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STar-DETR: A Lightweight Real-Time Detection Transformer for Space Targets in Optical Sensor Systems.

Yao Xiao¹, Yang Guo¹, Qinghao Pang¹

¹Shandong Key Laboratory of Space Debris Monitoring and Low-Orbit Satellite Networking, Qingdao University of Technology, Qingdao 266520, China.

Sensors (Basel, Switzerland)

|February 26, 2025

Summary

This summary is machine-generated.

This study introduces STar-DETR, a lightweight optical system for real-time space target detection. It balances accuracy and efficiency, significantly reducing model size for resource-constrained sensors.

Keywords:

RT-DETR data augmentation lightweight object detection space targets

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Area of Science:

Aerospace Engineering
Computer Vision
Optical Sensing

Background:

Optical sensor systems are crucial for space target detection.
Existing models often sacrifice efficiency for accuracy, limiting use on resource-limited sensors.

Purpose of the Study:

To develop a lightweight and efficient model for real-time space target detection.
To balance detection accuracy with reduced computational complexity for constrained optical sensors.

Main Methods:

Proposed the lightweight Space Target Real-time Detection Transformer (STar-DETR).
Utilized an improved MobileNetv4 (IMNv4) backbone and group shuffle convolution (GSConv) for efficiency.
Introduced dynamic depthwise shuffle transformer (DDST) for feature fusion and minimum points distance scylla intersection over union (MPDSIoU) loss for accuracy.

Main Results:

Achieved 89.9% AP0.5:0.95 in detecting dim and discontinuous space targets.
Reduced model parameters by 64.8% and computational complexity by 41.8%.
Demonstrated robustness through a dataset with diverse augmentation techniques.

Conclusions:

STar-DETR offers a significant advancement in lightweight, accurate space target detection.
The model is suitable for deployment on resource-constrained optical sensors.
Provides a valuable reference for future space target detection research.