This　paper　proposes　Target　detection　system　design　and　FPGA　implementation　based　on　YOLOX　algorithm,　in　order　to　realize　offline　real-time　image　detection　in　a　UAV　platform　with　limited　resources　and　power　consumption.　First,　this　paper　studied　the　algorithm　of　YOLOX　convolutional　neural　network,image　fusion　mechanism　is　added　to　this　network,　designed　and　trained　the　neural　network.　Secondly,　an　embedded　edge　computing　system　is　designed　to　further　speed　up　the　target　detection　speed　at　the　hardware　level.In　this　paper,　the　above　scheme　is　implemented　at　the　board　level.　The　test　results　show　that　the　average　recognition　speed　is　50frame/s　on　the　system,　which　basically　achieves　the　design　goal　of　real-time　detection.　©　2022　ACM.