Arnaud Breloy

497 total citations
42 papers, 249 citations indexed

About

Arnaud Breloy is a scholar working on Signal Processing, Aerospace Engineering and Statistics and Probability. According to data from OpenAlex, Arnaud Breloy has authored 42 papers receiving a total of 249 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Signal Processing, 18 papers in Aerospace Engineering and 14 papers in Statistics and Probability. Recurrent topics in Arnaud Breloy's work include Direction-of-Arrival Estimation Techniques (16 papers), Sparse and Compressive Sensing Techniques (13 papers) and Advanced Statistical Methods and Models (11 papers). Arnaud Breloy is often cited by papers focused on Direction-of-Arrival Estimation Techniques (16 papers), Sparse and Compressive Sensing Techniques (13 papers) and Advanced Statistical Methods and Models (11 papers). Arnaud Breloy collaborates with scholars based in France, Hong Kong and United States. Arnaud Breloy's co-authors include Guillaume Ginolhac, Frédéric Pascal, Philippe Forster, Mohammed Nabil El Korso, Daniel P. Palomar, Ying Sun, Esa Ollila, Prabhu Babu, Alexandre Renaux and Sandeep Kumar and has published in prestigious journals such as IEEE Transactions on Information Theory, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Signal Processing.

In The Last Decade

Arnaud Breloy

35 papers receiving 245 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Arnaud Breloy France 10 114 85 53 47 41 42 249
Sudan Han China 13 344 3.0× 140 1.6× 17 0.3× 61 1.3× 29 0.7× 27 414
Mohammed Nabil El Korso France 13 265 2.3× 266 3.1× 41 0.8× 55 1.2× 44 1.1× 71 491
Junhui Qian China 7 191 1.7× 101 1.2× 15 0.3× 162 3.4× 38 0.9× 13 356
Amar Mezache Algeria 14 330 2.9× 32 0.4× 16 0.3× 102 2.2× 17 0.4× 57 448
R. S. Raghavan United States 11 497 4.4× 235 2.8× 37 0.7× 126 2.7× 24 0.6× 35 620
Stéphanie Bidon France 12 397 3.5× 195 2.3× 9 0.2× 85 1.8× 65 1.6× 61 489
Xinliang Chen China 10 259 2.3× 59 0.7× 5 0.1× 109 2.3× 31 0.8× 48 343
Faouzi Soltani Algeria 12 273 2.4× 25 0.3× 7 0.1× 61 1.3× 11 0.3× 27 325
K. James Sangston United States 7 571 5.0× 141 1.7× 32 0.6× 156 3.3× 20 0.5× 15 642
N.B. Pulsone United States 7 394 3.5× 251 3.0× 20 0.4× 72 1.5× 14 0.3× 12 432

Countries citing papers authored by Arnaud Breloy

Since Specialization
Citations

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

Fields of papers citing papers by Arnaud Breloy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arnaud Breloy. 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 Arnaud Breloy. The network helps show where Arnaud Breloy may publish in the future.

Co-authorship network of co-authors of Arnaud Breloy

This figure shows the co-authorship network connecting the top 25 collaborators of Arnaud Breloy. A scholar is included among the top collaborators of Arnaud Breloy 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 Arnaud Breloy. Arnaud Breloy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Breloy, Arnaud, et al.. (2025). Covariance Fitting Interferometric Phase Linking: Modular Framework and Optimization Algorithms. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–18.
2.
Ginolhac, Guillaume, et al.. (2024). Online change detection in SAR time-series with Kronecker product structured scaled Gaussian models. Signal Processing. 224. 109589–109589.
3.
Renaux, Alexandre, et al.. (2024). Intrinsic Bayesian Cramér-Rao Bound With an Application to Covariance Matrix Estimation. IEEE Transactions on Information Theory. 70(12). 9261–9276.
4.
Breloy, Arnaud, et al.. (2024). Through-The-Wall Radar Imaging With Wall Clutter Removal Via Riemannian Optimization On The Fixed-Rank Manifold. SPIRE - Sciences Po Institutional REpository. 8596–8600.
5.
Breloy, Arnaud, et al.. (2023). Through the Wall Radar Imaging via Kronecker-structured Huber-type RPCA. Signal Processing. 214. 109228–109228. 1 indexed citations
6.
Breloy, Arnaud, et al.. (2023). Robust Phase Linking in InSAR. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–11. 14 indexed citations
7.
Breloy, Arnaud, et al.. (2023). Riemannian Optimization for Non-Centered Mixture of Scaled Gaussian Distributions. IEEE Transactions on Signal Processing. 71. 2475–2490. 1 indexed citations
8.
Breloy, Arnaud, et al.. (2022). Robust PCA for Through-the-Wall Radar Imaging. 2022 30th European Signal Processing Conference (EUSIPCO). 2246–2250. 3 indexed citations
9.
Breloy, Arnaud, et al.. (2021). Probabilistic PCA From Heteroscedastic Signals: Geometric Framework and Application to Clustering. IEEE Transactions on Signal Processing. 69. 6546–6560. 6 indexed citations
10.
Breloy, Arnaud, Guillaume Ginolhac, Yongchan Gao, & Frédéric Pascal. (2021). MIMO filters based on robust rank-constrained Kronecker covariance matrix estimation. Signal Processing. 187. 108116–108116. 3 indexed citations
11.
Breloy, Arnaud, et al.. (2021). A Tyler-Type Estimator of Location and Scatter Leveraging Riemannian Optimization. HAL (Le Centre pour la Communication Scientifique Directe). 11. 5160–5164. 1 indexed citations
12.
Breloy, Arnaud, et al.. (2020). Robust Low-Rank Change Detection for Multivariate SAR Image Time Series. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13. 3545–3556. 7 indexed citations
13.
Breloy, Arnaud, et al.. (2020). Matched and Mismatched Estimation of Kronecker Product of Linearly Structured Scatter Matrices Under Elliptical Distributions. IEEE Transactions on Signal Processing. 69. 603–616. 6 indexed citations
14.
Korso, Mohammed Nabil El, et al.. (2020). Two-Dimensional Robust Source Localization Under Non-Gaussian Noise. Circuits Systems and Signal Processing. 39(9). 4740–4761. 1 indexed citations
15.
Korso, Mohammed Nabil El, et al.. (2019). Robust estimation of structured scatter matrices in (mis)matched models. Signal Processing. 165. 163–174. 12 indexed citations
16.
Breloy, Arnaud, et al.. (2019). Detection Methods Based on Structured Covariance Matrices for Multivariate SAR Images Processing. IEEE Geoscience and Remote Sensing Letters. 16(7). 1160–1164. 7 indexed citations
17.
Breloy, Arnaud, et al.. (2019). Bayesian signal subspace estimation with compound Gaussian sources. Signal Processing. 167. 107310–107310. 10 indexed citations
18.
Breloy, Arnaud, et al.. (2018). Intrinsic Cramér–Rao Bounds for Scatter and Shape Matrices Estimation in CES Distributions. IEEE Signal Processing Letters. 26(2). 262–266. 18 indexed citations
19.
Breloy, Arnaud, Ying Sun, Prabhu Babu, & Daniel P. Palomar. (2016). Block majorization-minimization algorithms for low-rank clutter subspace estimation. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 33. 2186–2190. 2 indexed citations
20.
Sun, Ying, Arnaud Breloy, Prabhu Babu, et al.. (2015). Low-Complexity Algorithms for Low Rank Clutter Parameters Estimation in Radar Systems. IEEE Transactions on Signal Processing. 64(8). 1986–1998. 34 indexed citations

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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