Resource-efficient In-orbit Detection of Earth Objects
Qiyang Zhang, Xin Yuan, Ruolin Xing, Yiran Zhang, Zimu Zheng, Xiao Ma,, Mengwei Xu, Schahram Dustdar, Shangguang Wang

TL;DR
This paper introduces TargetFuse, a satellite-ground collaborative system that enhances onboard Earth object detection in LEO satellites by optimizing limited computational and communication resources, significantly reducing errors and bandwidth use.
Contribution
Proposes TargetFuse, a novel satellite-ground collaboration system that improves in-orbit object detection efficiency under resource constraints.
Findings
Reduces detection errors by 3.4 times on average.
Achieves 9.6 times better bandwidth efficiency.
Effectively balances detection accuracy with resource limitations.
Abstract
With the rapid proliferation of large Low Earth Orbit (LEO) satellite constellations, a huge amount of in-orbit data is generated and needs to be transmitted to the ground for processing. However, traditional LEO satellite constellations, which downlink raw data to the ground, are significantly restricted in transmission capability. Orbital edge computing (OEC), which exploits the computation capacities of LEO satellites and processes the raw data in orbit, is envisioned as a promising solution to relieve the downlink burden. Yet, with OEC, the bottleneck is shifted to the inelastic computation capacities. The computational bottleneck arises from two primary challenges that existing satellite systems have not adequately addressed: the inability to process all captured images and the limited energy supply available for satellite operations. In this work, we seek to fully exploit the…
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Taxonomy
TopicsSpace Satellite Systems and Control · Spacecraft Design and Technology · Inertial Sensor and Navigation
