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Efficient target estimation in distributed MIMO radar via the ADMM

Bo Li, Athina Petropulu
2014 2014 48th Annual Conference on Information Sciences and Systems (CISS)  
We consider the problem of target estimation in distributed MIMO radars that employ compressive sensing.  ...  A solution is proposed based on the alternating direction method of multipliers (ADMM), which significantly lowers the computational complexity of sparse recovery and improves the estimation accuracy.  ...  The sparse model for distributed MIMO radar system is presented in Section II.  ... 
doi:10.1109/ciss.2014.6814116 dblp:conf/ciss/LiP14 fatcat:saqq33cqjjbrfeqk4y5uxernpy

Multitarget Direct Localization Using Block Sparse Bayesian Learning in Distributed MIMO Radar

Bin Sun, Haowen Chen, Xizhang Wei, Xiang Li
2015 International Journal of Antennas and Propagation  
In this paper, we explore a novel sparsity-based DPD method to locate multiple targets using distributed MIMO radar.  ...  The target localization in distributed multiple-input multiple-output (MIMO) radar is a problem of great interest.  ...  We introduce the signal model for a distributed MIMO radar and formulate the block sparse representation of signal in Section 2.  ... 
doi:10.1155/2015/903902 fatcat:bxzpcmc3cranzhhewvoh5rbewe

SAM 2020 Author Index

2020 2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)  
Tang, Mengjiao R12.2 Adaptive T-AMF for Radar Detection in Diffuse Multipath Tang, Zhifeng R02.3 Block-Sparse Signal Recovery Based on Adaptive Matching Pursuit via Spike and Slab Prior Tao,  ...  MIMO Radar with One-bit DACs via Block-Sparse SDR Wei, Wei SS19.5 Wavenumber Domain SAR Imaging Algorithm Based on the Principle of Chirp Scaling Wei, Ye R13.2 Resilient Multitask Distributed  ... 
doi:10.1109/sam48682.2020.9104397 fatcat:cfp5gsikrzabhhcnkalahjkxze

Sparse Frequency Diverse MIMO Radar Imaging for Off-Grid Target Based on Adaptive Iterative MAP

Xuezhi He, Changchang Liu, Bo Liu, Dongjin Wang
2013 Remote Sensing  
Here, we propose a novel approach of sparse adaptive calibration recovery via iterative maximum a posteriori (SACR-iMAP) for the general off-grid FD-MIMO radar imaging.  ...  For FD-MIMO radar imaging, conventional imaging methods based on Matched Filter (MF) cannot enjoy good imaging performance owing to the few and incomplete wavenumber-domain coverage.  ...  Based on the iterative MAP idea, we propose a novel sparse recovery algorithm for more generalized off-grid FD-MIMO radar imaging, named sparse adaptive calibration recovery via iterative maximum a posteriori  ... 
doi:10.3390/rs5020631 fatcat:4s6syrzhgrdqjkecgzsjyoraem

[SAM 2020 Title Page]

2020 2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)  
Modeling Marine Mammal Whistle Calls 33 1570620259 Block-Sparse Signal Recovery Based on Adaptive Matching Pursuit via Spike and Slab Prior C 34 1570620530 Chance Constrained Beamforming for Joint Radar-Communication  ...  Transmit Beampattern Design for Dual-Function Radar-Communication System with an Interleaved Array 154 1570618284 Transmit Beampattern Design for MIMO Radar with One-bit DACs via Block-Sparse SDR 155 1570617783  ... 
doi:10.1109/sam48682.2020.9104267 fatcat:erntqdmhdrdspcrkvjowtplyyq

Direction-of-Arrival Estimation for CS-MIMO Radar Using Subspace Sparse Bayesian Learning [chapter]

Yang Bin, Huang Dongmei, Li Ding
2016 IFIP Advances in Information and Communication Technology  
To improve the recovery accuracy and speed up the Bayesian iteration, a subspace sparse Bayesian learning algorithm is developed.  ...  The proposed scheme, which needs less iteration steps, can provides high precision DOA estimation performance for CS-MIMO radar, even at the condition of low signal-to-noise ratio and coherent sources.  ...  Introduction Multiple-input multiple-output (MIMO) radar is a relatively new concept for radar system.  ... 
doi:10.1007/978-3-319-48390-0_4 fatcat:vy252p5ggnckpejzfcalo77jsi

Distributed MIMO radar based on sparse sensing: Analysis and efficient implementation

Bo Li, Athina P. Petropulu
2015 IEEE Transactions on Aerospace and Electronic Systems  
In sparse sensing based distributed MIMO radars, the problem of target estimation is formulated as a sparse vector recovery problem, where the vector to be recovered is block sparse, or equivalently, the  ...  In [13] , [14] , the problem of target location and DRAFT 2 speed estimation in distributed MIMO radars is investigated as a block sparse signal recovery problem.  ...  The sparse model for distributed MIMO radar system is presented in Section III.  ... 
doi:10.1109/taes.2015.140367 fatcat:xnexl5lzdjhctmlzswkov3ljfq

Target Estimation Using Sparse Modeling for Distributed MIMO Radar

S. Gogineni, A. Nehorai
2011 IEEE Transactions on Signal Processing  
Index Terms-Adaptive, compressive sensing, multiple-input multiple-output (MIMO) radar, multiple targets, optimal design, sparse modeling, widely separated antennas.  ...  We also introduce a new metric to analyze the performance of the radar system. We propose an adaptive mechanism for optimal energy allocation at the different transmit antennas.  ...  Block-Matching Pursuit Before we describe BMP, we shall first give a description of the conventional MP. It is an iterative algorithm [40] that can be used for sparse signal recovery.  ... 
doi:10.1109/tsp.2011.2164070 fatcat:rsaqyliec5d4phvri2kc24t24i

Angular Positions Estimation of Spatially Extended Targets for MIMO Radar Using Complex Spatiotemporal Sparse Bayesian Learning

Zhongfei Ni, Binke Huang, Meng Cao
2019 IEEE Access  
sparse model and collocated MIMO radar is proposed, which is helpful to obtain the structure information of targets and improve the success rate of target recognition.  ...  be modeled as a multi-task group sparse problem and can be solved by multi-task group sparse recovery.  ...  In Section 2, the group sparse model for angle estimation based on collocated MIMO radar platform is developed.  ... 
doi:10.1109/access.2019.2926442 fatcat:5puc25ab65fpvowhpyzxfwqrla

Multitarget Detection in Passive MIMO Radar Using Block Sparse Recovery

Hossein Nikaein, Abbas Sheikhi, Saeed Gazor
2021 IEEE Access  
In this paper, we develop a new algorithm for centralized target detection in passive MIMO radar (PMR) using sparse recovery technique.  ...  INDEX TERMS Passive coherent location, passive MIMO radar, block sparse recovery, radar multitarget detection. This work is licensed under a Creative Commons Attribution 4.0 License.  ...  In [28] a block sparse Bayesian learning method is used to localize targets in an active MIMO radar.  ... 
doi:10.1109/access.2021.3108195 fatcat:duuvbebibncmbib6kjnmyl3zgi

Learned-SBL: A Deep Learning Architecture for Sparse Signal Recovery [article]

Rubin Jose Peter, Chandra R. Murthy
2019 arXiv   pre-print
In particular, for block sparse recovery, learned-SBL does not require any prior knowledge of block boundaries.  ...  Simulation results illustrate that the proposed approach offers superior sparse recovery performance compared to the state-of-the-art methods.  ...  For example, the detection of an extended target using a MIMO radar can be formulated as the recovery of a block sparse signal vector.  ... 
arXiv:1909.08185v1 fatcat:ngeqfk464rct3eyuwo4b5cc47q

An Accurate Sparse Recovery Algorithm for Range-Angle Localization of Targets via Double-Pulse FDA-MIMO Radar

Qi Liu, Xianpeng Wang, Liangtian Wan, Mengxing Huang, Lu Sun, Lisheng Fan
2020 Wireless Communications and Mobile Computing  
In this paper, a sparse recovery algorithm based on a double-pulse FDA-MIMO radar is proposed to jointly extract the angle and range estimates of targets.  ...  Therefore, we adopt an iterative grid refinement method to alleviate the above limitation on parameter estimation and propose a new iteration criterion to improve the error between real parameters and  ...  In this paper, a sparse recovery algorithm is proposed based on a double-pulse FDA-MIMO radar.  ... 
doi:10.1155/2020/6698446 fatcat:bol3zhi3qrecdll57dyrgw3zh4

Table of Contents

2021 IEEE Transactions on Signal Processing  
Chen Co-Located MIMO Radar Target Detection in Cluttered and Noisy Environment Based on 2D Block Sparse Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Li Target Localization Geometry Gain in Distributed MIMO Radar . . . . . . . . M. Sadeghi, F. Behnia, R. Amiri, and A.  ... 
doi:10.1109/tsp.2021.3136798 fatcat:kzkdhzcz3fgx3jv6gfjofooseq

Simultaneous Sparse Approximation Using an Iterative Method with Adaptive Thresholding [article]

Shahrzad Kiani, Sahar Sadrizadeh, Mahdi Boloursaz, Farokh Marvasti
2017 arXiv   pre-print
Additionally, we compare our method with other group-sparse reconstruction techniques, i.e., Simultaneous Orthogonal Matching Pursuit (SOMP), and Block Iterative Method with Adaptive Thresholding (BIMAT  ...  Moreover, SIMAT is considerably less complicated than BIMAT, which makes it feasible for practical applications such as implementation in MIMO radar systems.  ...  ACKNOWLEDGMENT The authors would like to thank Ehsan Asadi for helping in the analytical discussion subsection and Babak Barazandeh for introducing this topic to one of the authors.  ... 
arXiv:1707.08310v1 fatcat:yv6jahn5angavgqtypeu3tp54e

Robust Space–Time Joint Sparse Processing Method with Airborne Active Array for Severely Inhomogeneous Clutter Suppression

Qiang Wang, Bin Xue, Xiaowei Hu, Guangen Wu, Weihu Zhao
2022 Remote Sensing  
This method has several outstanding advantages: (1) only the single snapshot cell under test (CUT) data is used for the superior clutter suppression performance; and (2) the proposed method completely  ...  To solve this problem, a novel robust space–time joint sparse processing method with airborne active array is proposed.  ...  recovery method; (4) A fast sparse recovery algorithm based on the block SBL framework is used to obtain the sparse solution expression of the multi-frame echo data of CUT; (5) The sparse solution should  ... 
doi:10.3390/rs14112647 fatcat:k4gywyi3mra2rnptzt4x4spula
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