【摘要】 针对于非视距环境下(NLOS)的室内定位,传统的算法是将泰勒级数展开算法(Taylor)与卡尔曼滤波算法(KF)相结合,这种算法能够在一定程度上降低非视距误差,而当环境中的多径效应严重时,此算法误差将会显著增大。因此提出了一种基于信号残差加权(RRW)的组合定位算法,通过基站不同的组合方式,进行多轮定位,把每一轮的信号残差作为权重,实现最终的加权求和定位结果。实验结果表明,该方法能够有效地降低非视距误差,而且在遮挡严重的环境下,也能实现高精度定位。更多还原

【Abstract】 For indoor positioning in a non-line-of-sight environment(NLOS).The traditional algorithm is combines the Taylor series expansion algorithm(Taylor) with the kalman filter algorithm(KF).This algorithm can reduce the error of non-line-ofsight to some extent,but when the multipath effect in the environment is serious,the error of this algorithm will increase significantly.Therefore,a combined localization algorithm based on signal residuals(RRW) is proposed.Through the different combination of the base station,the multi-round positioning is carried out,and the signal residual of each round is taken as the weight to achieve the final weighted sum positioning result.Experimental results show that the method can effectively reduce the non-line-of-sight error,and can also achieve high precision positioning under the circumstance of severe occlusion.更多还原