Neartracker: Acoustic 2-D Target Tracking with Nearby Reflector in Siso System

Acoustic target tracking has shown significant potential for contactless human-computer interaction. However, most existing acoustic 2-D tracking approaches for portable devices require at least one speaker and two microphones, incapable for universal devices. In this paper, we propose NearTracker, a contactless acoustic tracking system, achieves 2-D target tracking with only one speaker and one microphone (i.e., Single Input Single Output, SISO). With the help of a nearby reflector, the additional valuable echoes from target are combined for positioning. Actually, the dynamic interferences from non-target echoes pose huge challenges for target echo extraction. NearTracker extracts and enhances these faint target echoes with novel signal processing methods and estimates the target’s location accurately via a designed particle filter algorithm. Extensive experiments show that our system achieves on average 1.36 cm error for 2-D target tracking, which can satisfy most devices and application scenarios.

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Neartracker: Acoustic 2-D Target Tracking with Nearby Reflector in Siso System

Semantic Scholar · Engineering · 2022

Abstract

Acoustic target tracking has shown significant potential for contactless human-computer interaction. However, most existing acoustic 2-D tracking approaches for portable devices require at least one speaker and two microphones, incapable for universal devices. In this paper, we propose NearTracker, a contactless acoustic tracking system, achieves 2-D target tracking with only one speaker and one microphone (i.e., Single Input Single Output, SISO). With the help of a nearby reflector, the additional valuable echoes from target are combined for positioning. Actually, the dynamic interferences from non-target echoes pose huge challenges for target echo extraction. NearTracker extracts and enhances these faint target echoes with novel signal processing methods and estimates the target’s location accurately via a designed particle filter algorithm. Extensive experiments show that our system achieves on average 1.36 cm error for 2-D target tracking, which can satisfy most devices and application scenarios.

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