A Weighted Convex Optimized Phase Retrieval Method for Short-Time Fourier Transform Measurement With Outliers

Ning Fu, Xiaodong Li, Pinjun Zheng, Liyan Qiao

Research output: Contribution to journalArticlepeer-review

Abstract

As a problem of reconstructing the original signal from phaseless short-time Fourier transform (STFT) measurement, STFT phase retrieval (PR) is widespread in many fields. The existing PR algorithms for STFT measurement can uniquely determine the original signal (up to a global phase), however they are invalid when outlier interference exists. Aiming at this problem, we propose a weighted convex optimization PR method by introducing a weight matrix that can identify outliers. Meanwhile, a two-channel phaseless measurement structure based on the mask technique and the corresponding calculation algorithm are proposed to obtain the weight matrix. In particular, by accumulating the measurement results of all short-time segments, the support of outliers can be well identified in the weight matrix calculation. Simulation and hardware experiments demonstrate the performance improvement of the proposed approach compared to the existing methods, which shows its effectiveness in suppressing outlier interference.
Original languageEnglish (US)
Pages (from-to)1-1
Number of pages1
JournalIEEE Transactions on Instrumentation and Measurement
DOIs
StatePublished - Sep 20 2023

ASJC Scopus subject areas

  • Instrumentation
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'A Weighted Convex Optimized Phase Retrieval Method for Short-Time Fourier Transform Measurement With Outliers'. Together they form a unique fingerprint.

Cite this