Data Collection and Analysis Scripts for "Experimental Tracking of an Ultrasonic Source with Unknown Dynamics Using a Stereo Sensor".

Data Description: This data was collected using two Dodotronic Momimic microphones and a Teensy 4.0 development board. The raw data recorded are samples of incoming ultrasonic signals output by a modified senscomp ultrasonic transducer and the measured time between recorded samples. This data is used to create a measurement matrix of the estimated bearing of the ultrasonic source and the measured time between samples. These measurements are used in a linear minimum mean square error algorithm for estimating the distance of the ultrasonic source to the sensor, allowing tracking of the source. <br> Abstract of related Resource: Sound source localization (SSL) is the ability to successfully estimate the bearing and distance of a sound in space relative to the sensing position and pose. SSL as a topic of interest for engineers often revolves around the ability of robots to track other robots, human voices, or other acoustic objects. Common approaches to this goal frequently use large arrays, computationally intensive and complex machine learning methods, or require known dynamic models of a system which may not always be available. In this work we seek to experimentally verify a solution to SSL using a minimal amount of inexpensive equipment on a two microphone, i.e. stereo, sensing platform. A previously developed Bayesian estimator allows for localization of an emitter using easily available a priori information and timing data received from the sensor platform. Our results show that our approach is accurate for the tested paths and that the estimator can correct itself when dynamic assumptions are broken for short times due to hardware and software limitations.