Launch, deploy, and operate “22 satellites in less than 3 years.” That’s two satellites every three months, leading to a four-at-once launch in 2014. And that’s the challenge that Europe and the European Space Agency (ESA) now face.

This pointed call to action during the opening plenary of the European Navigation Conference (ENC) came from Didier Faivre, director of Galileo Programme and Navigation Related Activities at ESA. It was the only somber note sounded during the keynote speeches, which otherwise paraded the stirring recent accomplishments of the Galileo In-Orbit Validation (IOV) phase. IOV now concludes, and Galileo’s operational phase opens.

The ENC takes place in Vienna, Austria this week (April 23–25), hosted by the Austrian Institute of Navigation. Privately and informally, a handful of knowledgeable conference attendees expressed confidence that OHB System can furnish the completed satellites, at least, according to schedule. OHB System is the prime contractor for  construction of 22 Full Operational Capability (FOC) Galileo satellites and is responsible for developing the satellite bus and for integrating the satellites. Surrey Satellite Technology Ltd. (SSTL) is developing and constructing the navigation payload and  assisting OHB with final satellite assembly.

“Using only European tools and means, European ground infrastructure deployed on European territory, our conception, machine and design, is totally validated,” stated Faivre, referring to the recent Galileo-only positioning fix by ESA. The March 12, 2013, event marks “the end of the beginning,” and culminates 12 years of intense work at all levels of European industry.

“Europe is at par with GPS” with performance as expected. “I hope that soon our U.S. colleagues will be jealous of our performance,” Faivre stated, implying yet again the persistent Galileo claim that the system will be more accurate than GPS. He returned to this theme with reference to Fugro’s accomplishment of real-time precise point positioning at the centimeter level.

He acknowledged that “It’s a technological competition with the United States, Russia, and China,” even though all may be friendly and collegial.

In that competitive light, “the success of Galileo will be measured by the number of users,” and not by the number of satellites, or the degree of accuracy, or the strength of the signal.

Previously, the ENC audience had heard from Ingolf Schädler that “Europe has closed the gap with the technological superpowers,” in what “may be the most complex invention ever of mankind, the system of navigation that is GNSS.” He also made a proud reference to Austrian-produced signal generators aboard Galileo’s orbiting IOV satellites. Schädler is the deputy director general of innovation for the Austrian federal Ministry for Transport, Innovation and Technology.

“We have reached cruising speed,” announced the third keynote speaker, Carlo des Dorides of the European GNSS Agency (GSA). He was referring explicitly to the re-positioning of the GSA headquarters from Brussels to Prague, but the remarks reverberated to the Galileo program as a whole.

David Blanchard, deputy head of unit, EU Satellite Navigation Programmes for the European Commission, quoted an unnamed U.S. publication: “With the capability to make a position fix from four signal-broadcasting satellites, we can now say that Galileo has truly arrived.”

That statement appeared in the May 2013 GPS World, an issue of the magazine that was distributed in conference bags to all attendees at the ENC.

Blanchard then shifted the focus slightly from Galileo, to Galileo together with the European Geostationary Navigation Overlay Service (EGNOS), Europe’s satellite-based augmentation service that also broadcasts GPS corrections. “We have to make sure that all the capabilities afforded by EGNOS are realized.” He also made strong references to the EGNOS Data Access Service (EDAS).

Blanchard cited a current ongoing study that shows that 6 to 7 percent of European gross domestic product (GDP) is dependent upon GNSS.

“A gold mine within arm’s reach of European industry” was how Gard Ueland, head of Galileo Services, characterized the present situation. “Development of European downstream market is crucial; it also has to bring more benefits to European society.” Galileo Services will host a workshop of  industry stakeholders in late October, at the OHB System premises in Bremen, Germany. Watch GPS World Events calendar and news for an announcement with specific dates.

Having attained altitude and cruising speed, the Galileo program must now shift to warp speed to hit its goals on time: 18 satellites in orbit by the end of 2014, and a total of 26 by the end of 2015. Early services by the end of 2014, and full services in 2016. Stable, continuous services, as Blanchard emphasized.

Better go to overdrive.

That’s been one of the mantras — a controversial one, granted — of technological advance in the late 20th and early 21st centuries. It has succeeded in penetrating the global positioning, navigation, and timing vanguard, as evidenced by a handful of key presentations on the first day of the Institute of Navigation (ION) International Technical Meeting in San Diego on Monday.

Skybox Imaging, a company that is “passionate about bringing Moore’s Law to space via disruptive microsatellite technology, rapid development cycles, and a scalable web-based delivery platform,” spoke to the ION ITM plenary session in the person of Ronny Votel, an engineer leading the company’s guidance, navigation and control division. Skybox’s goal is to provide “easy access to reliable and frequent high-resolution images . . . through a “constellation of imaging microsatellites delivering high-resolution imagery of any spot on Earth multiple times per day.”

To achieve that goal, Skybox is developing a low-cost imaging satellite system:

• design life of the satellites, 3 years;
• size of the satellites, a mini-fridge;
• size of the constellation, in the tens.

Skybox will pair that flying system with web-accessible big data processing platform to capture video or images of any location on Earth within a couple of days — an unheard of delivery turnaround in the current global imaging industry, unless you happen to be a government (as in central, high, federal, perhaps military) customer.

The low-cost nature of the satellite opens the possibility of deploying tens of satellites which, when integrated together, have the potential to image any spot on Earth within an hour. Votel several times made the analogy in his talk of using an iPhone camera to capture desired imagery, and indeed that could be a next logical step in FBC development: just throw a bunch of camera phones up into orbit.

Skybox expects to launch its first two satellites later this year.

In April of last year, Wired published a fascinating history and analysis: “Smaller, Quicker, Secret, Robotic: Inside America’s New Space Force.” Between Between 1992 and 1999, the U.S. National Aeronautics and Space Administration (NASA) launched 16 faster, smaller, cheaper missions, including Mars probes and space telescopes. Ten missions succeeded; six failed. Analysts declared the initiative a failure, and to a large extent it has been forsaken. Recent public writings, though, show second thinking. “I would like to respectfully suggest that success-per-dollar is a more meaningful measurement of achievement than success per-attempt,” stated one Air Force lieutenant colonel in a treatise on program management lessons from NASA.

Could such an approach work for GNSS satellites, some of which are burdened with extraneous non-PNT payloads that make them far from FSC? Time will tell the wiser.

Microtechnology

In that FSC vein, at one of the afternoon’s technical sessions, Andrei Shkel of UC-Irvine had been scheduled to deliver a paper on “Precision Navigation and Timing Enabled by Microtechnology,” but apparently something came up and he was not able to appear. I had looked forward very much to what I anticipated would be an update to his September 2011 article in GPS World, “Microtechnology Comes of Age,” which was itself an update to a plenary talk he gave at ION ITM back in 2011. For now, that article will have satisfy us.

Other presentations in the same MEMS, atomic clock, and MicroPNT session:

Michael Bulatowicz of Northrop Grumman talked about a DARPA-backed project, the nuclear magnetic resonance (NMR) gyroscope. Northrop’s development and research has shown a viable solution to producing a small (size of a U.S. quarter coin) low-power navigation grade gyro using non-vibratory technology. The company has produced two prototypes and is at work on two more. Feed the NMR gyro into Shkel’s work and who knows what you’ll get in terms of FBC PNT? Well, maybe not cheaper in the immediate future. Bulatowicz said that as an assembled device he expected its cost, at least initially, to be substantially higher than MEMS technology.

Richard Waters of Lumedyne Technologies spoke on next-generation MEMS inertial sensors with white-noise characteristics, a new paradigm based on time-domain switching for how MEMS sensors might work. TDS inertial sensors provide some key benefits: a purely digital approach, recalibration due to bias drift is not required, output is independent of oscillator conditions. Power is low, less than 1 millwatt. The device demonstrated switch stability under static conditions to –170 db. The same TDS concept can also be applied to a mechanical gyro.

QZSS

In other ION ITM first-day news, H. Tokura of the Tokyo University of Marine Science and Technology talked about “The Possibility of Precise Automobile Navigatin using GPS/QZS and Galileo E5 Pseudoranges.” Currently, research and prototype automobile high-precision PNT is done with real-time kinematic (RTK) networks, but this has some disadvantages, as discussed in an article by authors from the University of Nottingham, UK, in the February issue of GPS World.

Japan’s QZSS now broadcasts L5 signals. Japan has essentially leapfrogged the United States, since the L5 signals with full CNAV message is already broadcast by satellite QZSS-1. Currently, three U.S. GPS satellites are L5 CNAV-capable, but none are broadcasting such a signal.

Tokura showed results demonstrating that pseudorange observables from L5 are basically robust enough for this task. Further investigation for L5 is required because manufacturers are still developing the tracing technique for the new L5 signal. A software-defined receiver is indicated for usage.

Hideki Yamada of Japan’s Electronic Navigation Research Institute spoke about the possibility of using only the QZSS constellation, “in case of GPS failure,” for RTK positioning in precision ag and machine control, with 4 to 7 QZSS satellites that could be launched in a future version of the constellation. QZSS has been shown to provide 10-meter accuracy in absence of GPS; now the research looks at an RTK method.

With only one satellite in orbit, RTK-QZSS cannot be tested in the field. The researchers simulated a fuller constellation by using QZS-1, Multifunctional Transport Satellites (MTSAT), a set of geostationary weather and aviation control satellites, and GPS signals. Using a JAVAD Alpha receiver, Trimble and NovAtel antennas, they obtained results with low multipath error (about 30 centimeters) in a Tokyo environment. Multi-epoch processing is necessary for RTK-QZSS. This solution can work well as a minimum backup system of high-precision position under relatively moderate DOP condition.

__________________

Living may be easy, dying may be hard. But I’m wide awake, staying up late, sending my regards.

To play fair, do not use Google or any other research, reference, or resource. Dinner guests were honor-bound not to employ their smartphones — just their smarts. You are, too.

The first six questions had known answers (at least to the gamesmasters) at the time of the dinner. The final three peered into the future, as of that evening. Two of them have since been determined. Once the Galileo question is settled, the What Do You Know Grand Winners — 10 individuals who sat and gamed together among the 21 competing tables — will be announced, and suitable tchotchkes distributed.

A special division for online contestants has been established; send your answers to editor@gpsworld.com. Any entries that are too suspiciously close to the true answers will be disqualified for use of unauthorized resources.

The accounting and awarding — and all the answers — will appear on the Wide Awake Blog in the very near future. Do not touch that dial.

Game Rules

1. What Do You Know? What’s Your CEP? consists of nine quantitative questions. Answer each question as best you can — without the aid of outside sources! Then give your error range: an upper bound and a lower bound.

Answers will be graded on how close they are to the true answer, the size of the error range given, and whether that error range encompasses the true answer. The smaller your error range, the higher your potential score — but if the true answer falls outside your error range, you score zero for that question.

2. The second and third rules pertained to “play by tables” at the dinner, and are irrelevant and thus omitted here.

4. A final trifecta of three questions asks you to predict events in the future.  After turning in your answers to these questions, game play concludes for the evening. A final Grand Prize to the winning table will be awarded after the last event.

A more detailed mathematical explanation of the scoring process is available at the scorer’s table, should you wish to see it.

And now, are you ready to play . . . .

What Do You Know??!!??!!  What’s Your CEP??!!??

1.  Estimate the distance in kilometers from Shanghai, China, to Nashville, Tennessee, along a Great Circle global route, and from that derive the number of Delta II booster rockets (used to launch GPS satellites) laid end-to-end that would cover that distance.

Upper bound  ______________

Absolute answer _________ 

Lower bound  ______________

­­­

2. Give the total area, in either square inches or square centimeters (specify which you are giving) of a rather substantial hat worn by Kate Middleton, Duchess of Cambridge, to a friend’s wedding in July of this year.

Kate Middleton

That hat!

Upper bound  ______________

Absolute answer __________ 

Lower bound  ______________

3.  Peg the number of total orbiting and operating GNSS satellites, including SBAS, as of September 20, 2012.

Upper bound  ______________

Absolute answer _____________   

Lower bound  ______________

4.  Jack Daniel’s, a sour mash whiskey made in Lynchburg, Tennessee and the best-selling whiskey in the world, is known for its square bottles and black label. How many shots of whiskey does a white-oak barrel of Jack Daniel’s contain?

Jack Daniel’s barrel in the Hermitage Hotel, Nashville

Upper bound  ______________

Absolute answer _____________   

Lower bound  ______________

5. How many of Richard Langley’s “Innovation” columns have appeared in GPS World magazine?

Upper bound  ______________

Absolute answer _____________  

Lower bound  ______________

6.  In his memoirs, Tony Blair mentions that, when he first met Queen Elizabeth II as Prime Minister of the UK, the Queen put him in his place by telling him,  “You are my tenth prime minister. The first was Winston. That was before you were born.”

In a similar vein, how many individuals have served as Prime Minister (official, not acting or deputy) of Japan from the beginning of the Shōwa era under Emperor Hirohito in 1926 until today? (Note:  This is the count of individual persons. A single person serving as Prime Minister several times, such as the postwar Prime Minister Shigeru Yoshida, counts only once.)

Upper bound  ______________

Absolute answer _____________   

Lower bound  ______________

Final Trifecta

7.  Predict the number of days that will elapse between the day of the combined launch of the Galileo IOV-3 and IOV-4 satellites and the day when the first satellite of that pair is declared operational. Dates are defined based on UTC. For example, if the launch should take place on the currently scheduled date of October 10, then October 11 would be 1 day, October 31 would be 21 days, and so on.  If the launch occurs on a different date, we start counting from there.

Upper bound  ______________

Absolute answer _____________

Lower bound  ______________

8. Predict the number of U.S. states, out of 50, that go blue in the Presidential election on November 6, 2012 — that is, their electoral votes go to President Obama’s Democratic Party ticket.

Upper bound  ______________

Absolute answer _____________

Lower bound  ______________

9.  Predict the total number of combined points scored in all three NFL football games to be played on Thanksgiving, November 22: Houston Texans vs. Detroit Lions, Dallas Cowboys vs. Washington Redskins, New England Patriots vs. New York Jets.

Upper bound  ______________

Absolute answer _____________

Lower bound  ______________

_________________________________________________________________

Sleep was what I wanted, you know what I got. Wide Awake, staying up late, wishing I was not.

The National Geodetic Survey (NGS) has issued a “Kinematic GPS Challenge” to the community in support of NGS’ airborne gravity data collection program, called Gravity for the Redefinition of the American Vertical Datum (GRAV-D). The “Challenge” is meant to provide a unique benchmarking opportunity for the kinematic GPS community by making available two flights of data from GRAV-D’s airborne program for their processing. By comparing the gravity products that are derived from a wide variety of kinematic GPS processing products, a unique quality assessment is possible.

GRAV-D has made available two flights over three data lines (one line was flown twice) from the Louisiana 2008 survey. For more information on the announcement of the Challenge and descriptions of the data provided, see Gerald Mader’s blog on November 29, 2011. The GRAV-D program routinely operates at long-baselines (up to 600 km), high altitudes (20,000 to 35,000 ft), and high speeds (up to 280 knots), a challenging data set from a GPS perspective. As of December 2011, ten groups of kinematic GPS processors have provided a total of sixteen position solutions for each flight. At two data lines per flight, this yielded 64 total position solutions. Only a portion of the December 2011 data is discussed here, but all test results will soon be available on when the Challenge website is completed.

Why use the application of airborne gravity to investigate the quality of kinematic GPS processing solutions? Because the gravity measurement itself is an acceleration, which is being recorded with a sensor on a moving platform, inside a moving aircraft, in a rotating reference frame (the Earth). The gravity results are completely reliant on our ability to calculate the motion of the aircraft— position, velocity, and acceleration. These values are used in several corrections that must be applied to the raw gravimeter measurement in order to recover a gravity value (Table 1). The corrections in Table 1 are simplified to assume that the GPS antenna and gravimeter sensor are co-located horizontally and offset vertically by a constant, known distance.

Table 1. GPS-Derived Values that are used in the Calculation of Free-Air Gravity Disturbances

All Challenge solutions are presented anonymously here, with f## designations. For each flight of data, the software that made the f01 solution is the same as for f16, f02 the same as f17, and so on.

Test #1: Are the solutions precise and accurate?

The first Challenge test compares each free-air gravity result versus the unweighted average of all the results, here called the ensemble average solution (Figure 1). This comparison highlights any GPS solutions whose gravity result is significantly different from the others, and will group together solutions that are similar to each other (precise). Precision is easy to test this way, but in order to tell which gravity results are accurate calculations of the gravity field, a “truth” solution is necessary. So, the Challenge data are also plotted alongside data from a global gravity model (EGM08) that is reliable, though not perfect, in this area.

Figure 1 shows two of the four data lines processed for the Challenge; these two data lines are actually the same planned data line, which was reflown (F15 L206, flight 15 Line 206) due to poor quality on the first pass (F06 L106, flight 6 Line 106). The 5-10 mGal amplitude spikes of medium frequency along L106 are due to turbulence experienced by the aircraft, turbulence that the GPS and gravity processing could not remove from the gravity signal.

Figure 1.

Figure 2.

Data from Flight 6, Line 106 (F06 L106, top) and Flight 15, Line 206 (F15, L206, bottom) for all Challenge solutions (anonymously labeled with f## designators). Figures 1 and 2. Comparison of Challenge free-air gravity disturbances (FAD) to the ensemble average gravity disturbance (dotted black line) and comparison to a reliable global gravity model, EGM08 (dotted red line).

Figure 3.

Figure 4.

Figures 3 and 4. Difference between the individual Challenge gravity disturbances and the ensemble average. The thin black lines mark the 2-standard deviation levels for the differences. For F15 L206, one solution (f23) was removed from the difference plot and statistics because it was an outlier. For both lines, the ensemble’s difference with EGM08 is not plotted because it is too large to fit easily on the plot.

The results of test #1 are surprising in several ways:

• The data using the PPP technique (precise point positioning, which uses no base station data) and the data using the differential technique (which uses base stations) produce equivalent gravity data results, where any differences between the methods are virtually indistinguishable.
• There was one outlier solution (f23) that was removed from the difference plots and is still under investigation. Also, on F15 L206, solution f28 had an unusually large difference from the average though it performed predictably on the other lines. Of the remaining solutions, four solutions stand out as the most different from all the others: f03/f18, f04/f19, f05/f20, and f07/f22.
• The solutions on the difference plots (right panels) cluster closely together, with 2-standard deviation values shown as thin horizontal lines on the plots. The Challenge solutions meet the precision requirements for the GRAV-D program: +/- 1 mGal for 2-standard deviations.
• However, the large differences between the Challenge gravity solutions and the EGM08 “truth” gravity (left panels) mean that none of the solutions come close to meeting the GRAV-D accuracy requirement, which is the more important criterion for this exercise.

Test #2: Does adding inertial measurements to the position solution improve results?

NGS operates an inertial measurement unit (IMU) on the aircraft for all survey flights. The IMU records the aircraft’s orientation (pitch, roll, yaw, and heading). Including the orientation information in the calculation of the position solution should yield a better position solution than GPS-only calculations, but it was not expected to be significantly better. Figure 2 shows the NGS best loosely-coupled GPS/IMU free-air gravity result versus the Challenge GPS-only results and Table 2 shows the related statistics.

Figure 5.

Figure 6.

Figures 5 and 6. F06 L105. (Figure 5) Comparison of Challenge FAD gravity solutions (ensemble=black dotted line) with EGM08 (red dotted line); (Figure 6) comparison of Challenge gravity solutions (all GPS-only; ensemble=black dotted line) with NGS’ coupled GPS/IMU gravity solution (red dotted line).

Table 2. Statistics for Comparison of GPS-only Challenge Ensemble Gravity and NGS GPS/IMU Gravity.

For all data lines, the GPS/IMU solution matches the EGM08 “truth” gravity solution more closely than any of the Challenge GPS-only solutions. In fact, the more motion that is experienced by the aircraft, the more that adding IMU information improves the solution. One conclusion from this test is that IMU data coupled with GPS data is a requirement, not optional, in order to obtain the best free-air gravity solutions.

Additional Testing and Future Research

Other testing has already been completed on the Challenge data and the results will be available on the Challenge website soon. Important results are:

• Two Challenge participants’ solutions perform better than the rest, two perform worse, and one is a low quality outlier. The reasons for these differences are still under investigation.
• A very small magnitude sawtooth pattern in the latitude-based gravity correction (normal gravity correction) is the result of a periodic clock reset for the Trimble GPS unit in the aircraft. This clock reset is uncorrected in the majority of Challenge solutions. The clock reset causes an instantaneous small change in apparent position, which results in a 1-2 mGal magnitude unreal spike in the gravity tilt correction at each epoch with a clock reset.
• There are significant differences, as noted by Gerry Mader, in the ellipsoidal heights of the Challenge solutions and the differences result in unusual patterns and magnitude differences in the free-air gravity correction.

In order to further explore these Challenge results, IMU data will be released to the GPS Challenge participants in the spring of 2012 and GPS/IMU coupled solutions solicited in return. Additionally, basic information about the Challenge participants’ software and calculation methodologies will be collected and will form the basis of the benchmarking study.

We will still accept new Challenge participants through the end of February, when we will close participation in order to complete final analyses. Please contact Theresa Diehl and visit the Challenge website for data if you’re interested in participating.

Not planned for in the sense of actually making provision for.  Seeing if there’s enough resource on hand. Calculating if the ecosystem will handle it.

No, wireless carriers and everyone else involved in this industry make money on data. So let’s make, make, make, more, more, more.

Did anyone happen to estimate the amount of bandwidth needed to upload and download all this data? Has anyone thought about what pressure it might bring on other spectrum users such as, perhaps, GNSS?

My guess is no, and no, and we don’t care. Because we are creating the future, don’t you see?!!?

From this brave new world sprang LightSquared, born of the ravenous need for more wireless data. It doesn’t take much time at the Mobile World Congress to see that venture as just the first very tentative probe. Armies are massed at our borders.

I didn’t get to location as a blue-chip commodity, as promised yesterday. That will have to come tomorrow.

There’s a whole lot of change coming for North America and European users, too, and much of that is being envisioned, enthusiastically promulgated, and occasionally even demonstrated at this global village of 60,000 modcom movers and shakers that congregate here every year.  Just a few examples:

• granting access to one’s location data for only a set period, from 15 minutes to 4 hours, via Glympse.
• location-based display advertising, not just coupons, but glossy little ads on your screen, called up by proximity to the advertiser, via Sofialys.
• centimeter-accurate indoor navigation, to the product on the shelf and not to its competitor product next to it on the same shelf, via Wi-Fi and near-field communication (NFC), Broadcom again but others including LocAid are talking about it too.
• An alarm clock function on your phone that will wake you (or let you sleep) at exactly the right time for that morning, based on real-time traffic and weather conditions on your commute route, from Airbiquity.

All this with either a few deft touches of the smartphone screen, or automatically enabled.

And this is just the location aspect of smartphones, which represents maybe 5 percent of what’s being talked about here.  Tons of other apps for health and entertainment and more.

Tomorrow: location as a blue-chip commodity.

Question One. The greatest challenge to realizing new technical capabilities is:

A.   staying ahead of the competition.  4.3% voted for this one.
B.   funding.  34%
C.   meeting expectations of the consumer (user).  34%
D.   establishing standards.  8.5%
E.   overcoming opposition (policy, privacy, regulations, etc..).   19.1%

Few surprises here. The biggest problems are always getting hands on the money to make a product, and then getting someone to buy the product.  The latter, of course, by making the product enough of a value proposition for the discerning prospect to buy.

Question Two. The predominate source of technical vision/innovation is:
A.     Governments.   1.7%
B.     Industry on its own.   53.3%
C.     Industry responding to government requirements.   28.3%
D.     Academia.   16.7%

Most of you out there believe you know what you are doing and are best left to yourselves to do it. Good on ya.

By the way, all the questions here were devised by Doug Taggart, president of Overlook Systems Technologies, Inc., and moderator of the plenary session at the Institute of Navigation’s (ION’s) International Technical Meeting. The ION ITM plenary took place three hours before our webinar, and audience members voted on these same questions. We then adjourned to a hotel room at the conference site and essentially re-presented a portion of the webinar content, interspersed with the polling questions.

The full 60-minute webinar, with presentations by Jules McNeff, VP Strategy and Programs, Overlook Systems Technologies, Inc., and Chuck Schue, president and CEO of UrsaNav, is available for download and replay at www.gpsworld.com/webinar (scroll down).

Question Three. Successful innovation is most dependent on:
A.     technology revolution.   11.5%
B.     technology evolution.   39.3%
C.     market demand.   34.4%
D.      project management.   6.6%
E.      funding.   8.2%

The free-market Keynesians out there are exceeded (in numbers) only by the techno visionaries, who believe that technology itself is a live organism, evolving and developing under its own impetus (perhaps aided or driven in part by market demand). Unless I’m putting words into someone’s mouth.

Question Four. Should innovative military capabilities be made available for civil/commercial exploitation?
A.      Yes, always.  The commercial spin-off value is far greater.  31.3%
B.      Sometimes.  When military capability is not compromised.   68.7%
C.      No.  Military capabilities are for military use only.  Every advantage must be protected.   0%

“Sometimes” is always a safe answer. But a coalition of free-marketers and techno visionaries made a surprisingly strong showing, garnering nearly one-third of the votes on an unequivocal up-down issue. This pushback should not be ignored by those in power.

Question Five. GPS will continue to be the world’s space-based PNT “Gold Standard”:
A.    for the next 20 years.   50%
B.    until Europe’s Galileo system is declared operational.   20.8%
C.    until China’s Compass system is declared operational.   14.6%
D.    until Glonass incorporates L1C.   8.3%
E.    it is not the Gold Standard today.   6.2%

At first glance, one might find few worries here for those who design new products with GPS uppermost or even solely in mind. On the other hand, if you combine the four non-GPS gold standard answers, you get a separate but equal body politic.

Mind you, the other 50% are not saying that any other system will surpass GPS and become a new gold standard. The question does not ask that. But it does leave the door open for anyone to conclude that there may not be a gold standard at all at some point in the future — that all or at least a plurality of systems will be equally capable, or that an interoperable, interchangeable GNSS will surpass any single system component.

Question Six. From a user perspective, what is the most concerning aspect of having access to PNT information derived from GNSS?
A.    It is susceptible to interference.   58%
B.    Without augmentation, it does not meet my needs.   26%
C.    It is overshadowing the need for complementary systems that do not have similar shortcomings.   8%
D.    No concerns.   8%

Interference is on nearly everyone’s mind. In fact, those who voted the B or C ticket can also be inferred to be driven by interference concerns, they are just taking their concern a step further by envisioning a solution. Chuck Shue’s webinar presentation (see above link) on e-Loran should be of interest to everyone here except the bottom 8.

Question Seven. Regarding GNSS systems, which is more important to design and field first?
A.      The Space segment (satellites).   21.4%
B.      The Ground Control Segment.   23.2%
C.      The User Equipment.   1.8%
D.      All are equally important, and should be fielded simultaneously.   53.6%

I feel this result is of little use to anyone except the U.S. Air Force, the European Space Agency, Roscosmos, and the China National Space Administration. And I’m pretty sure they all knew it already.

Question Eight. How does a country gain and maintain GNSS superiority?
A.      Create technological advantage (better mouse trap).   25%
B.      Create political/policy advantage (better playing field).   11.5%
C.      Create fiscal advantage (better funding).   36.5%
D.      Create public/private partnerships (better risk mitigation).   26.9%

A majority, but not a thumping one, opts for money.  Another safe vote in almost any circumstance.

David Last, another panel speaker at the morning’s plenary, made a cogent comment when this question was presented. He could understand, he said, how a country might want to gain and maintain military superiority. That’s a question of survival. But GNSS superiority? In this age of interoperability, surely that’s beside the point.

Well, we’ve tossed our chaff into the wind to see which way it blows. Now we must all put our heads down and our shoulders to the wheel, pushing on to Election ’12, coming up  November 4.

But there’s an earlier Election ’12 that takes place September 20: the return showdown between the Satellite Party and the Signal Party. The Reds and the Blues. They last contested, you may or may not remember, in the previous election year, 2008; Put to a Vote, GPS World’s Leadership Dinner — held during ION-GNSS 2008 in Savannah, Georgia — convoked a lively debate: Would the community gain more from new signals, or from more satellites? A made-up scenario that elicited important insights.

The Satellite Party has been in power since its ’08 victory. Are you better off now than you were four years ago? We will return to the hustings in Nashville during ION-GNSS, as again GPS World hosts GNSS Election ’12.

Given the current tenor of debates around the country and around the world, I have a feeling we’ll be hearing from the Occupy GPS movement as well as the two frontrunners.

Nearly half of all highway fatalities occur from unintended lane departures, which comprise approximately 20,000 deaths annually in the United States.  Studies have shown great promise in reducing unintended lane departures by alerting the driver when they are drifting out of the lane. At the core of these systems is a lane detection method typically based around the use of a vision sensor, such as a lidar (light detection and ranging) or a camera, which attempts to detect the lane markings and determine the position of the vehicle in the lane. Lidar-based lane detection attempts to detect the lane markings based on an increase in reflectivity of the lane markings when compared to the road surface reflectivity. Cameras, however, attempt to detect lane markings by detecting the edges of the lane markings in the image. This project seeks to compare two different lane detection techniques-one using a lidar and the other using a camera. Specifically, this project will analyze the two sensors’ ability to detect lane markings in varying weather scenarios, assess which sensor is best suited for lane detection, and determine scenarios where a camera or a lidar is better suited so that some optimal blending of the two sensors can improve the estimate of the position of the vehicle over a single sensor.

Lidar-based lane detection

The specific lidar-based lane detection algorithm for this project is based on fitting an ideal lane model to actual road data, where the ideal lane model is updated with each lidar scan to reflect the current road conditions. Ideally, a lane takes on a profile similar to the 100-averaged lidar reflectivity scans seen in Figure 1 with the corresponding segment.
Figure 1. Lidar reflectivity scan with corresponding lane markings.

Note that this profile has a relatively constant area bordered by peaks in the data, where the peaks represent the lane markings and the constant area represents the surface of the road.  An ideal lane model is generated with each lidar scan to mimic this averaged data, where averaging the reflectivity directly in front of the vehicle generates the constant portion and increasing the average road surface reflectivity by 75 percent mimics the lane markings.  This model is then stretched over a range of some minimum expected lane width to some maximum expected lane width, and the minimum RMSE between the ideal lane and the lidar data is assumed to be the area where the lane resides. For additional information on this method, see Britt, Rose & Levy, September 2011.

Camera-based lane detection

The camera-based method for this project was built in-house and uses line extraction techniques from the image to detect lane markings and calculate a lateral distance from a second-order polynomial model for the lane marking in image space. A threshold is chosen from the histogram of the image to compensate for differences in lighting, weather, or other non-ideal scenarios for extracting the lane markings. The thresholding operation converts the image into a binary image, which is followed by Canny edge detection. The Hough transform is then used to extract the lines from the image, fill in holes in the lane marking edges, and exclude erroneous edges. Using the slope of the lines, the lines are divided into left or right lane markings. Two criteria based on the assumption that the lane markings do not move significantly within the image from frame to frame are used to further exclude non-lane marking lines in the image. The first test checks that the slope of the line is within a threshold of the slope of the near region of the last frame’s second-order polynomial model. The second test uses boundary lines from the last frame’s second-order polynomial to exclude lines that are not near the current estimate of the polynomial. second-order polynomial interpolation is used on the selected lines’ midpoint and endpoints to determine the coefficients of the polynomial model, and a Kalman filter is used to filter the model to decrease the effect of erroneous polynomial coefficient estimates. Finally, the lateral distance is calculated using the polynomial model on the lowest measurable row of the image (for greater resolution) and a real-distance-to-pixel factor. For more information on this camera-based method, see Britt, et al.

Figure 2. Camera-based lane detection (green-detected lanes,blue-extracted lane lines, red-rejected lines).

Testing

Testing was performed at the NCAT (National Center for Asphalt Technology) in Opelika, Alabama, as seen in Figure 3.  This test track is very representative of highway driving and consists of two lanes bordered by solid lane markings and divided by dashed lane markings.  The 1.7-mile track is divided into 200-foot segments of differing types of asphalt with some areas of missing lane markings and other areas where the lanes are additionally divided by patches of different types and colors of asphalt.

Figure 3. NCAT Test Facility in Opelika, Alabama.

A precision survey of each lane marking of the test track as well as precise vehicle positions using RTK GPS were used in order to have a highly accurate measurement of the ability of the lidar and camera to determine the position of the vehicle in the lane. Testing occurred only on the straights, and the performance was analyzed on the ability of the lidar and camera to determine the position of the lane using metrics of mean absolute error (MAE), mean square error (MSE), standard deviation of error (σ­_error), and detection rate. The specific scenarios analyzed included varying speeds, varying lighting conditions (noon and dusk/ dawn), rain, and oncoming traffic. Table 1 summarizes the results for these scenarios. For additional results, please see [8].

Table 1. Lidar and camera results for various environments.

Additional testing on the effects of oncoming traffic at night was examined by parking a vehicle on the test track at a known location with the headlights on. Figure 4 shows the lateral error with respect to closing distance where a positive closing distance indicates driving at the parked vehicle, and a negative closing distance indicates driving away from the vehicle. Note that the camera does not report a solution at -200 m, which is due to track conditions and not the parked vehicle.

Figure 4. Error vs. Closing Distance.

Based on these findings it would appear that the camera provided slightly more accurate measurements than the lidar while having a decrease in detection rate. Additionally the camera performed well in the rain where the lidar experienced decreased detection rates.

References

Frank S. Barickman. Lane departure warning system research and test development. Transportation Research Center Inc., (07-0495), 2007.

J. Kibbel, W. Justus, and K. Furstenberg. using multilayer laserscanner. In Proc. Lane estimation and departure warning Proc. IEEE Intelligent Transportation Systems, pages 607 611, September 13 15, 2005.

P. Lindner, E. Richter, G. Wanielik, K. Takagi, and A. Isogai. Multi-channel lidar processing for lane detection and estimation. In Proc. 12th International IEEE Conference on Intelligent Transportation Systems ITSC ’09, pages 1 6, October 4 7, 2009.

K. Dietmayer, N. Kämpchen, K. Fürstenberg, J. Kibbel, W. Justus, and R. Schulz. Advanced Microsystems for Automotive Applications 2005. Heidelberg, 2005.

C. R. Jung and C. R. Kelber, “A lane departure warning system based on a linear-parabolic lane model,” in Proc. IEEE Intelligent Vehicles Symp, 2004, pp. 891–895.

C. Jung and C. Kelber, “A lane departure warning system using lateral offset with uncalibrated camera,” in Intelligent Transportation Systems, 2005. Proceedings. 2005 IEEE, sept. 2005, pp. 102 – 107.

A. Takahashi and Y. Ninomiya, “Model-based lane recognition,” in Proc. IEEE Intelligent Vehicles Symp., 1996, pp. 201–206.

Jordan Britt, C. Rose, & D. Bevly, “A Comparative Study of Lidar and Camera-based Lane Departure Warning Systems,” Proceedings of ION GNSS 2011, Portland, OR, September 2011.