Physically Based Simulation Model for Acoustic Sensor Robot Navigation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Spatial Sampling Criterion for Sonar Obstacle Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Differentiating Sonar Reflections from Corners and Planes by Employing an Intelligent Sensor
IEEE Transactions on Pattern Analysis and Machine Intelligence
A physically based navigation strategy for sonar-guided vehicles
International Journal of Robotics Research
Building a Sonar Map in a Specular Environment Using a Single Mobile Sensor
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection, Estimation, and Modulation Theory: Radar-Sonar Signal Processing and Gaussian Signals in Noise
Digital Picture Processing
A Probabilistic Approach to the Coupled Reconstruction and Restoration of Underwater Acoustic Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
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A physical model-based analysis of unstructured environments is presented using sonar as a sensing device. Previous methods have relied only on time-of-flight (TOF) methods and have examined only homogenous environments consisting of either smooth or rough surfaces. In this paper, a forward model for the reflection from a class of surfaces with varying degrees of roughness is presented based on the Kirchhoff approximation method. This model integrates different types of environments into a single analytical framework. The echo intensity is parametrized in terms of its energy content and duration, which are functions of the surface roughness, distance, and orientation. The echo-energy and echo-duration maps are introduced to display these parameters. A systematic and robust procedure (ENDURA method) is presented to analyze the reflections and to differentiate and localize the reflecting surfaces. The methodology is verified with experimental results obtained in our laboratory. The results indicate a significant improvement over conventional TOF systems.