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compressed sensing algorithm for neighbour discovery in mobile ad hoc networks

IET COMMUNICATIONS 2019年第12期13卷 1781-1786页

作者： Luo, Yuan Dang, Jiaoiao Song, Zuxun Wang, Baoping Northwestern Polytech Univ Sch Elect & Informat Xian Shaanxi Peoples R China Northwestern Polytech Univ Sci & Technol UVA Lab Radio Dept Xian Shaanxi Peoples R China

Considering the neighbour discovery problem in mobile ad hoc networks (MANETS) with omnidirectional antennas, all nodes want to discover the nodes within a single hop and obtain their identities. However, many existing algorithms spend an extra overhead for neighbour discovery and there is a need of response from neighbours. In this study, a slot allocation scheme is introduced for duplex communication, making all nodes recognisable to each other with a unique codeword. Then, a novel neighbour discovery algorithm based on compressed sensing to apply in this scheme is proposed;it enables all nodes to update neighbour information through the received signal after one or several frames and spends no extra overhead. Furthermore, many algorithms cannot be applied in the overload networks, but the algorithm proposed here is suited for overload networks;the upper bound for its active neighbours is limited to the performance of the network. Finally, the algorithm is validated through simulation and the effect of the three main factors on the performance of the algorithm is researched. The result implies that this algorithm can adapt to various scenarios of the MANETS.

关键词： mobile ad hoc networks compressed sensing omnidirectional antennas network coding compressed sensing algorithm mobile ad hoc networks neighbour discovery problem omnidirectional antennas single hop slot allocation scheme MANET duplex communication codeword

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Reconstruction of Slice Image from Solid Rocket Motor Skiagrams Based on compressed sensing algorithm

Reconstruction of Slice Image from Solid Rocket Motor Skiagr...

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International Conference on Mechatronics and Industrial Informatics (ICMII 2013)

作者： Xu, Zhigao Ning, Chao Ma, Jing Li, Xiangbin Xian Res Inst High Technol Xian 710025 Peoples R China

ISBN: (纸本)9783037856949

A reconstruction program of slice image based on Solid Rocket Motor (SRM) skiagrams is put forward to overcome the deficiency of artificial radiographic interpretation. The algebraic reconstruction algorithm based on compressed sensing technology is designed. The influence of radiographic interval angle and skiagram sizes on reconstructed slice image is studied. Radiographic interval angle has a great impact on the quality of the reconstructed image. Slender defects are not sensitive to changes in the length of the skiagram, but circular defects are sensitive to changes in the length of the skiagram. The reconstruction tests of model SRM skiagrams show that the sizes and locations of the debonded defects can be easily ascertained and the efficiency of radiographic interpretation can be greatly improved.

关键词： compressed sensing algorithm Solid Rocket Motor Skiagram Reconstruction

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Research on Intelligent System of Complex Structured Light Three-Dimensional Measurement Based on Machine Vision 4

Research on Intelligent System of Complex Structured Light T...

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4th IEEE International Conference on Data Science and Computer Application, ICDSCA 2024

作者： Xu, Zhihua Xu, Wenquan School of Design and Art Jingdezhen Ceramic University Jingdezhen China

ISBN: (纸本)9798350368239

This system integrates complex structured light projection and machine vision imaging technology to achieve efficient and accurate measurement of three-dimensional structures. In order to deal with the high computational load and error problems of traditional methods in data processing, this paper designs an image processing solution based on compressed sensing algorithm. By means of compressed sensing technology, the quantity of data is effectively decreased during the process of image collection and data reconstruction, thus remarkably lessening the computational load. This approach not only streamlines the data-processing procedure but also enhances the measurement precision of the system on complex surfaces, allowing the system to attain a better equilibrium between real-time performance and accuracy. To confirm the performance and superiority of the algorithm, this paper builds multiple test models in a simulation environment and comprehensively assesses the impact of the compressed sensing algorithm by contrasting the measurement results under different structured light modes. The experimental outcomes demonstrate that in comparison with the traditional method, the proposed algorithm exhibits remarkable advantages in handling complex curved surfaces and unevenly reflecting surfaces. It can keep low inaccuracies while guaranteeing high precision and has strong sturdiness against external interference. Specific data show that the measurement error of the system under complex surface conditions is controlled within 0.05 mm, meeting the needs of high-precision measurement. ©2024 IEEE.

关键词： complex structure compressed sensing algorithm Machine vision optical 3D measurement

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Clinical feasibility study of 3D intracranial magnetic resonance angiography using compressed sensing

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JOURNAL OF MAGNETIC RESONANCE IMAGING 2019年第6期50卷 1843-1851页

作者： Lin, Zhiyong Zhang, Xiaodong Guo, Li Wang, Ke Jiang, Yuan Hu, Xiaoyu Huang, Yong Wei, Juan Ma, Shuai Liu, Yi Zhu, Lina Zhuo, Zhizheng Liu, Jing Wang, Xiaoying Peking Univ Hosp 1 Dept Radiol 8 Xishiku St Beijing 100034 Peoples R China Philips Res China Shanghai Peoples R China Philips Healthcare Beijing Peoples R China

Background compressed sensing (CS) has been widely used to improve the speed of MRI, but the feasibility of application in 3D intracranial MR angiography (MRA) needs to be evaluated in clinical practice. Purpose To evaluate the clinical feasibility of CS-MRA in comparison with conventional 3D-MRA (Con-MRA). Study Type Retrospective. Subjects Forty-nine consecutive patients with suspected intracranial arterial disease. Field Strength/Sequence 3T MRI. 3D time-of-flight (TOF) MRA using a CS algorithm and conventional 3D TOF MRA scan. Assessment Three radiologists (4, 11, and 12 years of experience in neuroradiology) independently assessed the image quality, vascular lesions, and variations of intracranial arteries of both CS-MRA and Con-MRA, respectively. Statistical Tests The Kendall W test was performed to assess the interobserver agreement of image quality and intracranial arterial stenosis. A nonparametric test (Wilcoxon test) was used for comparison of the image quality and definition of the external carotid artery (ECA). Weighted kappa analysis was performed for the interstudy agreement of intracranial arterial stenosis. The aneurysm, decreased branches, congenital hypoplasia, absence, and variant branching of intracranial arteries were observed and evaluated for interobserver agreement and interstudy agreement by kappa analysis. Paired-t-tests for signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were conducted. Results Image quality is better for CS-MRA compared with Con-MRA with significance (Z = -3.710 to -2.673, with P < 0.01). The interstudy agreement of lesion and variation of intracranial arteries assessment for each observer was excellent. The SNR and CNR were significantly higher in CS-MRA compared with Con-MRA (P < 0.001). The definition of ECA of CS-MRA was significantly better (Z = -4.9, P < 0.001). Data Conclusion CS-MRA showed significantly higher image quality with less blur, comparable image diagnostic performance of intracranial arte

关键词： magnetic resonance angiography compressed sensing algorithm cerebrovascular disease

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MP mitigation in GNSS positioning by GRU NNs and adaptive wavelet filtering

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IET COMMUNICATIONS 2019年第17期13卷 2756-2766页

作者： Li, Dengao Zhang, Pei Zhao, Jumin Cheng, Junbing Zhao, Hongyan Taiyuan Univ Technol Dept Elect & Commun Engn Coll Informat & Comp Sci Taiyuan Shanxi Peoples R China

In urban canyons, multipath (MP) signals have some problems such as short time delay, high dynamic, and uncontrollable. To solve this problem and mitigate the interference of MP effect on positioning, the authors proposed a new method which uses gated recurrent unit (GRU) neural networks (NNs) aided by compressed sensing algorithm to estimate parameters of MP signal accurately. They showed how to build the GRU - deformation of recurrent NNs (RNNs) - in a dynamic environment, and estimated the MP signals parameters accurately. Also, considering the special cases in a dynamic environment, they used the adaptive wavelet filter to optimise the NNs, compensated pseudo-distance, and improved the accuracy of positioning. Like other NNs, the learning process of this machine learning method in the dynamic environment can be summarised as obtaining data from different environmental conditions. For this, they collected signal data from different speeds to train GRU-RNN model, which correctly estimated the MP signal's parameter value in a different environment and different speeds. By experimental verification, when the speed is slower than 20 km/h, GRU-RNN can reduce code tracking error to 0.08 chips, and increased the positioning accuracy by about 13%.

关键词： satellite navigation learning (artificial intelligence) Global Positioning System recurrent neural nets wavelet transforms adaptive filters recurrent NNs dynamic environment MP signals parameters adaptive wavelet filter compensated pseudodistance machine learning method signal data MP signal positioning accuracy MP mitigation GNSS positioning adaptive wavelet filtering urban canyons multipath signals short time delay MP effect recurrent unit neural networks compressed sensing algorithm GRU-RNN model GRU NN velocity 20 0 km h

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Study on the key technology of spectral reflectance reconstruction based on a single pixel detector

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LASER PHYSICS LETTERS 2017年第12期14卷

作者： Li, Bei Zhang, Haojun Zhang, Leihong Kang, Yi Zhan, Wenjie Yi, Wenjuan Zhang, Dawei Univ Shanghai Sci & Technol Coll Commun & Art Design Shanghai 200093 Peoples R China Shanghai Radio Equipment Res Inst Shanghai 200090 Peoples R China Univ Shanghai Sci & Technol Sch Opt Elect & Comp Engn Shanghai 200093 Peoples R China

In order to realize an accurate reconstruction of images, this article explores image reconstruction from a spectrum point of view. Combined with a principal component analysis method and compressed sensing algorithm, this article puts forward a spectral reflectance reconstruction algorithm based on a single pixel detector, and compares the different modulation matrixes for DMD in the experiment. From subjective evaluation and three objective evaluation methods: color difference, peak signal-to-noise ratio and structural similarity, we compare and analyze the reconstruction effects of two modulation methods: random modulation and Hadamard modulation. The experimental results show that the color difference of the spectral reflectance reconstruction method of a single pixel detector based on random modulation is smaller, the similarity of the structure is higher, and the peak signal-to-noise ratio is greater than Hadamard modulation. To sum up, the spectral reflectance reconstruction algorithm of a single pixel detector based on random modulation is better than Hadamard modulation, which is more conducive to an accurate reconstruction of spectral reflectance.

关键词： single pixel detector spectral reflectance reconstruction principal component analysis compressed sensing algorithm

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Joint High Resolution Imaging and Autofocusing Technique via an Iterative Method for Multistatic Passive Radar

Joint High Resolution Imaging and Autofocusing Technique via...

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International Conference on Radar Systems

作者： Jue Wang Jun Wang Haiting Song Xidian University Xian Shaanxi CN

ISBN: (纸本)9781785616723

The performance of the multistatic passive radar imaging system (MPRIS) based on illuminators of opportunity is not as good as traditional SAR/ISAR due to the narrow bandwidth of the radiated signal and the unevenly distribution of the non-cooperation illuminators. Moreover, the inaccurate position measurement of illuminators, receivers and the target would cause phase errors in the target echo and the quality of the image would further subject to degradation. With the motivation to improve the performance of the MPRIS, an imaging algorithm based on the principle of tomographic imaging is presented. On account of the sparse distribution of the scatterer of the target, the compressed sensing algorithm is extended to the multistatic configuration to realize the super resolution image formation. In addition, an autofocusing technique based on the multistatic observation model is proposed. By defining a quality measure of the image, the phase error is found by iteratively solving an equation which is derived by optimizing the quality measure of the image. The convergence and performance of the presented autofocusing technique have been validated by simulation results.

关键词： Multistatic passive radar Tomographic imaging compressed sensing algorithm Autofocusing technique

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