The　combination　of　increased　amount　of　＇space　junk＇,　lack　of　precise　tracking　information　and　control　of　items　orbiting　Earth,　and　debris　from　past　collisions　posed　important　threats　to　human　space　missions.　In　this　study,　a　strategy　enabling　＇multispacecraft　to　multidebris＇debris　removal　task　is　proposed.　By　analyzing　the　current　distribution　of　space　debris,　282　large　debris　and　rocket　bodies　are　selected　as　target　database.　The　traditional-density-based　spatial　clustering　of　applications　with　noise　algorithm　is　innovatively　modified　by　defining　the　speed　increment　as　threshold　parameter　for　dividing　target　debris　into　different　clusters.　Then,　the　Hungarian-algorithm-based　target　allocation　strategy　is　used　to　assign　multispacecraft　to　different　debris　clusters　for　the　removal　mission.　Simulations　verify　the　effectiveness　of　the　proposed　＇multispacecraft　to　multidebris＇strategy　that　is　able　to　remove　as　much　as　83.33%　of　the　total　282　target　debris.　©　2024　Bao-Zhen　Yang　et　al.