R. Moose

801 citations
22 papers · 592 · h-index 10

Impact in

Papers in

R. Moose

21 papers receiving 545 citations

Peers

R. Moose
Comparison fields: 5 of 41
  • Artificial Intelligence 460
  • Aerospace Engineering 246
  • Control and Systems Engineering 222
  • Oceanography 76
  • Signal Processing 61
Replace D. Lerro with:
D. Lerro United States
D.T. Magill United States
C. Chang United States
Gregory A. Watson United States
G.W. Pulford Australia
G. van Keuk Germany
B.F. La Scala Australia
Vincent C. Vannicola United States
X.R. Li United States
Sherry E. Hammel United States
R. Moose relative to D. Lerro United States D. Lerro's profile →
Citations per field
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D. Lerro · 1×
Citations per year

Countries citing papers authored by R. Moose

Since Specialization
Citations

This map shows the geographic impact of R. Moose's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by R. Moose with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R. Moose more than expected).

Fields of papers citing papers by R. Moose

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R. Moose. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by R. Moose. The network helps show where R. Moose may publish in the future.

Co-authors

The 2 scholars most cited alongside R. Moose, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with R. Moose Line = papers co-authored together R. Moose links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1979170
2 1977145
3 1975102
4 198544
5 198117
6 197814
7 198513
8 197713
9 198613
10 199311
11 19879
12 19788
13 19808
14 19878
15 19927
16 19763
17 19772
18 19862
19 19781
20
Study of an automatic trajectory following control system
19831

About R. Moose

R. Moose is a scholar working on Artificial Intelligence, Control and Systems Engineering, Oceanography, Ocean Engineering and Aerospace Engineering, having authored 22 papers that have together received 592 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (18 papers), Fault Detection and Control Systems (9 papers), Control Systems and Identification (7 papers), Underwater Acoustics Research (5 papers), Underwater Vehicles and Communication Systems (4 papers), Advanced Control Systems Optimization (2 papers), Neural Networks and Applications (2 papers) and Guidance and Control Systems (2 papers). The work is most often cited by research in Artificial Intelligence (460 citations), Aerospace Engineering (246 citations), Control and Systems Engineering (222 citations), Oceanography (76 citations) and Signal Processing (61 citations). R. Moose has collaborated with scholars based in United States. Frequent co-authors include H.F. VanLandingham and Paul Wang. Their work appears in journals such as IEEE Transactions on Aerospace and Electronic Systems, IEEE Journal of Oceanic Engineering, IEEE Transactions on Automatic Control, Automatica and IEEE Transactions on Acoustics Speech and Signal Processing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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