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Research of GNSS Spoofer Localization Using Information Fusion Based on Particle Filter

机译:基于粒子滤波的信息融合GNSS卫星定位器研究

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A spoofer localization algorithm using information fusion based on the particle filter (PF) is proposed. There are many researches about the jammer localization, but less researches about the spoofer localization. The jamming signal, whose structure is unknown to us, usually is above the thermal noise. According to the effect of jamming signal bandwidth on the measuring of time and frequency, we cannot obtain the precise measurements of TDOA and FDOA simultaneously. Thus, we usually cannot implement the information fusion of time and frequency in the jammer localization. Besides, we cannot locate the spoofer directly with the method of jammer localization, because the spoofing signal is usually below the noise. However, we can obtain the precise measurements of time and frequency of the spoofing signal at the same time because the spoofing signal needs to disguise as the true GNSS signal. Based on this, we propose a localization algorithm using the information fusion of TDOA and FDOA. We couple the position and velocity together by the PF, which will not introduce the linearization error. By the analysis of the CRLB, we find the information fusion can improve the system performance. To verify the algorithm, we simulate and analyze the results of PF and the weighted least squares (WLS). Compared to the WLS without information fusion, the PF has a better performance of locating and tracking, which can work properly under the circumstances where the spatial layout is poor, the number of base stations is small and the measuring errors are large.
机译:提出了一种基于信息融合的基于粒子滤波器的小球定位算法。关于干扰物定位的研究很多,但是关于spoofer定位的研究却很少。我们不知道其结构的干扰信号通常高于热噪声。根据干扰信号带宽对时间和频率测量的影响,我们无法同时获得TDOA和FDOA的精确测量值。因此,我们通常无法在干扰定位中实现时间和频率的信息融合。此外,由于干扰信号通常在噪声以下,因此我们无法使用干扰定位方法直接定位spoofer。但是,由于欺骗信号需要伪装成真正的GNSS信号,因此我们可以同时获得精确的时间和频率测量值。在此基础上,提出了一种基于TDOA和FDOA信息融合的定位算法。我们通过PF将位置和速度耦合在一起,这不会引入线性化误差。通过对CRLB的分析,我们发现信息融合可以提高系统性能。为了验证该算法,我们模拟并分析了PF和加权最小二乘(WLS)的结果。与没有信息融合的WLS相比,PF具有更好的定位和跟踪性能,在空间布局不良,基站数量少,测量误差大的情况下可以正常工作。

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