Frequency modulated (FM) signals sampled below the Nyquist rate or with missing samples (nowadays part of wider compressive sensing (CS) framework) are considered. Recently proposed matching pursuit and greedy techniques are inefficient for signals with several phase parameters since they require a search over multidimensional space. An alternative is proposed here based on the random samples consensus algorithm (RANSAC) applied to the instantaneous frequency (IF) estimates obtained from the time-frequency (TF) representation of recordings (undersampled or signal with missing samples). The O’Shea refinement strategy is employed to refine results. The proposed technique is tested against third- and fifth-order polynomial phase signals (PPS) and also for signals corrupted by noise.

考虑了以奈奎斯特速率以下采样或缺少采样（现在是更广泛的压缩感测（CS）框架的一部分）的调频（FM）信号。最近提出的匹配追踪和贪婪技术对于具有几个相位参数的信号效率低下，因为它们需要在多维空间上进行搜索。在此基于随机采样共识算法（RANSAC）提出了一种替代方法，该算法应用于从记录（欠采样或缺少采样的信号）的时频（TF）表示中获得的瞬时频率（IF）估计值。O'Shea细化策略用于细化结果。针对三阶和五阶多项式相位信号（PPS）以及受噪声破坏的信号，对提出的技术进行了测试。