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Related papers: Spatial Compressive Sensing for MIMO Radar

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Multiple-input multiple-output (MIMO) radar systems have been shown to achieve superior resolution as compared to traditional radar systems with the same number of transmit and receive antennas. This paper considers a distributed MIMO radar…

Information Theory · Computer Science 2016-11-15 Yao Yu , Athina P. Petropulu , H. Vincent Poor

In colocated multiple-input multiple-output (MIMO) radar using compressive sensing (CS), a receive node compresses its received signal via a linear transformation, referred to as measurement matrix. The samples are subsequently forwarded to…

Information Theory · Computer Science 2015-05-27 Y. Yu , A. P. Petropulu , H. V. Poor

A distributed MIMO radar is considered, in which the transmit and receive antennas belong to nodes of a small scale wireless network. The transmit waveforms could be uncorrelated, or correlated in order to achieve a desirable beampattern.…

Information Theory · Computer Science 2009-07-28 Athina P. Petropulu , Yao Yu , H. Vincent Poor

We analyze a multiple-input multiple-output (MIMO) radar model and provide recovery results for a compressed sensing (CS) approach. In MIMO radar different pulses are emitted by several transmitters and the echoes are recorded at several…

Information Theory · Computer Science 2015-09-14 Dominik Dorsch , Holger Rauhut

This paper proposes compressed domain signal processing (CSP) multiple input multiple output (MIMO) radar, a MIMO radar approach that achieves substantial sample complexity reduction by exploiting the idea of CSP. CSP MIMO radar involves…

Signal Processing · Electrical Eng. & Systems 2020-06-18 Ehsan Tohidi , Alireza Hariri , Hamid Behroozi , Mohammad Mahdi Nayebi , Geert Leus , Athina Petropulu

We present a compressive radar design that combines multitone linear frequency modulated (LFM) waveforms in the transmitter with a classical stretch processor and sub-Nyquist sampling in the receiver. The proposed compressive illumination…

Information Theory · Computer Science 2022-04-13 Nithin Sugavanam , Siddharth Baskar , Emre Ertin

A MIMO radar system is proposed for obtaining angle and Doppler information on potential targets. Transmitters and receivers are nodes of a small scale wireless network and are assumed to be randomly scattered on a disk. The transmit nodes…

Information Theory · Computer Science 2015-05-14 Yao Yu , Athina P. Petropulu , H. Vincent Poor

We present the design and hardware implementation of a radar prototype that demonstrates the principle of a sub-Nyquist collocated multiple-input multiple-output (MIMO) radar. The setup allows sampling in both spatial and spectral domains…

In the area of near-field millimeter-wave imaging, the generalized sparse array synthesis (SAS) method is in great demand. The traditional methods usually employ the greedy algorithms, which may have the convergence problem. This paper…

Signal Processing · Electrical Eng. & Systems 2022-08-10 Shuoguang Wang , Shiyong Li , Ahmad Hoorfar , Ke Miao , Guoqiang Zhao , Houjun Sun

A novel compressive-sensing based signal multiplexing scheme is proposed in this paper to further improve the multiplexing gain for multiple input multiple output (MIMO) system. At the transmitter side, a Gaussian random measurement matrix…

Information Theory · Computer Science 2016-04-05 Chanzi Liu , Qingchun Chen , Xiaohu Tang

Multiple-input multiple-output (MIMO) radar has several advantages with respect to the traditional radar array systems in terms of performance and flexibility. However, in order to achieve high angular resolution, a MIMO radar requires a…

Signal Processing · Electrical Eng. & Systems 2023-03-01 Himali Singh , Arpan Chattopadhyay

We consider a multiple-input-multiple-output radar system and derive a theoretical framework for the recoverability of targets in the azimuth-range domain and the azimuth-range-Doppler domain via sparse approximation algorithms. Using tools…

Information Theory · Computer Science 2012-03-14 Thomas Strohmer , Benjamin Friedlander

In this paper, we investigate jointly sparse signal recovery and jointly sparse support recovery in Multiple Measurement Vector (MMV) models for complex signals, which arise in many applications in communications and signal processing.…

Signal Processing · Electrical Eng. & Systems 2020-09-09 Ying Cui , Shuaichao Li , Wanqing Zhang

Multiple input multiple output (MIMO) radar exhibits several advantages with respect to traditional radar array systems in terms of flexibility and performance. However, MIMO radar poses new challenges for both hardware design and digital…

Information Theory · Computer Science 2016-08-30 David Cohen , Deborah Cohen , Yonina C. Eldar , Alexander M. Haimovich

In colocated compressive sensing MIMO radar, the measurement matrix is specified by antenna placement. To guarantee an acceptable recovery performance, this measurement matrix should satisfy certain properties, e.g., a small coherence.…

Information Theory · Computer Science 2022-10-25 Bastian Eisele , Ali Bereyhi , Ingrid Ullmann , Ralf Müller

In the context of the compressed sensing problem, we propose a new ensemble of sparse random matrices which allow one (i) to acquire and compress a {\rho}0-sparse signal of length N in a time linear in N and (ii) to perfectly recover the…

Information Theory · Computer Science 2013-04-15 Maria Chiara Angelini , Federico Ricci-Tersenghi , Yoshiyuki Kabashima

Millimeter (mm) wave massive MIMO has the potential for delivering orders of magnitude increases in mobile data rates, with compact antenna arrays providing narrow steerable beams for unprecedented levels of spatial reuse. A fundamental…

Signal Processing · Electrical Eng. & Systems 2018-12-05 Maryam Eslami Rasekh , Upamanyu Madhow

Multiple-input multiple-output (MIMO) radar offers several performance and flexibility advantages over traditional radar arrays. However, high angular and Doppler resolutions necessitate a large number of antenna elements and the…

Signal Processing · Electrical Eng. & Systems 2025-09-11 Chandrashekhar Rai , Himali Singh , Arpan Chattopadhyay

Compressive sensing aims to recover a high-dimensional sparse signal from a relatively small number of measurements. In this paper, a novel design of the measurement matrix is proposed. The design is inspired by the construction of…

Information Theory · Computer Science 2016-03-22 Xu Chen , Dongning Guo

In this paper, {the goal is to design deterministic sampling patterns on the sphere and the rotation group} and, thereby, construct sensing matrices for sparse recovery of band-limited functions. It is first shown that random sensing…

Information Theory · Computer Science 2020-04-22 Arya Bangun , Arash Behboodi , Rudolf Mathar
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