## 1 Introduction  
In response to the needs of scientific and economic advancement, an extensive array of space-based systems, including space stations and satellites, have been deployed into the vast expanse of space [1, 2]. So far, optical telescopes [3, 4] and ground-based radars [5] are the main detection sensors of satellites in orbit. High-resolution observations of celestial bodies are feasible with optical telescopes; however, the clarity of the resulting images is significantly influenced by the lighting circumstances. Ground-based radar systems are capable of conducting continuous, round-the-clock surveillance and ISAR imaging for space objects, and they have emerged as the predominant method for such oversight. However, they still have some drawbacks. Initially, the limitation of transmission power poses challenges in detecting High Earth Orbit (HEO) satellite targets and small satellite targets, as the extended transmission distance and their low Radar Cross Section (RCS) contribute to their difficulty in being observed. The second challenge is that current ground-based radar systems typically operate in frequency bands below the W-band. This choice is made to mitigate the effects of atmospheric attenuation, which can degrade radar signals as they pass through the atmosphere. However, operating at lower frequencies also comes with a trade-off: it limits the imaging resolution. As a result, it is not possible to achieve detailed imaging and recognition of space objects down to the component level, meaning that the fine details of the satellite structure or individual components may not be discernible with these radar systems. Thirdly, when observing the target in HEO, the change in the elevation angle of the Line of Sight (LOS) is not enough to match the change in the azimuth angle, resulting in an unbalanced distribution of attitude parameters. Furthermore, accurately confirming the status of the target requires a detailed understanding of the component information, which the current methods are unable to fully provide. Furthermore, certain key structural features of the object may be susceptible to fading and blurring during radar imaging. This can be problematic for intelligent image interpretation, as the loss of clarity in these features may hinder the ability to accurately identify and analyze the object's components or characteristics. Such limitations can affect the overall effectiveness of radar surveillance and the subsequent analysis of space objects. Terahertz (THz) waves are a form of electromagnetic radiation characterized by wavelengths that span from 3 mm (mm) to 30 \(\upmu\)m (\(\upmu\)m). This range corresponds to frequencies that fall between 0.1 terahertz (THz) and 10 THz. The use of THz waves in various applications is of interest due to their unique properties, such as their ability to penetrate certain materials without significant attenuation, making them useful for non-destructive testing and imaging as well as for communication and sensing [6]. Since terahertz waves have a shorter wavelength than low-frequency microwaves, this allows terahertz waves to achieve high-resolution imaging at shorter synthetic apertures. In addition, the terahertz region has many unique characteristics, including but not limited to a certain anti-interference [7] and penetration [8], and is widely used in astronomical exploration and wireless communication [9; 10; 11]. A space-based terahertz radar imaging system is proposed because of the above advantages. Therefore, in the application scenario of high-resolution radar, the performance of terahertz radar imaging is expected to reflect the detailed characteristics of the key component structure of the target. The parabolic antenna load, as we all know, is a key component of satellite communication systems, and accurate identification of parabolic antennas is important to condition assessment and function maintenance, and it provides favorable support for subsequent three-dimensional reconstruction and pointing estimation tasks.