2 includes new features designed to increase productivity, efficiency and ease-of-use. The Coordinate Conversion tool included allows users to choose from a number of local reference frames for inputting base station coordinates,” said Edith Roy, Development Manager of POSPac MMS at Applanix. “POSPac MMS Version 6.2 demonstrates our commitment to providing customers with not only the most advanced software solutions for mobile mapping applications, but also the easiest to use.”
POSPac MMS V6.2 can be purchased through Applanix’ global sales network. The software is available as an upgrade to all POSPac users currently under a maintenance contract.
Navevo specialists in satellite navigation solutions for heavy-goods vehicles (HGV) drivers, now offers the ProNav HGV Cyclist Alert. Supplied as standard on the new ProNav PNN420 satnav for truck drivers and soon to be rolled out across all current ProNav systems, the safety feature provides junction alerts at high convergence areas of trucks and cyclists and prompts drivers to take extra care.
The number of cyclists in London is on the rise, along with safety risks that arise when trucks and cyclists both are traversing busy London junctions and interchanges.
The ProNav HGV Cyclist Alert software was developed in association with Transport for London (TfL) to provide a commercial vehicle driver with an audible and visual alert as he or she approaches a junction (or section of road) that has been determined to be a location where there are high volumes of HGVs and cyclists. A warning symbol is displayed on the navigation system’s mapping that projects a 50-meter radius “warning zone” around each HGV/Cyclist convergence area. Drivers are also provided with a short audible tone as a reminder, giving the driver plenty of time to check for any cyclists on the road, Navevo said.
The HGV Cyclist Alert software uses data provided by TfL and the up-to-date Department for Transport HGV and pedal cycle flow figures for London’s road network. The dataset uses this information to identify locations where large numbers of HGVs and cyclists converge. Initially, 100 high-convergence areas across London have been included (alerts at every junction would be counterproductive to drivers). Working with other local authorities both in London and nationally, Navevo plans to increase the level of coverage and will provide free updates when new data becomes available.
“A navigation system is something a driver is likely to be listening to as they approach a junction, and so it makes perfect sense to also alert the driver of the risk of cyclists, reminding them to be observant and drive safely,” says Navevo CEO, Nick Caesari. “The safety of drivers, cyclists and other users of the road is a concern for everybody, and we are proud to lead the navigation industry by launching this ‘world first’ safety feature, which we believe could significantly contribute in improving road safety and reducing the number of incidents involving HGVs and cyclists.”
“For many years, London has worked to lead the way in pushing for the adoption of safer lorries and safer lorry driving,”
Ian Wainwright, head of Freight and Fleet at Transport for London. “The creation of a specific cyclist alert for HGV drivers is another positive step forward and will help to further raise awareness and improve cycle safety across the capital.”
Trimble RealWorks version 8.0 software will include a new 3D database engine, automated targetless registration and Web viewing capability incorporating RealWorks’ Scan Explorer interface. The new version is due to be released in June.
The new enhancements will allow surveyors, contractors, engineers and geospatial professionals to rapidly process 3D laser scanning data and expedite the creation of deliverables for their clients, increasing productivity and reducing costs, Trimble said.
The new 3D database engine in Trimble RealWorks version 8.0 will allow up to five times more data to be visualized and managed, compared to Trimble RealWorks version 7.2. The ability to handle larger data sets greatly increases usability and productivity for customers capturing data with 3D laser scanners such as the Trimble TX5 and Trimble FX.
The automated targetless registration function, together with additional workflow enhancements, will provide further productivity gains for customers. The automated targetless registration function automatically identifies planar objects in each scan and matches the planes from multiple stations, creating a combined data set. The function enhances productivity in the field by eliminating target placement prior to data capture in applicable environments. Office processing time is also reduced by the fully automated function.
Sharing of data with clients has been enhanced by the addition of a Publisher function within the Trimble RealWorks software that allows projects to be custom packaged for viewing via Microsoft Internet Explorer. The Scan Explorer interface, embedded inside a HTML web page, allows clients to navigate and explore the scan data as well as take measurements and add notes.
“Software is an integral part of Trimble’s 3D laser scanning solutions and is essential to extract information from 3D data captured in the field,” said Tim Lemmon, marketing director of Trimble. “The new version of Trimble RealWorks software significantly improves our customers’ productivity in processing field data, extracting information and preparing deliverables for their clients.”
The announcement was made today at SPAR International 2013, the leading conference for 3D data capture, processing and delivery technologies.
