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Have you ever used GPS while running or cycling? Usually, to get millimeter-level precision, your smartphone needs to 'talk' to satellites in space for a long time. This process is called PPP and can be a bit slow, like waiting for a video to buffer on a slow connection. But what if we had 'terrestrial satellites' ready to help us?

This is where 'pseudolites' come in. Imagine them as small repeaters placed near us on Earth, mimicking signals from space satellites. Because they are so close, the signal changes rapidly as we move, allowing the system to figure out exactly where you are in very little time.

A new study has found a way to make these two worlds work together super efficiently. Scientists designed a system that resolves small calculation errors (called 'ambiguities') one after another, like levels in a video game. First, it resolves the pseudolite ambiguities, then the space satellite ones. The result? Incredible precision almost instantly. This is a huge step forward for self-driving cars and drones, which will need to know their exact location with absolute precision and without endless waiting!

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The core of the research lies in overcoming the main limitation of Precise Point Positioning (PPP): convergence time. In traditional PPP, the receiver must estimate numerous parameters, including 'phase ambiguities'β€”the integer number of wavelengths of the signal between the satellite and the receiver. Until these are resolved, the position remains approximate.

Pseudolites (PLS) offer a unique geometric advantage: being close to the receiver, the signal variation due to user movement is much faster than that of GNSS satellites located about 20,000 km away. This study introduces a 'cascaded ambiguity resolution' strategy. Instead of trying to solve everything simultaneously (a mathematically complex and slow task), the proposed model first resolves the pseudolite ambiguities. Once these are fixed, the information is used as constraints to resolve the GNSS 'wide-lane' and 'L1' ambiguities. This sequential approach drastically reduces the time needed to achieve a high-precision positioning solution, making the technology much more practical for dynamic applications such as robotics and intelligent mobility.

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Authors:
Caoming FanZheng YaoJinling WangMingquan Lu
Date Published:
Original Article www.mdpi.com
Fact-check verified on 22/07/2026
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Creative Commons License CC BY-NC-SA 4.0

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