最大值约束的广义延拓逼近GNSS码鉴相算法

针对GNSS码跟踪环高精度鉴相需求,提出了一种最大值约束的广义延拓逼近码鉴相算法,利用5个相关臂的相关结果建立广义延拓逼近模型,拟合得到相关值分布函数,进而得到码相位差。同时利用相关结果最大的相关节点对拟合的相关值分布函数进行约束,进一步提高了码相位差的估计精度和适应性。将新算法与常用的归一化超前减滞后包络鉴相算法从鉴相线性范围、牵引范围和鉴相误差三方面进行了对比。蒙特卡罗仿真和在GPS软件接收机上对实际GPS信号采样数据进行测试的结果表明，结合最大值约束的广义延拓逼近鉴相误差性能大大优于传统的归一化超前减滞后包络鉴相,可以有效地提升码鉴相器的鉴相精度。

Generalized extended approximation GNSS code discriminator algorithm with maximum constraint

A new code discriminator algorithm of maximum constrained generalized extended approximation(GEA) is proposed to meet the requirment of high precision phase discriminator for GNSS code tracking loop. The GEA model is developed based on correlation results of five correlators. Correlation value distribution function and then code phase difference are obtained by fitting the five correlation nodes. Mean while the maximum of correlation nodes is used to constrain the fitting, which can further improve the precesion and adaptability of code phase difference estimation. The new algorithm is compared with the common normalized early minus late envelope(NEMLE) discriminator from three aspects: linear range, pull in range and phase discriminator error. Results of Monte Carlo simulation and tests of actual GPS sampling data on GPS software receiver platform show that the error performance of the GEA method combined with the maximum correlation node constraint which can effectively improve the precesion of code phase discriminator is greatly superior to that of the NEMLE discriminator.