Location Tracking of a Radio-Wave Antenna Utilizing the Radiation Pattern Recognized by Deep Network

This paper will introduce a radio frequency system to track the location of a stent designed to work inside a human artery. The stent is designed as a hemostasis aid tool for emergency situations where common surgical equipment, such as fluoroscopy systems, is not available, such as on the battlefield. In the application of interest, the stent must be guided to the correct location to achieve effective hemostasis and prevent complications. The locating approach uses the radiation pattern from the transmitter as the reference. When the transmitting frequency changes over a certain range, the measurement amplitude from a receiver depends on its relative location with respect to the transmitter. However, when the input frequency is unequal to the resonance frequency, the radiation pattern varies in an unpredictable way. To solve this problem, a deep learning model was trained to recognize variations in the radiation pattern and predict the receiver's location as one of the classes in the reference grid. The deep learning model also reduces the impact of noise and disturbing signals, which effectively improves the system's robustness.