Performance Test of MPMD Matching Algorithm for Geomagnetic and RFID Combined Underground Positioning

It is important that precise positioning and navigation of underground personnel for intelligent hedging and mine rescue in mine accidents or disasters. At present, there are many passive positioning methods such as RFID, Zigbee and other positioning products in the underground, which cannot work normally while there is power supply interruption or signal interruption in the underground. GRPM is a new active underground positioning method combining radio frequency identification and geomagnetic matching technology, which the positioning accuracy reach to the sub-meter level when the miner with the GRPM device in the underground. Geomagnetic matching algorithm is the core technology of GRPM, and its performance directly affects the accuracy of the geomagnetic positioning. For the MSD, MAD and PORD matching algorithms have low precision in geomagnetic matching localization; it is proposed a novel matching algorithm named MPMD to achieve underground geomagnetic precise positioning in this paper which is an optimal estimation of the eigenvector product of underground two magnetic variables. The matching test of underground geomagnetic positioning for the performance of MPMD algorithm was carried out in 9 tunnels about 150 meters long and 6 meters wide in mine. The geomagnetic data of the total magnetic field and the three axis component are measured with the portable FVM400 fluxgate magnetometer. MSD, MAD and MPMD algorithms were used to matching test for analyzed their effective matching length, positioning error, noise immunity. The test result shows that the MPMD algorithm has the advantages of minimum matching position error and better noise immunity than MSD, MAD matching algorithms under the same experimental conditions. It is suitable for the complications of underground geomagnetic spatial distribution, and meets the requirements of underground emergency refuge and navigation. However, matching process of MPMD algorithm is time-consuming, it can be further improved the search space and search strategy in later research.