一种自适应GNSS弱信号载噪比估计方法

An adaptive carrier-to-noise ratio estimation method for GNSS weak signal

全球导航卫星系统(GNSS)信号的载噪比(CNR)是衡量接收机工作性能的一个重要参数。为了准确得到载噪比估计值,推导并分析了2种常用的GNSS信号载噪比估计方法(方差求和法(VSM)、窄带宽带功率比值法(PRM)),并同时提出一种基于渐消因子容积卡尔曼滤波的自适应载噪比估计方法,比较了3种方法在通常的信号环境下和弱信号环境下的载噪比估计能力。结果显示:在信号较弱环境或信号受到遮挡产生突变等情况时,VSM方法与PRM方法均会产生较大的误差,而自适应载噪比估计方法能准确估计出信号的载噪比。

The Carrier-to-Noise Ratio(CNR)of Global Navigation Satellite System(GNSS)signals is an important parameter to describe GNSS receiver’s performance.In this paper,we derive and analyze two commonly used GNSS signal CNR estimation methods:Variance Summing Method(VSM)and Power Ratio Method(PRM).Meanwhile,we propose an adaptive CNR estimation method which is based on fading factor cubature Kalman filter.We compare the three methods to assess the CNR estimation ability in normal and weak signal environment.The results show that,when signal suddenly changes or signal is weak,the VSM and PRM will produce large estimation errors,while the adaptive CNR estimation methods can still accurately estimate the CNR of signal.