Using Kalman Filters to Reduce Noise from RFID Location System

Abstract

Nowadays, there are many technologies that support location systems involving intrusive and nonintrusive equipment and also varying in terms of precision, range, and cost. However, the developers some time neglect the noise introduced by these systems, which prevents these systems from reaching their full potential. Focused on this problem, in this research work a comparison study between three different filters was performed in order to reduce the noise introduced by a location system based on RFID UWB technology with an associated error of approximately 18 cm. To achieve this goal, a set of experiments was devised and executed using a miniature train moving at constant velocity in a scenario with two distinct shapes—linear and oval. Also, this train was equipped with a varying number of active tags. The obtained results proved that the Kalman Filter achieved better results when compared to the other two filters. Also, this filter increases the performance of the location system by 15% and 12% for the linear and oval paths respectively, when using one tag. For a multiple tags and oval shape similar results were obtained (11–13% of improvement).

Reducing the spread of COVID‐19 in road traffic control in Cameroon based on ICT

“…The Kalman filter is an algorithm that estimates the state of a system from measured data (Abreu et al, 2014). It was mainly developed by the engineer Rudolf Kalman.…”

“…This is obviously inappropriate. More importantly, the basic linear Kalman filter can operate smoothly and easily on the DR task on the resource-limited portable RFID reference positioning device (Abreu et al, 2014). 2), it appears that the Kalman filter is much better than the probability method in terms of repulsion interpretation time.…”

“…According to Abreu et al (2014) and Alsalamat et al (2022), bilateration is defined as a method of determining an isolated point M by measuring distances from two known points A, B, without measuring angles. Trilateration is the use of distances (or ranges) for determining the unknown position coordinates of a point of interest, often around Earth (geopositioning).…”

“…This is obviously inappropriate. More importantly, the basic linear Kalman filter can operate smoothly and easily on the DR task on the resource‐limited portable RFID reference positioning device (Abreu et al, 2014).…”

A Low-Cost Collaborative Location Scheme with GNSS and RFID for the Internet of Things

“…In the range-based RFID location scheme, many distance measurement technologies are proposed for calculating location. Those classical technologies include the angle of arrival (AOA) [13], the time of arrival (TOA) [14], the time difference of arrival (TDOA) [15], the received signal strength indicator (RSSI) [16], and the received signal phase (RSP) [17]. Although it can usually achieve sufficient location accuracy, there are a couple of drawbacks.…”