Restricted constellation design for regional navigation augmentation

Zhang, Tianjiao; Shen, Hong-Xin; Li, Zhao; Qie, Hang; Cao, Jing; Li, Hengnian; Yang, Yikang

doi:10.1016/j.actaastro.2018.04.044

Cited by 21 publications

(6 citation statements)

References 16 publications

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“…This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2023.3335235 [154] DE/rand-to-best/1/exp Efficient deformable 3D face model fitting to monocular images Ayala et al [155] DE/rand/1/exp Image thresholding segmentation Maesani et al [156] DE/rand/1/exp Memetic viability evolution for constrained optimization Li et al [157] DE/rand-to-best/1/exp Social force model for earthquake evacuation Tsakiridis et al [158], [159] DE/rand/1/exp Fuzzy rulebased classification systems Huang [160] DE/best/1/exp Parameters optimization of region growing segmentation Kunnapapdeelert et al [161] DE/rand/1/exp Multi-depot vehicle routing problem Li et al [162] DE/current-to-pbest/1/exp A laser-based measuring system for online quality control of car engine block Tsakiridis et al [163] DECO3RUM/current-to-rand/1/exp Vis-NIR soil spectroscopy Bhandari et al [164] DE/rand/1/exp Colored satellite image Miyao et al [165] DE/rand/1/exp QSAR model Arunkumar and Jothiprakash [166] DE/best/1/exp Optimal crop plans for a multi-reservoir system Vivekanandan et al [167] DE/rand/2-wt/exp Perform feature selection Zhao et al [168] DE/rand-to-best/1/exp Optimal layout design of obstacles for panic evacuation Fateh et al [169] DE/best/2/exp Two-point boundary value problems Ohenoja et al [170] DE/best/1/exp Hierarchical control of an integrated fuel processing and fuel cell system Bhuvanesh et al [171] DE/best/1/exp Multistage multiobjective electricity generation expansion planning Zhang et al [172] DE/rand-to-best/1/exp Restricted constellation design for regional navigation augmentation Zhang et al [ [190] DE/best/2/exp U-shaped assembly line balancing type 2 Rey and Delrieux [191] DE/best/1/exp Multithresholding techniques Wang et al [192] DE/rand/2/exp Integrated scheduling of job shops Krishna et al [193] DE/randrl/1/exp Application to customer segmentation Peng et al [194], [195] DE/rand/1/mexp,DE/best/1/mexp,DE/target-to-rand/1/mexp Mixed-variable optimization problems da et al [196] DE/rand/1/exp...…”

Section: Discussionmentioning

confidence: 99%

Differential Evolution With Exponential Crossover: An Experimental Analysis on Numerical Optimization

Li,

Meng

2023

IEEE Access

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Since the inception in 1995, Differential Evolution (DE) has gained significant attention from researchers worldwide, and many DE variants proposed in the last decades obtained excellent performance in many scientific and engineering applications. However, the vast majority of these well-performed DE variants employ binomial crossover rather than exponential crossover in generating trial vector candidates though both of the two schemes were proposed simultaneously. That may be also the reason why there still doesn't exist such a thorough analysis of DE with exponential crossover. Different from the majority of DE researchers believing that DE variants with binomial crossover usually exhibit superior performance than the ones employing exponential crossover and DE variants with exponential crossover are good at tackling optimization problems with linkages among neighboring variables, we found that DE variants with exponential crossover can achieve competitive performance with the ones employing binomial crossover regardless of whether there are linkages among the variables or not after discovering the proper crossover rate CR and its corresponding parameter control. In order to enrich research of DE on exponential crossover, this paper presents an thorough experimental analysis of DE algorithm with exponential crossover in numerical optimization, presenting the basic concepts of exponential crossover, giving the mathematical analysis on can actually achieve similar optimization between exponential crossover and binomial crossover, experimental validation under the 100 benchmark functions from CEC2013, CEC2014, CEC2017, CEC2022 test suites as well as the tension/compression spring design problem, and summarizing and classifying various engineering applications that exponential crossover DE are used to solve. Furthermore, we also look into the future challenges and potential directions for further development of DE with exponential crossover.INDEX TERMS Differential evolution, exponential crossover, binomial crossover, algorithms validation.

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Section: Discussionmentioning

confidence: 99%

Differential Evolution With Exponential Crossover: An Experimental Analysis on Numerical Optimization

Li,

Meng

2023

IEEE Access

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“…The DE algorithm has the advantage of quickly narrowing the search range and avoiding local optimization or premature convergence (Price, 1996; Stom & Price, 1995; Storn & Price, 1997). Furthermore, this algorithm is widely applied in production scheduling (Onwubolu & Davendra, 2006), combinatorial optimization (Liu et al., 2019), data mining (Das et al., 2008), and the design of Low Earth Orbit (LEO) navigation satellite constellation (Zhang et al., 2018), and so on. Thus, this study adopts the DE algorithm to design the DGPC.…”

Section: Determine the Optimal Initial Orbit Parameters Of The Chines...mentioning

confidence: 99%

The Temporal Improvement of Earth's Mass Transport Estimated by Coupling GRACE‐FO With a Chinese Polar Gravity Satellite Mission

Yan,

Ran,

Xiao

et al. 2023

JGR Solid Earth

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Over the past 20 years, the Gravity Recovery and Climate Experiment (GRACE), and its successor mission, GRACE‐Follow On (GRACE‐FO) have made significant contributions to time‐variable gravity field modeling. A Chinese low‐low satellite‐to‐satellite tracking gravimetry mission (i.e., Chinese future gravimetry mission) has been confirmed to be selected as the polar‐orbiting satellite gravimetry mission for China, because of the capability to collect gravity data globally. However, the analysis of potential contributions to geosciences from GRACE‐FO coupling with the Chinese future gravimetry mission is still limited. This study combines GRACE‐FO and Chinese future gravimetry missions as the Dual GRACE‐like Polar satellite Constellation (DGPC). By carefully choosing the initial orbit parameters of the Chinese future gravimetry mission with the differential evolution algorithm, the DGPC is expected to mitigate the temporal aliasing effects by improving the temporal resolution of time‐variable gravity solutions (i.e., 1‐day and 3‐day solutions). Regarding the spectral‐domain evaluation, zonal, tesseral, and sectorial coefficients estimated by the DGPC show approximately 6.01%–13.42% noise reductions compared with GRACE‐FO. Regarding the spatial‐domain evaluation, the DGPC can suppress noises of about 39.44% and 31.12% in annual amplitude and long‐term trend, respectively. On this basis, this paper analyzes the effectiveness of the DGPC in potential contributions to geosciences (e.g., hydrology, glaciology, and seismology). Specifically, the DGPC can improve accuracy by about 36.96%, 25.85%, and 33.16% with respect to GRACE‐FO for signals in the subhumid basin, signals of ice‐sheet mass balance over Greenland, and coseismic displacement of the fault zone, respectively. In general, the potential capability for high‐frequency signals recovery of the DGPC would facilitate contributions of satellite gravimetry to geosciences.

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“…Ma et al (2013) presented a LEO constellation for regional communication and considered symmetric and asymmetric structures of the constellation. Zhang et al (2018) designed a LEO constellation to obtain a Chinese regional navigation augmentation with the aim of minimizing overall system cost. Shtark and Gurfil (2018) introduced a LEO constellation optimization method for RNSS, generated and propagated various constellations, and demonstrated their performance.…”

Section: Introductionmentioning

confidence: 99%

“…Crossley et al (2000) proposed a simulated annealing and genetic algorithm to minimize the revisit time. Zhang et al (2018) designed the LEO satellite constellation using differential evolution (DE) algorithm. Shtark and Gurfil (2018) designed the LEO satellite constellation using genetic algorithms and gradient-based optimization.…”

Section: Introductionmentioning

confidence: 99%

Spatial Geometry Design of a Low Earth Orbit Constellation for Iranian Regional Navigation Satellite System

Zardashti

Emami

2021

J. Aerosp. Technol. Manag.

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The regional navigation satellite system (RNSS) is recently used in some countries to cover or enhance their local navigation. The most important satellite navigation systems to date are in the Earth medium orbit (MEO) and Earth synchronous Earth orbit (GEO), which are characterized by big satellites, and high launch, construction, and operation costs. In contrast, low Earth orbit (LEO) small-satellite constellations have recently become attractive because of their advantages, such as a significant reduction in system cost, an increase in communication volume, and a reduction in latency. Therefore, in this study, the spatial geometry of a LEO constellation is designed for Iran to increase the required regional navigation performance. For this purpose, the optimal constellation configuration is obtained through a multi-objective genetic algorithm (MOGA) utilizing a cost function with a combination of the geometry dilution of precision (GDOP), the number of satellites, and orbital height in the form of a design procedure. Moreover, reducing the feasible region of longitude of the ascending nodes of orbit planes is applied in the design process to reduce the search space. The simulation results indicate the constellation designed performance.

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Restricted constellation design for regional navigation augmentation

Cited by 21 publications

References 16 publications

Differential Evolution With Exponential Crossover: An Experimental Analysis on Numerical Optimization

Differential Evolution With Exponential Crossover: An Experimental Analysis on Numerical Optimization

The Temporal Improvement of Earth's Mass Transport Estimated by Coupling GRACE‐FO With a Chinese Polar Gravity Satellite Mission

Spatial Geometry Design of a Low Earth Orbit Constellation for Iranian Regional Navigation Satellite System

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