求翻译,帮忙把一下翻译成英文.非视距传输（NLOS）是无线定位误差的主要来源,利用卡尔曼滤波器处理到达时间值,再结合Chan算法可以提高定位的精度,但当误差较大时定位精度逐渐下降.本文

Question

求翻译,帮忙把一下翻译成英文.
非视距传输（NLOS）是无线定位误差的主要来源,利用卡尔曼滤波器处理到达时间值,再结合Chan算法可以提高定位的精度,但当误差较大时定位精度逐渐下降.本文以 COST259模型为基础,利用统计规律估计NLOS平均误差,对于误差较大的点利用预测残差调节卡尔曼滤波增益,两者相结合可以有效的抑制NLOS误差.仿真结果表明该方法能在一定程度上提高NLOS环境下定位的精度.

Answer 1

Non Line of Sight (hereinafter referred to as NLOS for short) is the primary source as for wireless location errors. Kalman filter was applied to manage arrival time values and, Chan algorithm was employed incorporately to promote the precision of location which yet might decrease gradually with larger errors. This paper/article/study(3选1,推荐末者) did use, based on COST259 model, statistics regularities to predict average errors of NLOS and, apply with predicted residuals to regulate Kalman filter gain as for those points with larger errors, and combination of both approaches may control NLOS errors with effect(或：effectively). Emulation results indicate that such method might improve precision of location under NLOS circumstance to some extent.