In　recent　decades,　radio-echo　sounding　(RES)　has　been　extensively　applied　to　study　the　flow　and　form　of　polar　ice　sheets.　In　certain　regions　within　the　ice　sheet,　the　RES　reveals　a　structure　referred　to　as　a　＂basal　unit,＂　which　differs　from　the　overlying　ice　in　terms　of　its　characteristics,　structure,　and　origin,　and　plays　a　significant　role　in　the　ice＇s　rheology　and　flow　dynamics.　However,　methods　for　detecting　basal　units　in　RES　data　are　semiquantitative　and　can　lead　to　inconsistent　identification.　To　address　this　issue,　we　propose　an　automatic　＂basal　unit　identification　method＂　based　on　residual　network　(ResNet)　and　weight　control.　The　method　improves　upon　previous　works　in　three　aspects:　1)　it　simultaneously　uses　the　signal　and　image　features　of　RES　and　reduces　inaccuracies　associated　with　image　analysis;　2)　this　method　assigns　weight　to　signal　features　that　are　affected　by　backscatter　consistent　with　high　particle　concentrations　in　basal　units,　reduces　the　interference　of　concentration　on　signal　characteristics,　and　improves　the　ability　to　identify　basal　unit;　and　3)　it　provides　weights　related　to　signal　feature　recognition　and　calculates　a　composite　recognition　result　that　automatically　identifies　basal　units.　To　validate　the　method＇s　effectiveness,　we　applied　it　to　airborne　RES　data　collected　in　recent　years　from　the　Gamburtsev　Subglacial　Mountains　(GSMs)　and　Princess　Elizabeth　Land　(PEL)　regions　in　East　Antarctica.　A　comparative　analysis　of　the　new　method　and　previous　methods　indicates　more　accurate　basal　unit　identification　due　to　stronger　resistance　to　interference　from　backscatter　consistent　with　high　particle　concentrations.