Iterative Methods for Sparse Signal Reconstruction from Level Crossings

TL;DR

This paper introduces new iterative algorithms for reconstructing sparse signals from level crossing data, extending 1-bit compressive sensing methods and demonstrating superior performance through simulations.

Contribution

It extends the SL0 algorithm to 1-bit CS and proposes the BSL0 algorithm for sparse signal reconstruction from level crossings.

Findings

Proposed algorithms outperform existing methods in simulations.

Extended SL0 to 1-bit CS with BSL0 for unknown sparsity.

Demonstrated superior reconstruction accuracy from level crossing data.

Abstract

This letter considers the problem of sparse signal reconstruction from the timing of its Level Crossings (LC)s. We formulate the sparse Zero Crossing (ZC) reconstruction problem in terms of a single 1-bit Compressive Sensing (CS) model. We also extend the Smoothed L0 (SL0) sparse reconstruction algorithm to the 1-bit CS framework and propose the Binary SL0 (BSL0) algorithm for iterative reconstruction of the sparse signal from ZCs in cases where the number of sparse coefficients is not known to the reconstruction algorithm a priori. Similar to the ZC case, we propose a system of simultaneously constrained signed-CS problems to reconstruct a sparse signal from its Level Crossings (LC)s and modify both the Binary Iterative Hard Thresholding (BIHT) and BSL0 algorithms to solve this problem. Simulation results demonstrate superior performance of the proposed LC reconstruction techniques in comparison with the literature.