EGO-6: Enhancing Geofencing Security Systems with Optimal Deployment of 6G TRPs

Famili, Alireza; Stavrou, Angelos; Wang, Haining; Park, Jung‐Min

doi:10.1109/svcc56964.2023.10165032

Cited by 1 publication

(1 citation statement)

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“…Beacon placement optimization is a well-known topic, seeking to optimize the location of beacons for indoor localization purposes [ 28 , 29 , 30 , 31 , 32 , 33 , 34 ] and wireless network localization [ 35 , 36 , 37 , 38 ]. There are two major issues: first, optimizing the number of beacons and their location to ensure full coverage for the entire indoor venue; and second, optimizing the placement of the beacons to minimize the localization error induced by the relative geometry between the target and the beacons.…”

Section: Related Workmentioning

confidence: 99%

OPTILOD: Optimal Beacon Placement for High-Accuracy Indoor Localization of Drones

Famili,

Stavrou,

Wang

et al. 2024

Sensors

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For many applications, drones are required to operate entirely or partially autonomously. In order to fly completely or partially on their own, drones need to access location services for navigation commands. While using the Global Positioning System (GPS) is an obvious choice, GPS is not always available, can be spoofed or jammed, and is highly error-prone for indoor and underground environments. The ranging method using beacons is one of the most popular methods for localization, especially for indoor environments. In general, the localization error in this class is due to two factors: the ranging error, and the error induced by the relative geometry between the beacons and the target object to be localized. This paper proposes OPTILOD (Optimal Beacon Placement for High-Accuracy Indoor Localization of Drones), an optimization algorithm for the optimal placement of beacons deployed in three-dimensional indoor environments. OPTILOD leverages advances in evolutionary algorithms to compute the minimum number of beacons and their optimal placement, thereby minimizing the localization error. These problems belong to the Mixed Integer Programming (MIP) class and are both considered NP-hard. Despite this, OPTILOD can provide multiple optimal beacon configurations that minimize the localization error and the number of deployed beacons concurrently and efficiently.

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