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Synthetic vision system

Synthetic vision system is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Synthetic vision system rather than just read about it. In short: A synthetic vision system (SVS) is a computer-mediated reality system for aerial vehicles, that uses 3D to provide pilots with clear and intuitive means of understanding their flying environment. Functionality Synthetic vision provides situational awareness to the operators by using terrain, obstacle, geo-political, hydrological and other databases.

Synthetic vision system — main illustration
Synthetic vision system — illustration

Key takeaways

  • Synthetic vision system belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Synthetic vision system to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Synthetic vision system from memory before moving on to harder problems.

Reference excerpt

A synthetic vision system (SVS) is a computer-mediated reality system for aerial vehicles, that uses 3D to provide pilots with clear and intuitive means of understanding their flying environment.

Functionality Synthetic vision provides situational awareness to the operators by using terrain, obstacle, geo-political, hydrological and other databases. A typical SVS application uses a set of databases stored on board the aircraft, an image generator computer, and a display. Navigation solution is obtained through the use of GPS and inertial reference systems. Highway In The Sky (HITS), or Path-In-The-Sky, is often used to depict the projected path of the aircraft in perspective view. Pilots acquire instantaneous understanding of the current as well as the future state of the aircraft with respect to the terrain, towers, buildings and other environment features.

History A forerunner to such systems existed in the 1960s, with the debut into U.S. Navy service of the Grumman A-6 Intruder carrier-based medium-attack aircraft. Designed with a side-by-side seating arrangement for the crew, the Intruder featured an advanced navigation/attack system, called the Digital Integrated Attack and Navigation Equipment (DIANE), which linked the aircraft's radar, navigation and air data systems to a digital computer known as the AN/ASQ-61. Information from DIANE was displayed to both the Pilot and Bombardier/Navigator (BN) through cathode ray tube display screens. In particular, one of those screens, the AN/AVA-1 Vertical Display Indicator (VDI), showed the pilot a synthetic view of the world in front of the aircraft and, in Search Radar Terrain Clearance mode (SRTC), depicted the terrain detected by the radar, which was then displayed as coded lines that represented preset range increments. Called 'Contact Analog', this technology allowed the A-6 to be flown at night, in all weather conditions, at low altitude, and through rugged or mountainous terrain without the need for any visual references. Synthetic vision was developed by NASA and the U.S. Air Force in the late 1970s and 1980s in support of advanced cockpit research, and in 1990s as part of the Aviation Safety Program. Development of the High Speed Civil Transport fueled NASA research in the 1980s and 1990s. In the early 1980s, the USAF recognized the need to improve cockpit situation awareness to support piloting ever more complex aircraft, and pursued SVS (also called pictorial format avionics) as an integrating technology for both crewed and remotely piloted systems.

Simulations and remotely piloted vehicles In 1979, the FS1 Flight Simulator by Bruce Artwick for the Apple II microcomputer introduced recreational uses of synthetic vision.

NASA used synthetic vision for remotely piloted vehicles (RPVs), such as the High Maneuverability Aerial Testbed or HiMAT. According to the report by NASA, the aircraft was flown by a pilot in a remote cockpit, and control signals up-linked from the flight controls in the remote cockpit on the ground to the aircraft, and aircraft telemetry downlinked to the remote cockpit displays (see photo). The remote cockpit could be configured with either nose camera video or with a 3D synthetic vision display. SV was also used for simulations of the HiMAT. Sarrafian reports that the test pilots found the visual display to be comparable to output of camera on board the RPV. The 1986 RC Aerochopper simulation by Ambrosia Microcomputer Products, Inc. used synthetic vision to aid aspiring RC aircraft pilots in learning to fly. The system included joystick flight controls which would connect to an Amiga computer and display. The software included a three-dimensional terrain database for the ground as well as some man-made objects. This database was basic, representing the terrain with relatively small numbers of polygons by today's standards. The program simulated the dynamic three-dimensional position and attitude of the aircraft using the terrain database to create a projected 3D perspective display. The realism of this RPV pilot training display was enhanced by allowing the user to adjust the simulated control system delays and other parameters. Similar research continued in the U.S. military services, and at Universities around the world. In 1995-1996, North Carolina State University flew a 17.5% scale F-18 RPV using Microsoft Flight Simulator to create the three-dimensional projected terrain environment.

In flight

In 2005 a synthetic vision system was installed on a Gulfstream V test aircraft as part of NASA's "Turning Goals Into Reality" program. Much of the experience gained during that program led directly to the introduction of certified SVS on future aircraft. NASA initiated industry involvement in early 2000 with major avionics manufacturers. Eric Theunissen, a researcher at Delft University of Technology in the Netherlands, contributed to the development of SVS technology. At the end of 2007 and early 2008, the FAA certified the Gulfstream Synthetic Vision-Primary flight display (SV-PFD) system for the G350/G450 and G500/G550 business jet aircraft, displaying 3D color terrain images from the Honeywell EGPWS data overlaid with the PFD symbology. It replaces the traditional blue-over-brown artificial horizon. In 2017, Avidyne Corporation certified Synthetic Vision capability for its air navigation avionics. Other glass cockpit systems such as the Garmin G1000 and the Rockwell Collins Pro Line Fusion offer synthetic terrain. Lower-cost, non-certified avionics offer synthetic vision like apps available for Android or iPad tablet computers from ForeFlight, Garmin, Air Navigation Pro, or Hilton Software

Regulations and standards "RTCA DO-315B". IEEE. 2011-06-21. Minimum aviation system performance standards for Enhanced Vision Systems, Synthetic Vision Systems, Combined Vision Systems and Enhanced Flight Vision Systems. "ED-179B - MASP for Enhanced Vision Systems and Synthetic Vision Systems and Combined Vision Systems and Enhanced Flight Vision Systems". EuroCAE. September 2011.

See also Aircraft collision avoidance systems Enhanced flight vision system External vision system Instrument landing system

References

External links

"Synthetic Vision Would Give Pilots Clear Skies All the Time". NASA. 2004-11-21. Stephen Pope (June 2006). "The promise of synthetic vision: turning ideas into (virtual) reality" (PDF). AIN online.

Illustrations

Synthetic vision system: A modern synthetic vision system produced by Honeywell
A modern synthetic vision system produced by Honeywell
Synthetic vision system: HiMAT Remotely Piloted Aircraft Cockpit with Synthetic Vision Display
HiMAT Remotely Piloted Aircraft Cockpit with Synthetic Vision Display
Synthetic vision system: A synthetic vision system that was tested by NASA in a Gulfstream V business jet in 2004.
A synthetic vision system that was tested by NASA in a Gulfstream V business jet in 2004.

Worked examples

Example 1 — a first encounter with Synthetic vision system

Start with the simplest possible case. Write down what Synthetic vision system claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Synthetic vision system before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Synthetic vision system ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Synthetic vision system

In research
Synthetic vision system appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Synthetic vision system in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Synthetic vision system is common in secondary-school and first-year university syllabi. It links to neighbouring topics Aircraft collision avoidance systems, Augmented reality, Avionics, so understanding it makes those chapters shorter.
In everyday life
Look for Synthetic vision system outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Synthetic vision system in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Synthetic vision system means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Synthetic vision system out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Synthetic vision system in simple terms?

A synthetic vision system (SVS) is a computer-mediated reality system for aerial vehicles, that uses 3D to provide pilots with clear and intuitive means of understanding their flying environment. Functionality Synthetic vision provides situational awareness to the operators by using terrain, obstac…

Why does Synthetic vision system matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Synthetic vision system?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Synthetic vision system.

Tags

  • Aircraft collision avoidance systems
  • Augmented reality
  • Avionics

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