In　order　to　make　the　rotor　UAV　land　on　the　ground　platform　quickly　and　accurately,　a　pose　estimation　method　based　on　visual　mark　detection　was　proposed.　Firstly,　based　on　the　geometric　features　of　the　standard　helipad,　a　five-step　landmark　extraction　algorithm　was　used　to　obtain　the　visual　landmarks　from　the　images　captured　by　the　airborne　camera.　In　order　to　satisfy　the　rapid　and　real-time　requirements　of　UAV　autonomous　landing　process,　a　distance-based　three-point　corner　detection　algorithm　was　proposed,　and　12　H-shaped　corners　were　obtained.　Then,　by　classifying　and　numbering　the　corners,　the　corners　of　the　visual　mark　in　the　current　image　were　matched　with　the　corresponding　corners　in　the　reference　image,　and　the　homography　matrix　containing　the　pose　information　was　calculated.　Finally,　the　attitude　angle　of　UAV　was　obtained　by　decomposing　homography　matrix　with　direct　linear　transformation　(DLT),　and　the　position　of　UAV　relative　to　visual　mark　was　calculated　according　to　the　similar　triangle　formed　by　camera　imaging.　The　real-time　performance　and　accuracy　of　the　proposed　methodology　were　proved　by　simulating　the　pose　of　UAV　in　different　flight　states　on　an　experiment　platform.　The　outcomes　showed　that　the　average　running　time　of　the　given　algorithm　was　307.2　ms,　the　maximum　root　mean　square　error　(RMSE)　of　position　estimation　was　0.006　2　m,　and　the　maximum　RMSE　of　attitude　angle　estimation　was　0.313°,　which　can　satisfy　the　requirements　of　accuracy　and　real-time　in　the　autonomous　landing　process.　©　2019,　Chinese　Society　of　Agricultural　Machinery.　All　right　reserved.