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A reliable command and control (C2) data link is required for unmanned aircraft systems (UAS) operations in order to monitor the status and support the control of UAS. A practical realization of the C2 communication and mission data links for commercial UAS operations is via LTE/5G networks. While the trajectory of each UAS directly determines the flight distance and mission cost in terms of energy dissipation, it also has a strong correlation to the quality of the communication link provided by a serving base station, where quality is defined as the achieved signal-to-interference-plus-noise ratio (SINR) required to maintain the control link of the UAS. Due to signal interference and the use of RF spectrum resources, the trajectory of a UAS not only determines the communication link quality it will encounter, but also influences the link quality of other UAS in its vicinity. Therefore, effective UAS traffic management must plan the trajectory for a group of UAS taking into account the impact to the interference levels of other base stations and UAS communication links. In this paper, an SINR Aware Predictive Planning (SAPP) framework is presented for trajectory planning of UAS leveraging 4G/5G communication networks in a simulated environment. The goal is to minimize flight distance while ensuring a minimum required link quality for C2 communications between UAS and base stations. The predictive control approach is proposed to address the challenges of the time varying SINR caused by the interference from other UAS’s communication. Experimental results show that the SAPP framework provides more than 3dB improvements on average for UAS communication parameters compared to traditional trajectory planning algorithms while still achieving shortest path trajectories and collision avoidance.
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This content will become publicly available on March 1, 2026
Ice-Bed Detection Capabilities of a Low-VHF Radar on a Small UAS
This paper presents an analysis of the bed detecting capabilities of an ice sounding radar integrated onto a small, unmanned aircraft system (UAS). We evaluated the average signal-to-noise ratio (SNR) and signal-to-interference ratio (SINR) of radar measurements collected by the UAS over Greenland’s Helheim Glacier in 2022 and compared those to radar measurements collected over the same region using a radar-equipped Twin Otter around 2008. The statistical analysis presented of the SNR and the SINR shows that both systems have comparable bed detection capabilities. While the average SNR for all points considered is more than 20 dB higher for the Twin Otter system, the average SINR of both has a similar value. The overall average SINR is 9.79 dB for the UAS and 9.19 dB for the MA. As it is discussed in the paper, the lower SNR of the UAS system is attributed to its lower operating frequency, while the comparable SINR depends on various factors. The results of this paper have implications on planning and design of future field deployments.
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- Award ID(s):
- 1848210
- PAR ID:
- 10629605
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-5597-0
- Page Range / eLocation ID:
- 1 to 9
- Format(s):
- Medium: X
- Location:
- Big Sky, MT, USA
- Sponsoring Org:
- National Science Foundation
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