CubeSats have been widely used in remote sensing applications such as global coverage, hotspots revisited, etc. However, due to the strict size limitation, the high-accuracy measuring instruments such as star tracker are too large to be applied in CubeSat, thus causing insufficient accuracy in satellite attitude and image positioning. In order to reduce the volume of star tracker without compromising the performance, the relationship between the volume and pointing accuracy or dynamic performance is studied and an optimization model of star tracker with a minimum volume is proposed. Compared with the traditional star tracker, a deployable star tracker with a novel deployable baffle and surrounded circuit structure is designed. The baffle consists of nested three-stage sub-baffles with a scientifically analyzed and verified taper to achieve smooth deployment and compression. The special circuit structure surrounds the lens and can be compressed in the inner sub-baffle. Therefore, the deployable star tracker can be compressed to the smallest volume and the sub-baffles can be deployed to the accurate position without self-lock risk. The experimental results verify its deployment accuracy and reliability as well as space environmental adaptability. The deployable star tracker has almost the same results on stray light suppression ability, pointing accuracy (better than 3″ $\left(3\sigma \right)$) and dynamic performance (up to 3°/s) with the traditional star tracker. Furthermore, an integrated attitude determination and control system based on the deployable star tracker for CubeSat is further designed and implemented to support high-accuracy remote sensing.

CubeSats have extensive applications in the realm of remote sensing. However, due to size constraints, attitude determination and control systems (ADCS) often adopt an integrated and densely packed structure. This leads to simple interference in the magnetic field measurements from components like reaction wheels and magnetorquers, resulting in magnetometer failures. Furthermore, the magnetic interference compromises the ability to dump the angular momentum of CubeSats. This leads to attitude control and remote sensing mission failures. To address these challenges, we introduce a dynamics-sensing, magnetic, fault-tolerant attitude control method that achieves attitude control without a priori magnetic field information generated from a magnetometer, restoring the remote sensing capabilities of CubeSats under magnetic failure. The proposed geomagnetic field sensing method, based on the temporal expansion geomagnetic vector calculate algorithm (GVCA), decouples the observation equations in three axes through control segmentation in the time domain to address the singularity issue of the Kalman coefficient matrix. Additionally, the magnetic field vector can be obtained in real time with acceptable computational consumption. Moreover, utilizing this real-time magnetic field information, the fault-tolerant control strategies and multi-mode control laws can progressively restore destabilized CubeSats to their regular states without performance degradation. We conducted numerical simulation experiments to evaluate the effectiveness of our method and system. Beyond the numerical simulations, we also built hardware systems. We designed and implemented a plug-and-play (PnP) ADCS to apply our methodology, further supporting CubeSats’ high-precision remote sensing. Furthermore, with the aid of a space environment simulation platform, we verified the performance of our system and method under conditions simulating the actual space environment. Ground testing demonstrated that our proposed method was able to identify the magnetic field and achieve high-performance attitude control with magnetic field measurement failures. The system’s pointing accuracy was better than 0.02 degrees, and the attitude stability surpassed 0.003 degrees per second.