On the Impact of Node Placement and Profile Point Selection on Indoor Localization

Abstract

Abstract. We present an indoor localization technique based on RF profiling using the received signal strength (RSS) measurements from a set of pre-selected reference points. We do not attach any interpretative significance to the measurements other than use them to calculate their difference from the measurements of the reference points. We study the performance of our technique in an environment with multiple adjacent rooms and find that it gives better results compared to the application of the k-Nearest Neighbor algorithm that has been used in the literature for the same task. We also study the proposed scheme and two other well-known localization schemes, with respect to the sensitivity of the localization on the number and layout of the reference points, as well as on the number and layout of the deployed fixed points (pegs) from where the measurements are collected. We find that one can achieve good localization performance with either fewer reference points or with fewer pegs as long as their layout is chosen carefully.

Wireless indoor positioning: Effective deployment of cells and auto-calibration

“…The system for positioning is based on the fingerprinting technique, with a wkNN algorithm, using k = 4 neighbors, as recommended in [8]. The radiomap grid resolution is 1 meter (X axis separation) by 0.65 meters (Y axis separation).…”

“…Abundant research has been conducted in relation to optimizing the deployment of stations for mobile technology, and as seen in previous research, special consideration has been given to the voice and data requirements (for example, [13]). However, there have been a limited number of studies published on location service requirements that offer some guidelines or applicable results (as [2] or [8]). Our investigation starts here because this is a relatively unexplored field.…”

Evaluation of RSS-based Position Tracking using WSNs for Resource Localization in an Indoor Construction Environment

“…Given that the ranges between a mobile node and three or more stationary nodes are determined, the location of the mobile node can be calculated by applying the geometric multilateration algorithm. RSSI-based ranging is low-cost and simple to implement and does not require expensive, specialized, infrastructure (Haque et al, 2009).…”

“…An alternative to range-based localization is rangefree localization. An example of a range-free localization is LEMON (Haque et al, 2009). It consists of two phases: 1) profiling and 2) actual localization.…”