A Novel Technique to Compute the Revisit Time of Satellites and Its Application in Remote Sensing Satellite Optimization Design

This paper proposes a novel technique to compute the revisit time of satellites within repeat ground tracks. Different from the repeat cycle which only depends on the orbit, the revisit time is relevant to the payload of the satellite as well, such as the tilt angle and swath width. The technique is discussed using the Bezout equation and takes the gravitational second zonal harmonic into consideration. The concept of subcycles is defined in a general way and the general concept of “small” offset is replaced by a multiple of the minimum interval on equator when analyzing the revisit time of remote sensing satellites. This technique requires simple calculations with high efficiency. At last, this technique is used to design remote sensing satellites with desired revisit time and minimum tilt angle. When the side-lap, the range of altitude, and desired revisit time are determined, a lot of orbit solutions which meet the mission requirements will be obtained fast. Among all solutions, designers can quickly find out the optimal orbits. Through various case studies, the calculation technique is successfully demonstrated.

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Tube Bending Forming Technologies: Advances and Trends

Encyclopedia of Aluminum and Its Alloys ◽

10.1201/9781351045636-140000210 ◽

2019 ◽

Author(s):

Li Heng ◽

Yang He ◽

Ma Jun

Keyword(s):

Health Care ◽

High Performance ◽

Optimization Design ◽

High Efficiency ◽

Complex Structures ◽

Tube Bending ◽

Multiple Defects ◽

Recent Advances ◽

Key Technologies

Bent tube parts have been widely used, as one kind of key components with enormous quantities and diversities, to satisfy the increasing demands for lightweight and high-performance products in broad industries such as aerospace, marine, automobile, energy, and health care. Tube bending is one of the key technologies used for manufacturing these lightweight products. The recent advances in tube bending are critically reviewed from four fundamental issues in tube bending, viz. characterization of tubular materials, prediction of multiple defects, bending formability, and innovative optimization design. Advantages and limitations of some recently developed innovative bending approaches are reviewed. Finally, considering the urgent requirements of more lightweight and high-performance bent tubes with hard-to-deform materials with complex structures, the development trends and corresponding challenges are thereafter presented for realizing the precision and high-efficiency tube bending.

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Payload Configurations for Efficient Image Acquisition – Indian Perspective

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-8-1201-2014 ◽

2014 ◽

Vol XL-8 ◽

pp. 1201-1206 ◽

Cited By ~ 1

Author(s):

D. R. M. Samudraiah ◽

M. Saxena ◽

S. Paul ◽

P. Narayanababu ◽

S. Kuriakose ◽

...

Keyword(s):

Remote Sensing ◽

Data Acquisition ◽

High Efficiency ◽

Image Acquisition ◽

Image Data ◽

Space Research ◽

Remotely Sensed Data ◽

Data Utilization ◽

Spectral Bands ◽

The World

The world is increasingly depending on remotely sensed data. The data is regularly used for monitoring the earth resources and also for solving problems of the world like disasters, climate degradation, etc. Remotely sensed data has changed our perspective of understanding of other planets. With innovative approaches in data utilization, the demands of remote sensing data are ever increasing. More and more research and developments are taken up for data utilization. The satellite resources are scarce and each launch costs heavily. Each launch is also associated with large effort for developing the hardware prior to launch. It is also associated with large number of software elements and mathematical algorithms post-launch. The proliferation of low-earth and geostationary satellites has led to increased scarcity in the available orbital slots for the newer satellites. Indian Space Research Organization has always tried to maximize the utility of satellites. Multiple sensors are flown on each satellite. In each of the satellites, sensors are designed to cater to various spectral bands/frequencies, spatial and temporal resolutions. Bhaskara-1, the first experimental satellite started with 2 bands in electro-optical spectrum and 3 bands in microwave spectrum. The recent Resourcesat-2 incorporates very efficient image acquisition approach with multi-resolution (3 types of spatial resolution) multi-band (4 spectral bands) electro-optical sensors (LISS-4, LISS-3* and AWiFS). The system has been designed to provide data globally with various data reception stations and onboard data storage capabilities. Oceansat-2 satellite has unique sensor combination with 8 band electro-optical high sensitive ocean colour monitor (catering to ocean and land) along with Ku band scatterometer to acquire information on ocean winds. INSAT- 3D launched recently provides high resolution 6 band image data in visible, short-wave, mid-wave and long-wave infrared spectrum. It also has 19 band sounder for providing vertical profile of water vapour, temperature, etc. The same system has data relay transponders for acquiring data from weather stations. The payload configurations have gone through significant changes over the years to increase data rate per kilogram of payload. Future Indian remote sensing systems are planned with very high efficient ways of image acquisition. <br><br> This paper analyses the strides taken by ISRO (Indian Space research Organisation) in achieving high efficiency in remote sensing image data acquisition. Parameters related to efficiency of image data acquisition are defined and a methodology is worked out to compute the same. Some of the Indian payloads are analysed with respect to some of the system/ subsystem parameters that decide the configuration of payload. Based on the analysis, possible configuration approaches that can provide high efficiency are identified. A case study is carried out with improved configuration and the results of efficiency improvements are reported. This methodology may be used for assessing other electro-optical payloads or missions and can be extended to other types of payloads and missions.

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Using Improved Edge Detection Method to Detect Mining-Induced Ground Fissures Identified by Unmanned Aerial Vehicle Remote Sensing

Remote Sensing ◽

10.3390/rs13183652 ◽

2021 ◽

Vol 13 (18) ◽

pp. 3652

Author(s):

Duo Xu ◽

Yixin Zhao ◽

Yaodong Jiang ◽

Cun Zhang ◽

Bo Sun ◽

...

Keyword(s):

Remote Sensing ◽

Edge Detection ◽

Unmanned Aerial Vehicle ◽

Field Experiments ◽

High Efficiency ◽

Detection Method ◽

Laplacian Operator ◽

Ground Fissures ◽

Aerial Vehicle ◽

Edge Detection Method

Information on the ground fissures induced by coal mining is important to the safety of coal mine production and the management of environment in the mining area. In order to identify these fissures timely and accurately, a new method was proposed in the present paper, which is based on an unmanned aerial vehicle (UAV) equipped with a visible light camera and an infrared camera. According to such equipment, edge detection technology was used to detect mining-induced ground fissures. Field experiments show high efficiency of the UAV in monitoring the mining-induced ground fissures. Furthermore, a reasonable time period between 3:00 a.m. and 5:00 a.m. under the studied conditions helps UAV infrared remote sensing identify fissures preferably. The Roberts operator, Sobel operator, Prewitt operator, Canny operator and Laplacian operator were tested to detect the fissures in the visible image, infrared image and fused image. An improved edge detection method was proposed which based on the Laplacian of Gaussian, Canny and mathematical morphology operators. The peak signal-to-noise rate, effective edge rate, Pratt’s figure of merit and F-measure indicated that the proposed method was superior to the other methods. In addition, the fissures in infrared images at different times can be accurately detected by the proposed method except at 7:00 a.m., 1:00 p.m. and 3:00 p.m.

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A novel technique to resample high resolution remote sensing satellite data

IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2002.1027203 ◽

2003 ◽

Author(s):

M. Ramanjaneyulu ◽

K.M.M. Rao

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Satellite Data ◽

Novel Technique ◽

Remote Sensing Satellite

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RDCRMG: A Raster Dataset Clean & Reconstitution Multi-Grid Architecture for Remote Sensing Monitoring of Vegetation Dryness

Remote Sensing ◽

10.3390/rs10091376 ◽

2018 ◽

Vol 10 (9) ◽

pp. 1376 ◽

Cited By ~ 9

Author(s):

Sijing Ye ◽

Diyou Liu ◽

Xiaochuang Yao ◽

Huaizhi Tang ◽

Quan Xiong ◽

...

Keyword(s):

Remote Sensing ◽

Data Storage ◽

Large Scale ◽

High Efficiency ◽

Data Extraction ◽

Automatic Monitoring ◽

Information Distortion ◽

Remote Sensing Monitoring ◽

Data Inversion ◽

Analysis Models

In recent years, remote sensing (RS) research on crop growth status monitoring has gradually turned from static spectrum information retrieval in large-scale to meso-scale or micro-scale, timely multi-source data cooperative analysis; this change has presented higher requirements for RS data acquisition and analysis efficiency. How to implement rapid and stable massive RS data extraction and analysis becomes a serious problem. This paper reports on a Raster Dataset Clean & Reconstitution Multi-Grid (RDCRMG) architecture for remote sensing monitoring of vegetation dryness in which different types of raster datasets have been partitioned, organized and systematically applied. First, raster images have been subdivided into several independent blocks and distributed for storage in different data nodes by using the multi-grid as a consistent partition unit. Second, the “no metadata model” ideology has been referenced so that targets raster data can be speedily extracted by directly calculating the data storage path without retrieving metadata records; third, grids that cover the query range can be easily assessed. This assessment allows the query task to be easily split into several sub-tasks and executed in parallel by grouping these grids. Our RDCRMG-based change detection of the spectral reflectance information test and the data extraction efficiency comparative test shows that the RDCRMG is reliable for vegetation dryness monitoring with a slight reflectance information distortion and consistent percentage histograms. Furthermore, the RDCGMG-based data extraction in parallel circumstances has the advantages of high efficiency and excellent stability compared to that of the RDCGMG-based data extraction in serial circumstances and traditional data extraction. At last, an RDCRMG-based vegetation dryness monitoring platform (VDMP) has been constructed to apply RS data inversion in vegetation dryness monitoring. Through actual applications, the RDCRMG architecture is proven to be appropriate for timely vegetation dryness RS automatic monitoring with better performance, more reliability and higher extensibility. Our future works will focus on integrating more kinds of continuously updated RS data into the RDCRMG-based VDMP and integrating more multi-source datasets based collaborative analysis models for agricultural monitoring.

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Design and Performance Analysis of a Supercritical CO2 Centrifugal Compressor With Variable Geometry

10.1115/gt2021-59723 ◽

2021 ◽

Author(s):

Gang Fan ◽

Kang Chen ◽

Shaoxiong Zheng ◽

Yang Du ◽

Yiping Dai ◽

...

Keyword(s):

Centrifugal Compressor ◽

Optimization Design ◽

High Efficiency ◽

Superior Performance ◽

Variable Geometry ◽

Power Cycles ◽

Operating Range ◽

Stable Operating ◽

And Performance ◽

Geometry Method

Abstract The supercritical carbon dioxide (SCO2) Brayton cycle is one of the most promising power cycles due to its high efficiency, compactness and environmentally friendliness. The centrifugal compressor is a key component of small and medium SCO2 Brayton cycles, and its efficiency has a significant impact on the cycle efficiency. Since the required electric load of power cycles always fluctuates over the year, the SCO2 compressor will operate away from its design point and the narrow stable operating range of a compressor is always a restriction. In this paper, the variable-geometry method, which refers to the combination of a variable inlet-guide-vanes and variable diffuser vanes is proposed for the operating range extension of SCO2 compressors. A set of one-dimensional (1D) loss correlations has been found to accurately predict various losses of the SCO2 compressor components. Based on the 1D thermodynamic model, two programs with internal MATLAB codes coupled with the NIST REFPROP database have been developed for preliminary optimization design and off-design performance predictions of the variable geometry SCO2 compressor. The contributions from the variable-inlet prewhirl and variable diffuser vanes to the shifts of the surge line and choke line are discussed in this paper. The results show the variable-geometry SCO2 compressor has a superior performance at off-design conditions and a wider operating range.

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A Lightweight SE-YOLOv3 Network for Multi-Scale Object Detection in Remote Sensing Imagery

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001421500373 ◽

2021 ◽

Author(s):

Lifang Zhou ◽

Guang Deng ◽

Weisheng Li ◽

Jianxun Mi ◽

Bangjun Lei

Keyword(s):

Remote Sensing ◽

High Efficiency ◽

Computational Cost ◽

Image Data ◽

Detection Accuracy ◽

Data Sets ◽

One Stage ◽

Efficiency And Effectiveness ◽

Spatial Pyramid Pooling ◽

Feature Augmentation

Current state-of-the-art detectors achieved impressive performance in detection accuracy with the use of deep learning. However, most of such detectors cannot detect objects in real time due to heavy computational cost, which limits their wide application. Although some one-stage detectors are designed to accelerate the detection speed, it is still not satisfied for task in high-resolution remote sensing images. To address this problem, a lightweight one-stage approach based on YOLOv3 is proposed in this paper, which is named Squeeze-and-Excitation YOLOv3 (SE-YOLOv3). The proposed algorithm maintains high efficiency and effectiveness simultaneously. With an aim to reduce the number of parameters and increase the ability of feature description, two customized modules, lightweight feature extraction and attention-aware feature augmentation, are embedded by utilizing global information and suppressing redundancy features, respectively. To meet the scale invariance, a spatial pyramid pooling method is used to aggregate local features. The evaluation experiments on two remote sensing image data sets, DOTA and NWPU VHR-10, reveal that the proposed approach achieves more competitive detection effect with less computational consumption.

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