Delay-Tolerant Distributed Inference in Tracking Networks

This paper discusses asynchronous distributed inference in object tracking. Unlike many studies, which assume that the delay in communication between partial estimators and the central station is negligible, our study focuses on the problem of asynchronous distributed inference in the presence of delays. We introduce an efficient data fusion method for combining the distributed estimates, where delay in communications is not negligible. To overcome the delay, predictions are made for the state of the system based on the most current available information from partial estimators. Simulation results show the efficacy of the methods proposed.

[1]  Giorgio Battistelli,et al.  Distributed joint sensor registration and target tracking via sensor network , 2019, Inf. Fusion.

[2]  Punyasha Chatterjee,et al.  Energy-Efficient Connected Target Coverage in Multi-hop Wireless Sensor Networks , 2018 .

[3]  Milica Stojanovic,et al.  Object Tracking Using Modified Lossy Extended Kalman Filter , 2017, WUWNet.

[4]  Ali H. Sayed,et al.  Diffusion LMS Strategies for Distributed Estimation , 2010, IEEE Transactions on Signal Processing.

[5]  Prabhat Kumar,et al.  Localization in three-dimensional wireless sensor networks: a survey , 2019, The Journal of Supercomputing.

[6]  Juan M. Corchado,et al.  Second-order statistics analysis and comparison between arithmetic and geometric average fusion: Application to multi-sensor target tracking , 2019, Inf. Fusion.

[7]  H. Vincent Poor,et al.  Distributed learning in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[8]  Milica Stojanovic,et al.  Object Tracking in Random Access Sensor Networks: Extended Kalman Filtering with State Overlapping , 2019, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[9]  Petar M. Djuric,et al.  Indoor Tracking: Theory, Methods, and Technologies , 2015, IEEE Transactions on Vehicular Technology.

[10]  Mónica F. Bugallo,et al.  Improving Accuracy by Iterated Multiple Particle Filtering , 2012, IEEE Signal Processing Letters.

[11]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[12]  Majid Ahmadi,et al.  A Novel Approach to Reliable Sensor Selection and Target Tracking in Sensor Networks , 2020, IEEE Transactions on Industrial Informatics.

[13]  Mónica F. Bugallo,et al.  Multiple Particle Filtering , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[14]  Mónica F. Bugallo,et al.  Efficient linear fusion of partial estimators , 2014, Digit. Signal Process..

[15]  A.S. Willsky,et al.  Distributed fusion in sensor networks , 2006, IEEE Signal Processing Magazine.

[16]  Imran Khan,et al.  Wireless sensor network virtualization: A survey , 2015, IEEE Communications Surveys & Tutorials.

[17]  Georgios B. Giannakis,et al.  Signal Processing for Big Data [From the Guest Editors] , 2014, IEEE Signal Process. Mag..

[18]  G.B. Giannakis,et al.  Distributed compression-estimation using wireless sensor networks , 2006, IEEE Signal Processing Magazine.

[19]  Pau Closas,et al.  Uncertainty Exchange Through Multiple Quadrature Kalman Filtering , 2016, IEEE Signal Processing Letters.

[20]  Jian Sun,et al.  Adaptive Consensus-Based Distributed Target Tracking With Dynamic Cluster in Sensor Networks , 2019, IEEE Transactions on Cybernetics.

[21]  Éfren Lopes Souza,et al.  Target Tracking for Sensor Networks , 2016, ACM Comput. Surv..

[22]  Ananthram Swami,et al.  Wireless sensor networks : signal processing and communications perspectives , 2007 .

[23]  Junhai Luo,et al.  Underwater Acoustic Target Tracking: A Review , 2018, Sensors.

[24]  Kenneth F. Wallis,et al.  Combining forecasts – forty years later , 2011 .

[25]  Milica Stojanovic,et al.  Object Tracking in Random Access Networks: A Large-Scale Design , 2020, IEEE Internet of Things Journal.

[26]  Frédéric Lavancier,et al.  A general procedure to combine estimators , 2014, Comput. Stat. Data Anal..

[27]  Georgios B. Giannakis,et al.  Signal processing for Big Data , 2014, 2014 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA).

[28]  Tanima Dutta,et al.  A Target Tracking System Using Directional Nodes in Wireless Sensor Networks , 2019, IEEE Systems Journal.

[29]  Soummya Kar,et al.  Gossip Algorithms for Distributed Signal Processing , 2010, Proceedings of the IEEE.

[30]  R. Mahler.  Multitarget Bayes filtering via first-order multitarget moments , 2003 .

[31]  Ali H. Sayed,et al.  Adaptive Networks , 2014, Proceedings of the IEEE.