Adapting LoRa Ground Stations for Low-latency Imaging and Inference from LoRa-enabled CubeSats

Author:

Gadre Akshay1ORCID,Machester Zachary2ORCID,Kumar Swarun2ORCID

Affiliation:

1. Electrical and Computer Engineering, University of Washington, Seattle, United States

2. Carnegie Mellon University, Pittsburgh, United States

Abstract

Recent years have seen the rapid deployment of low-cost CubeSats in low-Earth orbit, many of which experience significant latency (several hours) from the time information is gathered to the time it is communicated to the ground. This is primarily due to the limited availability of ground infrastructure that is bulky to deploy and expensive to rent. This article explores the opportunity in leveraging the extensive terrestrial LoRa infrastructure as a solution. However, the limited bandwidth and large amount of Doppler on CubeSats precludes these LoRa links to communicate rich satellite Earth images—instead, the CubeSats can at best send short messages. This article details our experience in designing LoRa-based satellite ground infrastructure that requires software-only modifications to receive packets from LoRa-enabled CubeSats recently launched by our team. We present Vista, a communication system that adapts encoding onboard the CubeSat and decoding configuration on commercial LoRa ground stations to allow images to be communicated. We perform a detailed evaluation of Vista by leveraging wireless channel measurements from a recent CubeSat (2021), and show that Vista can achieve 55.55% lower latency in retrieving data with 12.02 dB improvement in packet retrieval in the presence of terrestrial interference. We then evaluate Vista on a case study on land-use classification over images transmitted over the CubeSat link to further demonstrate a 4.56 dB improvement in image PSNR and 1.38× increase in classification accuracy over baseline approaches.

Funder

NSF

ONR

AFRETEC

MFI

CISCO

Safety21

CyLab-Enterprise

Publisher

Association for Computing Machinery (ACM)

Reference93 articles.

1. accessed Jan 01 2024. 3GPP - Release 17. Retrieved from https://www.3gpp.org/specifications-technologies/releases/release-17

2. accessed Jan 01 2024. 3GPP - Release 18. Retrieved from https://www.3gpp.org/specifications-technologies/releases/release-18

3. accessed Jan 01 2024. Artemis CubeSat Kit and Curriculum. Retrieved from https://franceszhu.space/artemis-cubesat-kit

4. accessed Jan 01 2024. Assessment of TLE-based Orbit Determination and Prediction for Cubesats. Retrieved from https://ntrs.nasa.gov/api/citations/20190004996/downloads/20190004996.pdf

5. accessed Jan 01 2024. Banco Santander funds Sateliot with €6 Million through its High- Growth Enterprise Program. Retrieved from https://sateliot.space/en/news-sateliot-space/banco-santander-funds-sateliot-with-e6-million-through-its-high-growth-enterprise-program/

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