RANSAC algorithm for instantaneous frequency estimation and reconstruction of frequency-modulated undersampled signals

被引：0
|
作者：
Igor Djurović
机构：
[1] University of Montenegro,Electrical Engineering Department
来源：
EURASIP Journal on Advances in Signal Processing | / 2021卷
关键词：
Compressive sensing; FM signals; Time-frequency analysis; Instantaneous frequency; RANSAC; Refinement;
D O I：
暂无
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学科分类号：
摘要：
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.
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