Phaseless Subspace Tracking
This addresses a theoretical challenge in signal processing and imaging for applications like dynamic systems, but it is incremental as it builds on existing low-rank phase retrieval work.
The paper tackles the problem of recovering time-varying signals from phaseless linear projections by assuming they lie in a gradually changing low-dimensional subspace, introducing the phaseless subspace tracking (PST) problem as a dynamic extension of low-rank phase retrieval.
This work takes the first steps towards solving the "phaseless subspace tracking" (PST) problem. PST involves recovering a time sequence of signals (or images) from phaseless linear projections of each signal under the following structural assumption: the signal sequence is generated from a much lower dimensional subspace (than the signal dimension) and this subspace can change over time, albeit gradually. It can be simply understood as a dynamic (time-varying subspace) extension of the low-rank phase retrieval problem studied in recent work.