论文部分内容阅读
为解决卫星导航接收机在受到欺骗干扰时难以识别欺骗干扰这一问题,提出了一种基于模型的欺骗干扰识别方法.首先将干扰机/卫星发射机以及通信信道建模为Hammerstein模型,然后使用一种新的模型辨识方法——狼群算法来进行模型参数辨识.将估计得到的模型参数作为特征参数,使用欧氏距离比较法实现欺骗干扰的识别.仿真实验验证了所提方法的有效性和鲁棒性.结果表明:狼群算法与最小二乘法、迭代法和蝙蝠算法等其他模型辨识算法相比,虽然在算法时间复杂度上比最小二乘法和蝙蝠算法略高,但具有更高的模型参数辨识精度和欺骗干扰识别率,甚至在信噪比较低时识别性能也最优.
In order to solve the problem that the satellite navigation receiver can not identify the spoofing interference when it is cheated, a model-based spoofing identification method is proposed. First, the jammer / satellite transmitter and the communication channel are modeled as Hammerstein model, A new model identification method - Wollastonian algorithm is used to identify the model parameters. The estimated model parameters are taken as the characteristic parameters, and the Euclidean distance is used to identify the deception jamming. Simulation results show the effectiveness of the proposed method And robustness.The results show that compared with other model identification algorithms such as least square method, iterative method and bat algorithm, Wollastonian algorithm has a slightly higher algorithm time complexity than the least square method and bat algorithm, but has a higher Model parameter identification accuracy and deception jamming recognition rate, even when the signal to noise ratio is low, the recognition performance is also optimal.