Multi-Scene Doppler Power Spectrum Modeling of LEO Satellite Channel Based on Atlas Fingerprint Method

Wen, Liu; Zheng, Shixuan; Deng, Zhongliang; Wang, Ke; Lin, Wenliang; Lei, Jizhao; Jin, Yihui; Líu, Hao

doi:10.1109/access.2021.3051774

Cited by 8 publications

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Every model has advantages and disadvantages, and the selection of a model depends on the needs of the specific application [30,31,32]. Recent research has demonstrated that deep learning models such as CNNs and DBNs outperform more conventional machine learning models such as SVMs and DTs in satellite image classification tasks [33,34,35]. To examine the full potential of ensemble models for the classification of satellite images, additional research is necessary for a variety of scenarios.…”

Section: Literature Reviewmentioning

confidence: 99%

MSDMCCG: Design of an efficient Multimodal Satellite Data Processing Model for Component-level analysis of Contextual Geographic entities

Bhoi,

Patel

2023

Preprint

View full text Add to dashboard Cite

This paper presents an efficient model for analysing contextual geographic entities in satellite data at a component level. The model utilizes various feature extraction techniques, including Fourier, Entropy, Wavelet, and Gabor, along with vegetation indices such as NDVI, SAVI, and EVI, to capture the multimodal characteristics of the satellite data. Classification operations are performed using a binary cascaded convolutional neural network (CNN), while incremental learning is facilitated through the Q-learning process. The proposed model offers a novel approach by combining different feature extraction methods, allowing for a comprehensive representation of satellite data. It employs the BCCNN, which exhibits high accuracy in identifying specific geographical features like land, forests, structures, and rivers. Additionally, by utilizing Q-learning for incremental learning, the model's accuracy can improve over time as new data becomes available. Evaluation of the model using an augmented cluster of datasets and samples demonstrated its ability to accurately identify contextual geographic entities with 99.5% accuracy, 98.5% precision, and 98.3% recall. This model holds promise for various applications, including environmental monitoring, disaster management, and urban planning.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

MSDMCCG: Design of an efficient Multimodal Satellite Data Processing Model for Component-level analysis of Contextual Geographic entities

Bhoi,

Patel

2023

Preprint

View full text Add to dashboard Cite

show abstract

Nonlinear Model of Vibrating Flip-Flow Screens That Considers the Effects of Screen Panels

Lin

et al. 2022

IEEE Access

View full text Add to dashboard Cite

Vibrating flip-flow screens have been widely used in the mineral processing industry. As the key components, flip-flow screen panels strongly affect the dynamics of vibrating flip-flow screens. However, there is no systematic research into this problem. In this study, the dynamic characteristics of flip-flow screen panel are identified by the finite element analysis. Furthermore, a nonlinear coupling dynamic model of vibrating flip-flow screens that considers the effects of flip-flow screen panels is proposed, and the analytical and numerical solutions of its governing equation are deduced via the equivalent linearization method and the time marching method. Also, experimental results show that the proposed model describes the movements of vibrating flip-flow screens more accurately than the classical mechanical model which does not consider flip-flow screen panels. Finally, the effects of the screen panel's parameters, such as the slack length and the stiffness, on the dynamics of vibrating flip-flow screens are investigated.

show abstract

High Doppler to Bandwidth Ratio Signal Detection Technique in a Satellite Communication System

Kislyy

Pchenikin

Lukanov

et al. 2022

2022 Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)

View full text Add to dashboard Cite

Multi-Scene Doppler Power Spectrum Modeling of LEO Satellite Channel Based on Atlas Fingerprint Method

Cited by 8 publications

References 20 publications

MSDMCCG: Design of an efficient Multimodal Satellite Data Processing Model for Component-level analysis of Contextual Geographic entities

MSDMCCG: Design of an efficient Multimodal Satellite Data Processing Model for Component-level analysis of Contextual Geographic entities

Nonlinear Model of Vibrating Flip-Flow Screens That Considers the Effects of Screen Panels

High Doppler to Bandwidth Ratio Signal Detection Technique in a Satellite Communication System

Contact Info

Product

Resources

About