Abstract A binaural sonar configuration with capability to detect and identify walls, edges and corners on real-time is presented in this work. A new multi-echo ultra-fast firing method increases the sonar acquisition rate, and provides crossed measurements without interference. A feature map is built on-line using Bayesian updating and classification rules. Three classifiers are implemented and analyzed: minimum risk (MR), maximum a posteriori (MAP), and minimum distance (MD). Experimental results of ultrasonic reflector recognition, using data collected in a specular indoor environment are presented in the paper.
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