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Loran (Long Range Navigation)

Electronics & Technology
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Loran (short for Long Range Navigation) is a radio-based navigation system that was developed in the early 1940s for use by the military during World War II. The system uses radio signals to determine a location and was primarily used by ships and aircraft.

The development of Loran began in the United States in the early 1940s, with the goal of creating a navigation system that could be used by the military to accurately determine a ship or aircraft's position over long distances, even in adverse weather conditions. The first Loran system was called Loran A and was developed by the US Coast Guard in collaboration with the Massachusetts Institute of Technology (MIT) and the Radio Corporation of America (RCA).

Loran A was first used by the US military in 1942 and was later adopted by the British and Canadian militaries as well. The system used two or more fixed ground stations that transmitted synchronized pulses of radio waves, which were received and measured by a Loran receiver on board the ship or aircraft. By measuring the time difference between the received pulses, the Loran receiver could calculate the distance to each of the ground stations and then use triangulation to determine the user's position.

In the 1950s, Loran B was developed, which used more advanced technology to improve the accuracy of the system. Loran C, the most widely used version of the system, was developed in the 1960s and provided even greater accuracy and coverage. Loran C was used extensively by the military and by civilian ships and aircraft for many years.

With the development of more advanced navigation systems, such as GPS (Global Positioning System), the use of Loran has declined. Loran C was officially decommissioned in 2010 in the United States, and many other countries have also discontinued their Loran systems.

Despite the decline of Loran, its development and evolution played a significant role in the advancement of radio-based navigation systems and helped pave the way for more advanced systems like GPS.


AI Competition: ChatGPT-Gemini-Grok 3, GabAI - RF CafeThis content was generated by primarily with the assistance of ChatGPT (OpenAI), and/or Gemini (Google), and/or Arya (GabAI), and/or Grok (x.AI), and/or DeepSeek artificial intelligence (AI) engines. Review was performed to help detect and correct any inaccuracies; however, you are encouraged to verify the information yourself if it will be used for critical applications. In all cases, multiple solicitations to the AI engine(s) was(were) used to assimilate final content. Images and external hyperlinks have also been added occasionally - especially on extensive treatises. Courts have ruled that AI-generated content is not subject to copyright restrictions, but since I modify them, everything here is protected by RF Cafe copyright. Many of the images are likewise generated and modified. Your use of this data implies an agreement to hold totally harmless Kirt Blattenberger, RF Cafe, and any and all of its assigns. Thank you. Here is Gab AI in an iFrame.

AI Technical Trustability Update

While working on an update to my RF Cafe Espresso Engineering Workbook project to add a couple calculators about FM sidebands (available soon). The good news is that AI provided excellent VBA code to generate a set of Bessel function plots. The bad news is when I asked for a table showing at which modulation indices sidebands 0 (carrier) through 5 vanish, none of the agents got it right. Some were really bad. The AI agents typically explain their reason and method correctly, then go on to produces bad results. Even after pointing out errors, subsequent results are still wrong. I do a lot of AI work and see this often, even with subscribing to professional versions. I ultimately generated the table myself. There is going to be a lot of inaccurate information out there based on unverified AI queries, so beware.

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