Physical modeling for radar and ultrasonic sensors

摘要

A machine learning module may generate a probability distribution from training data that includes tagged modeling data that is correlated with reflection data. Modeling data may include data from a LIDAR system, a camera and / or a GPS for a target environment / object. Reflection data may be collected from the same environment / object by a radar and / or ultrasound system. The probability distribution may associate reflection coefficients for radar and / or ultrasound systems that depend on values for modeling data. An imaging module may generate a reflection module to superimpose a virtual environment that is assembled from a second set of modeling data by applying the second set to the probability distribution to associate reflection data with surfaces within the virtual environment. In addition, a test bench may evaluate an algorithm with simulated reflection data from a virtual sensor detecting reflectance values assigned within the virtual environment to process reflection data to generate control signals to an autonomous vehicle.