基于同相支路输出与PCS融合的GNSS欺骗检测方法

Research on GNSS spoofing detection based on fusion of in-phase branch output and PCS

关键词:  全球卫星导航系统  欺骗检测  偏度  峰度  滑动平均  检测概率  稳健性

Key words:  Global navigation satellite system(GNSS)  Spoofing detection  Skewness  Kurtosis  Moving average  Detection probability  Robustness

摘要:

基于信号质量监测（SQM）的全球卫星导航系统（GNSS）欺骗检测算法具有运算量小、实时性好等优点，但其对复杂欺骗场景的普适性并不理想。而基于绝对功率监测与SQM融合（PCS）的欺骗检测算法对载波同步的欺骗场景检测效果不理想。为此，提出了一种基于跟踪环同相支路超前及滞后输出绝对值与PCS融合（AELCP）的欺骗检测算法。根据欺骗信号对接收机跟踪环路相关峰的影响特性，取同相支路超前及滞后输出的绝对值的加权并与PCS进行乘积运算，形成AELCP检测量。基于偏度和峰度指标，检验AELCP检测量的概率分布特性，为选取检测门限及评估检测概率提供了理论依据。进一步对AELCP采用滑动平均处理，形成AELCP-MA检测量，以降低噪声影响。利用美国德州大学的欺骗测试数据集（TEXBAT）中的DS3，DS4，DS5和DS7等多个场景数据，对比分析了各类算法的检测概率等性能。结果表明，与PCS-MA，ELP-MA和Delta-MA等SQM算法相比，AELCP-MA算法在多种欺骗场景下均表现出更高的检测概率和稳健性。

Abstract:

The GNSS spoofing detection algorithm based on signal quality monitoring（ＳＱＭ） has the advantages of low computational complexity and excellent real-time performance, but its universality for complex spoofing scenarios is not ideal. Since the spoofing detection algorithm based on power combined with SQM (PCS) shows suboptimal detection effectiveness in carrier synchronization spoofing scenarios, a spoofing detection algorithm based on the absolute early and late outputs of the in-phase branch of the tracking loop combined with PCS (AELCP) is proposed. Based on the influence characteristics of the spoofing signal on the correlation peaks of the receiver tracking loop, the absolute values of the early and late outputs of the in-phase branch are weighted and multiplied by the PCS to form the AELCP detection metric. Based on the skewness and kurtosis indexes, the probability distribution characteristics of the AELCP detection metric are examined to provide a theoretical basis for selecting the detection threshold and evaluating the detection probability. A moving average method is also applied to AELCP so that the AELCP-MA detection metric can be formed to reduce the noise effect. Using data from multiple scenarios such as DS3, DS4, DS5, and DS7 in the Texas spoofing test battery (TEXBAT) at the University of Texas, the performance such as detection probability of different algorithms are compared and analyzed. The results show that the AELCP-MA algorithm can be applied to multiple spoofing scenarios and has higher detection probability and robustness in various spoofing scenarios compared to the SQM algorithms such as PCS-MA, ELP-MA, and Delta-MA.