基于Zernike矩和双谱特征的新型干扰识别算法

Jamming Identification Algorithms of Advanced Jamming Based on Bispectrum Feature and Zernike Moment

为了有效应对频谱弥散干扰(SMSP)和切片组合干扰(C&I),提出了一种利用Zernike矩和双谱分析的干扰识别方法。首先对雷达接收信号进行双谱分析,经过降维和归一化处理后,将三维双谱信息转化为二维特征信息,然后将得到的二维特征谱变为灰度图,运用数字图像处理技术对灰度图进行一系列的预处理后,利用Zernike矩特征提取图像的形状特征进行识别。仿真实验证明该方法具有较好的识别率,特别是受信噪比影响较少,且在低信噪比下识别率仍能达到90%。通过与文献[4~6]比较表明,该算法识别效果最好,进一步说明了采用该算法在雷达干扰信号识别领域中的可行性。

A novel jamming identification method based on bi-spectrum and Zernike moment feature is proposed to effectively deal with two new kinds of jamming of smeared spectrum（SMSP）and chopping and interleaving（CI）.In this method,the bi-spectrum analysis of received radar signal under three cases is given firstly through a series of dimensionality reduction and normalization,and a three-dimensional feature information is turned into two-dimensional feature information.Then the two-dimensional feature spectrum is transformed into a gray image through a series of image processing,and Zernike moment feature is utilized for extracting image shape feature to constitute feature vector for signal recognition.The result shows that the proposed approach can achieve satisfying recognition.Particularly the method is less affected by SNR and the recognition rate can still reach 90% under low signal to noise ratio.In comparison with paper[4~6],this algorithm is the best in the recognition results,and this algorithm is also good in recognition rate under low signal-to-noise ratio.The method is feasible in the field of radar jamming signal recognition.