Coal mine underground positioning algorithm based on RSSI model correction and node cooperation

• Autorzy: Qiao Xin , Chang Fei , Wang Jing , Wang Xiuying , Jiang Yun

Identyfikatory

DOI

10.24425/ams.2025.154162

• Języki publikacji: EN

Abstrakty

EN

To address the issues of environmental complexity and low positioning accuracy faced by coal mine underground positioning systems, an improved localisation algorithm based on Received Signal Strength Indication (RSSI) model correction and node collaboration, namely, the RSSI-MCNC (RSSI Model Correction and Node Collaboration) algorithm, is proposed. First, this algorithm employs Kalman filter technology to optimise the collected RSSI values, improving signal stability and range model accuracy. Second, more precise ranging results are achieved by dynamically adjusting the RSSI model parameters to adapt to changes in mining environments. In the localisation stage, the localised unknown nodes are used as cooperative nodes to position other unknown nodes and solve the objective function through the improved weighted centroid algorithm and gradient descent method, precisely locating the unknown nodes. The simulation results indicate that the RSSI-MCNC algorithm can significantly improve the positioning coverage and accuracy of fixed anchor nodes and the random distribution of unknown nodes in mine roadways, especially in the case of limited anchor nodes. This is significant for improving the safety of mine personnel and equipment.

Słowa kluczowe

EN

coal mine underground; model correction; node collaboration; Kalman filter; objective function

PL

kopalnia węgla; filtr Kalmana; bezpieczeństwo kopalni

• Wydawca: Instytut Mechaniki Górotworu PAN
• Czasopismo: Archives of Mining Sciences
• Rocznik: 2025
• Tom: Vol. 70, no. 1
• Strony: 45--62
• Opis fizyczny: Bibliogr. 25 poz., rys., wykr.

Twórcy

autor

Qiao Xin

• Chaohu University, School of Electronic Engineering, Chaohu, Anhui, 238000, China

• https://orcid.org/0009-0003-6868-3768

autor

Chang Fei

• Huishang Futures Co. Lt d., Hefei, Anhui, 230061, China

• https://orcid.org/0009-0000-6502-8045

autor

Wang Jing

• Chaohu University, School of Electronic Engineering, Chaohu, Anhui, 238000, China

• https://orcid.org/0009-0005-6824-9675

autor

Wang Xiuying

• Chaohu University, School of Electronic Engineering, Chaohu, Anhui, 238000, China

• https://orcid.org/0009-0007-1846-3264

autor

Jiang Yun

• Chaohu University, School of Electronic Engineering, Chaohu, Anhui, 238000, China

• https://orcid.org/0009-0007-6929-4923

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025)