Airborne　observation　is　an　important　approach　to　collect　data　in　the　remote,　hostile　Antarctica　and　study　the　relationship　between　the　Antarctica　and　global　climate.　During　airborne　observations,　it　is　necessary　to　conduct　data　processing　and　quality　control　on　site,　which　can　help　to　timely　evaluate　the　status　of　airborne　instruments,　provide　scientific　clues,　and　develop　ideal　schemes　for　following　airborne　observations.　As　one　critical　component　of　airborne　instruments,　airborne　ice　sounding　radar　can　delineate　sub-ice　bedrock　topography　and　internal　layers,　which　cannot　be　realized　by　other　instruments.　In　this　study,　we　present　an　on-site　data　processing　algorithm　for　high-resolution　and　high　signal-to-noise　ratio　(SNR)　ice　sounding　radar　data　acquired　by　the　＇Snow　Eagle　601＇,　the　first　fixed-wing　airplane　deployed　by　China　for　the　Antarctic　expeditions.　In　addition,　the　algorithm　is　further　optimized　in　terms　of　static　pre-allocated　memory　and　parallel　and　block　processing　of　data　to　enhance　processing　speed　and　meet　the　requirements　for　quality　control　and　analysis　of　on-site　data.　Finally,　we　test　the　optimized　algorithm　with　different　volume　of　ice　sounding　radar　data　through　implementing　on　different　computer　configurations,　including　i7,　i5　CPU　and　8G,　16G　memory　with　the　same　disk.　The　results　show　that　the　average　processing　speed　of　the　optimized　algorithm　is　5.143　times　faster　than　the　non-optimized　algorithm　on　different　computer　configurations.　©　2021　International　Archives　of　the　Photogrammetry,　Remote　Sensing　and　Spatial　Information　Sciences　-　ISPRS　Archives.　All　rights　reserved.