Research status and prospect of UWB radar personnel positioning for mine rescue

Due to its strong penetration (UWB) resolution, ultra-broadband (UWB) radar can detect and locate the trapped people in the mine. This paper system combed the UWB radar positioning principle and its application in mine rescue, from the radar positioning method, dynamic and static target positioning, single multiple three aspects, put forward the research problems: ① mine disaster environment medium complex, collapse structure layout of random, UWB electromagnetic wave propagation attenuation, echo signal processing, traditional positioning method in large thickness, uneven, discontinuous medium environment.② In the non-visual-distance environment, the signal fluctuation, scattering and attenuation effects are significant, resulting in weak radar echo signal and significant clutter interference, significant decrease in signal quality, low detection and positioning accuracy of micro-moving targets, and large real-time positioning error of dynamic targets.③ Interference between multiple targets, radar signal aliasing and occlusion effect is significant, resulting in the clarity of signals and low identification of targets, and then affect the positioning accuracy of the radar. The paper discusses the future research trend of personnel positioning for mine rescue: ① Iteratively optimize the positioning method applicable to mine post-disaster environment, build cross-modal information fusion model, and improve the adaptability of positioning system to complex environment.② By improving VMD and spectrum analysis algorithm to extract weak signals, combined with DBN fusion static and dynamic target features, build a comprehensive positioning model based on target state switching, so as to improve the applicability of UWB radar for the comprehensive detection and positioning of static and static targets in the post-disaster environment.③ By improving the UWB radar echo processing algorithm, combined with adaptive beamforming technology, MIMO technology and optimized K-means + + or entropy analysis stratification algorithm, the multi-target location information is effectively distinguished, and its adaptability and reliability in complex environment are tested through a large number of simulation experiments.