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Sound localization using compressive sensing

Hong Jiang, Boyd Mathews, Paul Wilford
2013 arXiv   pre-print
In this paper, we propose a novel method for localization of a sound source using compressive sensing.  ...  The compressive measurements can be used to accurately compute the location of a sound source.  ...  In practice, it has been found that randomly permutated rows of the Walsh-Hadamard matrix may be used to form a sensing matrix with satisfactory results Zhang, 2011, Jiang, et al., 2012) .  ... 
arXiv:1302.7070v1 fatcat:or7ul6v2kfae7dvj3e3vadjolq

Sub-sampling-based 2D localization of an impulsive acoustic source in reverberant environments

Muhammad Omer, Ahmed A Quadeer, Mohammad S Sharawi, Tareq Y Al-Naffouri
2014 EURASIP Journal on Advances in Signal Processing  
The arrival time of the direct path signal at a pair of microphones is identified from the estimated RIR, and their difference yields the desired time delay estimate (TDE).  ...  We consider the RIR as a sparse phenomenon and apply a recently proposed sparse signal reconstruction technique called orthogonal clustering (OC) for its estimation from the sub-sampled received signal  ...  of Petroleum and Minerals (KFUPM) for funding this work through project no. 09-ELE763-04 as part of the National Science, Technology and Innovation Plan.  ... 
doi:10.1186/1687-6180-2014-116 fatcat:5aqhulxkpzevxeju4mp452ku6q

2020 Index IEEE Signal Processing Letters Vol. 27

2020 IEEE Signal Processing Letters  
., +, LSP 2020 356-360 Compressed Arrays and Hybrid Channel Sensing: A Cramér-Rao Bound Based Analysis.  ...  ., +, LSP 2020 1455-1459 Primary Quantization Matrix Estimation of Double Compressed JPEG Images via CNN.  ... 
doi:10.1109/lsp.2021.3055468 fatcat:wfdtkv6fmngihjdqultujzv4by

Application of Compressive Sensing Techniques in Distributed Sensor Networks: A Survey [article]

Thakshila Wimalajeewa, Pramod K. Varshney
2019 arXiv   pre-print
reconstruction in centralized as well in decentralized settings, (ii) solve a variety of inference problems such as detection, classification and parameter estimation, with compressed data without signal  ...  In this survey paper, our goal is to discuss recent advances of compressive sensing (CS) based solutions in wireless sensor networks (WSNs) including the main ongoing/recent research efforts, challenges  ...  The TDOA estimates computed in the compressed domain can be used for source localization.  ... 
arXiv:1709.10401v2 fatcat:fnk6vwwykvc5radcgrl22g42hu

On the effect of random snapshot timing jitter on the covariance matrix for JADE estimation

Ahmad Bazzi, Dirk T. M. Slock, Lisa Meilhac
2015 2015 23rd European Signal Processing Conference (EUSIPCO)  
This sample covariance matrix is an input to the JADE and many other algorithms for signal parameter estimation.  ...  In this paper, we focus on joint multipath angle and delay estimation (JADE) in an OFDM communication setting.  ...  This rank-excess problem is, in fact, one problem in compressed sensing, where the true signal subspace is sparsely contained in the subspace of the covariance matrix.  ... 
doi:10.1109/eusipco.2015.7362857 dblp:conf/eusipco/BazziSM15 fatcat:xj3ztw6lxveavnoywvd2oulh4u

Table of Contents

2020 IEEE Signal Processing Letters  
Zhang, and Y. Y. Zhu 980 Improved Covariance Matrix Estimation With an Application in Portfolio Optimization . . . . . S. Deshmukh and A.  ...  Jia, and X. Fan 1220 Estimating the Number of Sinusoids in Additive Sub-Gaussian Noise With Finite Measurements . . . . . . . . . . . . . . H.  ...  Le Meur 1819 Underdetermined DOA Estimation via Covariance Matrix Completion for Nested Sparse Circular Array in Nonuniform Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/lsp.2020.3040840 fatcat:ezrfzwo6tjbkfhohq2tgec4m6y

Multidimensional Orthogonal Matching Pursuit-based RIS-aided Joint Localization and Channel Estimation at mmWave [article]

Murat Bayraktar, Joan Palacios, Nuria González-Prelcic, Charlie Jianzhong Zhang
2022 arXiv   pre-print
We propose to exploit a multidimensional orthogonal matching pursuit strategy for compressive channel estimation in a RIS-aided millimeter wave system.  ...  We also combine this strategy with a localization approach which does not rely on the absolute time of arrival of the LoS path.  ...  Compressed Channel Estimation via MOMP Our goal is to estimate the channel matrix from a set of observations of the received signal in (4), exploiting the multiple dictionaries defined in Section III-A  ... 
arXiv:2203.13327v1 fatcat:gy27oqrj2bbilnbp3knznrc6a4

Flexible MIMO Radar Antenna Selection for Vehicle Positioning in IIOT Based on CNN

Yang Xiong, Ke Wang, Liangtian Wan
2020 Mathematical Problems in Engineering  
Owing to the industrial big data (IBD), it is possible to obtain a massive labeled dataset offline, which contains all possible DOAs and the array measurement.  ...  Herein, we assume the DOA of the vehicle has been known as a prior, and the optimization criterion is to minimize the Crame´r–Rao based on DOA estimation when we use the selected Tx/Rx subarrays.  ...  To this end, the compressive sensing concept was introduced [7] , in which Tx/Rx is randomly chosen from a full array. e DOA can be accurately recovered with high probability via solving an optimization  ... 
doi:10.1155/2020/2048606 fatcat:ydzero74xrhvbic4texyqxljvq

Indoor acoustic localization: a survey

Manni Liu, Linsong Cheng, Kun Qian, Jiliang Wang, Jin Wang, Yunhao Liu
2020 Human-Centric Computing and Information Sciences  
with even a small measurement error [76] .  ...  In the first step, geographic information such as distances and angles are measured. In the second step, the target is located using those data.  ...  While the TDoA between a RF signal and an ultrasonic signal is applied in Cricket, and the TDoAs among multiple speakers are leveraged in [32, 75] , AMIL [21] on the other hand measures the TDoAs of  ... 
doi:10.1186/s13673-019-0207-4 fatcat:lueb6jrvqncytg2wzevf6naija

Sparse multi-target localization using cooperative access points

Hadi Jamali-Rad, Hamid Ramezani, Geert Leus
2012 2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM)  
In this paper, a novel multi-target sparse localization (SL) algorithm based on compressive sampling (CS) is proposed.  ...  Different from the existing literature for target counting and localization where signal/received-signal-strength (RSS) readings at different access points (APs) are used separately, we propose to reformulate  ...  It is worth mentioning that here we have a natural compression in the problem in the sense that the number of measurements is limited to the number of APs (M ) which in many practical scenarios is much  ... 
doi:10.1109/sam.2012.6250509 dblp:conf/ieeesam/RadRL12 fatcat:a54ldurfafbjhos6z3kqscqbbq

Parametric Sparse Bayesian Dictionary Learning for Multiple Sources Localization with Propagation Parameters Uncertainty and Nonuniform Noise [article]

Kangyong You, Wenbin Guo, Tao Peng, Yueliang Liu, Peiliang Zuo, and Wenbo Wang
2019 arXiv   pre-print
Furthermore, multiple snapshot measurements are utilized to improve the localization accuracy, and the Cramer-Rao lower bound (CRLB) is derived to analyze the theoretical estimation error bound.  ...  Moreover, most existing works only consider the single source and the identical measurement noise scenario, while in practice multiple co-channel sources may transmit simultaneously, and the measurement  ...  with the diagonal elements of matrix A. • is the Hadamard (element-wise) product operator.  ... 
arXiv:1911.08021v2 fatcat:ffbqp5r6trcgbilijpstx5kuj4

Spatial Sound Localization via Multipath Euclidean Distance Matrix Recovery

Mohammad Javad Taghizadeh, Afsaneh Asaei, Saeid Haghighatshoar, Philip N. Garner, Herve Bourlard
2015 IEEE Journal on Selected Topics in Signal Processing  
The recording time of the microphone and generation of the source signal is asynchronous and estimated via the proposed procedure.  ...  Source localization is achieved through optimizing the location of the source matching those measurements.  ...  We also would like to acknowledge the anonymous reviewers for the insightful and precise comments and remarks to improve the quality and clarity of the manuscript.  ... 
doi:10.1109/jstsp.2015.2422677 fatcat:q26daej3zvgwxerztih2wn2c3q

2010 Index IEEE Transactions on Signal Processing Vol. 58

2010 IEEE Transactions on Signal Processing  
., +, TSP July 2010 3681-3691 Mobile Emitter Geolocation and Tracking Using TDOA and FDOA Measurements.  ...  ., +, TSP Jan. 2010 175-188 Multidimensional Scaling Analysis for Passive Moving Target Localization With TDOA and FDOA Measurements. Wei, H.  ... 
doi:10.1109/tsp.2010.2092533 fatcat:4y66ezuo7zf6doe6nwjqwtc42i

Multichannel Source Separation Using Time-Deconvolutive CNMF

Thadeu Dias, Wallace Martins, Luiz Biscainho
2020 Journal of Communication and Information Systems  
The proposed parameter estimation framework is compatible with previous related works, and can be thought of as a step toward a more general method.  ...  We approach the problem using complex-valued non-negative matrix factorization (CNMF), and extend previous works by tailoring advanced (single-channel) NMF models, such as the deconvolutive NMF, to the  ...  sign(·) both operate elementwise on their arguments, and denotes the matrix Hadamard product.  ... 
doi:10.14209/jcis.2020.11 fatcat:uo3xxew5effbzl22x6yhk6iyvi

2019 Index IEEE Transactions on Signal Processing Vol. 67

2019 IEEE Transactions on Signal Processing  
., TSP June 1, 2019 2868-2883 Tight Performance Bounds for Compressed Sensing With Conventional and Group Sparsity.  ...  ., +, TSP April 15, 2019 2052- 2065 Tight Performance Bounds for Compressed Sensing With Conventional and Group Sparsity.  ... 
doi:10.1109/tsp.2020.2968163 fatcat:dvvpqntb2rc2bjed5nnk4xora4
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