High resolution beamforming using sparse recovery from sensor array data

2013 ◽  
Vol 133 (5) ◽  
pp. 3579-3579
Author(s):  
Ravi Menon ◽  
Peter Gerstoft
Keyword(s):  
High Resolution ◽  
Sensor Array ◽  
Sparse Recovery ◽  
Array Data

scholarly journals Partial Angular Sparse Representation Based DOA Estimation Using Sparse Separate Nested Acoustic Vector Sensor Array

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4465 ◽  
Author(s):  
Jianfeng Li ◽  
Zheng Li ◽  
Xiaofei Zhang
Keyword(s):  
High Resolution ◽  
Sparse Representation ◽  
Sensor Array ◽  
Doa Estimation ◽  
Sparse Recovery ◽  
Estimation Methods ◽  
Acoustic Vector Sensor ◽  
Angle Estimation ◽  
Vector Sensor ◽  
Cross Covariance

In this paper, the issue of direction of arrival (DOA) estimation is discussed, and a partial angular sparse representation (SR)-based method using a sparse separate nested acoustic vector sensor (SSN-AVS) array is developed. Traditional AVS array is improved by separating the pressure sensor array and velocity sensor array into two different sparse array geometries with nested relationship. This improved array geometry can achieve large degrees of freedom (DOF) after the extended vectorization of the cross-covariance matrix, and only partial SR of the angle is required by exploiting the cyclic phase ambiguity caused by the large inter-element spacing of the virtual array. Joint sparse recovery is developed to amend the grid offset and unitary transformation is utilized to transform the complex atoms into real-valued ones. After sparse recovery, the sparse vector can simultaneously provide high-resolution but ambiguous angle estimation and unambiguous reference angle estimation embedded in the AVS array, and they are combined to obtain unique and high-resolution DOA estimation. Compared to other state-of-the-art DOA estimation methods using the AVS array, the proposed algorithm can provide better DOA estimation performance while requiring lower complexity. Multiple simulation results verify the effectiveness of the approach.

scholarly journals Towards human distance estimation using a thermal sensor array

2021 ◽  
Author(s):  
Abdallah Naser ◽  
Ahmad Lotfi ◽  
Joni Zhong
Keyword(s):  
High Resolution ◽  
Independent Living ◽  
Sensor Array ◽  
Distance Estimation ◽  
Thermal Sensor ◽  
Indoor Environments ◽  
Contagious Diseases ◽  
Novel Approach ◽  
Thermal Cameras ◽  
Distance Estimator

AbstractHuman distance estimation is essential in many vital applications, specifically, in human localisation-based systems, such as independent living for older adults applications, and making places safe through preventing the transmission of contagious diseases through social distancing alert systems. Previous approaches to estimate the distance between a reference sensing device and human subject relied on visual or high-resolution thermal cameras. However, regular visual cameras have serious concerns about people’s privacy in indoor environments, and high-resolution thermal cameras are costly. This paper proposes a novel approach to estimate the distance for indoor human-centred applications using a low-resolution thermal sensor array. The proposed system presents a discrete and adaptive sensor placement continuous distance estimators using classification techniques and artificial neural network, respectively. It also proposes a real-time distance-based field of view classification through a novel image-based feature. Besides, the paper proposes a transfer application to the proposed continuous distance estimator to measure human height. The proposed approach is evaluated in different indoor environments, sensor placements with different participants. This paper shows a median overall error of $$\pm 0.2$$ ± 0.2  m in continuous-based estimation and $$96.8\%$$ 96.8 % achieved-accuracy in discrete distance estimation.

Flexible High‐Resolution Triboelectric Sensor Array Based on Patterned Laser‐Induced Graphene for Self‐Powered Real‐Time Tactile Sensing

2021 ◽  
pp. 2100709 ◽  
Author(s):  
Zhengguang Yan ◽  
Liangliang Wang ◽  
Yifan Xia ◽  
Rendong Qiu ◽  
Wenquan Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Sensor Array ◽  
Tactile Sensing ◽  
Self Powered

Adaptive Sparse Recovery of Moving Targets for Distributed MIMO Radar

2014 ◽  
Vol 933 ◽  
pp. 450-455
Author(s):  
Hui Yu ◽  
Guang Hua Lu ◽  
Hai Long Zhang
Keyword(s):  
High Resolution ◽  
Sparse Recovery ◽  
Mimo Radar ◽  
Moving Target ◽  
Recovery Algorithm ◽  
Low Snr ◽  
Computation Efficiency ◽  
Target Imaging ◽  
Moving Target Imaging ◽  
Recovery Error

The high resolution and better recovery performance with distributed MIMO radar would be significantly degraded when the target moves at an unknown velocity. In this paper, we propose an adaptive sparse recovery algorithm for moving target imaging to estimate the velocity and image jointly with high computation efficiency. With an iteration mechanism, the proposed method updates the image and estimates the velocity alternately by sequentially minimizing the norm and the recovery error. Numerical simulations are carried out to demonstrate that the proposed algorithm can retrieve high-resolution image and accurate velocity simultaneously even in low SNR.

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