Apparent beacon position estimation for accuracy improvement in lateration positioning system

Ciężkowski, Maciej; Romaniuk, Slawomir; Wolniakowski, Adam

doi:10.1016/j.measurement.2019.107400

Cited by 7 publications

(4 citation statements)

References 16 publications

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“…2 (10) where (X i , Y i ) are the apparent positions of the beacons and d ij correspond to the beaconreceiver distances measurements taken by the UWB receiver placed at points P j . We refer the reader to [22] for a more detailed description of the algorithm.…”

Section: Apparent Beacon Position Estimationmentioning

confidence: 99%

“…In further research, we developed a calibration method for a lateration positioning system based on measuring beacon-receiver distances. According to measurements based on lateration and known reference positions of the receivers, the proposed method estimates unknown positions of the beacons (i.e., apparent positions) and compensates for the static errors [22].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Hybrid NN-ABPE-Based Calibration Method for Improving Accuracy of Lateration Positioning System

Petrović

Ciężkowski

Romaniuk

et al. 2021

Sensors

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Positioning systems based on the lateration method utilize distance measurements and the knowledge of the location of the beacons to estimate the position of the target object. Although most of the global positioning techniques rely on beacons whose locations are known a priori, miscellaneous factors and disturbances such as obstacles, reflections, signal propagation speed, the orientation of antennas, measurement offsets of the beacons hardware, electromagnetic noise, or delays can affect the measurement accuracy. In this paper, we propose a novel hybrid calibration method based on Neural Networks (NN) and Apparent Beacon Position Estimation (ABPE) to improve the accuracy of a lateration positioning system. The main idea of the proposed method is to use a two-step position correction pipeline that first performs the ABPE step to estimate the perceived positions of the beacons that are used in the standard position estimation algorithm and then corrects these initial estimates by filtering them with a multi-layer feed-forward neural network in the second step. In order to find an optimal neural network, 16 NN architectures with 10 learning algorithms and 12 different activation functions for hidden layers were implemented and tested in the MATLAB environment. The best training outcomes for NNs were then employed in two real-world indoor scenarios: without and with obstacles. With the aim to validate the proposed methodology in a scenario where a fast set-up of the system is desired, we tested eight different uniform sampling patterns to establish the influence of the number of the training samples on the accuracy of the system. The experimental results show that the proposed hybrid NN-ABPE method can achieve a high level of accuracy even in scenarios when a small number of calibration reference points are measured.

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Section: Apparent Beacon Position Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid NN-ABPE-Based Calibration Method for Improving Accuracy of Lateration Positioning System

Petrović

Ciężkowski

Romaniuk

et al. 2021

Sensors

Self Cite

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“…When the location of at least two receivers and the time difference of the signal arrival are known, the object location can be estimated [33], [34];  analysis of the angle of the signal arrival (Angle of Arrival, AoA). It is used in the case of UWB (Ultra Wideband) location systems [35]- [37], and it is based on locating the signal source with the use of the amplitude method and the amplitude-phase method. The necessity of using extended systems of antennas is undoubtedly a disadvantage of this solution;  using the Doppler's method, i.e., the analysis of the transmitted and the received signal frequency, also called FDoA (Frequency Difference of Arrival).…”

Section: Introductionmentioning

confidence: 99%

“…In such cases, the multilateration technique is applied for this reason. It is based on the measurement of the RSSI signal value, the absolute time of the signal arrival from the transmitter to the remote ToA receiver, or the estimation of the differences in the signal arrival times at remotely located transmitting-receiving devices [16], [37].…”

Section: Introductionmentioning

confidence: 99%

Indoor Positioning Based on Bluetooth RSSI Mean Estimator for the Evacuation Supervision System Application

Janczak,

Walendziuk,

Sadowski

et al. 2024

IEEE Access

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Positioning precision analysis of passive phased array radar localization for construction safety monitoring in a non-line-of-sight environment via heatmap

Zhou

Jiang

et al. 2022

Measurement

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Apparent beacon position estimation for accuracy improvement in lateration positioning system

Cited by 7 publications

References 16 publications

A Novel Hybrid NN-ABPE-Based Calibration Method for Improving Accuracy of Lateration Positioning System

A Novel Hybrid NN-ABPE-Based Calibration Method for Improving Accuracy of Lateration Positioning System

Indoor Positioning Based on Bluetooth RSSI Mean Estimator for the Evacuation Supervision System Application

Positioning precision analysis of passive phased array radar localization for construction safety monitoring in a non-line-of-sight environment via heatmap

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