Research on multi-source data fusion positioning algorithm for coal mine roadway

Abstract

In the non-line-of-sight condition of coal mine roadway, the use of time of flight(TOF) positioning algorithm or received signal strength（RSS） algorithm alone has problems such as inaccurate direction judgement and large positioning errors; TOF positioning algorithm combined with RSS positioning algorithm, although accuracy of direction judgement is improved compared with the single TOF algorithm, the judgement of tags in non-line-of-sight motion scenes is still not accurate enough, and the positioning track is not smooth enough.In view of the above problems, a multi-source data fusion positioning algorithm based on TOF, RSS and polynomial interpolation prediction(PIM) was proposed. The algorithm first measures TOF between label and positioning base station and calculates RSS, then uses PIM to fit and forecast label position at the current moment combined with historical location data, and according to the combination of predicted position, TOF and RSS, the direction of the tag relative to the base station is determined. Finally, the positioning result is optimized by weighted data fusion, so as to improve positioning stability and accuracy. The experimental results show that compared with the single TOF positioning algorithm or RSS algorithm, the proposed algorithm can effectively improve accuracy and stability of the positioning system, and can more accurately determine direction of the tag relative to the base station, and direction determination accuracy is above 99%.

Keywords

• coal mine underground precise positioning
• positioning base station
• direction determination
• time of flight
• received signal strength
• interpolation prediction
• multi-source data fusio