Visible to the public Indoor Silent Object Localization using Ambient Acoustic Noise Fingerprinting

TitleIndoor Silent Object Localization using Ambient Acoustic Noise Fingerprinting
Publication TypeConference Paper
Year of Publication2020
AuthorsJiang, M., Lundgren, J., Pasha, S., Carratù, M., Liguori, C., Thungström, G.
Conference Name2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
Date PublishedMay 2020
ISBN Number978-1-7281-4460-3
Keywordsacoustic, Acoustic Fingerprints, acoustic noise, Acoustic signal processing, ambient acoustic noise fingerprinting, composability, Fingerprinting, Human Behavior, Indoor, indoor radio, indoor silent object localization, lateral localization, localization, microphones, Noise, noise absorption characteristic, noise signal, object position, pubcrawl, resilience, Resiliency, signal denoising, Silent object, stationary sound sources, subtraction method

Indoor localization has been a popular research subject in recent years. Usually, object localization using sound involves devices on the objects, acquiring data from stationary sound sources, or by localizing the objects with external sensors when the object generates sounds. Indoor localization systems using microphones have traditionally also used systems with several microphones, setting the limitations on cost efficiency and required space for the systems. In this paper, the goal is to investigate whether it is possible for a stationary system to localize a silent object in a room, with only one microphone and ambient noise as information carrier. A subtraction method has been combined with a fingerprint technique, to define and distinguish the noise absorption characteristic of the silent object in the frequency domain for different object positions. The absorption characteristics of several positions of the object is taken as comparison references, serving as fingerprints of known positions for an object. With the experiment result, the tentative idea has been verified as feasible, and noise signal based lateral localization of silent objects can be achieved.

Citation Keyjiang_indoor_2020