Predicting the Distance of Objects in the Blind Zone of an Ultrasonic Array

This study is driven by the primary goal of mitigating ultrasound signal interference within blind spots. The presence of overlapping ultrasound signals and objects often leads to erroneous object detection due to the convergence of reflected waves and accumulated reverberations from obstacles, thus creating a blind zone for ultrasound signals. Consequently, measurements conducted within this region frequently yield inaccuracies in judgment and distance estimation. To address these challenges, this research advocates the implementation of an array wall constructed from multiple ultrasound transducers as a foundational solution. The design of this array wall is intricately crafted based on considerations of diffusion angles and directional coefficients within the sound field. The proposed approach involves the emission and collection of multiple signals for comprehensive analysis, facilitated by a distributed computing architecture for signal processing and visualization. By adopting this innovative methodology, the study aims to achieve effective object identification within the blind zone. Furthermore, the research endeavors to develop a prototype system for object detection within blind spots and path planning. To validate the effectiveness of this solution, the Google Maps API will be utilized, shedding light on the challenges associated with measuring distances using ultrasound signals in blind spots.