To reduce the burden of multiple sensors on satellites with limited resources, distributed
compressed sensing (DCS) is applied to microvibration measurement. An improved joint …

Distributed Compressed Sensing (DCS) is an important research area of compressed
sensing (CS). This paper aims at solving the Distributed Compressed Sensing (DCS) …

For compressed sensing over arbitrarily connected networks, we consider the problem of
estimating underlying sparse signals in a distributed manner. We introduce a new signal …

We study the sparse signal reconstruction problem in a wireless sensor network (WSN)
using distributed compressed sensing. The sparse signals from multiple sensors are …

We consider a distributed compressed sensing scenario where many sensors measure
correlated sparse signals and the sensors are connected through a network. Correlation …

We develop a greedy pursuit algorithm for solving the distributed compressed sensing
problem in a connected network. This algorithm is based on subspace pursuit and uses the …

Multi-signal joint reconstruction is critical in distributed compressed sensing (DCS). We
propose a joint reconstruction algorithm for subspace pursuit of residual correlation steps to …

In this article, to get a high-resolution radar image with distributed frequency modulated
continuous waveform multiple-input-multiple-output (FMCW MIMO) radar, Bayesian …

Due to the powerful learning capability and fast processing speed of deep neural networks,
a series of pure data-driven and deep unfolding networks for image reconstruction have …

In this paper, we propose a novel greedy algorithm referred to as look-ahead hybrid
matching pursuit (LAHMP) for multipolarization through-wall radar imaging (TWRI). From the …