Example of Journal of Guidance, Control, and Dynamics format
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Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format
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Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format Example of Journal of Guidance, Control, and Dynamics format
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open access Open Access
recommended Recommended

Journal of Guidance, Control, and Dynamics — Template for authors

Categories Rank Trend in last 3 yrs
Applied Mathematics #35 of 548 up up by 12 ranks
Aerospace Engineering #11 of 129 -
Electrical and Electronic Engineering #130 of 693 down down by 1 rank
Control and Systems Engineering #57 of 260 down down by 3 ranks
Space and Planetary Science #26 of 97 up up by 5 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 921 Published Papers | 5544 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 04/06/2020
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Related Journals

open access Open Access

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Quality:  
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CiteRatio: 3.7
SJR: 0.396
SNIP: 1.133
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SJR: 1.321
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Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

2.692

31% from 2018

Impact factor for Journal of Guidance, Control, and Dynamics from 2016 - 2019
Year Value
2019 2.692
2018 2.061
2017 2.024
2016 1.856
graph view Graph view
table view Table view

6.0

3% from 2019

CiteRatio for Journal of Guidance, Control, and Dynamics from 2016 - 2020
Year Value
2020 6.0
2019 6.2
2018 4.8
2017 4.3
2016 4.3
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 31% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has decreased by 3% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

1.573

SJR for Journal of Guidance, Control, and Dynamics from 2016 - 2020
Year Value
2020 1.573
2019 1.573
2018 1.142
2017 1.104
2016 1.181
graph view Graph view
table view Table view

1.754

12% from 2019

SNIP for Journal of Guidance, Control, and Dynamics from 2016 - 2020
Year Value
2020 1.754
2019 1.996
2018 2.293
2017 2.072
2016 2.503
graph view Graph view
table view Table view

insights Insights

  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 12% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Journal of Guidance, Control, and Dynamics

Guideline source: View

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American Institute of Aeronautics and Astronautics

Journal of Guidance, Control, and Dynamics

This Journal is devoted to the advancement of the science and technology of guidance, control, and dynamics through the dissemination of original archival papers disclosing significant technical knowledge, exploratory developments, design criteria, and applications in aeronaut...... Read More

Mathematics

i
Last updated on
04 Jun 2020
i
ISSN
0731-5090
i
Impact Factor
High - 2.264
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
unsrt
i
Citation Type
Numbered
[25]
i
Bibliography Example
C. W. J. Beenakker. Specular andreev reflection in graphene. Phys. Rev. Lett., 97(6):067007, 2006.

Top papers written in this journal

Journal Article DOI: 10.2514/2.4231
Survey of Numerical Methods for Trajectory Optimization

Topics:

Direct multiple shooting method (64%)64% related to the paper, Sequential quadratic programming (62%)62% related to the paper, Trajectory optimization (61%)61% related to the paper, Nonlinear programming (60%)60% related to the paper, Hamilton–Jacobi–Bellman equation (56%)56% related to the paper
2,491 Citations
Journal Article DOI: 10.2514/3.20031
An eigensystem realization algorithm for modal parameter identification and model reduction
Jer-Nan Juang1, Richard S. Pappa1

Abstract:

A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is ... A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system modes and noise modes. For illustration of the algorithm, examples are shown using simulation data and experimental data for a rectangular grid structure. read more read less

Topics:

Eigensystem realization algorithm (75%)75% related to the paper, Realization (systems) (56%)56% related to the paper, System identification (55%)55% related to the paper, Modal (55%)55% related to the paper, Singular value decomposition (53%)53% related to the paper
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2,366 Citations
Journal Article DOI: 10.2514/3.20029
Distributed Piezoelectric-Polymer Active Vibration Control of a Cantilever Beam
Thomas Bailey1, James E. Hubbard1

Abstract:

An active vibration damper for a cantilever beam was designed using a distributed-parameter actuator and distributed-parameter control theory. The distributed-parameter actuator was a piezoelectric polymer, poly (vinylidene fluoride). Lyapunov's second method for distributed-parameter systems was used to design a control algo... An active vibration damper for a cantilever beam was designed using a distributed-parameter actuator and distributed-parameter control theory. The distributed-parameter actuator was a piezoelectric polymer, poly (vinylidene fluoride). Lyapunov's second method for distributed-parameter systems was used to design a control algorithm for the damper. If the angular velocity of the tip of the beam is known, all modes of the beam can be controlled simultaneously. Preliminary testing of the damper was performed on the first mode of the cantilever beam. A linear constant-gain controller and a nonlinear constant-amplitude controller were compared. The baseline loss factor of the first mode was 0.003 for large-amplitude vibrations (± 2 cm tip displacement) decreasing to 0.001 for small vibrations (±0.5 mm tip displacement). The constant-gain controller provided more than a factor of two increase in the modal damping with a feedback voltage limit of 200 V rms. With the same voltage limit, the constant-amplitude controller achieved the same damping as the constant-gain controller for large vibrations, but increased the modal loss factor by more than an order of magnitude to at least 0.040 for small vibration levels. read more read less

Topics:

Active vibration control (59%)59% related to the paper, Control theory (55%)55% related to the paper, Constrained-layer damping (55%)55% related to the paper, Vibration (54%)54% related to the paper, Damper (54%)54% related to the paper
1,408 Citations
Journal Article DOI: 10.2514/3.19717
Three-axis attitude determination from vector observations
Malcolm D. Shuster1, S. D. Oh1

Abstract:

Two computationally efficient algorithms are presented for determining three-axis attitude from two or more vector observations. The first of these, the TRIAD algorithm, provides a deterministic (i.e., nonoptimal) solution for the attitude based on two vector observations. The second, the QUEST algorithm, is an optimal algori... Two computationally efficient algorithms are presented for determining three-axis attitude from two or more vector observations. The first of these, the TRIAD algorithm, provides a deterministic (i.e., nonoptimal) solution for the attitude based on two vector observations. The second, the QUEST algorithm, is an optimal algorithm which determines the attitude that achieves the best weighted overlap of an arbitrary number of reference and observation vectors. Analytical expressions are given for the covariance matrices for the two algorithms using a fairly realistic model for the measurement errors. The mathematical relationship of the two algorithms and their relative merits are discussed and numerical examples are given. The advantage of computing the covariance matrix in the body frame rather than in the inertial frame (e.g., in terms of Euler angles) is emphasized. These results are valuable when a single-frame attitude must be computed frequently. They will also be useful to the mission analyst or spacecraft engineer for the evaluation of launch-window constraints or of attitude accuracies for different attitude sensor configurations. read more read less

Topics:

Triad method (61%)61% related to the paper, Covariance matrix (55%)55% related to the paper, Estimation of covariance matrices (55%)55% related to the paper, Covariance (55%)55% related to the paper, Wahba's problem (54%)54% related to the paper
1,394 Citations
Journal Article DOI: 10.2514/3.56190
Kalman Filtering for Spacecraft Attitude Estimation
E. J. Lefferts1, F. L. Markley2, Malcolm D. Shuster

Abstract:

HIS report reviews the methods of Kalman filtering in attitude estimation and their development over the last two decades. This review is not intended to be complete but is limited to algorithms suitable for spacecraft equipped with three-axis gyros as well as attitude sensors. These are the systems to which we feel that Kalm... HIS report reviews the methods of Kalman filtering in attitude estimation and their development over the last two decades. This review is not intended to be complete but is limited to algorithms suitable for spacecraft equipped with three-axis gyros as well as attitude sensors. These are the systems to which we feel that Kalman filtering is most ap- plicable. The Kalman filter uses a dynamical model for the time development of the system and a model of the sensor measurements to obtain the most accurate estimate possible of the system state using a linear estimator based on present and past measurements. It is, thus, ideally suited to both ground-based and on-board attitude determination. However, the applicability of the Kalman filtering technique rests on the availability of an accurate dynamical model. The dynamic equations for the spacecraft attitude pose many difficulties in the filter modeling. In particular, the external torques and the distribution of momentum internally due to the use of rotating or rastering instruments lead to significant uncertainties in the modeling. For autonomous spacecraft the use of inertial reference units as a model replacement permits the circumvention of these problems. In this representation the angular velocity of the spacecraft is obtained from the gyro data. The kinematic equations are used to obtain the attitude state and this is augmented by means of additional state-vector components for the gyro biases. Thus, gyro data are not treated as observations and the gyro noise appears as state noise rather than as observation noise. It is theoretically possible that a spacecraft is three-axis stabilized with such rigidity that the time development of the system can be described accurately without gyro information, or that it is one-axis stabilized so that only a single gyro is needed to provide information on the time history of the system. The modification of the algorithms presented here in order to apply to those cases is slight. However, this is of little practical importance because a control system capable of such read more read less

Topics:

Fast Kalman filter (59%)59% related to the paper, Extended Kalman filter (59%)59% related to the paper, Invariant extended Kalman filter (58%)58% related to the paper, Kalman filter (57%)57% related to the paper, Spacecraft (52%)52% related to the paper
1,266 Citations
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Frequently asked questions

1. Can I write Journal of Guidance, Control, and Dynamics in LaTeX?

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Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Journal of Guidance, Control, and Dynamics citation style.

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Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Journal of Guidance, Control, and Dynamics that you can download at the end.

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12. Is Journal of Guidance, Control, and Dynamics's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Journal of Guidance, Control, and Dynamics?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Journal of Guidance, Control, and Dynamics. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Journal of Guidance, Control, and Dynamics?

The 5 most common citation types in order of usage for Journal of Guidance, Control, and Dynamics are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Journal of Guidance, Control, and Dynamics?

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16. Can I download Journal of Guidance, Control, and Dynamics in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Journal of Guidance, Control, and Dynamics Endnote style according to Elsevier guidelines.

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