Fuzzy clustering and enumeration of target type based on sonar returns
The fuzzy c-means (FCM) clustering algorithm is used in conjunction with a cluster validity criterion, to determine the number of different types of targets in a given environment, based on their sonar signatures. The class of each target and its location are also determined. The method is experimentally verified using real sonar returns from targets in indoor environments. A correct differentiation rate of 98% is achieved with average absolute valued localization errors of and 0.8 in range and azimuth, respectively.
target classification target differentiation target localization fuzzy c-means clustering sonar sensing