Indoor positioning using multi-frequency RSS with foot-mounted INS

Abstract

Abstract-This paper presents a system which combines a zero-velocity-update-(ZUPT-)aided inertial navigation system (INS), using a foot-mounted inertial measurement unit (IMU), with opportunistic use of multi-frequency received signal strength (RSS) measurements. The system does not rely on maps or pre-collected data from surveys of the radio-frequency (RF) environment. Instead it builds its own database of collected RSS measurements during the course of the operation. New RSS measurements are continuously compared with the stored values in the database, and when the user returns to a previously visited area this can thus be detected. This enables loop-closures to be detected online and used for error drift correction. The system utilises a distributed particle simultaneous localization and mapping (DP-SLAM) algorithm which provides a flexible 2D navigation platform that can be extended with more sensors. The experimental results presented in this paper indicates that the developed RSS SLAM algorithm can, in many cases, significantly improve the positioning performance of a foot-mounted INS.

Indoor localization using multi-frequency RSS

“…One motivation for this paper was the good SLAM results of the thesis work in [22], also reported in [14], and the need to better understand the underlying signals. Below, the usefulness of GP for the signals and the uniqueness of fingerprints are analysed, leading up an assesment of their use in SLAM especially collaborative SLAM.…”

“…Still, some students were moving around in the corridors during the measurements probably affecting the data. One of the university sites have measurements in corridors that overlap with the experiments in [14] providing the possibility to analyze these results further.…”

“…A few sites have a unique fingerprint but in the majority of cases the fingerprint can be reasonably well matched in more places than one resulting in multimodal posterior densities. This indicate that batch solutions that are working with the whole sequence, or other methods working on the whole succession of fingerprints, such as the particle filter solution in [14], and can handle temporary position ambiguities are probably more successful. As noted in [23] deep fades from fast fading effects could present a challenge for single fingerprints.…”

“…The indoor localization system in [10] uses a floor attenuation factor propagation model in favor of Rayleigh fading [11] or Rician distribution [12]. In more recent work [3,9,13,14] Gaussian processes are used to model the RSS, and [15] also models the signals source location.…”

“…In our previous work [14] a RSS SLAM system with with foot mounted (INS) was designed, and shown to be successful. However, the added value of using multi-frequency RSS from opportunistic signals in this SLAM solution is difficult to separate from the contribution of the foot-mounted INS subsystem and the filtering solution itself.…”