scholarly journals An Accurate Doppler Parameters Calculation Method of Geosynchronous SAR Considering Real-Time Zero-Doppler Centroid Control

2021 ◽  
Vol 13 (20) ◽  
pp. 4061
Author(s):  
Faguang Chang ◽  
Chunrui Yu ◽  
Dexin Li ◽  
Yifei Ji ◽  
Zhen Dong
Keyword(s):  
Real Time ◽  
Considerable Effect ◽  
Synthetic Aperture ◽  
Simulation Experiments ◽  
The Real ◽  
Time Zero ◽  
Proposed Model ◽  
Ground Target ◽  
Azimuth Resolution ◽  
Parameters Calculation

The zero-Doppler centroid control in geosynchronous synthetic aperture radar (GEO SAR) is beneficial to reduce the imaging complexity (reduces range-azimuth coupling in received data), which can be realized by adjusting the radar line of sight (RLS). In order to maintain the zero-Doppler centroid throughout the whole orbit of the GEO SAR satellite, the RLS needs to be adjusted in real-time. Due to the ultra-long synthetic aperture time of GEO SAR, the RLS variation during the synthetic aperture time cannot be neglected. However, in the previous related papers, the real-time variation of RLS during the synthetic aperture time was not taken into account in the calculation of Doppler parameters, which are closely related to the RLS, resulting in inaccurate calculation of Doppler parameters. Considering this issue, an accurate Doppler model (the model of relative motion between satellite and ground target) of GEO SAR is proposed in this paper for the accurate calculation of Doppler parameters (Doppler centroid and Doppler bandwidth and other parameters). Finally, simulation experiments are designed to confirm the effectiveness and necessity of the proposed model. The results indicate that the RLS variation during the synthetic aperture time has a considerable effect on Doppler parameters performance of the GEO SAR, and refers to a more stable azimuth resolution performance (the resolution is kept near a relatively stable value at most positions of the elliptical orbit) compared with the case that does not consider the real-time zero-Doppler centroid control.

Contingent Rule: Information Aesthetic, Performance and Hypermediacy

Leonardo ◽  
2011 ◽  
Vol 44 (3) ◽  
pp. 286-287 ◽  
Author(s):  
Eung Suk Kim ◽  
Joonsung Yoon
Keyword(s):  
Stock Market ◽  
Real Time ◽  
Information Visualization ◽  
Market Data ◽  
The Real ◽  
Proposed Model ◽  
Aesthetic Performance

This paper proposes a model of information aesthetic performance in the context of hypermediacy. It addresses the need to consider the features of performance in recently emerging information visualization artwork. By analyzing an artwork, the real-time stock market data-based Contingent Rule, the authors discuss aesthetic effects of performance as well as information visualization. The proposed model could contribute to a better understanding of information visualization in terms of Jay David Bolter and Richard Grusin's ‘hypermediacy.’ This research provides a new guideline for reviewing information visualization.

scholarly journals ON THE DEMAND OF PLANNING THE IMPLEMENTATIONOF MEASURES FOR PRODUCTION STIMULATION BY APPLYING HYDROCHLORIC ACID SOLUTION IN THE REAL TIME MODE

2017 ◽  
pp. 66-71
Author(s):  
V. V. Mukhametshin
Keyword(s):  
Hydrochloric Acid ◽  
Acid Solution ◽  
Real Time ◽  
Hydrochloric Acid Solution ◽  
Considerable Effect ◽  
Time Factor ◽  
The Real ◽  
Real Time Mode ◽  
Performance Time ◽  
Bottom Hole

The authors of the paper observed considerable effect on performance time factor based onthe experience of bottom hole zone treatment with the use of hydrochloric acid solution preventing emulsification. The paper presents models and algorithms allowing planning effectiveness, choice of wells and technologies considering this factor in the real time mode.

scholarly journals A Superfast Super-Resolution Method for Radar Forward-Looking Imaging

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 817
Author(s):  
Weibo Huo ◽  
Qiping Zhang ◽  
Yin Zhang ◽  
Yongchao Zhang ◽  
Yulin Huang ◽  
...  
Keyword(s):  
Computational Complexity ◽  
Real Time ◽  
Super Resolution ◽  
Coefficient Matrix ◽  
Resolution Method ◽  
The Real ◽  
L1 Regularization ◽  
Regularization Problem ◽  
Azimuth Resolution ◽  
Forward Looking

The super-resolution method has been widely used for improving azimuth resolution for radar forward-looking imaging. Typically, it can be achieved by solving an undifferentiable L1 regularization problem. The split Bregman algorithm (SBA) is a great tool for solving this undifferentiable problem. However, its real-time imaging ability is limited to matrix inversion and iterations. Although previous studies have used the special structure of the coefficient matrix to reduce the computational complexity of each iteration, the real-time performance is still limited due to the need for hundreds of iterations. In this paper, a superfast SBA (SFSBA) is proposed to overcome this shortcoming. Firstly, the super-resolution problem is transmitted into an L1 regularization problem in the framework of regularization. Then, the proposed SFSBA is used to solve the nondifferentiable L1 regularization problem. Different from the traditional SBA, the proposed SFSBA utilizes the low displacement rank features of Toplitz matrix, along with the Gohberg-Semencul (GS) representation to realize fast inversion of the coefficient matrix, reducing the computational complexity of each iteration from O(N3) to O(N2). It uses a two-order vector extrapolation strategy to reduce the number of iterations. The convergence speed is increased by about 8 times. Finally, the simulation and real data processing results demonstrate that the proposed SFSBA can effectively improve the azimuth resolution of radar forward-looking imaging, and its performance is only slightly lower compared to traditional SBA. The hardware test shows that the computational efficiency of the proposed SFSBA is much higher than that of other traditional super-resolution methods, which would meet the real-time requirements in practice.

Arterial-Friendly Local Ramp Metering Control Strategy

2021 ◽  
pp. 036119812199458
Author(s):  
Yao Cheng ◽  
Gang-Len Chang
Keyword(s):  
Real Time ◽  
Time Of Day ◽  
Ramp Metering ◽  
Real Time Control ◽  
Simulation Experiments ◽  
Traffic Conditions ◽  
Time Control ◽  
Proposed Model ◽  
Time Extension ◽  
Base Module

To prevent local streets being blocked by overflowing on-ramp queues, a standard practice of ramp metering control is to restrain its function when a series of preset conditions are identified by on-ramp queue detectors. Such a trade-off between potential ramp queue spillback and the restraint resulting from the operation of metering control may often fail to either effectively mitigate bottlenecks caused by on-ramp waving or convince arterial users and local traffic agencies of the need for ramp metering operations. This study, therefore, presents an arterial-friendly local ramp metering system (named AF-ramp) that can achieve the target metering rate to produce optimal freeway conditions without ramp queues spilling back onto local streets. This is achieved by concurrently optimizing the signal plans for those intersections that send turning flows to the ramp. At this stage, this system has been developed for time-of-day control. It could also serve as the base module for extending to real-time control, or multi-ramp coordinated operations. The AF-ramp model, with its ability to optimize the arterial signals concurrently with the ramp metering rate, can ensure the best use of the capacity of local intersections and prevent any gridlock caused by overflows from on-ramp queue spillback or arterial turning traffic. With extensive simulation experiments, the evaluation results confirmed the AF-ramp model’s effectiveness in improving traffic conditions on both the freeway and its neighboring arterial links at the same time. This study has also introduced the real-time extension of the proposed model and a framework of a transition from the time-of-day control to fully responsive real-time operations.

scholarly journals On-Line Interpretation and Real-Time Diagnosis of Rocket’s Single Equipment

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Erbao Xu ◽  
Yan Li ◽  
Lining Peng ◽  
Yuxi Li ◽  
Mingshun Yang
Keyword(s):  
Real Time ◽  
Launch Vehicle ◽  
The Real ◽  
Abnormal State ◽  
Proposed Model ◽  
Single Vehicle ◽  
On Line ◽  
Edge Layer ◽  
Time Diagnosis ◽  
Sheer Number

The work state of a launch vehicle is generally interpreted automatically on software. However, the sheer number of target parameters makes it difficult to realize real-time interpretation, and abnormal interpretation result does not necessarily mean that the vehicle is in abnormal state. This paper introduces the edge computing to achieve on-line interpretation and real-time diagnosis of a single launch vehicle. Firstly, the parameters to be interpreted were subjected to thresholding, leaving only those with high interpretation value. Next, the interpretation server layer of the real-time diagnosis model was built based on the attribute and value reduction algorithm of variable precision rough set (VPRS). Moreover, the higher-grade criteria were written in criterion modeling language (CML) and used to interpret the various higher-grade interpretation data pushed by the edge layer in real time. On this basis, the outputs of the edge layer and interpretation server layer were integrated to achieve the real-time diagnosis of single vehicle faults. Finally, the proposed model was proved feasible through the application in a launch vehicle.

scholarly journals A Real-Time Chain and Variable Bulk Arrival and Variable Bulk Service (VBAVBS) Model with λF

2020 ◽  
Vol 10 (10) ◽  
pp. 3651
Author(s):  
Nohpill Park ◽  
Abhilash Kancharla ◽  
Hye-Young Kim
Keyword(s):  
Open Source ◽  
Real Time ◽  
Theoretical Foundation ◽  
Queueing Model ◽  
Time System ◽  
Real Time System ◽  
The Real ◽  
Proposed Model ◽  
Bulk Service ◽  
Bulk Arrival

This paper proposes a real-time chain and a novel embedded Markovian queueing model with variable bulk arrival (VBA) and variable bulk service (VBS) in order to establish and assure a theoretical foundation to design a blockchain-based real-time system with particular interest in Ethereum. Based on the proposed model, various performances are simulated in a numerical manner in order to validate the efficacy of the model by checking good agreements with the results against intuitive and typical expectations as a baseline. A demo of the proposed real-time chain is developed in this work by modifying the open source of Ethereum Geth 1.9.11. The work in this paper will provide both a theoretical foundation to design and optimize the performances of the proposed real-time chain, and ultimately address and resolve the performance bottleneck due to the conventional block-synchrony by employing an asynchrony by the real-time deadline to some extent.

scholarly journals YOLO-Highway: An Improved Highway Center Marking Detection Model for Unmanned Aerial Vehicle Autonomous Flight

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zhiwei Zhao ◽  
Jianfeng Han ◽  
Lili Song
Keyword(s):  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
Visual Navigation ◽  
Detection Accuracy ◽  
Highway Maintenance ◽  
The Real ◽  
Detection Model ◽  
Proposed Model ◽  
Time Requirements ◽  
Aerial Vehicle

Automatic visual navigation flight of an unmanned aerial vehicle (UAV) plays an important role in the highway maintenance field. Automatic highway center marking detection is the most important part of the visual navigation flight of a UAV. In this study, the UAV-viewed highway data are collected from the UAV perspective. This paper proposes a model named the YOLO-Highway that uses an improved form of the You Only Look Once (YOLO) model to enhance the real-time detection of highway marking problems. The proposed model is mainly designed by optimizing the network structure and the loss function of the original YOLOv3 model. The proposed model is verified by the experiments using the highway center marking dataset, and the results show that the average precision (AP) of the trained model is 82.79%, and the frames per second (FPS) is 25.71 f/s. In comparison with the original YOLOv3 model, the detection accuracy of the proposed model is improved by 7.05%, and its speed is improved by 5.29 f/s. Moreover, the proposed model had stronger environmental adaptability and better detection precision and speed than the original model in complex highway scenarios. The experimental results show that the proposed YOLO-Highway model can accurately detect the highway center markings in real-time and has high robustness to changes in different environmental conditions. Therefore, the YOLO-Highway model can meet the real-time requirements of the highway center marking detection.

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