Ground Surveillance Radar Targets Classification Using Wald Sequential Test

In this research the Wald sequential test is applied for ground surveillance radar real signal classification. Central Doppler frequency and spectrum width around it are used as features for classification. The classification of signal from vehicle apart from all other classes is performed. For estimation of the probability density function, the Parzen method is used. Conducted results show that the Wald sequential test could be applied to classification of radar signals whose duration is 0.5 seconds, with average number of observation for signals that origin from vehicle 1.61, and for signals that origin from other classes 1.22.