基于熵最小化的LFM信号调频率估计算法

利用LFM信号频谱的熵随着调频率减小而降低的性质,提出了一种基于频谱熵最小化的LFM信号调频率的估计SEM方法。建立参数待估的相位补偿因子,通过搜索得到使得补偿后信号频谱熵全局最小的调频率估值。在搜索过程中,采用两级搜索策略,并引入牛顿迭代算法,有效降低了算法复杂度。理论推导和仿真结果证明,该算法为有偏算法,估计偏差量与初始频率相关,理论估计方差比较CR下界低12d B。对雷达实测回波信号进行验证,与离散多项式变换算法相比发现,提出算法估计的鲁棒性更好,并具有较高的测速精度,具有一定的应用价值。

Estimation Method of LFM Signal Chirp Rate Based on Entropy Minimization

Based on the fact that the spectrum entropy decreases with the chirp rate being smaller, this paper proposes a spectrum entropy minimization (SEM) based chirp rate estimation method. A phase filter is established and the chirp rate estimation is accomplished via minimization of the spectrum entropy. In this process,a two-step search strategy is utilized. In step one,a large searching step is chosen to achieve the coarse estimation of the parameter and then Newton iterative search algorithm is used in step two to estimation the chirp rate accurately. Theoretical derivation shows that the proposed algorithm is biased,which is related to the fractional part of the initial frequency and the variance is about 12dB lower than Cramer-Rao lower bound. Simulation result proves the correctness of the derivation and the comparison with classic discrete polynomial phase transform is made.