In the wake of last month’s Expert Advice column on eLoran — “The Low Cost of Protecting America” by Dana Goward of the Resilient Navigation and Timing Foundation — come several positive comments and encouraging developments. Rather than rehearse all the arguments why we should care about this, I’ll repeat the one word that I heard most often in GNSS circles in 2013: jamming. Followed closely by: spoofing.
“I have been advocating strongly for reconsideration of the government’s domestic Loran decision for the last year or so,” writes one reader positioned on Washington’s Beltway, “and specifically working within the Department of Defense (DoD) to ensure it is aware of international developments for eLoran in the UK and South Korea, and the possibilities inherent in other former Loran chains.
“The DoD is beginning to recognize the value of eLoran as a complement to GPS, not only for international missions, but in cooperation with the departments of Transportation and Homeland Security for domestic critical infrastructure.”
Last fall, Don Jewell’s Defense PNT newsletter on the same subject drew this reply from another well-known expert:
“One of the key short-term actions is to prevent the decommissioned [Loran] sites from being sold off for subdivisions. These sites are a national treasure with unique properties: soil conductivity, water content, metal content, and more that are hugely important in siting low-frequency positioning systems. Those long-gone engineers of the 1940s and ’50s knew this and chose accordingly.”
Before last month’s issue appeared but after it had gone to press, President Obama signed the National Defense Authorization Act (NDAA) for 2014. It contained several favorable New Year’s auguries for positioners, navigators, and timers.The act evinced an acute awareness of the vulnerability of space systems to disruption. The act is also a law governing the land. Through it Congress requires the administration to, among other things, explain biennially in its “Space Protection Strategy” report exactly how, in the event space systems are disrupted, DOD and the intelligence community “plan to provide necessary national security capabilities through alternative space, airborne, or ground systems.”
Since said administration acted early in its first term to decommission Loran-C, the congressional directive is pointed.
The next big thing coming up on the GNSS international horizon takes place in Rotterdam, the Netherlands, April 15–17: the European Navigation Conference, ENC-GNSS 2014. It includes a track session on “eLoran and other Low-Frequency Systems,” and I’ll be there with pencil sharpened.
Brad Parkinson will give the ENC keynote, and he is on record as one of an august group of Institute for Defense Analyses experts who unanimously recommended that the existing Loran-C be greatly updated and modernized to eLoran. We should hear more from him on this subject amid the wharves, waterways, and docks of Europe’s largest port (world’s third busiest).
There’s barely room left to report the successful tests of Enhanced Differential Loran (eDLoran) by Dutch specialists Reelektronika: absolute accuracy of 5 meters in the North Sea and in the Rotterdam Europort harbor area.
Figure 1. Overall system architecture for MUSTER: Multi-platform signal and trajectory estimation receiver.
More Receiver Nodes Bring Ubiquitous Navigation Closer
Encouraging results from new indoor tests and advances in collaborative phased arrays come from MUSTER: multiple independently operating GPS receivers that exchange their signal and measurement data to enhance GNSS navigation in degraded signal environments, such as urban canyons and indoors.
By Andrey Soloviev and Jeffrey Dickman
Bringing GNSS navigation further indoors by adding new users to a collaborative network can help realize the concept of ubiquitous navigation. Increasing the number of receiver nodes to improve signal-to-noise ratios and positioning accuracy lies at the heart of the MUlti-platform Signal and Trajectory Estimation Receiver (MUSTER). This article focuses on benefits of integrating multi-node receiver data at the level of signal processing, considering two case studies:
Collaborative GNSS signal processing for recovery of attenuated signals, and
Use of multi-node antenna arrays for interference mitigation.
MUSTER organizes individual receiver nodes into a collaborative network to enable:
Integration at the signal processing level, including:
Multi-platform signal tracking for processing of attenuated satellite signals;
Multi-platform phased arrays for interference suppression;
Integration at the measurement level, including:
Joint estimation of the receiver trajectory states (position, velocity and time); and,
Multi-platform integrity monitoring via identification and exclusion of measurement failures.
To exclude a single point of failure, the receiver network is implemented in a decentralized fashion. Each receiver obtains GNSS signals and signal measurements (code phase, Doppler shift and carrier phase) from other receivers via a communication link and uses these data to operate in a MUSTER mode (that is, to implement a multi-platform signal fusion and navigation solution). At the same time, each receiver supplies other receivers in the network with its signal and measurement data. Figure 1 illustrates the overall system architecture.
Open-loop tracking is the key technological enabler for multi-node signal processing. Particularly, MUSTER extends an open-loop tracking concept that has been previously researched for single receivers to networked GNSS receivers. Signals from multiple platforms are combined to construct a joint 3D signal image (signal energy versus code phase and Doppler shift). Signal parameters (code phase, Doppler shift, carrier phase) are then estimated directly from this image and without employing tracking loops.
Open-loop tracking is directly applied to accommodate limitations of military and civilian data links. To support the functionality of the receiver network at the signal processing level (that is, to enable multi-platform signal tracking and multi-platform phased arrays) while satisfying bandwidth limitations of existing data link standards, individual receivers exchange pre-correlated signal functions rather than exchanging raw signal samples.
Before sending its data to others, each receiver processes the incoming satellite signal with a pre-processing engine. This engine accumulates a complex amplitude of the GNSS signal as a function of code phase and Doppler frequency shift. Receivers then broadcast portions of their pre-correlated signal images that are represented as a complex signal amplitude over the code/Doppler correlation space for 1-ms or 20-ms signal accumulation. For broadcasting, portions of signal images are selected around expected energy peaks whose locations are derived from some initial navigation and clock knowledge.
This approach is scalable for the increased number of networked receivers and/or increased sampling rate of the ranging code (such as P(Y)-code vs. CA-code). The link bandwidth is accommodated by tightening the uncertainty in the location of the energy peak. As a result, the choice of the data link becomes a trade-off between the number of collaborative receivers and MUSTER cold-start capabilities (that is, maximum initial uncertainties in the navigation and clock solution).
Multi-Node Signal Accumulation
An earlier paper that we presented at the ION International Technical Meeting, January 2013, describes the approach of multi-platform signal accumulation for those cases where relative multi-node navigation and clock states are partially known. This section reviews that approach and then extends it to cases of completely unknown relative navigation and clock states. The following assumptions were previously used:
Relative position between networked receivers is known only within 100 meters;
Relative receivers’ velocity is known within 2 meters/second;
Relative clock states are calibrated with the accuracy of 100 nanoseconds (ns) or, equivalently, 30 meters.
These assumptions are generally suitable for a pedestrian type of receiver network (such as a group of cellular phone users in a shopping mall area) where individual nodes stay within 100 meters from each other; their relative velocities do not differ by more than 2 meters/second; and, the clocks can be pre-calibrated using communication signals. In this case, zero relative states are used for the multi-node signal accumulation and subsequent tracking. Figure 2 summarizes the corresponding MUSTER tracking architecture.
Figure 2. Multi-platform tracking architecture for approximately known relative navigation states.
Relative navigation states are initialized based on clock calibration results only: zero relative position and velocity are assumed. These initial states are then propagated over time, based on MUSTER/supplemental tracking results (Doppler frequency estimates and higher-order Doppler terms). Code and frequency tracking states are computed by combining biased and unbiased measurements. Biased measurements are obtained by adjusting supplemental signal images for approximately known relative states only. Unbiased measurements are enabled by relative range/Doppler correction algorithms that estimates range and frequency adjustments for each supplemental receiver.
The Kalman filter that supports the optimal combination of biased and unbiased tracking measurements also includes code-carrier smoothing to mitigate noise in measured code phase. For those cases where multi-platform signals are combined coherently, a standard carrier-smoothing approach is used. When non-coherent signal combinations are applied, a so-called pseudo-carrier phase is first derived by integrating Doppler estimates over time and then applied to smooth the code phase.
Multi-platform signal accumulation and tracking can be extended to include cases where the relative navigation parameters are completely unknown. For such cases, MUSTER implements an adjustment search to find the values of code phase and Doppler shift for each supplemental receiver that maximize the overall signal energy.
Adjustment search must be implemented if MUSTER/supplemental relative states are completely unknown, or if their accuracy is insufficient to enable direct accumulation of multi-platform energy, for example, when the relative range accuracy is worse than 150 meters and an energy loss of at least 3 dB is introduced to the signal accumulation process. For each code phase, Doppler and carrier phase (if coherent integration is performed) from the adjustment search space, a supplemental 1-ms function is adjusted accordingly and then added to the MUSTER function. Multiple 3D GPS signal images are constructed, and the image with the maximum accumulated energy is applied to initialize relative navigation parameters: code phase and Doppler shift adjustments values from the adjustment search space that correspond to the energy peak serve as approximate estimates of relative range and Doppler.
The accuracy of these estimates is defined by the resolution of the adjustment search, which would be generally kept quite coarse in order to minimize the search space. For instance, a 300-meter search grid is currently implemented for the code phase, which enables the resolution of relative ranges within 150 meters only. Hence, to mitigate the influence of relative state uncertainties on the tracking quality, a correction algorithm is applied as described in our earlier paper. Figure 3 shows the overall system architecture.
Figure 3. MUSTER signal-tracking approach for cases of unknown relative states.
The architecture keeps all the previously developed system components and adds the adjustment search capability (red block in Figure 3) to incorporate cases of unknown MUSTER/supplemental receivers’ relative navigation states. To minimize the computational load, adjustment search is performed only for the first tracking epoch. Search results are applied to initialize the estimates of MUSTER/supplemental range and Doppler, which are then refined at each subsequent measurement epoch using a combined biased/noisy tracking scheme.
The updated architecture can support cases of completely unknown relative states, as well as those cases where relative states are coarsely known, but this knowledge is insufficient to directly combine multi-platform signals.
The complete adjustment search is possible. However, it is extremely challenging for actual implementations due to both large computational load and a data exchange rate associated with it. To exemplify, NcodexNDoppler versions of the multi-platform 3D function have to be computed for the case where Ncode code phase and NDoppler Doppler shift adjustment search bins are used and outputs from two receivers are combined non-coherently. A complete search (1023 code bins and 11 frequency bins) requires computation of 11,253 3D functions. This number increases to (11,253)2 or 126,630,009 if the third receiver is added.
In addition, receivers must exchange their complete pre-correlated signal functions, which puts a considerable burden on the computational data link. For instance, the exchange of complete 1-ms functions with the 4-bit resolution of samples (required to track the carrier phase) results in the 45 Mbit/s data rate for only a 2-receiver network. Hence, it is anticipated that for practical scenarios, a reduced adjustment search will be utilized for cases where the accuracy of relative states does not support the direct accumulation of multi-platform signals: for example, when the distance between users in the network exceeds 150 meters. In this case, only segments of 1-ms functions around expected energy peaks (estimated based on approximate navigation knowledge) are exchanged.
Phased Arrays
Multi-platform phased arrays have been developed to enable interference and jamming protection for GNSS network users who cannot afford a controlled reception pattern antenna (CRPA) due to size, weight, and power (SWAP), as well as cost constraints. The multi-node phased array approach presented here cannot match the performance of CRPA, with its careful design, antenna calibration, and precise knowledge of relative location of phase centers of individual elements. However, it can still offer a significant interference protection to networked GNSS users.
The multi-platform phased array implements a cascaded space-time adaptive processing (STAP) as illustrated in Figure 4.
Figure 4. Implementation of multi-platform phased array with cascaded space-time adaptive processing.
Cascaded STAP implements temporal filtering at a pre-correlation stage, while spatial filtering (in a form of the digital beam forming or DBF) is carried out at post-correlation. Cascaded STAP is implemented instead of joint STAP formulation to
remove the need to exchange raw signal samples (which is necessary when DBF is applied at pre-correlation); and,
support a novel DBF approach that does not require precise (that is, sub-centimeter to centimeter-level) knowledge of relative position and clock states between network nodes (described later).
Signal samples are still exchanged for the estimation of signal covariance matrices that are required for the computation of temporal and spatial weights. However, the sample exchange rate is reduced significantly as compared to the joint STAP: for example, only 100 samples are currently being exchanged out of the total of 5000 samples over a 1-ms signal accumulation interval.
The DBF uses the Minimum Variance Distortion-less Response (MVDR) formulation for the computation of spatial weight vector. MVDR constrains power minimization by the undisturbed signal reception in the satellite’s direction: (1)
where Φ is the multi-node signal covariance matrix that is computed based on temporal filter outputs; superscript H denotes the transpose and complex conjugate operation; and, η is the steering vector that compensates for phase differences between array elements for the signal coming from the satellite’s direction: (2)
In (2), u is the receiver-to-satellite line-of-sight (LOS) unit vector; rm is the relative position vector between phase centers of the mth node and MUSTER; (,) is the vector dot product; and, λ is the carrier wavelength.
Following computation of DBF weight, multi-node 1-ms GPS signal functions are combined: (4)
where is the complex 1-ms accumulated signal amplitude of the mth node for the (l,p) bin of the code/carrier open-loop tracking search space. The result is further accumulated (for example, over 20 ms) and then applied for the open-loop estimation of signal parameters.
One of the most challenging requirements of the classical MVDR-based DBF is the necessity to estimate relative multi-node position and clock states at a centimeter level of accuracy. To eliminate this requirement and extend potential applications of multi-node phased arrays, the DBF was modified as illustrated in Figure 5.
Figure 5. Modified DBF for a multi-node phased array with unknown relative navigation states.
The modified approach searches through phase adjustments to supplemental receivers and chooses the adjustment combination that maximizes the output carrier-to-noise ratio (C/N0). As a result, no knowledge of the relative navigation states is needed. For each phase combination, , from the adjustment search space, the satellite lookup constraint is computed as:
(5)
Due to the cyclic nature of the phase, the search space is limited to the [0,2π] region. The search grid resolution of π/2 is currently being used.
The obvious drawback of the exhaustive search-based DBF is that the approach is not scalable for the increased number of network users. However, it can still be efficiently applied to a relatively limited network size such as, for example, five collaborative receivers. In addition, the method does not generally support interference suppression with carrier-phase fidelity. However, code and Doppler frequency tracking statuses are still maintained as it is demonstrated in the next section using experimental results.
Experimental Results
We used two types of experimental setups as shown in Figures 6 and 7, respectively.
The first setup (Figure 6) was used to demonstrate multi-platform signal accumulation with unknown relative states and multi-node phased arrays. Raw GPS signals received by three antennas were acquired by a multi-channel radio-frequency (RF) front-end and recorded by the data collection server. The first antenna served as the MUSTER platform, the second and third antennas were used as supplemental platforms. Relative antenna locations were measured as [-0.00; 0.99; 0.05] m (East, North, Up components) for the MUSTER/supplemental receiver 1; and, [0.16; 0.76; 0.27] m for the MUSTER/supplemental receiver 2.
Figure 6. Test setup 1 applied for multi-platform signal accumulation with unknown relative states and multi-platform phased arrays.
A stationary test scenario was considered. Clock biases were artificially induced to emulate a case of asynchronous network. Clock biases were introduced by converting raw GPS signal samples into the frequency domain (applying a fast Fourier transform (FFT) to 1-ms batches of signal samples); implementing a frequency-domain timing shift; and, converting shifted signals back into the time domain (via inverse FFTs). Multi-platform signal processing algorithms were then applied to raw GPS signals with asynchronous multi-platform clocks.
The second setup (Figure 7) was applied for the demonstration of indoor signal tracking. Two receiver nodes (roof and cart) with independent front-ends were used. The roof node remained stationary, while the cart was moved indoors. Each node in the data collection setup includes a pinwheel GPS antenna, an RF front-end, an external clock for the front-end stabilization, and a data collection computer. Figure 7 illustrates corresponding test equipment for the cart node.
Figure 7. Test setup 2 used for indoor signal tracking.
Multi-Platform Signal Tracking with Unknown Relative States. Two platforms were used to demonstrate the case of completely unknown states (antennas 1 and 3 in Figure 6). The third platform was not used due to the extreme computational burden of the complete adjustment search (about 106 grid points for the case of three platforms). A 0.2-ms (60 km) clock bias was added to GPS signal samples recorded by antenna 3. Complete adjustment search was implemented for the code phase. No adjustment search was needed for the Doppler shift. The use of adjustment search provides approximate estimates of relative shifts in multi-platform code phases. These approximate estimates are then refined using a relative range estimation algorithm. Figures 8 and 9 exemplify experimental results for cases of coherent (C/N0 is 31 dB-Hz) and non-coherent (C/N0 is 29 dB-Hz) multi-platform signal accumulation.
Consistent code- and carrier-phase tracking is maintained for the coherent accumulation case.
Carrier-phase and code-phase error sigmas were estimated as 8.2 mm and 28.8 meters, accordingly. The carrier-smoothed code tracking error varies in the range from –4 to –2 meters for the steady-state region. For the non-coherent tracking case, errors in the carrier smoothed code measurements stay at a level of –5 meters. These example test results validate MUSTER tracking capabilities for the case of completely unknown relative navigation states.
Indoor Signal Processing
The indoor test was performed to demonstrate the ability of MUSTER to maintain signal tracking status under extreme signal attenuation conditions. The test was carried out at the Northrop Grumman campus in Woodland Hills, California, with no window view for the entire indoor segment; all the received GPS signals were attenuated by the building structure. Raw GPS signal data was collected from the test setup shown in Figure 6 and then post-processed with multi-platform signal accumulation algorithm with partially known relative navigation states. A combined 20-ms coherent/0.2-s non-coherent signal accumulation scheme was applied. A complete position solution was derived from five highest-elevation satellites.
As the results for the indoor test show in Figure 10, MUSTER supports indoor positioning capabilities for the entire test trajectory. The GPS-only indoor solution reconstructs the right trajectory shape and size. Solution discontinuities are still present. However, the level of positioning errors (20 meters is the maximum estimated error) is lowered significantly as compared to traditional single-node high-sensitivity GPS implementations where errors at a level of hundreds of meters are commonly observed. This accuracy of the multi-node solution can be improved further when it is integrated with other sensors such as MEMS inertial and vision-aided navigation.
Figure 10. Indoor test results.
Multi-Platform Phased Arrays
For the functionality demonstration of multi-platform phased arrays, live GPS signal samples were collected with the test setup shown in Figure 6. Interference sources were then injected in software including continuous wave (CW) and matched spectrum interfering signals. The resultant data were post-processed with the multi-platform phased array approach described above. Relative navigation and clock states were unknown; the DBF formulation was augmented with the phase adjustment search.
Figures 11 and 12 exemplify experimental results.
Figure 11. Example performance of the multi-platform phased array: PRN 31 tracking results; jamming-to-signal Ratio of 50 dB was implemented for all interference sources.Figure 12. PRN 14 tracking results; jamming-to-signal ratio of 55 dB implemented for all interference sources.
Test results presented demonstrate consistent GPS signal tracking for jamming-to-signal (J/S) ratios from 50 to 55 dB. The steady-state error in the carrier-smoothed code is limited to 5 meters.
Acknowledgment
This work was funded, in part, by the Air Force Small Business Innovation Research (SBIR) grant, Phase 1 and Phase 2, topic number AF103-185, program manager Dr. Eric Vinande.
Andrey Soloviev is a principal at Qunav. Previously he served as a Research Faculty at the University of Florida and as a Senior Research Engineer at the Ohio University Avionics Engineering Center. He holds B.S. and M.S. degrees in applied mathematics and physics from Moscow Institute of Physics and Technology and a Ph.D. in electrical engineering from Ohio University.
Jeff Dickman is a research scientist with Northrop Grumman Advanced Concepts and Technologies Division. His area of expertise includes GPS baseband processing, integrated navigation systems, and sensor stabilization. He holds a Ph.D. in electrical engineering from Ohio University. He has developed high-accuracy sensor stabilization technology and is experienced with GPS interferometry for position and velocity aiding as well as high-sensitivity GPS processing techniques for challenging GPS signal conditions.
The Institute of Navigation (ION) presented its Annual Awards during the ION International Technical Meeting (ITM) 2014 in San Diego, California, January 27-29.
ION also announced the recipients of the 2014 fellow memberships.
Awards
The ION Annual Awards Program is sponsored by The Institute of Navigation to recognize individuals making significant contributions or demonstrating outstanding performance relating to the art and science of navigation.
Dr. Jacques Georgy received the Early Achievement Award for contributions to portable and indoor navigation using MEMS inertial sensors on consumer devices. The Early Achievement Award is presented in recognition of outstanding contributions made early in one’s career.
Captain Alexander Dufault received the Superior Achievement Award for his dedication as MC-130P Navigator in developing and executing new techniques, increasing the full range employment and navigation prevision of the MC-130P Combat Shadow. The Superior Achievement Award is presented to an individual demonstrating outstanding accomplishments as a practicing navigator.
Dr. Young Chang Lee received the Dr. Samuel M. Burka Award for his paper “New Advanced RAIM with Improved Availability for Detecting Constellation Wide Faults, Using Two Independent Constellations” published in the Spring 2013 issue of NAVIGATION, Journal of The Institute of Navigation, Vol. 60, No. 1, pp. 71-83. The Dr. Samuel M. Burka Award recognizes outstanding achievement in the preparation of a paper contributing to the advancement of the art and science of positioning, navigation and timing.
Dr. Mikel Miller received the Captain P. V. H. Weems Award for his contributions to the management and encouragement of advanced navigation research and for his service to The Institute of Navigation. The Captain P. V. H. Weems Award is presented to individuals for continuing contributions to the art and science of navigation.
Dr. Mark Psiaki received the Tycho Brahe Award For exceptional contributions to the theory and practice of spacecraft attitude and orbit determination and to the advancement of GNSS algorithms for satellite navigation. The Tycho Brahe Award is given in memory of Mary Tornich Janislawski, developer of the Mark II Plotter, a charter member of The Institute of Navigation, the first woman to have received an ION Annual Award, a civilian aviation instructor, a teacher at the University of California at Berkeley and Stanford and a respected author. This award has been generously endowed by Col. Leonard Sugerman (USAF, Ret.), a past president of The Institute of Navigation (1970–1971).
Dr. Yu (Jande) Morton received the Thomas L. Thurlow Award for significant contributions to the understanding of ionospheric effects on navigation satellite signals, development of several innovative signal processing algorithms and dedication to navigation education. The Thomas L. Thurlow Award recognizes outstanding contributions to the science of navigation.
Mr. Ronald Braff received the Distinguished Service Award in recognition of more than 24 years of service to NAVIGATION, The Journal of The Institute of Navigation. The Distinguished Service Award is presented for extraordinary service to The Institute of Navigation.
A special recognition was given to the GPS III SLR Implementation Team in grateful recognition for the multi-year effort to make the implementation of laser retro-reflector on GPS III a reality and enhance its performance and interoperability for generations to come. GPS SLR Implementation Team Members included Adde, Barbara, Ballenger, Allan, Col (Ret.), Bar-Sever, Yoaz, Dr., Beard, Ronald L., Bolden, Charles Jr., Honorable, Buckman, David, Col (Ret.), Carter, David, Davis, Mark, Dobson, Craig, Freilich, Michael, Dr., Garver, Lori, Honorable, Gruber, Bernard, Col (Ret.), Hothem, Larry, Hudnut, Kenneth, Dr., Johnson, Thomas, Dr., Kaye, Jack, Kehler, Robert, Gen, Koch, Janelle, Maj, LaBrecque, John L., Dr., Lewis, Kirk, Long, Letitia, Madden, David, Col (Ret.), Malys, Stephen, Merkowitz, Stephen, Dr. Miller, James J., Moreau, Michael, Dr., Oria, A.J., Dr., Pace, Scott, Dr., Pavlis, Erricos, Dr., Pearlman, Michael, Dr., Puhek, James, Col, Rosenberg, Robert, Maj Gen (Ret.), Scolese, Christopher Shelton, William, Gen, Skalski, Hank, Slater, James, Standley, Vaughn, Dr., Thomas, Linda, Dr. Weinberg, Norm, Wetzel, Scott, Whelan, Martin, Maj Gen, Yelle, Ray, Younes, Badri, National Space-Based PNT Advisory Board co-chaired by: Dr. James Schlesinger and Dr. Bradford Parkinson.
Fellow Membership
Election to fellow membership recognizes the distinguished contributions of The Institute of Navigation members to the advancement of the technology, management, practice and teaching the arts and science of navigation; and/or for lifetime contributions to the Institute.
Dr. Mark Psiaki has been elected for contributions to GNSS signal processing, software receivers, ionospheric scintillation modeling, and for satellite orbit and attitude determination.
Mr. Logan Scott has been elected for contributions to GNSS signal processing, anti-jam antennas, anti-spoofing measures, and crowd sourcing to locate jammers.
Prof. Peter Teunissen has been elected for invention of the LAMBDA method, the current standard for integer ambiguity resolution in GNSS carrier phase measurements, and for reliability theory of integer estimation.
Sokkia Corporation is offering enhanced abilities and versatility to its DX series of total stations with the introduction of the DX-200 in the North American market.
When configured for hybrid positioning, the DX-200 has the ability to use both GNSS positioning and optical positioning data simultaneously. The standard Sokkia Hybrid Robotic System includes the DX, GRX2 GNSS receiver and MESA large-screen tablet controller.
“The DX-200 is ideal for the professional looking for a mid-range, auto-pointing total station that can become a full-robotic instrument with a simple firmware upgrade,” said Ray Kerwin, director of global surveying products. “Advanced functionality such as hybrid positioning can be added to the robotic unit, making the DX-200 a versatile system for multiple applications.”
The DX-200 can be used with the RC-PR5 remote controller for increased Bluetooth wireless operating range. “The remote allows for rapid prism search and lock up to 2,000 feet (600 meters) away,” Kerwin said.
“Hybrid positioning adds a new dimension of versatility,” Kerwin said. “When line-of-sight is blocked, for example, shots can be measured with the GNSS receiver, and the receiver can also be used for quick lock functionality.”
Standard additional features of the DX series include Direct Aiming auto-collimation technology, TSshield security and maintenance technology, MAGNET integrated software onboard and Sokkia’s patented RED-tech reflectorless measurement system.
The DX-200 is available in 1, 3 and 5 arc second accuracy models.
Exelis has successfully completed several software upgrades for the new Global Positioning System Next Generation Operational Control System, or GPS OCX. Integration and testing were recently conducted on iteration 1.5 of the OCX navigation, encryption and Mission Upload Generator, or MUG, software.
The new version of GPS software will help ground controllers better understand the satellites’ exact positioning in space. The encryption software is also designed to automatically code and decode GPS signals, facilitating the exchange of user information by securely transmitting navigation payload data between the OCX ground system and the orbiting constellation of satellites.
The MUG software is responsible for creating spacecraft payload updates to refresh the navigation data transmitted to all GPS users. This data is typically generated for each satellite multiple times a day and helps to consistently minimize user error.
“These software milestones demonstrate a clear path to improved GPS accuracy and integrity,” said Drew Trainor, OCX program manager for Exelis Geospatial Systems. “Civilian and military users will have more accurate and secure GPS signals, and these milestones bring us one step closer to GPS modernization.”
Under a February 2010 contract award from Raytheon, Exelis is providing software that will simulate the behavior of GPS signals in space. In addition, Exelis is building high-precision receivers for use in ground monitoring stations placed strategically around the world. Exelis is also providing data encryptors that help ensure secure information exchange between the ground and space segments of the system.
Once the new operational control segment is implemented, GPS will improve a variety of business and economic practices, including air traffic control, crop management, and environmental monitoring, among others. The new capabilities offered by GPS modernization will also provide military users increased accuracy, availability, anti-jam power and international interoperability.
Telenav, Inc., announced today that it has acquired skobbler GmbH, the European-based navigation company with the highest rated OpenStreetMap (OSM)-based GPS navigation apps in the world. With this acquisition, Telenav brings the most successful OSM navigation experts in the world together as one team — including the founder of OSM, Steve Coast, who joined Telenav in 2013 — and becomes a major contributor to the creation of the open-sourced and most comprehensive map of the world, according to the announcement.
The acquisition closed on January 29 for consideration of approximately $19.2 million in cash and $4.6 million of company common stock.
“Crowdsourced OSM can power personalized navigation services like Scout — with highly detailed maps on a global scale,” said HP Jin, Telenav’s chairman and CEO. “We plan to offer Scout with OSM for much of the world. We have already made significant headway toward this goal in the U.S., including using OSM for our HTML5 version of Scout.”
OSM is the only crowdsourced and open-sourced map of the globe and, for many developers, it has become a clear alternative to Google Maps.
“Waze and Google — or, just Google now — provide similar mechanisms to improve their maps, based mostly on OSM’s innovations. With one big catch. It is very much their map. Not yours,” said Coast in his blog commentary today regarding the acquisition. “OpenStreetMap is different. All of the quality data contributed is openly available — just like Wikipedia. So, anyone can download, experiment and play with it freely. It’s not locked up beyond your reach.”
Since Coast founded OSM, the community has doubled year over year to more than 1.5 million registered editors, becoming a global community of local editors in every corner of the world. Its crowdsourced model publishes edits every minute on openstreetmap.org, resulting in maps that are detailed and up to date. For example, newly laid streets and newly developed areas can be updated on a regular basis and in real time. In addition, OSM allows for greater map detail for pedestrians such as alleys, sidewalks, parks, hiking trails, zoos, and even city trees.
Telenav has been an active contributor to OSM for more than three years, working closely with the community to enhance specific features needed for navigation, traffic and other future location-based services.
With offices in Germany and Romania, skobbler was the first company to launch a commercial navigation app using OSM (in 2010) for both Android and iOS devices and is available in app stores in 49 regions with worldwide map coverage. In order to do this, skobbler developed sophisticated algorithms that evolved OSM data from a display map to a navigable map.
skobbler’s apps are top ranked and highly rated in multiple countries including Germany, the Netherlands, and Sweden. skobbler’s CEO, Peter Scheufen, previously served as the CEO of Navigon, which became a leading GPS device manufacturer in Europe and was eventually purchased by Garmin. The other skobbler founders also held senior roles at Navigon before founding skobbler. Telenav expects that all skobbler employees will join Telenav as part of its OSM team, bringing significant industry-leading software expertise in location-based services, navigation and mapping.
“By joining our efforts with skobbler, we will build on our combined successes to bring the best mapping and navigation services to our customers around the world,” said Jin. “The benefits of an open source model will provide an enormous opportunity to change the economic models of navigation and other location-based services.”
“OSM is currently one of the most active and dynamic crowdsourcing communities and is growing at an explosive rate,” said Scheufen. “Our team lives and breathes OSM and so we are excited to join forces with Telenav to create the largest, most sophisticated, and smartest OSM navigation team in the world.”
In connection with the acquisition and in accordance with NASDAQ Marketplace Rule 5635(c), Telenav granted four employees of skobbler and its subsidiaries, upon the closing of the acquisition, restricted stock units for an aggregate of 634,920 shares of common stock.
These RSUs were granted outside of the existing Telenav stock plans and without stockholder approval pursuant to NASDAQ Marketplace Rule 5635(c)(4) with the following terms: each RSU vests as to 50% of the award on the anniversary of Acquisition and as to 50% of the award on the second anniversary of the Acquisition, subject to continued employment through each relevant date.
Telenav, Inc., announced today that it has acquired skobbler GmbH, the European-based navigation company with the highest rated OpenStreetMap (OSM)-based GPS navigation apps in the world. With this acquisition, Telenav brings the most successful OSM navigation experts in the world together as one team — including the founder of OSM, Steve Coast, who joined Telenav in 2013 — and becomes a major contributor to the creation of the open-sourced and most comprehensive map of the world, according to the announcement.
The acquisition closed on January 29 for consideration of approximately $19.2 million in cash and $4.6 million of company common stock.
“Crowdsourced OSM can power personalized navigation services like Scout — with highly detailed maps on a global scale,” said HP Jin, Telenav’s chairman and CEO. “We plan to offer Scout with OSM for much of the world. We have already made significant headway toward this goal in the U.S., including using OSM for our HTML5 version of Scout.”
OSM is the only crowdsourced and open-sourced map of the globe and, for many developers, it has become a clear alternative to Google Maps.
“Waze and Google — or, just Google now — provide similar mechanisms to improve their maps, based mostly on OSM’s innovations. With one big catch. It is very much their map. Not yours,” said Coast in his blog commentary today regarding the acquisition. “OpenStreetMap is different. All of the quality data contributed is openly available — just like Wikipedia. So, anyone can download, experiment and play with it freely. It’s not locked up beyond your reach.”
Since Coast founded OSM, the community has doubled year over year to more than 1.5 million registered editors, becoming a global community of local editors in every corner of the world. Its crowdsourced model publishes edits every minute on openstreetmap.org, resulting in maps that are detailed and up to date. For example, newly laid streets and newly developed areas can be updated on a regular basis and in real time. In addition, OSM allows for greater map detail for pedestrians such as alleys, sidewalks, parks, hiking trails, zoos, and even city trees.
Telenav has been an active contributor to OSM for more than three years, working closely with the community to enhance specific features needed for navigation, traffic and other future location-based services.
With offices in Germany and Romania, skobbler was the first company to launch a commercial navigation app using OSM (in 2010) for both Android and iOS devices and is available in app stores in 49 regions with worldwide map coverage. In order to do this, skobbler developed sophisticated algorithms that evolved OSM data from a display map to a navigable map.
skobbler’s apps are top ranked and highly rated in multiple countries including Germany, the Netherlands, and Sweden. skobbler’s CEO, Peter Scheufen, previously served as the CEO of Navigon, which became a leading GPS device manufacturer in Europe and was eventually purchased by Garmin. The other skobbler founders also held senior roles at Navigon before founding skobbler. Telenav expects that all skobbler employees will join Telenav as part of its OSM team, bringing significant industry-leading software expertise in location-based services, navigation and mapping.
“By joining our efforts with skobbler, we will build on our combined successes to bring the best mapping and navigation services to our customers around the world,” said Jin. “The benefits of an open source model will provide an enormous opportunity to change the economic models of navigation and other location-based services.”
“OSM is currently one of the most active and dynamic crowdsourcing communities and is growing at an explosive rate,” said Scheufen. “Our team lives and breathes OSM and so we are excited to join forces with Telenav to create the largest, most sophisticated, and smartest OSM navigation team in the world.”
In connection with the acquisition and in accordance with NASDAQ Marketplace Rule 5635(c), Telenav granted four employees of skobbler and its subsidiaries, upon the closing of the acquisition, restricted stock units for an aggregate of 634,920 shares of common stock.
These RSUs were granted outside of the existing Telenav stock plans and without stockholder approval pursuant to NASDAQ Marketplace Rule 5635(c)(4) with the following terms: each RSU vests as to 50% of the award on the anniversary of Acquisition and as to 50% of the award on the second anniversary of the Acquisition, subject to continued employment through each relevant date.
Applanix Corporation and American Aerospace Advisors have completed a successful series of test flights of AAAI’s RS-16 platform equipped with Applanix’ DMS-UAV aerial photogrammetry payload. This is the first successful mission for a long-endurance UAS (unmanned aerial system) capable of producing professional-grade, directly georeferenced mapping imagery for civilian applications such as pipeline monitoring, power line and emergency response mapping.
The RS-16 Unmanned Aircraft System equipped with the Applanix Direct Mapping Solution (DMS).
Tests were conducted over restricted airspace in the state of New Jersey. A joint team from Applanix and AAAI planned and flew a sequence of missions to evaluate the capabilities of the UAS. These include, critically, the ability to provide highly accurate, directly georeferenced and orthorectified aerial imagery without the need for ground control points or aerial triangulation calculations. The system, consisting of the airframe, its avionics, mobile ground control station and the digital mapping payload, performed according to expectations and successfully produced high-quality imagery.
“Performing safe and successful missions with long endurance unmanned aircraft in civilian airspace are a challenge that goes far beyond selecting the right aircraft and payload,” said David Yoel, CEO of American Aerospace Advisors. “Working with Applanix, we have produced an integrated system that is designed from the ground up with civilian mapping operations in mind. We believe this system has the capability to transform the aerial mapping industry.”
The Applanix RS-16 in flight.
The RS-16 DMS is a complete, operational system capable of conducting large area operations within the National Airspace System in the United States, and in other jurisdictions as local regulations allow. Within the USA, AAAI is engaged with several of the recently announced UAS research and test sites, which operate under the auspices of the FAA to develop the certification and operational requirements necessary to safely integrate UAS into the national airspace.
The GNSS-Inertial systems at the core of Applanix’ DMS-UAV aerial mapping payload uses commercial inertial technologies that are offered globally.
“The market for airborne imaging systems is in a state of rapid change,” said Joe Hutton, director of Inertial Technology and Airborne Products at Applanix. “Developments in imaging technology, in processing capability, and in the nature of inertial sensors, make a directly georeferenced UAS a reality today, where it would have been inconceivable even a few years ago. Our ability to take our established market-leading manned solutions, and integrate the technology successfully into an unmanned platform, speaks volumes for the engineering expertise of Applanix and AAAI.”
The Lockheed Martin team developing the U.S. Air Force’s next generation Global Positioning System (GPS) recently turned on power to the bus and network communications equipment payload of the program’s second satellite designated GPS III Space Vehicle 2 (SV-02).
The successful powering on of GPS III SV-02, on December 19, 2013, at Lockheed Martin’s Denver-area GPS III Processing Facility (GPF), is a major production milestone which demonstrates the satellite’s mechanical integration, validates its interfaces, and leads the way for electrical and integrated hardware-software testing.
“The GPS III SV-02 bus power on is a significant milestone, positioning SV-02 in line with the Air Force’s first GPS III space vehicle, SV-01, in our GPF, where both satellites are progressing through sequential integration and test work stations specifically designed for efficient and affordable satellite production,” explained Mark Stewart, vice president for Lockheed Martin’s Navigation Systems mission area.
On November 11, 2013, the propulsion core module for SV-02 was delivered to the GPF from Lockheed Martin’s Space & Technology Center, in Stennis, Mississippi, where the core was manufactured. The structural backbone of the satellite, the core contains the integrated propulsion subsystem that allows the GPS III to maneuver on orbit immediately after launch, as well as to conduct repositioning maneuvers throughout its mission life.
The GPS III program will affordably replace aging GPS satellites, while improving capability to meet the evolving demands of military, commercial and civilian users, Lockheed Martin said. GPS III satellites will deliver three times better accuracy; provide up to eight times improved anti-jamming capabilities; and include enhancements which extend spacecraft life 25 percent further than the prior GPS block. The GPS III also will carry a new civil signal designed to be interoperable with other international global navigation satellite systems, enhancing civilian user connectivity.
Lockheed Martin is under contract for production of the first six GPS III satellites (SV 01-06), the first four funded under the original contract and the fifth and sixth recent fully funded by an exercised Air Force option on December 13, 2013. Lockheed Martin had previously received advanced procurement funding for long-lead components for the fifth, sixth, seventh and eighth satellites (SV 05-08).
The first GPS III satellite (SV-01) was powered on February 28, 2013. GPS III SV-01’s spacecraft bus and antenna assemblies were delivered to Lockheed Martin’s GPF this summer. SV-01 is now in the integration and test flow leading to delivery “flight-ready” to the Air Force.
The GPS III team is led by theGlobal Positioning Systems Directorateat the U.S. Air Force Space and Missile Systems Center. Lockheed Martin is the GPS III prime contractor with teammates Exelis, General Dynamics, Infinity Systems Engineering, Honeywell, ATK and other subcontractors. Air Force Space Command’s 2nd Space Operations Squadron(2SOPS), based at Schriever Air Force Base, Colo., manages and operates the GPS constellation for both civil and military users.
China’s BeiDou system claimed a user range error (URE) of 2.5 meters zero age of data (ZAOD) 95% recently. The parallel GPS specifications commit to 6 meters 95% ZAOD and 7.8 meters 95% all AODs. Does this mean that BeiDou is more accurate than GPS? Not so fast.
In late December, director Ran Chengqi of China’s Satellite Navigation System Management Office announced the BeiDou Navigation Satellite System (BDS) Public (or Open) Service Performance Standard. The document details the public service performance parameters of the BeiDou system, including service area, accuracy, integrity, continuity, and availability. It is a basic commitment to customers from BDS providers, but also an important basis for customers to choose, use, and evaluate the system performance.
A few important qualifications of BeiDou’s performance standard first:
According to the foreword of the document, “This document specifies the BDS open service performance standard at the current stage.” This is as it should be.
A paragraph on service volume, however, highlights the fact that BeiDou is as yet a regional service.
“4.4 BDS OS Service Volume
The BDS OS service volume is defined as the OS SIS coverage of the BDS satellites where both the BDS OS horizontal and vertical position accuracy are better than 10 meters (probability of 95%). At the current stage, the BDS regional service capability has been achieved, which can provide continuous OS to the area as shown in Figure 2 & Figure 3, including the most part of the region from 55°S to 55°N, 70°E to150°E.”
The BDS Service Area.
This means that BeiDou commits to 2.5 meter accuracy in China, as well as neighboring countries — and importantly, trading partners — in Southeast Asia plus Australia.
Does this mean that once BeiDou attains global status, it will provide 2.5 meter accuracy everywhere, on its basic single frequency, open service? Hard to tell. Much of its strength, its core strength, one might say, comes from 5 geostationary Earth orbit (GEO) satellites and 5 Inclined Geosynchronous Satellite Orbit (IGSO) satellites. The GEOs hover over the Equator more or less permanently, south of but in the general longitude of China’s sovereign national territory. The IGSOs move back and forth from the northern to the southern hemispheres in the same area.
When BeiDou achieves its planned global reach, an event scheduled for 2020, the constellation will consist of 35 satellites: 5 GEOs, stationed at longitudes so their footprints cover China, 27 medium Earth orbit (MEO) satellites encircling the globe in continuous paths as do those of GPS, and 3 IGSOs over the East and Southeast Asian regions.
Will globally available accuracy at that point match what is achievable in China? It takes a better geometric mind than mine to fathom this.
Even disregarding the geographic limit of the 2.5-meter claim, and ignoring for the moment the mathematical conundrum outlined above, there are reasons to scrutinize the BeiDou Performance Standard more closely, as John Lavrakas of Advanced Research Corporation has done. His notes, and an illuminating table, follow below after a bit more introduction and background on the general topic.
The publishing of the Public Service Performance Standard, a common practice among GNSS operators, is also a prerequisite for BeiDou system involvement in international civil aviation, international maritime, 3rd Generation Mobile [phone] System, and other international standard-setting organization activities.
The document has Chinese and English versions. Because document download from the BDS government website can be difficult, Richard Langley has made them available at the University of New Brunswick website:
John Lavrakas of Advanced Research Corporation posted the following comment to the an earlier online article announcing the Performance Standard document.
“I took a quick look at comparing the BeiDou Open Service Performance Standard with the GPS Standard Positioning Service Performance Standard and obtained mixed results.”
Table 1. Coded to show green for the GNSS service committing to a more stringent standard over the other. Courtesy of Advanced Research Corporation.
“In some cases, the commitments from BeiDou were stronger (URE accuracy, vertical position), and in other cases the commitments from GPS were stronger (continuity of service, advance notice of outages).
“The good news is that GNSS systems are documenting the service levels that users can expect. What we will need next is monitoring to verify these service levels are being met.
A final note. As the GPS stewards from the U.S. Air Force carefully and proudly remind us at each GNSS conference where they deliver a briefing, actual GPS performance has almost always bettered its specs over the last decade or two — often by a considerable margin.
And with that, I think we may all return to our various pursuits, secure in the knowledge that while the gold standard may — repeat, may — at times pass in limited special circumstances or under particular conditions, from system to system, overall GNSS Things Are Getting Better All the Time.
u‑blox has introduced its MAX, NEO and LEA GNSS modules in its next-generation, multi-constellation positioning platform u‑blox M8.
The new module series satisfies a wide range of requirements by providing a scalable range of features including antenna management, integrated filters, data logging, crystal or TCXO, and rich set of interfaces, u-blox said.
The modules can acquire and track all visible GPS, GLONASS, BeiDou, QZSS and SBAS satellites and can track any two GNSS systems simultaneously for increased reliability, accuracy and faster acquisition time. For an overview of all modules, click here to download u-blox’ GNSS module selector guide.
“Our advanced u-blox M8 modules are the result of u-blox’ in-house GNSS chip design expertise and end-to-end ownership of the entire IC and module manufacturing processes. This gives us full control over features, quality and production allowing us to react quickly to customer requirements,” said Thomas Seiler, u-blox CEO. “Being independent of third-party GNSS chip suppliers means we offer our customers exactly the right feature set, chip and module options, smooth upgrade path and a clearly defined product roadmap extending years into the future.”
u-blox’ online assisted-GNSS service, AssistNow, has also been radically improved to support an unbeatable level of global positioning performance. The free service is available in online and offline versions and supports both assisted GPS and GLONASS.
The MAX-M8, NEO-M8 and LEA-M8 modules provide cutting edge positioning performance and -167 dBm tracking sensitivity for a wide range of applications including vehicle and asset tracking, eCall / ERA-GLONASS emergency call systems, vehicle telematics for insurance, road pricing and anti-theft devices, navigation, security, and point-of-sales terminals.
u-blox continues to offer u-blox 7 based modules MAX, NEO and LEA-7 which remain optimal for low-power, cost-efficient, single-GNSS designs. The new u-blox M8 modules maintain hardware and software compatibility with u-blox 7 modules to allow easy upgrade or product variants utilizing the same PCB layout.
u‑blox’ capability of delivering u-blox 7 and u-blox M8 GNSS technologies in both module and integrated circuit form-factors provides maximum design flexibility and protects customers’ development investments over successive product generations.
First samples and evaluation kits for u-blox M8 modules are available for customer evaluation.
