Artificial bee colony-based satellite selection for multi-constellation GNSS receiver.
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| Title: | Artificial bee colony-based satellite selection for multi-constellation GNSS receiver. |
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| Authors: | Singh, Prateek1 (AUTHOR) prateeksingh047@gmail.com, Sharma, Nitin1 (AUTHOR) nitinn@goa.bits-pilani.ac.in |
| Source: | Sādhanā: Academy Proceedings in Engineering Sciences. Jun2026, Vol. 51 Issue 2, p1-14. 14p. |
| Subjects: | Metaheuristic algorithms, Swarm intelligence, Bees algorithm, Global Positioning System |
| Abstract: | Over the past decade, more global navigation satellite system (GNSS) satellites have led to the development of receivers that support multiple constellations. Advances in receiver technology to support multi-GNSS constellations require more power and resources, making them unsuitable for budget-friendly wearables and smartphones. For multi-GNSS constellations, geometric dilution of precision (GDOP) is a key measurement unit selection parameter. Identifying the optimal subset requires an exhaustive search since the GDOP performance criterion is both non-linear and non-separable, making direct analytical solutions impractical. Traditional matrix inverse GDOP calculation requires several operations that use more resources and power. This paper revisits GDOP parameterization in multi-GNSS constellations and proposes an efficient swarm-based meta-heuristic approach to filter satellites using GDOP without compromising receiver performance accuracy. The proposed method optimizes computation by selecting the best satellites for position calculation. Multi-GNSS (GPS and NAVIC) cases show that the proposed method is 4–7 times faster and 72–87% more efficient than the traditional traversal method. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Over the past decade, more global navigation satellite system (GNSS) satellites have led to the development of receivers that support multiple constellations. Advances in receiver technology to support multi-GNSS constellations require more power and resources, making them unsuitable for budget-friendly wearables and smartphones. For multi-GNSS constellations, geometric dilution of precision (GDOP) is a key measurement unit selection parameter. Identifying the optimal subset requires an exhaustive search since the GDOP performance criterion is both non-linear and non-separable, making direct analytical solutions impractical. Traditional matrix inverse GDOP calculation requires several operations that use more resources and power. This paper revisits GDOP parameterization in multi-GNSS constellations and proposes an efficient swarm-based meta-heuristic approach to filter satellites using GDOP without compromising receiver performance accuracy. The proposed method optimizes computation by selecting the best satellites for position calculation. Multi-GNSS (GPS and NAVIC) cases show that the proposed method is 4–7 times faster and 72–87% more efficient than the traditional traversal method. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 02562499 |
| DOI: | 10.1007/s12046-026-03068-x |
