The　recognition　of　airport　apron　targets　and　the　determination　of　target　positions　are　critically　important　in　positioning　the　apron　when　there　are　abnormal　target　positions　or　unmanned　aerial　vehicles　(UAVs)　engaged　in　autonomous　cargo　retrieval.　This　is　crucial　for　ensuring　the　safety　and　efficiency　of　the　apron.　However,　challenges　such　as　resource-intensive　processes　and　suboptimal　accuracy　in　position　solving　have　been　encountered　due　to　limitations　in　hardware　equipment　and　the　complexity　of　multi-sensor　fusion.　In　this　paper,　we　propose　an　adaptive　target　location　method　for　airport　aprons　based　on　monocular　high-speed　cameras.　This　method　employs　adaptive　frame　differencing　and　perspective　transformation　based　on　geometric　shape　extraction　to　detect　apron　objects　and　calculate　their　azimuth　and　deflection　from　the　apron　center.　Importantly,　our　approach　relies　solely　on　a　single　visible-light　camera,　eliminating　the　need　for　complex　multi-sensor　fusion　involving　binocular　matching,　Global　Navigation　Satellite　Systems　(GNSS),　or　Inertial　Measurement　Units　(IMU).　Experimental　results　demonstrate　that　the　proposed　method　achieves　position　solving　accuracy　within　1　meter　and　real-time　recognition　and　solving　capabilities　for　apron　objects.　©　2023　ACM.