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An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers

机译：GNSS接收机中用于跟踪误差估计的增强型非相干预滤波器设计

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Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration—which are the basis of tracking error estimation—are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (−0.25 cycle, 0.25 cycle) to (−0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio is less than 28.8 dB-Hz, in carrier frequency error estimation when carrier-to-noise density ratio is less than 20 dB-Hz, and in carrier phase error estimation when carrier-to-noise density belongs to (15, 23) dB-Hz  ∪  (26, 50) dB-Hz.
机译：跟踪误差估计在全球导航卫星系统（GNSS）接收机中非常重要。跟踪误差的任何不准确估计都会降低信号跟踪环的信号跟踪能力以及位置固定，速度确定和定时的准确性。跟踪误差估计可以通过传统的鉴别器或基于卡尔曼滤波器的预滤波器来完成。预滤波器可以分为两类：相干和非相干。本文着重于非相干前置滤波器的性能改进。首先，详细分析了相干和非相干积分的信号特性，它们是跟踪误差估计的基础。然后，根据相干积分数学模型，推导了四象限反正切（ATAN2）鉴别器的估计噪声概率分布。其次，通过蒙特卡罗模拟研究了非相干前置滤波器观测噪声的统计特性，以正确设置观测噪声方差矩阵。第三，非相干预滤波器设计引入了一种简单的故障检测与排除（FDE）结构，因此其有效的载波相位误差估计工作范围从（-0.25周期，0.25周期）扩展到（-0.5周期） ，0.5个周期）。最后，通过精心设计的实验场景，对评估器，相干预滤波器和增强型非相干预滤波器的估计精度进行了全面评估。在估计精度方面，预滤波器优于传统的鉴别器。在高度动态的情况下，与相干前置滤波器相比，增强型非相干前置滤波器在载波相位误差，载波频率误差和码相位误差估计方面的精度分别提高了41.6％，46.4％和50.36％。过滤。当载波噪声密度比小于28.8 dB-Hz时，增强型非相干预滤波器在代码相位误差估计中优于相干滤波器，在载波噪声比小于时，在载波频率误差估计中小于20 dB-Hz，并且在载波相位误差估计中，当载噪比密度为（15，23）dB-Hz∪（26，50）dB-Hz时。

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