Settop Survey is offering the Settop Repeater, which allows network RTK rover use in areas of low- or non-GSM coverage by receiving differential corrections via radio. A new firmware update allows connection via any external radio to connect the repeater to precision agriculture systems or machine control. Repeater field application versatility is managed by intuitive software using a touchscreen.
Author: GPS World Staff
-
Settop Survey Offers Network RTK Repeater
-
GNSS and Radio Astronomical Observations
An alternative tool for detecting underground nuclear explosions?
By Dorota A. Grejner-Brzezinska, Jihye Park, Joseph Helmboldt, Ralph R. B. von Frese, Thomas Wilson, and Jade Morton
Well-concealed underground nuclear explosions may go undetected by International Monitoring System sensors. An independent technique of detection and verification may be offered by GPS-based analysis of local traveling ionospheric disturbances excited by an explosion. Most of the work to date has been at the research demonstration stage; however, operational capability is possible, based on the worldwide GPS network of permanently tracking receivers. This article discusses a case study of detecting underground nuclear explosions using observations from GPS tracking stations and the Very Large Array radio telescope in New Mexico.
More than 2,000 nuclear tests were carried out between 1945 and 1996, when the Comprehensive Nuclear Test Ban Treaty was adopted by the United Nations General Assembly. Signatory countries and the number of tests conducted by each country are the United States (1000+), the Soviet Union (700+), France (200+), the United Kingdom, and China (45 each). Three countries have broken the de facto moratorium and tested nuclear weapons since 1996: India and Pakistan in 1998 (two tests each), and the Democratic People’s Republic of Korea (DPRK) in 2006 and 2009, and most recently, in 2013.
To date, 183 countries have signed the treaty. Of those, 159 countries have also ratified the treaty, including three nuclear weapon states: France, the Russian Federation, and the United Kingdom. However, before the treaty can enter into force, 44 specific nuclear-technology-holder countries must sign and ratify. Of these, India, North Korea and Pakistan have yet to sign the CTBT, and China, Egypt, Iran, Israel, and the United States have not ratified it.
The treaty has a unique and comprehensive verification regime to make sure that no nuclear explosion goes undetected. The primary components of the regime are:
- The International Monitoring System: The IMS includes 337 facilities (85 percent completed to date) worldwide to monitor for signs of any nuclear explosions.
- International Data Center: The IDC processes and analyzes data registered at IMS stations and produces data bulletins.
- Global Communications Infrastructure: This transmits IMS data to the IDC, and transmits data bulletins and raw IMS data from IDC to member states.
- Consultation and Clarification: If a member state feels that data collected imply a nuclear explosion, this process can be undertaken to resolve and clarify the matter.
- On-Site Inspection: OSI is regarded as the final verification measure under the treaty.
- Confidence-Building Measures: These are voluntary actions. For example, a member state will notifying CTBTO when there will be large detonations, such as a chemical explosion or a mining blast.
The IMS (see Figure 1) uses the following state-of-the-art technologies. Numbers given reflect the target configuration:
- Seismic: Fifty primary and 120 auxiliary seismic stations monitor shockwaves in the Earth. The vast majority of these shockwaves — many thousands every year — are caused by earthquakes. But man-made explosions such as mine explosions or the North Korean nuclear tests in 2006, 2009, and 2013 are also detected.
- Hydroacoustic: As sound waves from explosions can travel extremely far underwater, 11 hydroacoustic stations “listen” for sound waves in the Earth oceans.
- Infrasound: Sixty stations on the surface of the Earth can detect ultra-low-frequency sound waves that are inaudible to the human ear, which are released by large explosions.
- Radionuclide: Eighty stations measure the atmosphere for radioactive particles; 40 of them can also detect the presence of noble gas.
Figure 1. The International Monitoring System (IMS): worldwide facilities grouped by detection technologies used. 
Only the radionuclide measurements can give an unquestionable indication as to whether an explosion detected by the other methods was actually nuclear or not. The observing stations are supported by 16 radionuclide laboratories.
Since radionuclide detection method provides the ultimate verification as far as the type of blast goes, it should be mentioned that while the 2006 North Korean event (yield of less than a kiloton) was detected by the IMS stations in more than 20 different sites within two hours of detonation, and both seismic signal and radioactive material were detected, the 2009 event (yield of a few kilotons) was detected by 61 IMS stations; seismic and infrasound signals were detected, but no radioactive material was picked up by the radionuclide stations. Seismic signal was consistent with a nuclear test, but there was no “ultimate” proof by the radionuclide method.
Thus, well-concealed underground nuclear explosions (UNEs) may be undetected by some of the IMS sensors (such as the radionuclide network). This raises a question: Is there any other technology that is readily available that can detect and discriminate various types of blasts, particularly those of nuclear type? Recent experiments have shown that an independent technique of detection and verification may be offered by GPS-based analysis of local traveling ionospheric disturbances (TIDs) excited by an explosion.
GNSS-Based Detection
Atmospheric effects from mostly atmospheric nuclear explosions have been studied since the 1960s.The ionospheric delay in GNSS signals observed by the ground stations can be processed into total electron content (TEC), which is the total number of electrons along the GNSS signal’s path between the satellite and the receiver on the ground. The TEC derived from the slant signal path, referred to as the slant TEC (STEC), can be observed and analyzed to identify disturbances associated with the underground nuclear explosion.
STEC signature (in spectral and/or spatial-temporal domains) can be analyzed to detect local traveling ionospheric disturbances (TID).TID can be excited by acoustic gravity waves from a point source, such as surface or underground explosions, geomagnetic storms, tsunamis, and tropical storms. TIDs can be classified as Large-Scale TID (LSTID) and Medium-Scale TID (MSTID) based on their periods regardless of the generation mechanism. The periods of LSTIDs generally range between 30–60 minutes to several hours, and those of MSTIDs range from 10 to 40 or even 60 minutes. LSTIDs mostly occur from geophysical events, such as geomagnetic storms, which can be indicated by global Kp indices, while MSTIDs are genrally not related to any high score Kp indices. An underground nuclear explosion can result in an MSTID.
TIDs are generated either by internal gravity wave (IGW) or by acoustic gravity wave (AGW). The collisional interaction between the neutral and charged components cause ionospheric responses. The experimental results indicate IGWs can change the ozone concentration in the atmosphere. In the ionosphere, the motion of the neutral gas in the AGW sets the ionospheric plasma into motion.
The AGW changes the iso-ionic contours, resulting in a traveling ionospheric disturbance.
The past 10–15 years has resulted in a significant body of research, and eventually a practical application, with worldwide coverage, of GPS-based ionosphere monitoring. A significant number of International GNSS Service (IGS) permanent GNSS tracking stations (see Figure 2) form a powerful scientific tool capable of near real-time monitoring and detection of various ionospheric anomalies, such as those originating from the underground nuclear explosions (UNEs).
Figure 2. The IGS global tracking network of 439 stations. The network is capable of continuously monitoring global ionospheric behavior based on ionospheric delays in the GNSS signals. The GNSS signals are readily accessible anywhere on Earth at a temporal resolution ranging from about 30 seconds up to less than 1 second.
A powerful means to isolate and relate disturbances observed in TEC measurements from different receiver-satellite paths is to analyze the spectral coherence of the disturbances. However, in our algorithms, we emphasize the spatial and temporal relationship among the TEC observations. Spatial and temporal fluctuations in TEC are indicative of the dynamics of the ionosphere, and thus help in mapping TIDs excited by acoustic-gravity waves from point sources, as well as by geomagnetic storms, tropical storms, earthquakes, tsunamis, volcanic explosions, and other effects.
Methodology of UNE Detection
Figure 3 illustrates the concept of the generation of the acoustic gravity wave by a UNE event, and its propagation through the ionosphere that results in a traveling ionospheric disturbance (TID). The primary points of our approach are: (1) STEC is calculated from dual-frequency GPS carrier phase data, (2) after eliminating the main trend in STEC by taking the numerical third order horizontal 3-point derivatives, the TIDs are isolated, (3) we assume an array signature of the TID waves, (4) we assume constant radial propagation velocity, vT, using an apparent velocity, vi, of the TID at the ith observing GNSS station, (5) since the TID’s velocity is strongly affected by the ionospheric wind velocity components, vN and vE, in the north and east directions, respectively, the unknown parameters,vT, vN, and vE, can be estimated relative to the point source epicenter, and (6) if more than six GNSS stations in good geometry observe the TID in GNSS signals, the coordinates of the epicenter can also be estimated.
Figure 3a. Pictorial representation of the scenario describing a GNSS station tracking a satellite and the ionospheric signal (3-point STEC derivative); not to scale. 
Figure 3b. The scenario describing a GNSS station tracking a satellite and the ionospheric signal and a point source (e.g., UNE) that generates acoustic gravity waves; not to scale. 
Figure 3c. The scenario describing a GNSS station tracking a satellite and the ionospheric signal, and the propagation of the acoustic gravity waves generated by a point source (e.g., UNE); not to scale. 
Figure 3d. The scenario describing a GNSS station tracking a satellite and the ionospheric signal, at the epoch when the GNSS signal is affected by the propagation of the acoustic gravity waves generated by a point source (e.g., UNE); not to scale. 
Figure 3e. Same as 3D, indicating that the geometry between GNSS station, the satellite and the IPP can be recovered and used for locating the point source; multiple GNSS stations are needed to find the point source location and the the velocity components of TID and ionospheric winds; not to scale. 
Figure 3f. Same as 3D, after the TID wave passed the line of sight between the GNSS stations and the satellite; not to scale. Figure 4 illustrates the geometry of detection of the point source epicenter. Determination of the epicenter of the point source that induced TIDs can be achieved by trilateration, similarly to GPS positioning concept. The TIDs, generated at the point source, propagate at certain speed, and are detected by multiple GPS stations.
The initial assumption in our work was to use a constant propagation velocity of a TID. By observing the time of TID arrival at the ionospheric pierce point (IPP), the travel distance from the epicenter to the IPP of the GPS station that detected a TID (which is the slant distance from the ith station and the kth satellite) can be derived using a relationship with the propagation velocity. In this study, we defined a thin shell in the ionosphere F layer, 300 kilometers above the surface, and computed the IPP location for each GPS signal at the corresponding time epoch of TID detection.
Figure 4. Geometry of point source detection based on TID signals detected at the IPP of GPS station, i, with GPS satellite k. Unknown: coordinates of the point source, ( ф, λ ); three components of TID velocity vT, vN, and vE ; Observations: coordinates of IPP, (xik, yik, zik) and the corresponding time epoch to TID arrival at IPP, tik; Related terms: slant distance between IPP and UNE, sik; horizontal distance between the point source epicenter and the GPS station coordinates, di; azimuth and the elevation angle of IPP as seen from the UNE, αjk and εjk , respectively. Very Large Array (VLA)
In addition to GNSS-based method of ionosphere monitoring, there are other more conventional techniques, for example, ground-based ionosondes, high-frequency radars, Doppler radar systems, dual-frequency altimeter, and radio telescopes. In our research, we studied the ionospheric detection of UNEs using GPS and the Very Large Array (VLA) radio telescope.
The VLA is a world-class UHF/VHF interferometer 50 miles west of Socorro, New Mexico. It consists of 27 dishes in a Y-shaped configuration, each one 25 meters in diameter, cycled through four configurations (A, B, C, D) spanning 36, 11, 3.4, and 1 kilometers, respectively. The instrument measures correlations between signals from pairs of antennas, used to reconstruct images of the sky equivalent to using a much larger single telescope. While conducting these observations, the VLA provides 27 parallel lines of sight through the ionosphere toward cosmic sources.
Past studies have shown that interferometric radio telescopes like the VLA can be powerful tools for characterizing ionospheric fluctuations over a wide range of amplitudes and scales. We used these new VLA-based techniques and a GPS-based approach to investigate the signature of a TID originated by a UNE jointly observed by both GPS and the VLA. For this case study, we selected one of the 1992 U.S. UNEs for which simultaneous GPS and VLA data were available.
Table 1. Characteristics of the analyzed events (UNEs). Experimental Results
We summarize here the test studies performed by the OSU group in collaboration with Miami University and the U.S. Naval Research Laboratory on detection and discrimination of TIDs resulting from UNEs using the GNSS-based and VLA-based techniques. Table 1 lists the UNE events that have been analyzed to date. As of March 2013, the results of the 2013 North Korean UNE were not fully completed, so they are not included here.
In the 2006 and 2009 North Korean UNE experiments, STEC data from six and 11 nearby GNSS stations, respectively, were used. Within about 23 minutes to a few hours since the explosion, the GNSS stations detected the TIDs, whose arrival time for each station formulated the linear model with respect to the distance to the station. TIDs were observed to propagate with speeds of roughly 150–400 m/s at stations about 365 km to 1330 km from the explosion site. Considering the ionospheric wind effect, the wind-adjusted TIDs located the UNE to within about 2.7 km of its seismically determined epicenter (for the 2009 event; no epicenter location was performed for the 2006 event due to insufficient data). The coordinates estimated by our algorithm are comparable to the seismically determined epicenter, with the accuracy close to the seismic method itself. It is important to note that the accuracy of the proposed method is likely to improve if the stations in better geometry are used and more signals affected by a TID can be observed. An example geometry of UNE detection is shown in Figure 5.
Figure 5. Locations of the underground nuclear explosion (UNE) in 2009 and GNSS stations C1 (CHAN), C2 (CHLW), D1 (DAEJ), D2 (DOND), I1 (INJE), S1 (SUWN), S2 (SHAO), S3 (SOUL), U1 (USUD), Y1 (YANP), Y2 (YSSK) on the coastline map around Korea, China, and Japan. The TID waves are highlighted for stations C1, D1, D2, I1. The bold dashed line indicates the ground track for satellite PRN 26 with dots that indicating the arrival times of the TIDs at their IPPs. All time labels in the figure are in UTC. For the Hunters Trophy and the Divider UNE tests, the array signature of TIDs at the vicinity of GPS stations was observed for each event. By applying the first-order polynomial model to compute the approximate velocity of TID propagation for each UNE, the data points — that is the TID observations — were fit to the model within the 95 percent confidence interval, resulting in the propagation velocities of 570 m/s and 740 m/s for the Hunters Trophy and the Divider, respectively.
The VLA has observing bands between 1 and 50 GHz, and prior to 2008 had a separate VHF system with two bands centered at 74 and 330 MHz. A new wider-band VHF system is currently being commissioned. The VHF bands and L-band (1.4 GHz) are significantly affected by the ionosphere in a similar way as the GPS signal. In this study, we used VLA observations at L-band of ionospheric fluctuations as an independent verification of the earlier developed method based on the GNSS TID detection for UNE location and discrimination from TIDs generated by other types of point sources.
The VLA, operated as an interfer-ometer, measures the correlation of complex voltages from each unique pair of antennas (baselines), to produce what are referred to as visibilities. Each antenna is pointed at the same cosmic source; however, due to spatial separation, each antenna’s line of sight passes through a different part of the ionosphere. Consequently, the measured visibilities include an extra phase term due to the difference in ionospheric delays, which translates to distortions in the image made with the visibilities. This extra phase term is proportional to the difference in STEC along the lines of sight of the two telescopes that form a baseline. Thus, the interferometer is sensitive to the STEC gradient rather than STEC itself, which renders it capable of sensing both temporal and spatial fluctuations in STEC.
The spectral analysis was performed on the STEC gradients recovered from each baseline that observed the Hunters Trophy event. Briefly, a time series of the two-dimensional STEC gradient is computed at each antenna. Then, a three-dimensional Fourier transform is performed, one temporal and two spatial, over the array and within a given time period (here ~15 minutes). The resulting power spectrum then yields information about the size, direction, and speed of any detected wavelike disturbances within the STEC gradient data.
Roughly 20 to 25 minutes after the UNE, total fluctuation power increased dramatically (by a factor of about 5×103). At this time, the signature of waves moving nearly perpendicular to the direction from Hunters Trophy (toward the northeast and southwest) was observed using the three-dimensional spectral analysis technique. These fluctuations had wavelengths of about 2 km and inferred speeds of 2-8 m s-1. This implies that they are likely due to small-scale distortions moving along the wavefront, not visible with GPS. Assuming that these waves are associated with the arrival of disturbances associated with the Hunters Trophy event, a propagation speed of 570–710 m/s was calculated, which is consistent with the GPS results detailed above.
In addition, a TID, possibly induced by the February 12, 2013, North Korean UNE, was also detected using the nearby IGS stations, by the detection algorithm referred to earlier. Eleven TID waves were found from ten IGS stations, which were located in South Korea, Japan, and Russia. Due to the weakness of the geometry, the epicenter and the ionospheric wind velocity were not determined at this point. The apparent velocity of TID was roughly about 330–800 m/s, and was calculated using the arrival time of the TID after the UNE epoch and the slant distance between the corresponding IPP and the epicenter. The reported explosion yield was bigger, compared to the 2009 North Korean UNE, which possibly affected the propagation velocity by releasing a stronger energy. However, more in-depth investigation of this event and the corresponding GPS data is required.
Conclusions
Research shows that UNEs disturb the ionosphere, which results in TIDs that can be detected by GNSS permanent tracking stations as well as the VLA. We have summarized several GNSS-based TID detections induced by various UNEs, and verified the GNSS-based technique independently by a VLA-based method using the 1992 U.S. UNE, Hunters Trophy. It should be noted that VLA observation was not available during the time of the Divider UNE test; hence, only the Hunters Trophy was jointly detected by GPS and the VLA. Our studies performed to date suggest that the global availability of GNSS tracking networks may offer a future UNE detection method, which could complement the International Monitoring System (IMS).
We have also shown that radio-frequency arrays like the VLA may also be a useful asset for not only detecting UNEs, but for obtaining a better understanding of the structure of the ionospheric waves generated by these explosions. The next generation of HV/VHF telescopes being developed (such as the Lower Frequency Array in the Netherlands, the Long Wavelength Array in New Mexico, the Murchison Widefield Array in Australia) utilize arrays of dipole antennas, which are much cheaper to build and operate and are potentially portable.
It is conceivable that a series of relatively economical and relocatable arrays consisting of these types of dipoles could provide another valuable supplement to the current IMS in the future, particularly for low-yield UNEs that may not be detectable with GPS.
Acknowledgment
This article is based on a paper presented at the Institute of Navigation Pacific PNT Conference held April 22–25, 2013, in Honolulu, Hawaii.
Dorota A. Grejner-Brzezinska is a professor and chair, Department of Civil, Environmental and Geodetic Engineering, and director of the Satellite Positioning and Inertial Navigation (SPIN) Laboratory at The Ohio State University.
Jihye Park recently completed her Ph.D. in Geodetic Science program at The Ohio State University. She obtained her B.A. and M.S degrees in Geoinformatics from The University of Seoul, South Korea.
Joseph Helmboldt is a radio astronomer within the Remote Sensing Division of the U.S. Naval Research Laboratory.
Ralph R.B. von Frese is a professor in the Division of Earth and Planetary Sciences of the School of Earth Sciences at Ohio State University.
Thomas Wilson is a radio astronomer within the Remote Sensing Division of the U.S. Naval Research Laboratory.
Yu (Jade) Morton is a professor in the Department of Electrical and Computer Engineering at Miami University.
-
Underwater Inertial Navigation Features GPS and Sensors
The Sublocus underwater inertial navigation system by Advanced Navigation features high-accuracy north-seeking fiber-optic gyroscopes and accelerometers with a GPS receiver and pressure depth sensor, fused to deliver positional accuracy of 0.08 percent of distance traveled. The system also provides highly accurate roll, pitch, heading, heave, depth, and altitude.
Sublocus is also available with an integrated RDI Workhorse Navigator DVL for combined acoustic and inertial navigation in the one product. Both models are supplied with a subsea GPS antenna and are rated to 3,000 meters depth.
-
Expert Advice: The Chip-Scale Combinatorial Atomic Navigator
Andrei Shkel, Defense Advanced Research Projects Agency (DARPA) Photo: Andrei Shkel, Defense Advanced Research Projects Agency (DARPA) By Andrei Shkel, Defense Advanced Research Projects Agency (DARPA)
Future breakthroughs in microtechnology for positioning, navigation, and timing (PNT) will likely rely on yet-to-be-exploited physics, new materials, highly specialized fabrication technologies, batch assembly techniques, selective wafer-level trimming and polishing, a combination of passive and active calibration techniques strategically implemented right on-chip, and introduction of innovative test technologies.
Such microtechnology advances for PNT are sought because reliance on satellite-based GPS for precision PNT information, which is critical to the conduct of many types of military operations and the performance of a wide range of military weapon systems, can mean dependence on a resource that may become inaccessible, whether as a result of some type of component or overall system malfunction or as a consequence of deliberate enemy action. The goal of the DARPA micro-PNT portfolio of programs is to develop micro-technology for self-contained, chip-scale inertial navigation and precision guidance that would effectively eliminate the dependence on GPS while enabling uncompromised navigation and guidance capabilities for advanced munitions and various military platforms, under a wide range of operation conditions.
In 2012, under the project name C-SCAN, DARPA solicited innovative research proposals in the area of co-integration of inertial sensors with dissimilar physics of operation in a single micro-scale inertial measurement unit (IMU). This solicitation is an integral part of DARPA’s microtechnology for positioning, navigation, and timing (micro-PNT) portfolio of programs. The overarching objective of the micro-PNT portfolio is to develop technologies for self-contained chip-scale inertial navigation and precision guidance that could effectively eliminate the dependence on GPS or any other external signals and enable uncompromised navigation and guidance capabilities for advanced munitions, mid- and long-range missiles, and various military platforms under a wide range of operating conditions. The micro-PNT program includes a number of important specific efforts that focus on development of precision timing devices, inertial sensors, and microsystems. C-SCAN leverages the results of these efforts and expands the scope of the micro-PNT program.
In this context, the program sought to address challenges associated with the long-term drift, dynamic range, and start-up time of chip-scale components for positioning, targeting, navigation, and guidance tasks. Specific interest lies in the development of a Chip-Scale Combinatorial Atomic Navigator (C-SCAN) that combines inertial sensors with dissimilar, but complementary, physics of operation into a single microsystem. The main objectives of the C-SCAN program are to:
- explore miniaturization and co-fabrication of atomic sensors with high-performance solid-state inertial sensors, and
- develop combinatorial algorithms and architectures that seamlessly co-integrate components with dissimilar physics in a single ensemble.
The deliverable is a miniature IMU that co-integrates atomic and solid-state inertial sensors in a single microsystem with a volume of no more than 20 cubic centimeters (20 cc) and power consumption of no more than 1 Watt (1 W). The performance of C-SCAN is expected to be above and beyond what is currently available, combining a high resolution of motion detection (10-4 deg/hour for rotation and 10-6 g for linear acceleration), exceptional long-term bias and scale-factor stability (1 ppm with respect to the full-scale of operation), and start-up time performance orders of magnitude better than available today (less than 10 seconds from cold start).
To meet these objectives, the C-SCAN program expects to develop a complete IMU comprised of combinatorial gyroscopes and accelerometers with the following characteristics: 10-4 deg/hour and 10-6 g bias stability, 5·10-4 deg/√hour angle random walk (ARW) and 5·10-4 m/sec/√hour Velocity Random Walk (VRW), 1 ppm bias and scale-factor drift characteristics of 40 Hz (or ~15,000 deg/sec), and 1,000 g range of operation, respectively.
Figure 1. C-SCAN conceptual implementation. Photo: Andrei Shkel, Defense Advanced Research Projects Agency (DARPA) The C-SCAN module will have three axes of rotation, as well as three axes of acceleration sensitivity. The misalignment between the axes of sensitivity in C-SCAN is not to exceed 10-4 radians when operating in a harsh military environment. The operational environments of interest are:
- in-operation exposure to temperatures varying from -55ºC to +85ºC,
- in-operation exposure to mechanical vibrations from 5 Hz to 5 kHz with an average amplitude 5 g, and
- device survivability and subsequent normal operation after exposure to
- 15,000 g shock exerted in less than 1 second,
- a peak acceleration amplitude on the level of 20 g through the frequency range for random vibrations from 5 Hz to 5 kHz, and
- a 100º C temperature difference thermal shock with transfer time not exceeding 10 seconds.
Current state-of-the-art microscale inertial instruments can provide the required level of precision for missions of only 30 seconds or less in duration. The micro-PNT program is developing chip-scale, small SWaP+C (Size, Weight and Power, plus Cost) inertial sensors for a variety of operational scenarios, missions ranging from minutes to hours, and for reliable operation under environmental conditions varying from moderate to severe. Ongoing work includes development of a broad range of chip-scale precision timing devices and inertial sensors, including chip-scale atomic clocks, chip-scale primary atomic clocks, solid-state oscillators, silicon accelerometers, and various gyroscopes: vibratory rate, rate-integrating, electrostatically levitated spinning-mass, micro-nuclear magnetic resonance, and cold-atom interferometric.
While recent results in the micro-PNT program have shown considerable progress toward development of small-scale inertial instruments approaching navigation-grade performance, the overall challenge remains: how to simultaneously meet all the stringent PNT requirements imposed by U.S. Department of Defense missions in a small SWaP+C package. Specific requirements include, but are not limited to, accuracy, resolution, scale-factor, bias stability (both in-run and long-term), extended dynamic range, fast warm-up time, and short integration time. These challenges are significant, and it is unlikely that all the requirements can be achieved in a single type of device.
Overall, more than 98 percent of the missiles currently in the U.S. arsenal have mission durations of less than 20 minutes, and today, almost all of these missions are critically dependent on GPS for achieving the required level of delivery accuracy. A preferable solution is to completely eliminate dependence on GPS or any other external signals during the mission and rely solely on self-contained solutions such as inertial navigation, which is immune to jamming, spoofing, and other intentional or unintentional modification of position, orientation, and time information. Achieving 20 minutes of free inertial guidance is a major technological challenge faced by small SWaP+C inertial instruments. Solving this problem is of great strategic importance.
Several recent developments in micro-technology, inertial instruments, and atomic devices may present an opportunity for solving the problem of extended inertial guidance and navigation, potentially offering a new breed of chip-scale navigators exhibiting favorable characteristics when combined in a single hybrid micro-system ensemble.
Andrei M. Shkel received a Ph.D. in mechanical engineering from the University of Wisconsin-Madison and is a program manager in the Microsystems Technology Office at the Defense Advanced Research Project Agency (DARPA).
This column builds on material presented in a September 2011 GPS World article, “Microtechnology Comes of Age.”
That article, also by Andrei Shkel, described:
- two then-current efforts involving the development of clocks: Chip-Scale Atomic Clock (CSAC) and Integrated Micro Primary Atomic Clock Technology (IMPACT), and
- three efforts involving the development of inertial sensors and systems: Navigation-Grade Integrated Micro Gyroscopes (NGIMG), Micro Inertial Navigation Technology (MINT), and Information Tethered Micro Automated Rotary Stages (IT-MARS).
The 2011 article continued to explore four complementary new developments:
- Microscale Rate Integrating Gyroscopes (MRIG),
- Chip-Scale Timing and Inertial Measurement Unit (TIMU),
- Primary and Secondary Calibration on Active Layer (PASCAL),
- Platform for Acquisition, Logging, and Analysis of Devices for Inertial Navigation & Timing (PALADIN&T).
This column goes yet further, announcing the start of development of the Chip-Scale Combinatorial Atomic Navigator (C-SCAN) — the subject of a 2012 Broad Agency Announcement and request for proposals.
-
Robot: Target on Its Back
Photos: Brian J. Geiger. Two Autonomous Vehicles Seek Safe Avoidance in Critical Tests
A new state-of-the-art research center runs car-makers’ safety systems through their paces, in tandem with a soft-target robot that can be crash-impacted without adverse effects. Precise positioning and exact repeatability of test sequences are key criteria.
Paul Perrone, Perrone Robotics
The Insurance Institute for Highway Safety has undertaken a $30 million expansion project at its Vehicle Research Center near Washington, D.C., enlarging and enhancing a state-of-the-art vehicle test track and building a new 700 x 300-foot (213 x 91-meter) covered track for weather-resistant testing.
The VRC will use new robotic and positioning technologies to achieve required levels of precision and repeatability for vehicle testing of frontal collision avoidance and other safety systems. Tests of both the same and different vehicles must be conducted under identical, controlled conditions for the results to have comparable fidelity.
Crash tests and research conducted at the VRC help drive life-saving improvements in vehicle designs. The new facility will enable staff to evaluate emerging automated vehicle technology in commercial vehicle systems intended to prevent crashes or lessen their severity, with the goal of encouraging the entire industry to adopt the most effective new features.
Safety systems in vehicles to be tested include the following:
◾ Adaptive cruise control
◾ Collision-imminent braking
◾ Lane-departure warning/correction
◾ Other automated technologies.Such functions represent semi-automated functions aboard vehicles now on the road. The system is also designed to address and test the full spectrum of semi- to fully-automated vehicles, addressing evolving levels of autonomy and ultimately producing driverless vehicle technology.
IIHS has contracted Perrone Robotics, Inc. (PRI), to deliver a robotic system for testing such vehicles. PRI develops new applications using its MAX robotics and suite of automation software building blocks. MAX enables rapid integration of a range of sensor and actuator types and has evolved with several frameworks, including MAX-UGV for unmanned ground vehicles. PRI has used MAX-UGV to build automated passenger cars, all-terrain vehicles, tractors, custom platforms, and rockstar Neil Young’s long-range electric LincVolt, a converted 1959 Lincoln Continental.
FIGURE 1. PRI test system. For the first phase of the IIHS project, the Perrone Robotics system includes a robot target vehicle with the footprint of a car, but measuring only 4 inches high, with a 1-inch ground clearance.
A robot target vehicle with the footprint of a car measure 4 inches high. Photos: Brian J. Geiger. Test Scenario Example. One instance to be tested is National Highway Traffic Safety Administration criteria for crash-imminent braking (CIB). The CIB concept goes beyond the forward-collision warning systems already found in many new cars by actually engaging the brakes when a driver, at fairly slow speeds, gets too close to the car in front of him. In tests, the while the test vehicle travels at similar speeds on a programmed collision course with the robot.
The target robot vehicle carries one of a number of soft targets. If the vehicle under test fails to prevent a collision with the robot target, the test vehicle runs over the robot target vehicle, dislodging the soft target, but avoiding damage to the test vehicle, robot target vehicle, and the soft target. The next phase of the project adds smaller-footprint target robot platforms with soft targets, representative of pedestrians and cyclists.
To ensure that the test vehicle can perform repeatable tests, the system also includes a drop-in actuator kit that can be installed into any test vehicle in 30 minutes or less. The system is designed to allow a human driver to sit comfortably in the vehicle and optionally drive, but can also control the throttle, brake, and steering to drive test profiles. Repeatability is key for the operation of robots and vehicles, as well as track conditions, which will be helped by the covered track.
The VRC test track is installing Locata as its positioning system. In addition to alleviating concerns about GPS outages or dead/weak signal spots, this enables the PRI system to be operated reliably inside the new covered test track. While GPS is not an option for covered or indoor test sites and suffers from environmental issues, the high fidelity and localized positioning provided by Locata overcomes these barriers to test.
Drop-in actuator kit steering. Photos: Brian J. Geiger. 
Drop-in actuator kit throttle-brake. Photos: Brian J. Geiger. PRI will deliver the target robot and drop-in actuators custom-built. The company looked at starting with existing platforms and building from them, but it would have been infeasible or overly expensive to meet the IIHS requirements for this system. Most existing systems were developed for vehicle dynamics testing or low-speed/simple collision testing. Most couldn’t handle some or all of the more challenging requirements such as the following:
Drop-in actuator kit:
- Allow human driver to sit comfortably and drive the vehicle without interfering;
- Drive autonomously while also allowing for hybrid modes whereby test drivers and onboard systems may assist or take over controls;
- Offer out-of-the-box programmability and flexibility to handle a wide range of test scenarios and automated vehicle levels;
- Install into any vehicle in 30 minutes or less;
- Do not damage vehicle with installation; retain a significant percent of resale value.
Target robot vehicle:
- Accelerate from 0 to 55 mph in 10 seconds;
- Survive collisions at speeds up to 55 mph;
- Allow collision-avoidance testing with minimal damage to test vehicles and target robot;
- Scale for carrying a wide variety of soft-target payloads and enable a wide range of vehicles, from small car to SUV to tractor-trailer) to be tested.
Locata positioning system:
- Work outside and also on covered track; cover track area with no dead/weak spots;
- Deliver better than 10-centimeter accuracy for position measurements and relative position control of robots and vehicles;
- Deliver position updates at 100 Hz in combination with attitude and heading reference system (AHRS) or inertial navigation system (INS).
The positioning requirement derives from the testers’ need not only for accurate location data of each vehicle, but for precise knowledge of how far apart they are while performing real-time control to orchestrate repeatable scenarios, intersecting vehicle and robot paths to determine whether the vehicle acts to prevent a collision.
A human operator is easily accomodated within the drop-in actuator kit. Photos: Brian J. Geiger. Safety Systems
There is a driver in the test vehicle, and there are personnel present at the test site who could be injured by a test vehicle or target robot platform. In addition to wireless e-stop remotes, the test vehicle and target robot systems can be disabled and stopped by a number of events. In the target robot, an e-stop causes the battery pack to be completely disconnected from all vehicle systems, and a spring-load is released applying mechanical braking to stop the vehicle.
Under normal conditions, the spring is held back with a pneumatic system and air is dumped upon e-stop event. A target robot e-stop is triggered by
◾ remote e-stop controller
◾ a command issued by control software
◾ loss of communication with external systems
◾ failure of or loss of communication with internal systems
◾ loss of power.Aside from fail-safe remote and onboard e-stop systems, additional safety measures are employed by means of safety controllers that monitor safety-critical regions of software, implement a wide range of robot-safety checking rules, and ensure that the robot is operating within safe parameters of the environment (such as by staying within an invisible fence and pre-defined operation boundary).
Common MAX-UGV Robot Logic
A common instrumentation and control system (CICS) for both the target robot platforms and test vehicle instrumentation and robotic assist platforms is illustrated in Figure 2.
FIGURE 2. Target robot logic flow. Embedded Controller. The heart and soul of the vehicle hosts and runs the algorithms, receives sensor data, and executes actuation commands to the motor controllers based on desired route plans and dynamic sensor information. This controller runs the MAX software platform, MAX-UGV framework, and various MAX drivers.
I/O Controller. Handles inputs from sensors for temperatures, voltages, and currents as well as monitoring limit switches and actuating relays. Certain controls are planned such as mock brake lights on target robots and warning lights in test vehicles.
Locata. A constellation of nine LocataLite units on towers covers the existing track for Phase I of the project. Phase 2 will require additional units to add coverage to the covered track; some towers will provide coverage to both tracks. Each target robot vehicle and each drop-in kit for the test vehicles carries a Locata rover.
Locata’s new software essentially adds some capability from its indoor software to its outdoor software to deal with reflections/multipath issues caused by the metal buildings at the test site. The new software also allows the rover to perform real-time calculations on board, required for the less-than 10-cm accuracy. Previously this had to be done on a separate system and data had to be transferred back and forth, which worked against meeting real-time position update requirements for controlling speed, position, and relative position of robots and test vehicles. In test vehicles and target robots, the Locata rover position updates are merged with the output of an attitude, heading, and reference system (AHRS).
AHRS. The CICS in the robots and test vehicles includes an AHRS that provides the required heading, position, and velocity updates. Accuracy requirements are heading, 1 degree; position, less than 10 centimeters; velocity, 1 mph. Our required position update rate is 10 Hz. We expect to achieve 100 Hz in our system, which improves self-nav capability and overall performance. This rate also applies to other measured/logged data. A Kalman filter computes data from sources within the AHRS and from external sources: GPS and Locata.
Wireless Adapter, Antenna. On our critical channel, we exchange messages between vehicles to effect proper trajectory and relative positioning. Our e-stop controllers and safety systems also use this network. The non-critical channel is used for test setup and supervisory control, decimated data transmission for HMI monitoring, and logged data transmission.
Wireless E-stop Interface. This interface is for remote shutdown of a vehicle. The e-stop triggers are similar for the test vehicle systems, but the driver can also disable the robotic system. Rather than brake the test vehicle, an e-stop of the test vehicle systems disables the steering, brake, and throttle actuators into limp-mode and releases control of the test vehicle to the driver.
Safety Controller. A separate watchdog controller monitors live conditions and the embedded controller and onboard systems, and serves as a direct line for remote wireless e-stop.
Electronics, Motors. These includes six high-performance 4-inch motors, motor controllers, cut-off contactors, and overall cut-off system for e-stop.
Conclusion
The IIHS expansion project is a first of its kind for automated vehicle testing, breaking new ground for target positioning and control, and providing the first indoor test track for this purpose. Data from these tests will be used to improve safety of on road semi- and fully-automated vehicles and help save many thousands of lives, setting a high bar for capability and performance of all automated vehicle functions. Requirements for safety, repeatability, and seamless handoff between driver and autonomous control of the test vehicles, as well as the speeds at which the robots must travel and survive collisions, pose significant challenges. We believe our systems meet them fully.
-
The System: IRNSS Success, GLONASS Bellyflop
IRNSS Success
The Indian Regional Navigation Satellite System (IRNSS) successfully launched its first satellite on July 1 from the Satish Dhawan Space Centre at Sriharikota spaceport on the Bay of Bengal. An Indian-built Polar Satellite Launch Vehicle PSLV-C22, XL version, carried the 1,425-kg satellite aloft.
IRNSS-1A is the first of seven satellites that will make up the new constellation: four satellites in geosynchronous orbits inclined at 29 degrees, with three more in geostationary orbit. IRNSS-1A is one of the geosynchronous satellites.
Following launch, the master control facility conducted five orbit maneuvers to position the satellite in its circular inclined geosynchronous orbit (IGSO) with an Equator crossing at 55 degrees east longitude. Reports indicate that orbit-raising maneuvers have been completed, and all the spacecraft subsystems have been evaluated and are functioning normally.
IRNSS-1A’s drift eastward from 47 degrees east longitude on July 10 was gradually slowed, and the satellite achieved its assigned inclined geosynchronous orbit, with a 55-degree East equator crossing, by July 18. The orbit inclination is 27.03 degrees.
Payloads. IRNSS-1A carries two types of payloads, navigation and ranging. The navigation payload will operate in L5 band (1176.45 MHz) and S band (2492.028 MHz), using a Rubidium atomic clock. The ranging payload consists of a C-band transponder that facilitates accurate determination of the range of the satellite. IRNSS-1A also carries corner-cube retro-reflectors for laser ranging. Its mission life is 10 years.
GLONASS Bellyflop
A Russian Proton-M rocket carrying three GLONASS navigation satellites crashed soon after liftoff on July 2 from Kazakhstan’s Baikonur cosmodrome. About 10 seconds after takeoff at 02:38 UTC, the rocket swerved, began to correct, but then veered in the opposite direction. It then flew horizontally and started to come apart with its engines in full thrust. Making an arc in the air, the rocket plummeted to Earth and exploded on impact close to another launch pad used for Proton commercial launches.
Despite the loss, GLONASS still has a full operating constellation of 24 satellites.
The crash was broadcast live across Russia. Fears of a possible toxic fuel leak immediately surfaced following the incident, but no such leak has been confirmed. The rocket was initially carrying more than 600 tons of toxic propellants. No casualties or damage to surroundings structures or the town of Baikonur have been reported.
The crashed Proton-M rocket employed a DM-03 booster, which was being used for the first time since December 2010, when another Proton-M rocket with the same booster failed to deliver another three GLONASS satellites into orbit, crashing into the Pacific Ocean 1,500 kilometers from Honolulu.
A Russian government investigation revealed that at least “three of six angular rate sensors [on the booster stage] were installed incorrectly,” to be specific, upside-down. Examination of the wreckage discovered traces of forced, incorrect installation on three sensors. Assembly-line testing at the factory failed to detect the faulty installation.
Several videos of the crash are viewable online (YouTube).First Live Broadcast of GPS CNAV Messages
By Oliver Montenbruck, Richard B. Langley, and Peter Steigenberger
Over the past several years, some users of the GPS navigation system have already benefitted from the addition of various new signals in addition to the legacy C/A- and P(Y)-code. With the introduction of the Block IIR-M satellites in 2005, a new civil signal (L2C) was transmitted on the L2 frequency, and a new signal on a new frequency (L5) was introduced as a standard signal with the Block IIF satellites beginning in 2010. These new signals provide direct access to dual-frequency observations and thus enable improved ionospheric corrections for civil, including aeronautical, users. In addition, a new Civil Navigation (CNAV) broadcast message has been defined in the GPS Interface Specifications (IS-GPS-200 and IS-GPS-705).
This message will be transmitted jointly on the L2C and L5 signals and provides a variety of useful new parameters. Compared to the legacy L1 C/A-code navigation message, the CNAV message also offers an increased flexibility concerning the type, sequence, and repeat rate of specific messages.
CNAV messages have already been broadcast over the past two years by the Michibiki (QZS-1) satellite of the Japanese Quasi-Zenith Satellite System (QZSS), which shares many aspects of the GPS signal design. In contrast to this, Block IIR-M and IIF GPS satellites have only transmitted dummy messages so far and a fully operational CNAV transmission is only foreseen once the ongoing modernization of the GPS control segment has been completed.
Triggered by various interest groups, the Global Positioning Systems Directorate has just conducted a first test campaign with live CNAV transmissions on L2C and L5 over the two-week period from June 15 to 29 (see Global Positioning System Modernized Civil Navigation (CNAV) Live-Sky Broadcast Test Plan.) It served as a first opportunity for end users and receiver manufacturers to test the decoding and use of the new messages under a wide range of different configurations.
CNAV messages have a common length of 300 data bits and are identified by a message type number that signifies their contents. The messages presently defined for GPS are summarized in Table 1. For QZSS, complementary messages have been established, which enable, among other features, a rebroadcast of GPS-specific data to QZSS users.
Table 1. Summary of CNAV message types transmitted by space vehicles (SVs). Messages marked by an asterisk were transmitted during the recent CNAV test campaign.
Message
Type
CNAV Message Title
Function/Purpose
0*
Default Default message (transmitted when no message data is available) 10*
Ephemeris 1 SV position parameters for the transmitting SV 11*
Ephemeris 2 SV position parameters for the transmitting SV 12*
Reduced Almanac Reduced almanac data packets for seven SVs 13
Clock Differential Correction SV clock differential correction parameters 14
Ephemeris Differential Correction SV ephemeris differential correction parameters 15*
Text Text (29 eight-bit ASCII characters) 30*
Clock, Iono & Group Delay SV clock correction parameters, ionospheric and group delay correction parameters (inter-signal correction parameters) 31
Clock & Reduced Almanac SV clock correction parameters, reduced almanac data packets for four SVs 32*
Clock & EOP SV clock correction parameters, Earth orientation parameters; Earth-centered, Earth-fixed to Earth-centered inertial coordinate transformation 33*
Clock & UTC SV clock correction parameters, Coordinated Universal Time parameters 34
Clock & Differential Correction SV clock correction parameters, SV clock and ephemeris differential correction parameters 35*
Clock & GGTO SV clock correction parameters, GPS to GNSS time-offset parameters 36
Clock & Text SV clock correction parameters, text (18 eight-bit ASCII characters) 37
Clock & Midi Almanac SV clock correction parameters, midi (mid-accuracy) almanac parameters Other than the legacy L1 navigation message, which adheres to a fixed order of subframes, the sequence of CNAV messages can be varied widely to provide users with an optimized set of low latency information and parameters that change infrequently. As a baseline, the two ephemeris message types 10 and 11 are combined with any of the clock-and-auxiliary data messages (types 30 through 37) to provide users with the orbit and clock data of the received satellites. With a transmission duration of 12 seconds per CNAV message on L2C, a minimum of 36 seconds is required to transfer this information to the user if no other messages are transmitted. On L5, which operates at twice the data rate, a new frame is transmitted once every 6 seconds yielding a minimum of 18 seconds for the broadcast of ephemeris and clock data.
The recent test campaign started at 18:00 GPS Time on Saturday, June 15, 2013, with the transmission of message types 10, 11, 15, and 30 on a first space vehicle (PRN24) and included PRN12 from 18:42 onwards. Other space vehicles were sequentially phased in until all active IIR-M and IIF satellites (except for the recently launched IIF-4 satellite) transmitted CNAV on the supported signals. When the test ended exactly two weeks later (June 29, 18:00 GPST), all participating satellites were transmitting a complex master frame of 15 x 4 = 60 individual messages, which was repeated once every 12 minutes (on L2C). Each minor frame comprised the two ephemeris messages and at least one clock-data message (see Table 2).
Table 2. Sequence of message types in a CNAV master frame.
Message Types
10
11
15
30
10
11
32
33
10
11
12
35
10
11
12
30
10
11
12
33
10
11
12
35
10
11
12
30
10
11
32
33
10
11
15
35
10
11
32
30
10
11
12
33
10
11
12
35
10
11
12
30
10
11
12
33
10
11
12
35
Other messages included a reduced almanac (message type 12) and a text message (message type 15) with dummy content (“THIS IS A GPS TEST MESSAGE.”)
The CNAV data were recorded by selected multi-GNSS monitoring stations of the German Aerospace Establishment (Deutsches Zentrum für Luft- und Raumfahrt or DLR) and the University of New Brunswick (UNB), which were specifically configured to record raw GPS navigation frames in addition to the normal observation data. The stations are located at Singapore (SIN0); Sydney, Australia (UNX2); Maui, U.S.A. (MAO0); and Hartebeesthoek, South Africa (HRAG); as well as Fredericton, Canada (UNB) and are equipped with either Javad Delta-G2/G3TH or NovAtel OEM6 receivers. Following initial validation, the raw and decoded data from the CNAV test will be made available to interested users through the Multi-GNSS Experiment (MGEX) of the International GNSS Service (see http:/igs.org/mgex/) to facilitate the development of user software and suitable data formats (such as an extended RINEX navigation message format).
The CNAV orbit and clock data were updated once every two hours and offer a slightly higher bit resolution than their legacy counterparts. However, the accuracy of the ephemeris data has not yet been evaluated nor compared to that of the L1 C/A-code navigation data.
As indicated above, the CNAV data can also provide a particularly compact form of almanac data known as the reduced almanac. It does not offer clock information (that is not normally required for a signal search) and assumes a circular orbit, which reduces the overall accuracy. Still, it can be transmitted (and repeated) in a much shorter time interval than the legacy almanac, which requires a total of 12.5 minutes. Each reduced almanac message (message type 12) provides orbit information for a total of seven satellites and it takes a set of five such messages to convey information for a complete constellation. For the master frame layout described above, the full constellation reduced almanac is repeated twice within 12 minutes on L2C (and half this time on L5).
Novel types of CNAV data not covered by the legacy navigation message include the differential code biases (also known as inter-system corrections or ISCs), which are required for pseudorange-based positioning with signals other than the legacy P(Y)-code (in addition to the established Timing Group Delay parameter or TGD). An overview of TGD and ISC values broadcast by the various satellites participating in the CNAV test is given in Table 3.
Table 3. Differential code biases (in nanoseconds) of GPS Block IIR-M and IIF satellites broadcast during the test campaign as part of the message type 30 CNAV messages.
SV Type
SVN
PRN
TGO
ISC L1CA
ISC L2C
ISC L5I5
ISC L5Q5
IIR-M
48
07
-10.71
-0.84
6.52
IIR-M
50
05
-10.24
-0.32
5.41
IIR-M
52
31
-13.04
-0.55
7.36
IIR-M
53
17
-10.24
-0.84
6.17
IIR-M
55
15
-10.24
-0.47
5.62
IIR-M
57
29
-9.31
-0.76
5.06
IIR-M
58
12
-12.11
-0.76
6.64
IIF
62
25
5.59
-2.07
-5.24
-0.38
-0.87
IIF
63
01
8.38
-2.30
-7.57
0.38
2.15
IIF
65
24
2.79
-0.26
-2.27
2.27
3.70
Another important achievement is the provision of Earth orientation parameters (EOP) in message 32, which provides GPS users with access to the celestial reference frame. EOPs were transmitted during the second test week and updated on a daily basis (see Table 4). Knowledge of these parameters is of particular interest for GPS-based orbit determination and navigation of spacecraft (in low Earth orbit), which is preferably referred to an inertial rather than an Earth-fixed coordinate system.
Table 4. Daily Earth orientation parameters from the CNAV test campaign (pole coordinates and dUT1 (UT1-UTC) time differences and derivatives).
Epoch (GPST)
x_p
(arcseconds)
x_p_dot
(arcseconds per day)
y_p
(arcseconds)
y_p_dot
(arcseconds per day)
dUT1
(seconds)
dUT1_dot
(seconds per day)
June 22, 0:00
0.13517
0.00104
0.39657
-0.00054
0.06341
-0.00046
June 23, 0:00
0.13621
0.00102
0.39604
-0.00056
0.06295
-0.00049
June 24, 0:00
0.13740
0.00101
0.39535
-0.00058
0.06231
-0.00053
June 25, 0:00
0.13815
0.00099
0.39487
-0.00060
0.06164
-0.00063
June 26, 0:00
0.13846
0.00096
0.39443
-0.00062
0.06078
-0.00067
June 27, 0:00
0.13885
0.00094
0.39381
-0.00064
0.06004
-0.00067
June 28, 0:00
0.13947
0.00093
0.39310
-0.00066
0.05909
-0.00063
June 29, 0:00
0.13987
0.00090
0.39246
-0.00068
0.05842
-0.00053
Overall, CNAV offers exciting prospects for improved GPS utilization and users may look forward to the next test campaigns, which will tentatively be conducted once every six months.
As a side note, it should be mentioned that individual satellites could be observed to transmit various types of non-standard CNAV messages as well as CNAV messages with improper data (such as an invalid week count) after the end of the main test campaign. Various receivers in the MGEX network, which were processing the received CNAV messages internally and which put full confidence in their proper contents, were mislead by such information. During the actual test campaign, all data appeared fully valid and no problems were reported by the stations.
OLIVER MONTENBRUCK is the head of the GNSS Technology and Navigation Group at DLR’s German Space Operations Center in Oberpfaffenhofen, Germany.
RICHARD B. LANGLEY is a professor in the Department of Geodesy and Geomatics Engineering at the University of New Brunswick, Fredericton, New Brunswick, Canada.
PETER STEIGENBERGER is a staff member in the Institut für Astronomische und Physikalische Geodäsie of the Technische Universität München (TUM) in Munich, Germany.
-
The Business & Product Showcase — August 2013
The Business section and the Product Showcase from the August 2013 issue (Download the PDF).
-
Automatic Threat Assessment: Tracking System Tells Friend from Foe
INTRUSION SENSORS strive to have a high detection rate and low false alarm rate. By Eric Olson and Steven Pisciotta
Ongoing threats from terrorist activities at critical facilities require early detection before the threats can reach their target and complete their mission. This has produced the need for advanced security systems to effectively detect terrorist activity, while reducing alarms caused by normal friendly activity. Automatic Threat Assessment, also referred to as Identify Friend or Foe (IFF), is the ability to automatically acknowledge alarms created by friendly assets. It can be achieved with a security system that uses GPS and geospatial data to go beyond the typical intrusion-sensor-only configuration.
The addition of a tracking system associated with friendly vehicles and personnel can provide the missing information necessary to tighten security and reduce the need to take action on alarms caused by friendly targets, and reduce the material and personnel cost of threat assessment. Tracking systems and intrusion sensors can worktogether to automatically classify an actual intruder with high confidence and without operator intervention.
The Verification Problem
Typical intrusion sensors include intelligent fences, ground proximity sensors, radar, LIDAR, and video analytics. The role of the intrusion sensor is to identify a breach and notify security personnel so they may perform verification. Table 1 shows the formal alarm types received from intrusion sensors, which strive for a high detection rate and a low false-alarm rate. For this reason, the nuisance alarm can be problematic as it reflects a real event for the intrusion sensor, but often a non-event for the security operator.
These typical sensors only provide a “suspected intruder” list. The follow-on task is to decide whether or not to reclassify a suspected intruder as an actual intruder. This process is typically a manual task and can be difficult, confusing, and time-consuming.
For instance, a landscape crew will trigger alarms. Even for very accurate systems that can uniquely track the object over a long period, it is highly likely that over the period of time the landscapers are in the area, the track will be lost, causing the system to re-alarm on the same person or vehicle, as it represents a potential intrusion.
If the landscaping crew needs to open a gate, and that gate is integrated into the facility’s access control system via a dry contact or beam breaker device, it may continuously alarm while left open, or at a minimum, in the case of the beam, each time one of the workers or the vehicle passes through the entrance. In these situations, security will either need to validate each alarm by verifying it on a camera or having an officer follow the landscaping crew throughout their route.
The existence of a friendly alarm event that needs continual validation can lead to compacency of security personnel, either not verifying it, or not verifying it in a timely manner.
Table 1. Alarm types. Combined Detection, Location
A GPS tracking system combined with the intrusion sensors can help identify friends. Tracking systems consist of two main types of locating devices: GPS-enabled devices and wireless transponders.
Modern, low-cost GPS receivers can achieve an accuracy rating of less than 3 meters, provide an update once per second, and do not require visibility to the open sky. Wireless communication transmits the GPS data to the C2 system. A typical data set includes time, date, latitude, longitude, altitude, heading, speed, and quality of GPS signal.
The combination of intrusion sensors and tracking systems can produce automatic threat assessment. Routine situations requiring significant security involvement, such as the landscaping scenario, can be automatically managed by the system. The command and control system has the ability to know friendly targets and their location.
Further, the system can perform a check before actually alarming. In the case of a perimeter alarm, it now has the intelligence to understand, within a level of confidence, that the object detected by the intrusion sensors is the same friendly item being tracking by the tracking system. If the system determines the targets to be the same object, the alarm can be suppressed, eliminating the need for security to verify the event.
THE COMBINATION of intrusion sensors and a tracking system allows for Automatic Threat Detection. Common Operating Picture
The integration of these types of systems is not complex in terms of how to coordinate data. Interface documents exist for these types of integration and are done on a regular basis. Typical position and target information is communicated over XML in a standard format. However, to gain these benefits, the tracking systems and intrusion sensors must all work within a common geospatial operating picture.
Advantages of geospatial or geo-referenced systems systems include the ability to easily display and control data in a map-based format, allowing tracking systems and intrusion sensors to synergistically perform automatic verification. This combined knowledge of the target’s track also allows the fusing of the GPS data and the intrusion sensor data into a single object and path, aiding security by reducing target and track clutter on his command and control or PSIM (perimeter security information system).
Take for example a guard enabled with a tracking device, performing a tour around a fence protected by video analytics enabled cameras. On a typical PSIM, a normal guard tour would result in two icons on the display, one friendly from the tracking system and one unknown from the video analytics. This scenario would also result in two similar object tracks. Security would need to review the situation and understand that this symbology represents a single target and a single track.
Integrating the tracking system with the video analytics system allows for a fusing of this data, and the resulting command-and-control symbology is a single target and a single track.
Other considerations when combining a tracking system with intrusion sensors include update rate, time and location accuracies, and overlapping coverage.
Ideally, all sensors would be synchronized when it comes to timing aspects, but this is typically not the case. Different timing between data updates and time inaccuracies can result in the inability for the systems to confidently conclude that two tracks were created by the same target. Transport delay, the transmission of the GPS data through the satellite, can also be an issue. For tracking devices, it’s vital for the data to be received by the C2 system with a repeatable transport delay. Variability in the transport delay also decreases the ability to automatically verify the threat.
Geographic accuracy of both the GPS tracker and the intrusion sensor is another important factor in data fusion. Typical GPS trackers have an accuracy rating of 3–10 meters. Actual accuracy varies based upon the visible GPS satellites, tall buildings, body worn, and RF interference. Intrusion sensors also possess an inherent accuracy. Radar surveillance may have a resolution of 1 x 1 meter at close range, but it expands at far range to 1 x 20 meters.
Intelligent fence sensors and video analytic systems can have resolutions that vary from 1 to 25 meters, based on the type of sensor and the terrain. These geographic inaccuracies can be handled to some degree by considering other factors, including heading, speed, and previous track, but it’s important to understand where these inaccuracies can occur.
Overlapping coverage of surveillance sensors also affects data fusion. In the case of track fusion, this ability is only available is areas where both a geospatial intrusion sensor exists and a tracking system is operational. If there are gaps in overlapping coverage, or areas that do not include geospatial- based intrusion sensors, then fusion is not possible in those regions.
Eric Olson is vice president of Marketing at PureTech Systems.
Steven Pisciotta is president of Remote Tracking Systems.
-
Trimble Offers Software Data Integration for Construction Project Management
Trimble is offering data integration capabilities between a variety of its planning, estimating and management software applications. The new capabilities are designed to boost the ease, accuracy and transparency of conceptual or detailed time- and cost-modeling estimates for general contractors and capital construction project owners.
At their core, the five new software versions within the Trimble Buildings’ Design-Build-Operate (DBO) portfolio provide a synchronized way to plan, track, and capture cost and work parameters before, during and after construction projects.
The new software versions include:
WinEst 15.0: database-driven software that uses a highly flexible spreadsheet for creating, adjusting and presenting cost estimates.
Modelogix 3.2: software for collecting and analyzing past-project data and generating comprehensive cost models for future projects.
Prolog 9.6.1: project-management and cost-control software for general contractors (GCs) and construction managers, streamlining project workflows and providing access to information from anywhere.
Proliance 5.5: Office Application Pack – Microsoft Office extensions for Proliance software, combining capital planning and program and project management capabilities.
Vico Office 4.2: virtual construction software, augmenting 3D models with constructability analysis and coordination, location-based quantity takeoff, 4D (time) scheduling and production control, and 5D (cost) estimating.“With cost and productivity pressures facing the construction industry today, the ability to generate accurate estimates is vital — as is the need to integrate 3D models to time and cost,” said Mark Sawyer, general manager of Trimble Buildings’ General Contractor Division. “The updates to a variety of the core solutions in our DBO portfolio can help keep projects on track, on schedule, and within budget.”
At the earliest planning stage, when an owner proposes a new project and asks for a feasibility budget, the GC can use Modelogix to create a new project, and then push the cost model from Modelogix to WinEst to create a detailed estimate. Once the GC has been awarded the project, the WinEst estimate can be moved to Prolog as the official project budget for tracking and reconciliation of costs throughout the project lifecycle. At the project’s close, the reconciled budget can be sent back to Modelogix so that completed project data can be used to generate accurate parameter-driven cost models for future projects of similar scope. This “integrated cycle” can repeat with increasing accuracy over time and across projects as more types of estimates and budgets are created.
For building owners, the new Office Application Pack in Proliance software delivers similar benefits. Integration enables owners to develop detailed budget estimates directly from WinEst or conceptual budget estimates from Modelogix. Proliance also provides a new contingency-analysis tool, which uses statistical methods for recommending contingency amounts, based on the project risk profile represented in the Modelogix cost model. This structure provides a powerful way for project and building owners to build a library of detailed and conceptual estimates across a broad project portfolio.
For GCs and construction management firms working on building information modeling (BIM) projects, new integration between Vico Office 4.2 and Tekla Structures BIM software also improves project accuracy, with Vico Office 4.2 able to address the unique requirements of models generated in Tekla Structures.
With an increasing number of GCs using their own labor force to work with concrete or steel, the new Tekla model activation options in Vico Office 4.2 offer precisely tuned, location-based quantity takeoffs to improve the accuracy of scheduling and estimating created from today’s increasingly large and complex models. Tekla Structures users can also take advantage of Tekla’s Model Organizer to label model content so it is seamlessly registered as an element type (e.g., walls, slabs, beam profiles, rectangular columns, stairs, etc.) within Vico Office. These element types have specific quantity-calculation parameters, which help drive more precise quantity takeoffs.
“Tekla Structures provides enormous benefits as a modeling platform for GCs and Engineers. Our goal with the new publisher in Vico Office is to harness modeling specificity for construction-caliber quantity takeoffs, which in turn power estimates and schedules,” said Jon Fingland, business unit director of Trimble Buildings’ General Contractor Division. “This improved workflow from Trimble Buildings is yet one more way we are delivering critical project data when and where our customers need it.”
The new versions of WinEst, Modelogix, Prolog, Proliance and Vico Office are available now. Additional information on WinEst, Modelogix, Prolog, Proliance are available at www.meridiansystems.com. Information on Vico Office can be found at www.vicosoftware.com.
-
SeeControl Announces ThingTracr GPS Tracking Tool
Source: SeeControl SeeControl is announcing the roll out of ThingTracr, a hosted SaaS GPS tool for monitoring anything that needs to be tracked. The simple-to-use solution offers precise location tracking and historical analytics reporting for things of interest using a small and attachable GPS unit that requires no tools or wiring. The tracking service can be up and running in less than five minutes.
Using web browsers or mobile devices, a user can easily monitor the status of the tracked asset. It can be used for cars, trucks, trailers, packages, site equipment or anything else.
“There are several unique features that set ThingTracr apart from other tracking services,” said Bryan Kester, CEO of SeeControl. “One is a modifiable modern dashboard that allows users to personalize how they view the tracking information in the most convenient way for them. Another is the ability to upgrade and expand to new GPS trackers globally as they come on the market.”
Other features of ThingTracr include:
- 90-day location history
- User customizable dashboards
- Low battery alarms
- Satellite / hybrid map views
- Multiple reports
- Data export – CSV/ PDF
- Trip Reports
- Range of pre-certified hardware
- Trip replays on maps
ThingTracr uses various battery-powered GPS devices, which can also notify users of several alarms including motion detected, speeding, and information regarding battery life.
The ThingTracr GPS tracking tool is just one of many vertical solutions available from SeeControl M2M ( Machine 2 Machine ) cloud platform. The ThingTracr solution is available through SeeControl partners including M2M distributors, Network Operators and Systems Integrators.
-
Russian Officials Concerned over Reduced GLONASS Funding
Plans to reduce funding for GLONASS is causing concern among deputies of the State Duma. The government officials predict a loss of trust in the world by the Russian navigation system, according to a July 29 Roscosmos article.
Reduced funding of GLONASS will lead to a reduction of the orbital grouping system below acceptable levels, according to the first deputy chairman of the Committee on Industry, Vladimir Gutenev. The U.S. GPS system is functioning and both Europe and China are developing systems, Galileo and COMPASS respectively. This will “lead to the loss of confidence of the international community in the GLONASS system and, consequently, to a reduction in its use globally. Russia will lose a strategic global instrument of political and economic prestige,” Gutenev warned.
The proposal is to reduce budget funding of the state space program in 2014 by 11.7 billion rubles, in 2015 by 13.5 billion rubles, and in 2016 by 40 billion rubles, according to the ITAR-TASS news agency. In addition, the federal space program of Russia for 2006-2015 already lacks 10.5 billion rubles funding, and this year there has been a 2.3-billion-ruble additional reduction in R&D.The funding was in part intended to build and put into operation phase 1 of the Vostochny booster side building, which would use the Soyuz-2 space rocket system.
The State Duma, according to the ITAR-TASS news agency, has recommended that the government of the Russian Federation maintains funding of federal programs on space matters in the amount provided by an approved state program.