TOA Localization Algorithm of Underground Mine Moving Target Based on UWB and Fingerprint Localization
Aiming at the problem that the localization of targets such as personnel and equipment in underground mine is easily affected by non-line-of-sight propagation delay,resulting in low localization accuracy and poor real-time performance,a time of arrival(TOA)localization method for underground mine moving targets based on ultra-wide band(UWB)and fingerprint localization was proposed.Firstly,the distance between the localization base station and the target to be measured was measured by double-sided two-way ranging(DS-TWR),and the Chan algorithm was constructed to estimate the coordinates of the target to be measured.Secondly,the Taylor formula was used to iteratively update the localization results of the Chan algorithm to suppress the non-line-of-sight(NLOS)delay error in the mine roadway.Finally,the fingerprint database was constructed by collecting the distance fingerprints of specific points in turn.The horizontal and vertical coordinate errors of the target position to be measured were estimated by the improved arithmetic optimization algorithm to optimize the least squares support vector machine(AOA-LSSVM)model.Combined with the localization results of Chan-Taylor algorithm,the error compensation was carried out to obtain the optimal position estimation of the target to be measured.The experimental results show that the localization accuracy of the proposed algorithm is improved by 18.63％and 63.79％respectively compared with the Chan-Taylor algorithm in the static and dynamic experiments in the line-of-sight(LOS)environment.The localization accuracy of the algorithm is improved by 82.40％and 56.78％respectively compared with the Chan-Taylor algorithm in the static and dynamic experiments in NLOS environment,which can meet the high-precision localization requirements of the target in underground mine.
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维普
