准连续波雷达通信中微弱信号检测方法仿真

Simulation of Weak Signal Detection Method in Quasi-Continuous Wave Radar Communication

为提高准连续波雷达通信中微弱信号检测概率,增强信噪比,针对当前检测方法中存在的受杂波影响较大及计算复杂度较高的问题,提出基于小波变换的准连续波雷达通信中微弱信号检测方法。利用二元假设检验模型描述准连续波雷达通信微弱信号检测问题,假设接收端采集信号中非高斯杂波的统计特性符合复合高斯模型,采用逆Gamma分布来表征其中纹理分量的共轭先验分布,根据杂波协方差矩阵的最大似然估计值进行滤波器的自适应处理;对滤波器处理后的信号,采用小波变换与阈值法进行变换分解,根据小波分解所得的各尺度的信号分量,去除其中的噪声分量后,利用mallat算法进行有效信号分量重构,实现微弱信号检测。仿真结果表明,相比于当前的信号检测方法,该方法的检测效果有一定程度的提升,且计算复杂度更低。

In order to improve the detection probability of weak signals in quasi-continuous wave radar communication and enhance the signal-to-noise ratio(SNR),this paper puts forward a method to detect the weak signals in quasi-continuous wave radar communication based on wavelet transform.The binary hypothesis test model was used to describe the problem about the detection of weak signal in quasi-continuous wave radar communication.If the statistical characteristics of non-Gaussian clutter in the signal collected by receiving terminal met the composite Gaussian model,the inverse Gamma distribution was used to characterize the conjugate prior distribution of texture components.According to the maximum likelihood estimation value of clutter covariance matrix,the adaptive processing of the filter was carried out.Moreover,the signal processed by the filter was transformed and decomposed by wavelet transform and threshold method.In addition,the noise components were removed from the signal components of each scale obtained by wavelet decomposition,and then mallat algorithm was used to reconstruct the effective signal components to achieve the weak signal detection.Simulation results show that,compared with the current signal detection method,the detection effect of the proposed method is improved to a certain extent,and the computational complexity is lower.