A Review on Performance Optimization of Remote Sensing CubeSats Using Artificial Intelligence Techniques: Attitude Control, Data Transmission, and Thermal Management

Farhangi, Mahdi; Aghabalaei, Amir; Jamour, Yahya

doi:10.61186/jgst.14.3.115

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Volume 14, Issue 3 (3-2025)

JGST 2025, 14(3): 115-125

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A Review on Performance Optimization of Remote Sensing CubeSats Using Artificial Intelligence Techniques: Attitude Control, Data Transmission, and Thermal Management

Mahdi Farhangi

, Amir Aghabalaei ^*

, Yahya Jamour

Abstract: (260 Views)

Remote sensing CubeSats are valuable tools in space missions. This paper analyses the key challenges and innovations in three essential domains of these satellites: Attitude Determination and Control Systems (ADCS), data transmission to Earth, and thermal management. In the ADCS section, the paper examines challenges related to size and weight limitations, high precision, and the need for rapid responsiveness. The use of artificial intelligence and machine learning algorithms to enhance the performance of these systems—including neural networks and extended Kalman filters for CubeSat attitude control—is explored, with positive impacts on accuracy and error reduction analyzed. The data transmission section reviews issues related to bandwidth, data volume management, and transmission delays. The optimization of the data transmission process through compression algorithms and artificial intelligence techniques for data management and classification is discussed, focusing on reducing unnecessary data and improving communication efficiency. The thermal management section analyses temperature control challenges in CubeSats and proposes solutions such as thermal materials and coatings, along with precise thermal behavior simulation using artificial neural networks. This study evaluates methods for optimizing and predicting thermal conditions to maintain the performance of sensitive systems in space environments, with results indicating reduced processing time and computational costs. The paper also reviews innovative projects such as IPEX and Amazonia-1, analyzing the impact of AI technologies on enhancing CubeSat performance and efficiency. The findings of this review could contribute to advancing space technologies and enhancing remote sensing mission capabilities.

Article number: 8

Keywords: CubeSat, Remote Sensing, Artificial Intelligence, Performance Optimizations, Attitude Control, Thermal Management

Full-Text [PDF 683 kb] (127 Downloads)

Type of Study: Tarviji | Subject: Geo&Hydro
Received: 2024/11/6

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Farhangi M, Aghabalaei A, Jamour Y. A Review on Performance Optimization of Remote Sensing CubeSats Using Artificial Intelligence Techniques: Attitude Control, Data Transmission, and Thermal Management. JGST 2025; 14 (3) : 8
URL: http://jgst.issgeac.ir/article-1-1207-en.html

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