AIM: Acoustic Imaging on a Mobile (MobiSys'18)
The popularity of smartphones has grown at an unprecedented rate, which makes smartphone based imaging especially appealing. In this work, a novel acoustic imaging system called AIM is developed using only an off-the-shelf smartphone. It is an attractive alternative to camera based imaging under darkness and obstruction. AIM is based on Synthetic Aperture Radar (SAR). To image an object, a user moves a phone along a predefined trajectory to mimic a virtual sensor array. SAR based imaging poses several new challenges in this context, including strong self and background interference, deviation from the desired trajectory due to hand jitters, and severe speaker/microphone distortion. These challenges were addressed by developing a 2-stage interference cancellation scheme, a new algorithm to compensate trajectory errors, and an effective method to minimize the impact of signal distortion. A proof-of-concept prototype is implemented on Samsung S7. Results demonstrate the feasibility and effectiveness of acoustic imaging on a mobile.