Research on GNSS spoofing interference detection for multi-correlator combined power
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摘要: GNSS民用信号因其公开性和脆弱性易受外界欺骗干扰. 作为欺骗干扰检测的有效方法，信号质量监测(signal quality monitoring，SQM)技术通过检测接收机跟踪环路早码、即时码、晚码(early late phase，ELP)的相关结果，与无欺骗时的相关特性对比，判断是否存在欺骗干扰. 常规SQM算法仅利用ELP三个信息，检测性能受限，为此提出多相关器联合功率(SQM detection of power combined Multi-correlator groups，SPCM)算法. 以ELP之间多个等间隔相关器输出功率的加权为检测量，且取相关时刻与即时码时间差的反比为加权系数；进一步分析检测量的概率分布特性，并基于Neyman-Pearson理论确定最佳检测阈值，通过比较检测量与检测阈值的大小，判断是否存在欺骗干扰. 基于美国德克萨斯大学奥斯汀分校公开的场景四数据集进行试验，结果表明：与Ratio和ELP等典型SQM算法相比，在不同虚警率条件下，所提出SPCM算法兼具高检测概率和快速预警响应时间性能.Abstract: Global Navigation Satellite System (GNSS) civil signals are vulnerable to external spoofing because of their openness and vulnerability. As an effective method for spoofing detection, Signal Quality Monitoring (SQM) monitors the correlation results of early code, late code and phase code (ELP) after the receiver's tracking loop, and compares them with the correlation characteristics without spoofing to determine whether spoofing interference exists. The conventional SQM algorithm uses only three ELP information and the detection performance is limited. Therefore, a multi-correlator combined power algorithm is proposed. The weight of the output power of multiple equally spaced correlators between ELP is taken as the detection quantity, and the inverse ratio of the correlation time and the real-time code time difference is taken as the weighting coefficient. The probability distribution characteristics of the detected quantity were further analyzed, and the optimal detection threshold was determined based on the Neyman-Pearson theory. By comparing the detected quantity and the detection threshold, the existence of deception interference was determined. Based on the Scenario 4 set published by the University of Texas, the test results show that compared with typical SQM algorithms such as Ratio and ELP, the proposed algorithm has both high detection probability and fast early warning response time under different false alarm rates.
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