Distinction between objects with ultrasonic biaural system and only amplitude

This study investigates the processing of sonar signal using statistical methods (quadratic and linear) for differentiation of commonly encountered features in indoor robot environments. Statistical method can differentiate two targets (Plane and Corner) with higher accuracy, improving on previously reported methods. It achieves this by exploiting identifying echo features: the differential frequency, length, amplitude and time-of-flight (TOF) characteristics of these targets. The features extraction is also studied and the reduction of parameters is obtained with a SBS (Sequential Backward Selection) approach. The results indicate that the amplitude information is more crucial than other features. The study suggests a wider use of statistical methods and amplitude information in sonar-based mobile robotics.