An　atomic　force　microscopy　(AFM)　image　of　a　surface　is　a　convolution　of　the　tip　geometry　and　sample　features.　It　is　important　to　develop　tip　characterisers　and　estimate　the　tip　shape　for　a　more　accurate　AFM　image.　With　the　traditional　characterisers　with　special　microstructures　it　is　difficult　to　accurately　determine　tip　shape　because　of　their　dimensional　uncertainty.　Combined　with　tip　blind　reconstruction　algorithms,　some　nanomaterials　with　arrayed　nanostructures　are　often　used　to　estimate　the　AFM　tip　morphology.　However,　the　blind　reconstruction　algorithms　are　sensitive　to　image　noise.　To　solve　such　problems,　the　porous　anodic　alumina　(PAA)　film　with　well-ordered　porous　nanostructures　was　fabricated　and　used　as　a　new　tip　characteriser.　By　setting　the　appropriate　scanning　routine　and　scanning　mode,　the　two-dimensional　and　three-dimensional　tip　morphology　was　accurately　calculated.　PAA　film　as　the　AFM　tip　characteriser　can　effectively　reduce　the　influence　of　AFM　image　noise　and　sample-dimensional　uncertainty　of　tip　blind　estimation　results,　especially　avoiding　tip　wear　and　damage.