Abstract
In this paper, we present a novel, low-cost approach to indoor localization that is capable of performing localization processes in real indoor environments and does not require calibration or recalibration procedures. To this end, we propose a single-anchor architecture and design based on an electronically steerable parasitic array radiator (ESPAR) antenna and Nordic Semiconductor nRF52840 utilizing Bluetooth Low Energy (BLE) protocol. The proposed algorithm relies on received signal strength (RSS) values measured by the receiver equipped with the ESPAR antenna for every considered antenna radiation pattern. The calibration-free concept is achieved by using inexpensive BLE nodes installed in known positions on the walls of the test room and acting as reference nodes for the positioning algorithm. Measurements performed in the indoor environment show that the proposed approach can successfully provide positioning results better than those previously reported for single-anchor ESPAR antenna localization systems employing the classical fingerprinting method and relying on time-consuming calibration procedures.
Highlights
Positioning and navigation systems play an important role in daily lives, since global navigation satellite system (GNSS) applications cover a number of different location-based services, such as wildlife protection, road applications, and security and safety [1]
We propose a novel, low-complexity received signal strength (RSS)-based method of radio frequency (RF)-based indoor positioning using electronically steerable parasitic array radiator (ESPAR) antennas that is dedicated to wireless sensor network (WSN) applications
The results show that in the proposed setup, there is noticeable angular diversity between the directions of ESPAR antenna radiation patterns, which is necessary for the proposed single-anchor positioning process
Summary
Positioning and navigation systems play an important role in daily lives, since global navigation satellite system (GNSS) applications cover a number of different location-based services, such as wildlife protection, road applications, and security and safety [1]. In large areas, the calibration phase might be time- and effort-consuming, since the density of the radio map impacts the accuracy of the final estimation This can be minimized through the utilization of the channel state information (CSI) [19], which includes the amplitude and phase of each orthogonal frequency-division multiplexing (OFDM) channel subcarrier [15] to improve the estimation accuracy in locations outside of the reference points. This approach requires much higher computational power to perform the signal processing, making the system more expensive, and it is not applicable in BLE.
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