加权多窗口字典的非线性调频信号参数估计方法

非线性调频(NLFM)信号经脉冲压缩后具有较低的旁瓣电平,广泛应用于脉冲压缩雷达中,实现对NLFM 信号的精确参数估计,对雷达对抗侦察具有重要意义。针对非线性调频信号的准确参数估计问题,文中通过构建加权多窗口字典并结合稀疏重构算法提出了一种凸优化基追踪信号重构方法,实现了对NLFM 信号的精确重构。通过筛选的Gabor 原子获得了信号的瞬时频率,利用反正切无模糊相位重构算法获得了信号的相位信息。经过仿真验证:该方法可以实现NLFM信号的精确重构。

Parameter Estimation of Nonlinear Frequency-modulated Signal Based on Weighted Multi-window Dictionary

Nonlinear frequency-modulated (NLFM) signal is widely used in some pulse compression radars for the advantage of low sidelobe level. Accurate parameter estimation of NLFM signal is of great significance to radar countermeasure reconnaissance. In order to estimate the accurate parameter of the NLFM signal, the weighted multi-window dictionary and the sparse reconstruction algorithm are used to reconstruct the signal. The instantaneous frequency of the signal is obtained through filtered Gabor atoms, and the phase information of the signal is obtained by the unambiguous inverse tangent reconstruction algorithm. Simulation results show that the proposed method can achieve accurate reconstruction of NLFM signals.