Attributed relational tree approach to signal classification

An automatic method for target identification which uses a pattern recognition algorithm to analyse an ensemble of range image profiles is presented. Such profiles are typical of those produced by high resolution radar and sonar systems employing pulse compression techniques. The approach uses an attributed relational tree model to characterise features extracted from the waveform image profile. The algorithm is capable of learning generic models for each type of target during a supervised training session. Targets are then classified by matching tree models to a database of stored prototypes using a dynamic programming alignment algorithm. Probability attributes are used to model the large amount of scan to scan distortion in the signal caused by target motion. An experimental system has been implemented, and results derived from real data show that a high classification rate can be achieved