Using aerial photos, image-processing software created this 3-D model of San Francisco, accurate to 15 centimeters. Credit: C3 Technologies
Technology originally developed to help missiles home in on targets has been adapted to create 3-D color models of cityscapes that capture the shapes of buildings to a resolution of 15 centimeters or less. Image-processing software distills the models from aerial photos captured by custom packages of multiple cameras.
Collecting and processing rapidly is C3 Technologies’ core advantage. Since our spin out from the aviation and defense company, Saab AB, C3’s expertise in image processing and systems integration of airborne and terrestrial data capture systems ensures that our products are calculated with extremely high precision.
C3’s Technologies’ process is fully automated, producing large amounts of 3D data with minimal manual work. We are expanding our terrestrial collection capabilities to pedestrian and waterway locations and offer integration tools for those interested in interior places.
C3 is building a store of eye-popping 3-D models of major cities to license to others for mapping and other applications. The first customer to go public with an application is Nokia, which used the models for 20 U.S. and European cities for an upgraded version of its Ovi online and mobile mapping service released last week. “It’s the start of the flying season in North America, and we’re going to be very active this year,” says Paul Smith, C3’s chief strategy officer.
C3’s models are generated with little human intervention. First, a plane equipped with a custom-designed package of professional-grade digital single-lens reflex cameras takes aerial photos. Four cameras look out along the main compass points, at oblique angles to the ground, to image buildings from the side as well as above. Additional cameras (the exact number is secret) capture overlapping images from their own carefully determined angles, producing a final set that contains all the information needed for a full 3-D rendering of a city’s buildings. Machine-vision software developed by C3 compares pairs of overlapping images to gauge depth, just as our brains use stereo vision, to produce a richly detailed 3-D model.
“Unlike Google or Bing, all of our maps are 360° explorable,” says Smith, “and everything, every building, every tree, every landmark, from the city center to the suburbs, is captured in 3-D—not just a few select buildings.”
“The advantage of C3’s image-only scheme is that aerial LIDAR is significantly more expensive than photography, because you need powerful laser scanners,” says Zakhor. “In theory, you can cover more area for the same cost.” However, the LIDAR approach still dominates because it is more accurate, she says. “Using photos alone, you always need to manually correct errors that it makes,” says Zakhor. “The 64-million-dollar question is how much manual correction C3 needs to do.”
Smith says that C3’s technique is about “98 percent” automated, in terms of the time it takes to produce a model from a set of photos. “Our computer vision software is good enough that there is only some minor cleanup,” he says. “When your goal is to map the entire world, automation is essential to getting this done quickly and with less cost.” He claims that C3 can generate richer models than its competitors, faster.
Smith says that augmented-reality apps allowing a phone or tablet to blend the virtual and real worlds are another potential use. “We can help pin down real-world imagery very accurately to solve the positioning problem,” he says. However, the accuracy of cell phones’ positioning systems will first have to catch up with that of C3’s maps. Cell phones using GPS can typically locate themselves to within tens of meters, not tens of centimeters.
Carrier-Phase Enhancement (CPGPS) – CPGPS makes use of the 1.575 GHz L1 carrier wave, which plays the role of a clock signal for helps in resolving ambiguities. Usually ambiguities are caused due to frequent changes in C/A PRN, and location of the pulse transition, which is represented by the logic 0-1 and 1-0 transition.
How Does CPGPS Help in Improving GPS Accuracy Levels?
Basically, the root of the problem is that the C/A signal isn’t instantaneous; there is a considerable amount of tag lag between the instants when the signal reaches digital logic value ‘1’ from ‘0’, and vice versa. The end result is inconsistent satellite-receiver sequence matching.
The 1.575 GHz L1 carrier wave helps in defining a precise transition point (due to very small period of 1/1000 that of C/A bit width). As a result, CPGPS can help in achieving up to 1% ambiguity levels, which amounts to about 3mm, while the regular ambiguity levels in GPS operation are in the range of 2 to 3 meters.
To improve the GPS accuracy furthermore, DGPS (Differential GPS) can be clubbed with CPGPS (Carrier-Phase Enhancement) to realize high accuracy levels of about 20-30 centimeters.
Differential GPS, often referred to as DGPS in short, allows you to improve the accuracy of GPS readings up to an excellent level of about one meter to three meters, which is a lot better than the regular reading levels of 4-20 meters.
How Differential GPS Works
It makes use of a network of stationary GPS receivers, and it is quite similar to civilian system run by the US Coast Guard on most of the waterways, and marine longwave radio transmission.
In DGPS, the difference between the position of the reference object estimated by the satellite signals, and the actual pre-defined position is calculated, which is termed as error factor. Now, this error component is used as a carrier for transmitting FM signals, used by the local GPS received. Finally, necessary corrections are applied to achieve higher accuracy levels