Multipath-Assisted Smartphone Tracking Using a Single Speaker and a Built-In Monaural Microphone

Abstract

The use of location data offers significant convenience in both daily life and industry. However, global positioning system (GPS) is not effective indoors, so alternative technologies are necessary. Current positioning technologies require multiple transmitters and receivers or precollected data, leading to high installation and implementation costs. Our study presents a low-cost tracking method that utilizes a single speaker installed on the ceiling and a smartphone’s monaural microphone. We leverage reflected waves from the walls and floor, treating them as signals from virtual speakers at the mirror-image positions of these surfaces. This approach ensures the generation of necessary signals for positioning and allows for accurate tracking using only a single speaker. However, as all the reflected waves are quite similar, it becomes challenging to associate each reflected wave with its corresponding virtual speaker. We designed an evaluation function to address this, considering real-world challenges, such as undetected reflected waves, outliers, and overlapping signals. We evaluate the correspondence between the prediction and the observation using a likelihood function, weighted by the number of outliers. When the reflected signals are overlapped, we introduce ambiguity by increasing the variance of the normal distribution. Our method accurately identifies reflected waves and estimates the target’s trajectory with precision. We evaluated the method under varying conditions across multiple paths, achieving positioning accuracy with a 50th percentile error of 0.34 m and a 90th percentile error of 0.64 m. This led to a 62% performance improvement compared to the scenario that does not account for real-world challenges.