Abstract: Aircraft information can be transmitted very distant distance by shortwave.The study was executed to recognize aircraft type by using cockpit noise contained in shortwave speech communication.The main interference for cockpit noise is channel and speech noise,which was analyzed.To evaluate cockpit noise in speech segment,SNR (Signal-to-Noise Ratio) equation was defined.To enhance cockpit noise and restrain speech,self-adaptive model was proposed.Power spectrum density level feature for different frequency band was extracted respectively by using CZT. Binary classifier tree based-on support vector machine was designed to recognize aircraft type.Some experiment on eight types' aircraft field test data was done to evaluate these methods.The average SNR after enhancing aircraft noise is improved by 22 dB.Classifier output recognition rate for noise between speech response,noise in speech segment and enhanced noise is respectively 82.79%,15.25%,50.18%.Experimental results show that,noise between speech response can be used as aircraft type recognition.Speech restrain algorithm brings bigger gain in SNR and recognition rate,which provides existent proofs of aircraft type information in speech segment.Although the recognition rate is still smaller,it can provide reference for later research progress.