基于自适应SPRT的缓变式欺骗干扰检测算法

缓变式欺骗干扰信号在干扰初期与全球导航卫星系统（Global Navigation Satellite System， GNSS）真实信号保持一致，其隐蔽性强，危害性大。常见的缓变式欺骗干扰检测方法是将卡尔曼滤波新息序列作为检测量，基于卡方检验检测干扰。然而，这些方法存在检测时间较长、检测性能低的问题。针对这一问题，提出了基于序贯概率比检测（Sequential Probability Ratio Test， SPRT）的缓变式欺骗干扰检测算法，将新息序列检测量作为SPRT样本，计算检验统计量，检测欺骗的同时能识别受欺骗的卫星。同时，应用Bayes参数估计理论，提出自适应SPRT算法，自适应补偿检验统计量，加快算法检测速度，并可通过调整风险参数，进一步提高算法的检测性能。仿真结果表明，与传统方法比，本文算法对缓变式欺骗干扰的检测时间短、检测性能高，并且在多星受欺骗时，可达到较好的检测性能。 

Slowly Varying Spoofing Interference Detection Algorithm Based on Adaptive SPRT

? ?The slowly varying spoofing interference signal is consistent with the real signal of the global navigation satellite system （GNSS） in the early stage of interference， which has strong concealment and is difficult to detect effectively. The common slowly varying spoofing interference detection method usually uses the Kalman filter innovation sequence as the detection amount， and it detects the slowly varying spoofing interference based on the chi-square test. However， these methods have the problems of long detection time and low detection performance. Aiming at the problems， a spoofing detection algorithm for slowly varying spoofing interference based on SPRT was proposed， which used the detection amount of the innovation sequence as the SPRT sample to calculate the test statistic. The spoofing detection algorithm could identify the spoofed satellite while detecting the slowly varying spoofing interference. Simultaneously， using Bayes parameter estimation theory， an adaptive SPRT algorithm was proposed， which adaptively compensated the test statistics， speeded up the detection speed of the algorithm， and could further improve the detection performance of the algorithm by adjusting the risk parameters. The simulation results show that， compared with the traditional method， the algorithm in this paper has a shorter detection time and high detection performance for slowly varying spoofing interference， and it can achieve better detection performance when multiple satellites are spoofed.