稀疏重构下的非线性调频信号参数估计算法

Parameter Estimation of Nonlinear Frequency Modulated Signal Under the Sparse Reconstruction

非线性调频信号广泛应用于雷达声纳领域,其具有多阶多项式相位、未知参数多的特点,给参数估计带来困难。针对此问题,本文提出一种稀疏重构下的非线性调频信号参数估计算法。该方法利用Gabor原子良好时频特性,以l1范数稀疏正则最小二乘模型为目标函数,并推导了问题的二阶锥规划(SOCP)形式,最终通过求解的Gabor原子进行参数估计。算法分析信号的时频特征,完成信号的分解重构,适应于各类调频信号。仿真实验证明,本文算法对调频信号二阶与一阶相位参数估计精度都贴近CRB,而对二阶参数的估计较二次相位差分算法更适应较低信噪比。

The nonlinear frequency modulation signal(NLFM)is widely used in the field of radar and sonar.It has the characteristics of multiple order polynomial phase and many unknown parameters,which makes parameter estimation diffi-cult.According to this,a method of Parameter estimation of nonlinear frequency modulated signal under the sparse recon-struction is presented.The method utilizes good time-frequency characteristics of Gabor atoms,uses norm Sparse regular least squares model and deduces the Second Order Cone Programming(SOCP)form of the problem.Finally it estimates parameters with Gabor atoms screened out.The method analyzes the time-frequency characteristics of the signal,completes the decomposition and reconstruction of the signal and suits all kinds of FM signals.Simulation results show that the preci-sion to second order and first order phase parameter of the proposed method is closed to CRB,and is more suitable to low signal-to-noise ratio while compared with second phase difference algorithm.