Eun-Hwan Shin
- Aerospace Engineering top 5%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Ocean Engineering
- Oceanography
- Topics
- Inertial Sensor and Navigation (13 papers)Target Tracking and Data Fusion in Sensor Networks (9 papers)GNSS positioning and interference (7 papers)
- Journals
- Journal of NavigationNAVIGATION Journal of the Institute of NavigationJournal of Global Positioning Systems
- Partner nations
- Canada
In The Last Decade
Eun-Hwan Shin
13 papers receiving 245 citations
Peers
Comparison fields: 5 of 40
- Aerospace Engineering 249
- Artificial Intelligence 143
- Electrical and Electronic Engineering 97
- Ocean Engineering 39
- Oceanography 29
Countries citing papers authored by Eun-Hwan Shin
This map shows the geographic impact of Eun-Hwan Shin'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 Eun-Hwan Shin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eun-Hwan Shin more than expected).
Fields of papers citing papers by Eun-Hwan Shin
This network shows the impact of papers produced by Eun-Hwan Shin. 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 Eun-Hwan Shin. The network helps show where Eun-Hwan Shin may publish in the future.
Co-authorship network of co-authors of Eun-Hwan Shin
This figure shows the co-authorship network connecting the top 25 collaborators of Eun-Hwan Shin. A scholar is included among the top collaborators of Eun-Hwan Shin 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 Eun-Hwan Shin. Eun-Hwan Shin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 23 | |
| 3 | 11 | |
| 4 | Performance Comparison of the Extended and the Unscented Kalman Filter for Integrated GPS and MEMS-Based Inertial Systems | 16 |
| 5 | Accurate INS/GPS Positioning with Different Inertial Systems Using Various Algorithms for Bridging GPS Outages | 14 |
| 6 | Backward Smoothing for Pipeline Surveying Applications | 4 |
| 7 | 29 | |
| 8 | A Quaternion-Based Unscented Kalman Filter for the Integration of GPS and MEMS INS | 16 |
| 9 | 97 | |
| 10 | 6 | |
| 11 | Optimizing Smoothing Computation for Near Real-Time GPS Measurement Gap Filling in INS/GPS Systems | 11 |
| 12 | A New Calibration Method for strapdown Inertial Navigation Systems | 62 |
| 13 | Improving the Performance of Alignment Processes of Inertial Measurement Units Utilizing Adaptive Pre-Filtering Methodology | 1 |
About Eun-Hwan Shin
Eun-Hwan Shin is a scholar working on Aerospace Engineering, Artificial Intelligence and Oceanography, having authored 13 papers that have together received 291 indexed citations. Recurring topics across this work include Inertial Sensor and Navigation (13 papers), Target Tracking and Data Fusion in Sensor Networks (9 papers) and GNSS positioning and interference (7 papers). The work is most often cited by research in Aerospace Engineering (249 citations), Artificial Intelligence (143 citations) and Ocean Engineering (39 citations). Eun-Hwan Shin has collaborated with scholars based in Canada. Frequent co-authors include Naser El‐Sheimy, Xiaoji Niu, Sameh Nassar and Aboelmagd Noureldin. Their work appears in journals such as Journal of Navigation, NAVIGATION Journal of the Institute of Navigation and Journal of Global Positioning Systems.
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.