To improve the accuracy and generalization of tunnel personnel positioning systems, this article proposes a quadratic weighted centroid algorithm. By adopting a Gaussian filter model to improve the...

https://journals.sagepub.com/doi/pdf/10.1177/1550147720917021

A quadratic weighted centroid algorithm for tunnel personnel positioning

Target localization and tracking have the inseparable connection. On the one hand, localization is the basis of tracking. On the other hand, tracking can provide localization with prior information to correct the error of localization to some extent. At the same time, making the monitoring area be the grid area can let the localization and tracking system easy to be applied to different monitoring area. This paper mainly studies on the indoor passive localization and tracking in the grid area where ‘passive’ means there is no communication between sensors and the target. The indoor localization and tracking issue is modeled as a vector Kalman filtering problem. Two schemes are developed for the issue: one is based on the optimized weighted centroid algorithm and the other is based on the fingerprint algorithm. Both simulation results and real-world experimental results are used to demonstrate the effectiveness of the developed schemes.

Indoor passive localization and tracking: From theory to practice

This paper presents an indoor positioning solution based on Bluetooth low energy. The iBeacon Bluetooth base station is used as the transmitting end, and the RSSI signal strength value of each base station is collected by the mobile phone, the corrector is used to calculate the signal attenuation coefficient, the abstract coordinate space is established, and the relationship model between the distance and the signal value in the space is obtained, and the trilateral positioning algorithm is used to calculate The position coordinates of the node to be tested. The attenuation coefficient is updated in real time by the aligner to reduce the measurement error caused by environmental factors, so that the accuracy reaches 75% and above in the error range of 0.5 m. In practical applications, the abstract space is scaled according to the specific environment, and real-life positioning can be realized.

Indoor real-time three-side positioning technology based on low power consumption Bluetooth

The node localization is one of the key technologies in wireless sensor network.The centroid algorithm localization means that node self-localization relies on wireless sensor network connectivity,but error is large.In order to improve positioning precision,an optimization weighted centroid localization algorithm based on RSSI was presented in consideration of less affection by environment for centroid localization algorithm,and easy to use localization technology based on RSSI.Distance was got through RSSI,combined with optimization weighted centroid algorithm,node was located.Simulation results show that,the average error of positioning decreased,and localization precision was improved by this algorithm.

Research on optimization weighted centroid localization algorithm based on RSSI

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Research on optimization weighted centroid localization algorithm based on RSSI