MSMD Decoupled Collaborative Matching Algorithm: Efficient Arbitrary Matching of Space Debris in Low Earth Orbit Constellations Using Distributed Grassmann Distance

With the rapid development of low Earth orbit (LEO) satellite constellations, the issue of space debris has become increasingly severe. Building on existing methods for space debris recognition and fault diagnosis, this paper proposes a generalized multi-satellite multidebris matching algorithm for LEO constellations, aiming to enhance debris removal efficiency. For the case where Grassmann distance is used to quantify the similarity of arbitrary multidimensional cost functions, the satellite constellation is decoupled to reduce the dimension of the problem and improve the matching efficiency. For the potential problem of reluctant matching of debris, a decoupled collaborative matching algorithm is proposed to improve the flexibility of the matching process. The simulation results validate the effectiveness of the proposed algorithm in matching missions, with key performance metrics reduced by up to 37.6%, demonstrating its promising potential for application in national space debris removal efforts.