1种抑制巷道信号NLOS的矿井RSSI高精度定位算法

在RSSI(Received Signal Strength Indication)测距定位技术中,为抑制巷道信号NLOS(Non Line of Sight)传输对定位结果的影响,提出信号指纹定位和几何优化算法.在离线阶段利用高斯滤波最大值加权法和最小二乘法建立符合矿井巷道环境的无线信号测距模型,设计改进卡尔曼滤波器...

A RSSI high-precision localization algorithm for suppressing roadway signals NLOS of mine

In order to suppress the influence of the non line of sight (NLOS) transmission of roadway signals on the localization results in the ranging localization technology of received signal strength indication (RSSI),the signal fingerprint localization and geometric optimization algorithms were put forward.In the off-line stage,the maximal weighted method and least square method of Gaussian filter were used to establish the wireless signal ranging model in line with the mine roadway environment,then an improved Kalman filter was designed to smoothly process the off-line signal values for suppressing the influence of NLOS transmission of roadway signals,and a fingerprint database of off-line signals was established.In the online localization stage,the weighted K-nearest neighbor method (WKNN) was used to match the signal values received by the localization target with the signal values in the fingerprint database,and the matched optimal signal value was involved in the calculation of ranging localization.Finally,the localization results were normalized through the geometric optimization algorithm to make them conform to the one-dimensional localization distribution.The results showed that the average localization error of the proposed algorithm was 0.9 m,which was 2.36 m,1.17 m and 0.35 m less than that of the Gaussian filter maximum weighted method,the classical Kalman filter fingerprint localization algorithm and the improved Kalman filter fingerprint localization method,respectively.The proposed algorithm can effectively suppress the influence of NLOS transmission of roadway signals on the RSSI ranging localization,and realize the effective application of RSSI method in the NLOS environment of mine.