基于最大似然法的天波超视距雷达相位解污染算法

电离层解相位污染是天波超视距雷达信号处理的关键技术之一。由于模型的不准确性和电离层的复杂性，已有算法在污染较大时大多精度不高。该文提出一种基于最大似然法的相位解污染算法。该算法将信号建模为相位多项式，通过最大化似然函数来实现污染相位的估计。为了避免最大似然法中的矩阵求逆运算，该文进一步将最大似然问题转化为最小二乘问题，利用遗传算法求解相位系数。仿真结果表明，与传统算法比较，该文算法具有以下优点:相比HRR算法和CED算法，该文算法精度更高，校正后的信号频谱更加尖锐；在相位污染较大的情况下，该文算法仍具有较高的精度，有利于目标信息的提取；该文算法采用高阶多项式，避免分段处理和矩阵求逆，简化了运算。

Ionospheric Decontamination Algorithm Based on Maximum-likelihood Method in Over-the-horizon Radar

Ionospheric phase decontamination is a key technology in signal processing of sky-wave Over-The- Horizon Radar (OTHR). Due to the inaccuracy of the models and the complexity of the ionosphere, the accuracy of the existing algorithms is not satisfactory when the phase changes too fast. A new ionospheric phase decontamination algorithm is proposed based on the Maximum-Likelihood (ML) method. In this algorithm, the signal is modeled as a phase polynomial, and estimation of the perturbation phase is achieved by maximizing the likelihood function. To avoid matrix inversion in the ML method, the ML issue is further transformed to a least-squares issue. The coefficients of phase are solved by the genetic algorithm. The simulation results show that, compared with the traditional methods, the proposed algorithm has the following advantages: compared with the HRR algorithm and the CED algorithm, the algorithm proposed in this paper has higher accuracy, and the signal spectrum after decontamination is more sharp. Under the situation of serious phase contamination, the proposed algorithm still has higher precision, accordingly, the proposed algorithm is more advantageous to extract the target information. This algorithm adopts higher-order polynomials, which avoids segmented processing and computing the inverse of matrix, thus the computation process is simplified.