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Myriad non-linearity for GNSS robust signal processing

机译:用于GNSS鲁棒信号处理的无数非线性

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摘要

The robustness of standard correlation-based Global Navigation Satellite System (GNSS) signal processing can be significantly improved by pre-processing the input samples with a zero-memory non-linearity (ZMNL). A paradigm for the design of ZMNLs is provided by the M-estimator framework where heavy-tailed probability density functions (pdfs) are used to model the impairments affecting the input samples. The myriad non-linearity, obtained considering a Cauchy pdf, is analysed for the acquisition and tracking of GNSS signals in the presence of pulsed interference. The impact of the myriad non-linearity is theoretically characterised and Monte Carlo simulations are used to support theoretical findings. Finally, real GNSS signals collected in the presence of jamming are processed: the myriad non-linearity provides a significant performance improvement with respect to standard GNSS signal processing which is unable to acquire and track the samples affected by interference.
机译:通过使用零内存非线性(ZMNL)预处理输入样本,可以显着提高基于标准相关性的全球导航卫星系统(GNSS)信号处理的鲁棒性。 M估计器框架提供了ZMNL设计的范例,其中使用了重尾概率密度函数(pdf)来建模影响输入样本的损伤。考虑到Cauchy pdf,获得了无数非线性,分析了在存在脉冲干扰的情况下GNSS信号的采集和跟踪。从理论上描述了无数非线性的影响,并使用蒙特卡洛模拟来支持理论发现。最后,处理在干扰情况下收集的实际GNSS信号:无数非线性相对于无法获取和跟踪受干扰影响的样本的标准GNSS信号处理而言,提供了显着的性能改进。

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