PROBLEM TO BE SOLVED: To provide an automatic object classifying device and its method in which the frequency of wrong classification is minimized, compared with prior arts. SOLUTION: In order to automatically classify an object by Doppler widened radar echo signal, a nerve network having one output node for each class. An automatic object classifying device by Doppler widened radar echo signal has a neural network(NET) having an input layer (KL) having input nodes (IN1,...IN48) to the characteristics of Doppler widened radar echo signal and an output layer(OL) having output nodes (ON1,...ON5; ON1,...ON6) to classes (K1, K2; K) to which an object can be assigned. At least one of the classes (K1, K2; K) is divided into each sub-class (U11, U12, U21, U22, U23; U1,...U4), and the output nodes (NO1,...NO5; NO1,...NO6) are present for each sub-class (U11, U12, U21, U22, U23; U1,...U4). According to such a structure, the frequency of wrong classification can be reduced.
AUTOMATIC OBJECT CLASSIFYING DEVICE AND AUTOMATIC CLASSIFYING METHOD THEREOF