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Biologists have discovered a kind of weakly electric fish that identifies its prey by using active electrolocation in virtual darkness. In this study, we built an underwater active electrolocation system platform designed to investigate the biological mechanism allowing these fish to distinguish objects and determine how the amplitude information-frequency characteristic (AIFC) response are affected by the geometric characteristics of target objects in the active electrolocation system. We used a single-frequency sinusoidal signal to scan metal objects in different orientations and observed the amplitude information response variation of the disturbed detection signal. The detection frequency dead zone (DFDZ) and the frequency inflection point (FIP) were used to characterize the variation. In addition, we repeated the experiments after replacing the metal objects with objects of different materials and geometric characteristics to summarize the general laws. Our results showed that the FIP value of the detection signal was lowest when the object was detected in the orientation of its corner and highest when the object was detected in the orientation of its surface. The geometrical characteristics of metal objects in different orientations have a certain influence on the amplitude of the detection signal. Article Highlights: (1) The general law between the shape of metal probed objects, and electric field detection signal was found and summarized. (2) We used a single-frequency sinusoidal signal to scan regular metal probed objects, and it was found that the frequency inflection point (FIP) of the metal probed objects edge was the highest, whereas that of the corner was the lowest. (3) The shape of a metal object can be recognized by scanning regular metal objects with an electric field signal.

The Effect of Object Geometric Features on Frequency Inflection Point of Underwater Active Electrolocation System