Filtering the results of ZigBee distance measurements with RANSAC algorithm

Abstract

Positioning systems are usually based on the satellite observations. However the traditional satellite positioning has some outage, it cannot be used inside buildings or underground. But there are some new technologies that allow for indoor positioning. Among those methods, there is a conception of the RF ranging technology. There are two basic methods of obtaining the distance in RF networks -time of flight (and its variations) and RSSI-based algorithms. The new method to obtain a distance between nodes in RF network is a new ranging approach based on the phase shift measurement. Analyzing the results of the measurements performed with this new technology, it was observed that a large number of them significantly differ from the reference value. Thus, in order to obtain correct distance filtering of the measurement results must be introduced to "smooth" the results. There is a necessity to find an algorithm that filters the observations. The authors present a proposition to use the RANSAC algorithm in the filtration process. In this paper the strategy of the use of RANSAC algorithm was presented. Analyzing the results of the measurement it was observed that a large number of measure distances are disturbed and significantly different from the reference value (test value). Thus to obtain the correct distance, filtering of the measurement results must be introduced in order to "smooth" the results. The authors present a RANSAC algorithm that allows to find the correct solution in noisy data. ARTICLE INFO EXPERIMENT SETUP DESCRIPTION

A Robust Noise Mitigation Method for the Mobile RFID Location in Built Environment

“…On the other hand, the synthetic noise in mobile localization scheme is difficult to model for the traditional method. As many works of literature proposed [20,28], RANSAC-based noise robust mitigation framework for the mobile localization scheme still has two phases: Hypothesis and model verification.…”

“…The parameter min_samples means the minimum sample size of sampling subsets. Many pieces of the literature suggest that parameters should be as small as possible [20,27,28]. Therefore, for the hypothesis model in Equation (7), the value of min_samples is set to 2.…”

“…Random sample consensus (RANSAC) is a more robust noise mitigation method to yield very good results [13,19,20], which is widely used in building panel productions management [21], localization technologies [13,22], and other domains. Except for the RFID-based localization, RANSAC method was also used in GNSS-based and sound-based localization schema [23,24].…”

“…For example, the RANSAC method was used to estimate the parameters of RSSI-range localization models [22]. Researchers also used the RANSAC method to identify and filter outlier measurements [20]. Although RANSAC method is robust, many variants were developed aiming at increasing accuracy and efficiency.…”

The Analyzes of PDOP Factors for a Zigbee Ground – Based Augmentation Systems

“…Despite the main purpose of ZigBee devices (which is wireless communication), some devices are equipped with ranging capabilities. Successful tests of such a device are presented in [15,18,19] AT233RF device presented in those papers can measure a distance with decimeter accuracy in the ~300 meters range. The application of such a device next to the ships GNSS antenna can significantly improve the availability and accuracy of positioning in the area covered with the ZigBee signals.…”