The　ambient　pressure　is　an　important　indicator　for　ensuring　stable　and　efficient　testing　of　the　aeroengine　in　the　high-altitude　test　(HAT)　facilities.　With　the　complex　and　quickly　changing　test　environment　and　storage　limitation　of　the　underlying　hardware,　processing　the　pressure　signals　to　access　its　filtering　and　differentiating　signals　to　participate　in　designing　feedback　controller　becomes　difficult.　The　integration　step　of　a　differentiator　algorithm,　which　is　typically　closely　related　to　the　sampling　period,　affects　the　performances　of　filtering　and　differentiating.　In　this　work,　a　feature　recognition　based　adaptive　algorithm　is　proposed　to　enable　the　tracking　differentiator　(TD)　by　adaptively　selecting　an　appropriate　integration　step　in　real-time.　In　particular,　the　sampled　signals　are　transformed　into　images　and　analyzed　by　a　proposed　feature　recognition　algorithm.　This　algorithm　can　transform　the　real-time　signals　into　an　indice　of　system＇s　dynamic　characteristic.　Simulation　and　experiment　results　show　that　the　proposed　adaptive　TD　algorithm　can　effectively　improve　the　filtering　and　differentiating　performances　compared　with　the　original　TD,　and　meet　the　signal　processing　requirements　of　HAT facilities.　©　2025　The　Author(s).　IET　Control　Theory　&　Applications　published　by　John　Wiley　&　Sons　Ltd　on　behalf　of　The　Institution　of　Engineering　and　Technology.