Journal ArticleDOI
Consensus CPHD Filter for Distributed Multitarget Tracking
TLDR
A novel consensus Gaussian Mixture-Cardinalized Probability Hypothesis Density filter is developed that provides a fully distributed, scalable and computationally efficient solution to the distributed multitarget tracking problem.Abstract:
The paper addresses distributed multitarget tracking over a network of heterogeneous and geographically dispersed nodes with sensing, communication and processing capabilities. The contribution has been to develop a novel consensus Gaussian Mixture-Cardinalized Probability Hypothesis Density (GM-CPHD) filter that provides a fully distributed, scalable and computationally efficient solution to the problem. The effectiveness of the proposed approach is demonstrated via simulation experiments on realistic scenarios.read more
Citations
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Journal ArticleDOI
Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter
Ba-Ngu Vo,Ba-Tuong Vo,Dinh Phung +2 more
TL;DR: The present paper details efficient implementations of the δ-GLMB multi-target tracking filter and presents inexpensive look-ahead strategies to reduce the number of computations.
Journal ArticleDOI
Massive MIMO is a reality—What is next?: Five promising research directions for antenna arrays
TL;DR: In this paper, the authors explain how the first chapter of the massive MIMO research saga has come to an end, while the story has just begun, and outline five new massive antenna array related research directions.
Journal ArticleDOI
An Efficient Implementation of the Generalized Labeled Multi-Bernoulli Filter
TL;DR: An efficient implementation of the generalized labeled multi-Bernoulli (GLMB) filter is proposed by combining the prediction and update into a single step and an efficient algorithm for truncating the GLMB filtering density based on Gibbs sampling is proposed.
Posted Content
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
TL;DR: In this paper, the authors explain how the first chapter of the massive MIMO research saga has come to an end, while the story has just begun, and outline five new massive antenna array related research directions.
References
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Proceedings Article
Information Theory and an Extention of the Maximum Likelihood Principle
TL;DR: The classical maximum likelihood principle can be considered to be a method of asymptotic realization of an optimum estimate with respect to a very general information theoretic criterion to provide answers to many practical problems of statistical model fitting.
Book ChapterDOI
Information Theory and an Extension of the Maximum Likelihood Principle
TL;DR: In this paper, it is shown that the classical maximum likelihood principle can be considered to be a method of asymptotic realization of an optimum estimate with respect to a very general information theoretic criterion.
Journal ArticleDOI
Consensus and Cooperation in Networked Multi-Agent Systems
TL;DR: A theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees is provided.
Journal ArticleDOI
Unscented filtering and nonlinear estimation
Simon Julier,Jeffrey Uhlmann +1 more
TL;DR: The motivation, development, use, and implications of the UT are reviewed, which show it to be more accurate, easier to implement, and uses the same order of calculations as linearization.