FRI Sensing: 2D Localization from 1D Mobile Sensor Data

Sensor localization is a basic and important problem in many areas. It often relies on transmission-communication equipment to obtain the sensor geolocation information. However, in this work, on the contrary, our goal is to retrieve the 2D sensor location only from the 1D sensor data. We demonstrate that there is valuable 2D geometric information that can be unveiled hidden within the 1D sampled signal. We investigate the hypotheses needed and propose a very efficient and robust algorithm to realize this 2D localization. This method can be possibly applied to a series of biomedical applications, like robotic endoscopic capsules, medicine tracking, and biological tissue detection. For example, people inject tiny sensors about the size of a grain of sand to monitor human biometrics (like blood pH, etc) and accurate localization plays an essential role in pathological diagnosis.