Clutter Suppression for Indoor Self-Localization Systems by Iteratively Reweighted Low-Rank Plus Sparse Recovery

Self-localization based on passive RFID-based has many potential applications. One of the main challenges it faces is the suppression of the reflected signals from unwanted objects (i.e., clutter). Typically, the clutter echoes are much stronger than the backscattered signals of the passive tag landmarks used in such scenarios. Therefore, successful tag detection can be very challenging. We consider two types of tags, namely low-Q and high-Q tags. The high-Q tag features a sparse frequency response, whereas the low-Q tag presents a broad frequency response. Further, the clutter usually showcases a short-lived response. In this work, we propose an iterative algorithm based on a low-rank plus sparse recovery approach (RPCA) to mitigate clutter and retrieve the landmark response. In addition to that, we compare the proposed approach with the well-known time-gating technique. It turns out that RPCA outperforms significantly time-gating for low-Q tags, achieving clutter suppression and tag identification when clutter encroaches on the time-gating window span, whereas it also increases the backscattered power at resonance by approximately 12 dB at 80 cm for high-Q tags. Altogether, RPCA seems a promising approach to improve the identification of passive indoor self-localization tag landmarks.

Phased Array Analysis Incorporating the Continuous Wavelet Transform

ABSTRACT Nonlinear block thresholding of the continuous wavelet transform (CWT) of 2D phased array signals offers high time-resolution solutions for analyzing seismograms of local and regional seismic events. An initial denoising step on an array ensemble reveals the regions of the scale-time plane that contain high signal-to-noise arrivals. Individual seismic phase arrivals in ensemble, denoised seismograms can be partitioned using scale-time gating in which CWT wave packets of an individual seismic phase on the scale-time plane for a reference array element are time-correlated with all other elements to find an optimum time shift for the phase across all elements. The seismic phase is then clipped out of the CWT of each array element using this optimal time shift for further analysis. The seismogram can be separated into component seismic waves for a detailed view of wave characteristics such as slowness and arrival azimuth using conventional frequency–wavenumber methods. However, the process can be taken further using the CWT of each phase to construct high time-resolution signal beams over the CWT scale. Local explosion data from the 2016 Incorporated Research Institutions for Seismology (IRIS) Wavefields Community Experiment in northern Oklahoma are used to demonstrate these techniques in separating surface-wave modes and body waves and to examine the scattering of regional phases. High-resolution CWT processing in the 1–3 Hz band for northern Oklahoma reveals horizontal Rayleigh-wave refraction and multipathing. Rayleigh-wave phase-velocity dispersion measurements are used to construct a 1D velocity model under the IRIS experiment. Scale-time gating helps expose near-source surface reflections from a local M 3.6 earthquake that are used to verify the 4 km source depth obtained from a published regional moment tensor solution.