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This paper will apply various joint time-frequency (JTF) and wavelet techniques to extract features from shockwave and muzzle blast signatures for the purpose of classification. The techniques used will include short-time Fourier transform (STFT), Smoothed Pseudo Wigner-Ville distribution (SPWVD) and wavelet multi-scale analysis. A projectile's trajectory can be estimated by measuring the arrival times of the acoustic energy at several locations in space. In the case of a supersonic projectile fired from a gun, both the acoustic shockwave and muzzle blast may be observed. For acoustic sensor systems attempting to determine a projectile's trajectory, the challenge is to first, correctly classify the transient signal as either a shockwave or a muzzle blast and then, calculate the direction-of-arrival via appropriate arrival times across a sensor array. This can be extremely challenging when the shockwave has lost substantial high frequency content. The change in spectral characteristics can stem from propagation over a long distance, propagation over snow covered terrain or arriving from a non-perfect reflector. An incorrect classification will result in large estimation errors of the projectile's trajectory. Experimental results are presented for proper classification over various miss distances from the sensors for all of the above techniques mentioned.