Publications
2024
Decentralised multi-sensor target tracking with limited field of view via possibility theory
Houssineau, J., Xue, C., Cai, H., Uney, M., & Delande, E. (2024). Decentralised multi-sensor target tracking with limited field of view via possibility theory. In 2024 27th International Conference on Information Fusion (FUSION) (pp. 1-8). IEEE. doi:10.23919/fusion59988.2024.10706352
Two-stage Transfer Learning for Airborne Multi-spectral Image Classifiers
Two-Stage Transfer Learning for Fusion and Classification of Airborne Hyperspectral Imagery
Rise, B., Uney, M., & Huang, X. (2024). Two-Stage Transfer Learning for Fusion and Classification of Airborne Hyperspectral Imagery. In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 6555-6559). IEEE. doi:10.1109/icassp48485.2024.10445916
A Heterogeneous, Autonomous Passive Network for Underwater Surveillance: Experimental Results With Real Data Collected at Sea
Tesei, A., Stinco, P., Ferri, G., Uney, M., Been, R., & LePage, K. D. (2024). A Heterogeneous, Autonomous Passive Network for Underwater Surveillance: Experimental Results With Real Data Collected at Sea. IEEE Aerospace and Electronic Systems Magazine, 39(9), 16-35. doi:10.1109/maes.2024.3421408
2023
Coherent Long-Time Integration and Bayesian Detection With Bernoulli Track-Before-Detect
Uney, M., Horridge, P., Mulgrew, B., & Maskell, S. (2023). Coherent Long-Time Integration and Bayesian Detection With Bernoulli Track-Before-Detect. IEEE SIGNAL PROCESSING LETTERS, 30, 239-243. doi:10.1109/LSP.2023.3253039
2022
Passive Sensor Fusion and Tracking in Underwater Surveillance with the GLMB model
Uney, M., Stinco, P., Dreo, R., Micheli, M., De Magistris, G., & Tesei, A. (2022). Passive Sensor Fusion and Tracking in Underwater Surveillance with the GLMB model. In 2022 25th International Conference on Information Fusion (FUSION) (pp. 1-8). IEEE. doi:10.23919/fusion49751.2022.9841282
Fast Trajectory Forecasting With Automatic Identification System Broadcasts
Wang, Y., & Uney, M. (2022). Fast Trajectory Forecasting With Automatic Identification System Broadcasts. In 2022 Sensor Signal Processing for Defence Conference (SSPD) (pp. 1-5). IEEE. doi:10.1109/sspd54131.2022.9896218
Optimal Bernoulli point estimation with applications
Narykov, A., Uney, M., & Ralph, J. F. (2022). Optimal Bernoulli point estimation with applications. In 2022 Sensor Signal Processing for Defence Conference (SSPD) (pp. 1-5). IEEE. doi:10.1109/sspd54131.2022.9896190
2021
Modelling bi-static uncertainties in sequential Monte Carlo with the GLMB model
Uney, M., Narykov, A., Ralph, J., & Maskell, S. (2021). Modelling bi-static uncertainties in sequential Monte Carlo with the GLMB model. In 2021 SENSOR SIGNAL PROCESSING FOR DEFENCE CONFERENCE (SSPD) (pp. 85-89). doi:10.1109/SSPD51364.2021.9541502
2020
Selective Information Transmission using Convolutional Neural Networks for Cooperative Underwater Surveillance
De Magistris, G., Uney, M., Stinco, P., Ferri, G., Tesei, A., & Le Page, K. (2020). Selective Information Transmission using Convolutional Neural Networks for Cooperative Underwater Surveillance. In PROCEEDINGS OF 2020 23RD INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2020) (pp. 172-179). doi:10.23919/fusion45008.2020.9190461
Coherent track-before-detect with micro-Doppler signature estimation in array radars
Kim, K., Uney, M., & Mulgrew, B. (2020). Coherent track-before-detect with micro-Doppler signature estimation in array radars. IET RADAR SONAR AND NAVIGATION, 14(4), 572-585. doi:10.1049/iet-rsn.2019.0319
2019
ESTIMATION OF DRONE MICRO-DOPPLER SIGNATURES VIA TRACK-BEFORE-DETECT IN ARRAY RADARS
Kim, K., Uney, M., & Mulgrew, B. (2019). ESTIMATION OF DRONE MICRO-DOPPLER SIGNATURES VIA TRACK-BEFORE-DETECT IN ARRAY RADARS. In 2019 INTERNATIONAL RADAR CONFERENCE (RADAR2019) (pp. 218-223). doi:10.1109/RADAR41533.2019.171375
Estimation of Drone Micro-Doppler Signatures via Track-Before-Detect in Array Radars
Kim, K., Uney, M., & Mulgrew, B. (2019). Estimation of Drone Micro-Doppler Signatures via Track-Before-Detect in Array Radars. In 2019 International Radar Conference, RADAR 2019. doi:10.1109/RADAR41533.2019.171375
Type II approximate Bayes perspective to multiple hypothesis tracking
Uney, M. (2019). Type II approximate Bayes perspective to multiple hypothesis tracking. In 2019 22ND INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2019). doi:10.23919/fusion43075.2019.9011264
DATA DRIVEN VESSEL TRAJECTORY FORECASTING USING STOCHASTIC GENERATIVE MODELS
Uney, M., Millefiori, L. M., & Braca, P. (2019). DATA DRIVEN VESSEL TRAJECTORY FORECASTING USING STOCHASTIC GENERATIVE MODELS. In 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) (pp. 8459-8463). Retrieved from https://www.webofscience.com/
Maximum likelihood estimation in a parametric stochastic trajectory model
Uney, M., Millefiori, L. M., & Braca, P. (2019). Maximum likelihood estimation in a parametric stochastic trajectory model. In 2019 SENSOR SIGNAL PROCESSING FOR DEFENCE CONFERENCE (SSPD). doi:10.1109/sspd.2019.8751652
2018
OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT
Kim, K., Uney, M., & Mulgrew, B. (2018). OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT. In 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) (pp. 3320-3324). Retrieved from https://www.webofscience.com/
Prediction of Rendezvous in Maritime Situational Awareness
Uney, M., Millefiori, L. M., & Braca, P. (2018). Prediction of Rendezvous in Maritime Situational Awareness. In 2018 21ST INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) (pp. 622-628). Retrieved from https://www.webofscience.com/
Enabling self-configuration of fusion networks via scalable opportunistic sensor calibration
Uney, M., Copsey, K., Page, S., Mulgrew, B., & Thomas, P. (2018). Enabling self-configuration of fusion networks via scalable opportunistic sensor calibration. In SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXVII Vol. 10646. doi:10.1117/12.2303964
Fusion of Finite-Set Distributions: Pointwise Consistency and Global Cardinality
Uney, M., Houssineau, J., Delande, E., Julier, S. J., & Clark, D. E. (2019). Fusion of Finite-Set Distributions: Pointwise Consistency and Global Cardinality. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 55(6), 2759-2773. doi:10.1109/TAES.2019.2893083
Fusion of finite set distributions: Pointwise consistency and global cardinality
Enabling self-configuration of fusion networks via scalable opportunistic sensor calibration
Uney, M., Copsey, K., Page, S., Mulgrew, B., & Thomas, P. (2018). Enabling self-configuration of fusion networks via scalable opportunistic sensor calibration. In I. Kadar (Ed.), Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII Vol. 10646 (pp. 190-202). International Society for Optics and Photonics: SPIE. doi:10.1117/12.2303964
2017
Detection via simultaneous trajectory estimation and long time integration
Latent Parameter Estimation in Fusion Networks Using Separable Likelihoods
Latent Parameter Estimation in Fusion Networks Using Separable Likelihoods
Uney, M., Mulgrew, B., & Clark, D. E. (2018). Latent Parameter Estimation in Fusion Networks Using Separable Likelihoods. IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, 4(4), 752-768. doi:10.1109/TSIPN.2018.2825599
Simultaneous tracking and long time integration for detection in collaborative array radars
Kim, K., Uney, M., & Mulgrew, B. (2017). Simultaneous tracking and long time integration for detection in collaborative array radars. In 2017 IEEE Radar Conference (RadarConf) (pp. 0200-0205). IEEE. doi:10.1109/radar.2017.7944197
Simultaneous tracking and long time integration for detection in collaborative array radars
Kim, K., Uney, M., & Mulgrew, B. (2017). Simultaneous tracking and long time integration for detection in collaborative array radars. In 2017 IEEE RADAR CONFERENCE (RADARCONF) (pp. 200-205). Retrieved from https://www.webofscience.com/
2016
Detection of Manoeuvring Low SNR Objects in Receiver Arrays
Kim, K., Uney, M., & Mulgrew, B. (2016). Detection of Manoeuvring Low SNR Objects in Receiver Arrays. In 2016 Sensor Signal Processing for Defence (SSPD) (pp. 1-5). IEEE. doi:10.1109/sspd.2016.7590592
Distributed localisation of sensors with partially overlapping field-of-views in fusion networks
Ueney, M., Mulgrew, B., & Clark, D. (2016). Distributed localisation of sensors with partially overlapping field-of-views in fusion networks. In 2016 19TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) (pp. 1340-1347). Retrieved from https://www.webofscience.com/
Distributed estimation of latent parameters in state space models using separable likelihoods
Uney, M., Mulgrew, B., & Clark, D. (2016). Distributed estimation of latent parameters in state space models using separable likelihoods. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 4129-4133). IEEE. doi:10.1109/icassp.2016.7472454
A Cooperative Approach to Sensor Localisation in Distributed Fusion Networks
Uney, M., Mulgrew, B., & Clark, D. E. (2016). A Cooperative Approach to Sensor Localisation in Distributed Fusion Networks. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 64(5), 1187-1199. doi:10.1109/TSP.2015.2493981
DISTRIBUTED ESTIMATION OF LATENT PARAMETERS IN STATE SPACE MODELS USING SEPARABLE LIKELIHOODS
Uney, M., Mulgrew, B., & Clark, D. (2016). DISTRIBUTED ESTIMATION OF LATENT PARAMETERS IN STATE SPACE MODELS USING SEPARABLE LIKELIHOODS. In 2016 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING PROCEEDINGS (pp. CP1-CP97). Retrieved from https://www.webofscience.com/
Detection of manoeuvring low SNR objects in receiver arrays
Kim, K., Uney, M., & Mulgrew, B. (2016). Detection of manoeuvring low SNR objects in receiver arrays. In 2016 SENSOR SIGNAL PROCESSING FOR DEFENCE (SSPD) (pp. 71-75). Retrieved from https://www.webofscience.com/
2015
Maximum Likelihood Signal Parameter Estimation via Track Before Detect
Uney, M., Mulgrew, B., & Clark, D. (2015). Maximum Likelihood Signal Parameter Estimation via Track Before Detect. In 2015 Sensor Signal Processing for Defence (SSPD) (pp. 1-5). IEEE. doi:10.1109/sspd.2015.7288511
Maximum Likelihood Signal Parameter Estimation via Track Before Detect
Uney, M., Mulgrew, B., & Clark, D. (2015). Maximum Likelihood Signal Parameter Estimation via Track Before Detect. In 2015 SENSOR SIGNAL PROCESSING FOR DEFENCE (SSPD) (pp. 26-30). Retrieved from https://www.webofscience.com/
2014
Optimization of decentralized random field estimation networks under communication constraints through Monte Carlo methods
Uney, M., & Cetin, M. (2014). Optimization of decentralized random field estimation networks under communication constraints through Monte Carlo methods. DIGITAL SIGNAL PROCESSING, 34, 16-28. doi:10.1016/j.dsp.2014.07.014
Target aided online sensor localisation in bearing only clusters
Uney, M., Mulgrew, B., & Clark, D. (2014). Target aided online sensor localisation in bearing only clusters. In 2014 SENSOR SIGNAL PROCESSING FOR DEFENCE (SSPD). Retrieved from https://www.webofscience.com/
COOPERATIVE SENSOR LOCALISATION IN DISTRIBUTED FUSION NETWORKS BY EXPLOITING NON-COOPERATIVE TARGETS
Ueney, M., Mulgrew, B., & Clark, D. (2014). COOPERATIVE SENSOR LOCALISATION IN DISTRIBUTED FUSION NETWORKS BY EXPLOITING NON-COOPERATIVE TARGETS. In 2014 IEEE WORKSHOP ON STATISTICAL SIGNAL PROCESSING (SSP) (pp. 516-519). Retrieved from https://www.webofscience.com/
Optimization of decentralized random field estimation networks under communication constraints through Monte Carlo methods
Üney, M., & Çetin, M. (2014). Optimization of decentralized random field estimation networks under communication constraints through Monte Carlo methods. Digital Signal Processing, 34, 16-28. doi:10.1016/j.dsp.2014.07.014
2013
Regional Variance for Multi-Object Filtering
Delande, E., Ueney, M., Houssineau, J., & Clark, D. E. (2014). Regional Variance for Multi-Object Filtering. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 62(13), 3415-3428. doi:10.1109/TSP.2014.2328326
Regional variance for multi-object filtering
Distributed Fusion of PHD Filters Via Exponential Mixture Densities
Ueney, M., Clark, D. E., & Julier, S. J. (2013). Distributed Fusion of PHD Filters Via Exponential Mixture Densities. IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 7(3), 521-531. doi:10.1109/JSTSP.2013.2257162
2012
Distributed sensor registration based on random finite set representations
Uney, M., Clark, D. E., & Julier, S. J. (2012). Distributed sensor registration based on random finite set representations. In Sensor Signal Processing for Defence (SSPD 2012) (pp. 8). Institution of Engineering and Technology. doi:10.1049/ic.2012.0095
2011
Monte Carlo Optimization of Decentralized Estimation Networks Over Directed Acyclic Graphs Under Communication Constraints
Uney, M., & Cetin, M. (2011). Monte Carlo Optimization of Decentralized Estimation Networks Over Directed Acyclic Graphs Under Communication Constraints. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 59(11), 5558-5576. doi:10.1109/TSP.2011.2163629
Information measures in distributed multitarget tracking
Uney, M., Clark, D. E., & Julier, S. J. (2011). Information measures in distributed multitarget tracking. In Fusion 2011 - 14th International Conference on Information Fusion.
2010
Monte Carlo realisation of a distributed multi-object fusion algorithm
Uney, M., Julier, S., Clark, D., & Ristic, B. (2010). Monte Carlo realisation of a distributed multi-object fusion algorithm. In Sensor Signal Processing for Defence (SSPD 2010) (pp. 13). IET. doi:10.1049/ic.2010.0232
Monte Carlo realisation of a distributed multi-object fusion algorithm
Üney, M., Julier, S., Clark, D., & Ristić, B. (2010). Monte Carlo realisation of a distributed multi-object fusion algorithm. In Sensor Signal Processing for Defence (SSPD 2010) (pp. 1-5).
2009
AN EFFICIENT MONTE CARLO APPROACH FOR OPTIMIZING DECENTRALIZED ESTIMATION NETWORKS CONSTRAINED BY UNDIRECTED TOPOLOGIES
Uney, M., & Cetin, M. (2009). AN EFFICIENT MONTE CARLO APPROACH FOR OPTIMIZING DECENTRALIZED ESTIMATION NETWORKS CONSTRAINED BY UNDIRECTED TOPOLOGIES. In 2009 IEEE/SP 15TH WORKSHOP ON STATISTICAL SIGNAL PROCESSING, VOLS 1 AND 2 (pp. 485-488). doi:10.1109/SSP.2009.5278534
An efficient Monte Carlo approach for optimizing communication constrained decentralized estimation networks
Üney, M., & Çetin, M. (2009). An efficient Monte Carlo approach for optimizing communication constrained decentralized estimation networks. In European Signal Processing Conference (pp. 1047-1051).
Decentralized random-field estimation under communication constraints
Uney, M., & Cetin, M. (2009). Decentralized random-field estimation under communication constraints. In 2009 IEEE 17th Signal Processing and Communications Applications Conference (pp. 524-527). IEEE. doi:10.1109/siu.2009.5136448
Decentralized Random-Field Estimation Under Communication Constraints
Uney, M., & Cetin, M. (2009). Decentralized Random-Field Estimation Under Communication Constraints. In 2009 IEEE 17TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, VOLS 1 AND 2 (pp. 754-757). Retrieved from https://www.webofscience.com/
2008
Target localization in acoustic sensor networks using factor graphs
Uney, M., & Cetin, M. (2008). Target localization in acoustic sensor networks using factor graphs. In 2008 IEEE 16th Signal Processing, Communication and Applications Conference (pp. 1-4). IEEE. doi:10.1109/siu.2008.4632715
Target Localization in Acoustic Sensor Networks Using Factor Graphs
Ueney, M., & Cetin, M. (2008). Target Localization in Acoustic Sensor Networks Using Factor Graphs. In 2008 IEEE 16TH SIGNAL PROCESSING, COMMUNICATION AND APPLICATIONS CONFERENCE, VOLS 1 AND 2 (pp. 721-724). Retrieved from https://www.webofscience.com/
2007
Graphical model-based approaches to target tracking in sensor networks:: An overview of some recent work and challenges
Uney, M., & Cetin, M. (2007). Graphical model-based approaches to target tracking in sensor networks:: An overview of some recent work and challenges. In PROCEEDINGS OF THE 5TH INTERNATIONAL SYMPOSIUM ON IMAGE AND SIGNAL PROCESSING AND ANALYSIS (pp. 492-497). Retrieved from https://www.webofscience.com/