UWB-SAR抑制FI的ML参数估计方法

有效的射频干扰(RFI)抑制技术是超宽带合成孔径雷达(UWB-SAR)成像质量的重要保证。基于多正弦波模型的选代最大似然(ML)法能够在很大程度上抑制RFI。然而,这种方法存在局部最小及相近频率分辨问题。本文利用特征结构分析求解初始频率估计,较好地解决了上述问题。同时,对RFI谱峰中正弦信号个数的二元假设使算法得到简化。理论分析和仿真实验均表明本文算法的良好性能。

RFI SUPPRESSION IN UWB-SAR USING ML PARAMETER ESTIMATION

Radio Frequency Interference (RFI) plays an important role on the quality of Ultra-Wide Band Synthetic Aperture Radar (UWB-SAR) imaging. Being modeled as sinusoidal signals, the RFI can be greatly suppressed by the method of iterative Maximum Likelihood (ML) estimation. However, the problems of local minimum and separation of close frequencies exist. In this paper, the difficulty is considerably reduced by the use of eigenstructure analysis to give a better initial frequency estimation. The algorithm is further simplified using a binary hypothesis test on the number of sinusoidal signals in one spectral peak. The excellent performance of the algorithm is demonstrated by experiments on simulated and real RFI data.