Accurate target localization technology plays a very important role in ensuring mine safety production and higher production efficiency. The localization accuracy of a mine localization system is influenced by many factors. The most significant factor is the non‐line of sight (NLOS) propagation error of the localization signal between the access point (AP) and the target node (Tag). In order to improve positioning accuracy, the NLOS error must be suppressed by an optimization algorithm. However, the traditional optimization algorithms are complex and exhibit poor optimization performance. To solve this problem, this paper proposes a new method for mine time of arrival (TOA) localization based on the idea of comprehensive optimization. The proposed method utilizes particle filtering to reduce the TOA data error, and the positioning results are further optimized with fingerprinting based on the Manhattan distance. This proposed method combines the advantages of particle filtering and fingerprinting localization. It reduces algorithm complexity and has better error suppression performance. The experimental results demonstrate that, as compared to the symmetric double‐sided two‐way ranging (SDS‐TWR) method or received signal strength indication (RSSI) based fingerprinting method, the proposed method has a significantly improved localization performance, and the environment adaptability is enhanced.

WSN (wireless sensor network) is a perfect tool of temperature monitoring in coal goaf. Based on the three‐zone theory of goaf, the GtmWSN model is proposed, and its dynamic features are analyzed. Accordingly, a data transmission scheme, named DTDGD, is worked out. Firstly, sink nodes conduct dynamic grid division on the GtmWSN according to virtual semicircle. Secondly, each node will confirm to which grid it belongs based on grid number. Finally, data will be delivered to sink nodes with greedy forward and hole avoidance. Simulation results and field data showed that the GtmWSN and DTDGD satisfied the lifetime need of goaf temperature monitoring.

A deployment strategy for antennas is proposed to enhance the field coverage of wireless devices in underground coal mines, which uses the multimodal approach. Based on the attenuation coefficient of each mode, the propagation loss of the vertically polarized modes with n = 1, 2, and 3 and that of the horizontally polarized modes with m = 1, 2, and 3 are less. For the signal propagation in the near-field region of the source, these modes play significant role. According to the coupling of the antenna to the modes, the significant modes can be effectively excited by mounting horizontally polarized antenna on the ceiling or the vertically polarized antenna on the sidewall. For the signal propagation in the far-field region, the (1, 1) mode is significant, and the horizontally polarized excitation is preferred due to smaller attenuation. By comparing the total coupling efficiency of the antenna-radiated power, stronger excitation power can be obtained by mounting the antenna near the center of the ceiling or that of the sidewall. The field strength in the near-field and far-field region coverage can be maximized by optimizing the antenna polarization and position. For verification, a grid-based test system was designed and a series of measurements inside an underground coal mine tunnel were conducted. The measured results have a good agreement with the theoretical ones. In addition, the EM interference caused by the infrastructure in real mines on the signal received by the antennas at different positions was also measured and compared. Results show that the influences of cables with long-term stable loads, such as power cables and communication cables, can be neglected.

Existing wireless charging methods for one-dimensional space are not suitable for coal mine roadways due to the crowding problem of Mobile Chargers (MCs). To solve this problem, we propose a novel method called distributed cooperative wireless charging, in which a coal mine roadway segment is divided into sections, and each MC is responsible for charging the nodes in its own section. From time t=k-1/2t, all MCs of a segment start to work simultaneously, where K is the number of sections and T is the charging cycle. When the steady state is reached, distributed cooperative wireless charging is the fastest method to finish a round of charging. To guarantee the practicality of the algorithm, we also provide the method to determine the MC battery capacities and the roadway section lengths. Numerical simulations indicate that the proposed algorithm provides better charging efficiency than existing one-dimensional charging methods in coal mine roadways.