CAJ | 학술논문

为减小蜂窝网定位中影响定位精度的非视距(NLOS)传播误差，提出一种基于两步卡尔曼滤波到达时间差/到达角度的混合定位算法。利用卡尔曼滤波器的估计值计算非视距数据的方差，调节卡尔曼滤波器的参数，减小测量值的 NLOS误差，并将经过预处理的测量值输入到扩展卡尔曼滤波器，实现混合定位。实验结果表明，该算法能有效消除NLOS误差，与Chan算法相比，其定位精度更高。
위감소봉와망정위중영향정위정도적비시거(NLOS)전파오차，제출일충기우량보잡이만려파도체시간차/도체각도적혼합정위산법。이용잡이만려파기적고계치계산비시거수거적방차，조절잡이만려파기적삼수，감소측량치적 NLOS오차，병장경과예처리적측량치수입도확전잡이만려파기，실현혼합정위。실험결과표명，해산법능유효소제NLOS오차，여Chan산법상비，기정위정도경고。
The Non-line of Sight(NLOS) transmission error is the main difficulty for mobile user location in cellular wireless communication system. So a novel Time Difference of Arrival(TDOA)/Angle of Arrival(AOA) wireless position scheme based on the two step Kalman filter is proposed. The estimate of the Kalman filter is used to calculate the variance of NLOS, and it adjusts the Kalman filter parameters and mitigate the NLOS error of measurement. These preprocessed measurements are input to the hybrid location estimator implemented by Extended Kalman Filter(EKF). Experimental results show that this algorithm can mitigate the NLOS error, and compared with Chan algorithm, it can improve the positioning accuracy.