S.M. Tonissen

456 citations
6 papers · 359 indexed · h-index 4
Topics
Target Tracking and Data Fusion in Sensor Networks (6 papers)Distributed Sensor Networks and Detection Algorithms (5 papers)Gaussian Processes and Bayesian Inference (2 papers)
Journals
IEEE Transactions on Aerospace and Electronic SystemsQueensland's institutional digital repository (The University of Queensland)
Partner nations
AustraliaUnited States

In The Last Decade

S.M. Tonissen

6 papers receiving 336 citations

Peers

S.M. Tonissen
Comparison fields: 5 of 35
  • Artificial Intelligence 266
  • Aerospace Engineering 234
  • Computer Networks and Communications 89
  • Electrical and Electronic Engineering 68
  • Computer Vision and Pattern Recognition 42
Replace Kevin Gilholm with:
Kevin Gilholm United Kingdom
H. Driessen Netherlands
Jérémie Houssineau United Kingdom
Yunfei Guo China
Hans Driessen Netherlands
Monika Wieneke Germany
David L. Adamy
Norikazu Ikoma Japan
Mehmet B. Güldoǧan Türkiye
F. A. Studer Italy
S.M. Tonissen relative to Kevin Gilholm United Kingdom Kevin Gilholm's profile →
Citations per field
00.5×1.5×
Kevin Gilholm · 1×
Citations per year

Countries citing papers authored by S.M. Tonissen

Since Specialization
Citations

This map shows the geographic impact of S.M. Tonissen'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 S.M. Tonissen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S.M. Tonissen more than expected).

Fields of papers citing papers by S.M. Tonissen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S.M. Tonissen. 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 S.M. Tonissen. The network helps show where S.M. Tonissen may publish in the future.

Co-authorship network of co-authors of S.M. Tonissen

This figure shows the co-authorship network connecting the top 25 collaborators of S.M. Tonissen. A scholar is included among the top collaborators of S.M. Tonissen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with S.M. Tonissen. S.M. Tonissen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

6 of 6 papers shown
#WorkIndexed citations
1 1
2 15
3 108
4
Detection of Low Snr Moving Targets with Time Varying Amplitude
3
5
Techniques for Low Snr Target Detection and Tracking
1
6 231

About S.M. Tonissen

S.M. Tonissen is a scholar working on Computer Networks and Communications, Artificial Intelligence and Signal Processing, having authored 6 papers that have together received 359 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (6 papers), Distributed Sensor Networks and Detection Algorithms (5 papers) and Gaussian Processes and Bayesian Inference (2 papers). The work is most often cited by research in Aerospace Engineering (234 citations), Artificial Intelligence (266 citations) and Computer Networks and Communications (89 citations). S.M. Tonissen has collaborated with scholars based in Australia and United States. Frequent co-authors include Robin J. Evans, Yaakov Bar‐Shalom and A. Logothetis. Their work appears in journals such as IEEE Transactions on Aerospace and Electronic Systems and Queensland's institutional digital repository (The University of Queensland).

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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