Target Tracking and Data Fusion in Sensor Networks
Target Tracking and Data Fusion in Sensor Networks is a research topic within Artificial Intelligence. Science Explorer counts 36k research works in it since 1950. 24.1% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on particle filtering and nonlinear estimation methods, including Kalman filters, Monte Carlo methods, sensor fusion, sequential Monte Carlo, Gaussian filters, and Bayesian inference. The papers cover a wide range of applications such as state estimation, multitarget tracking, and sensor network management.
- Particle Filters
- Nonlinear Estimation
- Kalman Filters
- Monte Carlo Methods
- State Estimation
- Sensor Fusion
- Sequential Monte Carlo
- Gaussian Filters
- Multitarget Tracking
- Bayesian Inference
- Research works
- 36k fractional, since 1950
- In the world top 10%
- 8.6k per year above
- Top-10% rate
- 24.1% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- -8% the tick is no change
Which countries lead Target Tracking and Data Fusion in Sensor Networks research?
By volume, China and the United States publish the most (2.6k and 622 works in 2022–2025).
By volume, 2022–2025
- 1 China 2.6k works
- 2 United States 622 works
- 3 Germany 179 works
- 4 India 171 works
- 5 United Kingdom 133 works
- 6 France 128 works
- 7 South Korea 117 works
- 8 Italy 109 works
- 9 Canada 96 works
- 10 Japan 82 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Target Tracking and Data Fusion in Sensor Networks research?
By volume in 2022–2025, Northwestern Polytechnical University publishes the most Target Tracking and Data Fusion in Sensor Networks research, followed by University of Electronic Science and Technology of China and Beihang University.
By volume, 2022–2025
- 1 Northwestern Polytechnical UniversityChina 119 works
- 2 University of Electronic Science and Technology of ChinaChina 90 works
- 3 Beihang UniversityChina 88 works
- 4 National University of Defense TechnologyChina 83 works
- 5 Beijing Institute of TechnologyChina 81 works
- 6 Harbin Institute of TechnologyChina 79 works
- 7 Harbin Engineering UniversityChina 69 works
- 8 Xidian UniversityChina 64 works
- 9 Nanjing University of Aeronautics and AstronauticsChina 53 works
- 10 Southeast UniversityChina 47 works
Who are the leading researchers in Target Tracking and Data Fusion in Sensor Networks?
The most-cited researchers publishing on Target Tracking and Data Fusion in Sensor Networks include Xiaogang Wang, Sebastian Thrun and H. Vincent Poor.
- 1 Xiaogang Wang Russia 13k citations
- 2 Sebastian Thrun United States 10k citations
- 3 H. Vincent Poor United States 9.5k citations
- 4 Wolfram Burgard Germany 6.3k citations
- 5 Anil K. Jain United States 6.3k citations
- 6 Guanrong Chen Hong Kong 5.4k citations
- 7 Lei Zhang Hong Kong 5.3k citations
- 8 Peng Shi Australia 5k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Target Tracking and Data Fusion in Sensor Networks research done?
The largest centres of Target Tracking and Data Fusion in Sensor Networks research in 2022–2025 are Beijing (China), Xi'an (China), Nanjing (China) and Harbin (China). Among places with at least 20 works in it, it is an unusually large share of all research in Harbin and Xi'an.
Largest cities, 2022–2025
Where it is the local speciality
- HarbinCN · 200.0 works9.9×
- Xi'anCN · 329.2 works8.4×
Location quotient: how much more of its research is in Target Tracking and Data Fusion in Sensor Networks than the world average.
Where is the best place to study Target Tracking and Data Fusion in Sensor Networks?
Among universities, judged by research, Beihang University, University of Electronic Science and Technology of China and Northwestern Polytechnical University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Beihang UniversityChina | 67.3 | 33.3% | 15.8× | 88 | +12.7% |
| 2 | University of Electronic Science and Technology of ChinaChina | 64.0 | 27.8% | 15.9× | 90 | -1.4% |
| 3 | Northwestern Polytechnical UniversityChina | 62.3 | 25.0% | 20.7× | 119 | -34.5% |
| 4 | Harbin Engineering UniversityChina | 61.5 | 30.7% | 26.3× | 69 | -23.1% |
| 5 | Beijing Institute of TechnologyChina | 58.6 | 20.8% | 13.5× | 80 | -3.4% |
| 6 | National University of Defense TechnologyChina | 58.3 | 23.6% | 21.3× | 83 | -16.6% |
| 7 | RMIT UniversityAustralia | 58.3 | 33.0% | 6.0× | 11 | +323.1% |
| 8 | Xidian UniversityChina | 58.0 | 24.0% | 17.3× | 64 | -16.5% |
| 9 | Harbin Institute of TechnologyChina | 57.5 | 23.1% | 9.5× | 79 | -20.1% |
| 10 | Nanjing University of Science and TechnologyChina | 56.4 | 27.4% | 10.3× | 43 | -19.5% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Target Tracking and Data Fusion in Sensor Networks research growing?
Output in 2018–2022 was 8% lower than in 2013–2017, peaking in 2011. The fastest-growing topics are Target Tracking and Data Fusion in Sensor Networks.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.