Wi-Fi Positioning Based on Fourier Descriptors

Location Fingerprinting (LF) is a common Wi-Fi positioning method, which locates a device by accessing a pre-recorded database containing the location fingerprint (i.e., the received signal strengths and coordinates). Most LF methods use the absolute received signal strength (RSS) to estimate the location. There are two drawbacks for using the absolute RSS. First, the absolute RSS in a time interval may not be representable of the IEEE 802.11 signal, as the signal may fluctuate. Second, a manual error-pone calibration is needed across different mobile platform. In this paper, we proposed to use Fourier descriptors in LF. We first transform the IEEE 802.11b Wi-Fi signal into a Fourier domain. Then, the Fourier descriptors are used to estimate the location by applying the K-Nearest Neighbor algorithm. Our experimental results show that the effectiveness of LF methods based on Fourier descriptors lead to substantially more accurate and robust localization.