On-orbit operation results of the powered descent guidance algorithm for pinpoint lunar landing - Ueda, Satoshi; Ito, Takahiro; Yokota, Kentaro; Sakai, Shinichiro; Ishida, Takayuki; Miyazawa, Yu; Kushiki, Kenichi; Fukuda, Seisuke; Sawai, Shujiro (Acta astronautica, 2025)
This paper discusses the on-orbit operation results of the powered descent guidance algorithm that played a key role in the navigation, guidance, and control of the Smart Lander for Investigating Moon (SLIM) mission, which made a pinpoint lunar landing in January 2024. The SLIM mission successfully demonstrated pinpoint lunar landing, confirmed within 100 m. The technology required for a pinpoint lunar landing consists of a variety of elements: a vision-based navigation system that accurately detects the position of the spacecraft relative to the lunar surface, a propulsion system that operates stably, a landing descent reference trajectory that is in harmony with the system design, mature spacecraft navigation, guidance, and control technology, and precise guidance algorithms to guide the spacecraft to its target location. The SLIM landing descent sequence consists of a powered descent phase to reduce the horizontal velocity and a vertical descent phase to reduce the remaining vertical velocity after the powered descent. Dedicated guidance algorithms applied to both phases use advanced mathematical methods for high-precision landing and backup options. This paper focuses on the powered descent guidance algorithm. The powered descent phase consists of three boost parts and two coasting parts. The coasting sections adjust the attitude of the spacecraft and the direction of the body-fixed navigation camera. Image acquisition for vision-based navigation and guidance calculation for the next boost section are performed before each boost section. In the boost section, the spacecraft's translational control law follows the trajectory generated by the guidance algorithm. The powered descent guidance algorithm uses an explicit guidance method that sequentially calculates the optimal trajectory and necessary controls during flight. Highly accurate guidance algorithms are required to adapt the control acceleration to the thrust acceleration of the spacecraft. To achieve this, unique mechanisms are introduced: the trajectory is generated based on polynomials with dimensionless time and the boost start time is corrected based on navigation and machine learning. This combination achieved a guidance accuracy of 0.2 %, contributing to the pinpoint lunar landing. This paper presents details of these mechanisms and their evaluation based on telemetry from the landing.