JOURNAL ARTICLE

Approaches to Multisensor Data Fusion in Target Tracking: A Survey

David SmithSoraisam Gobinkumar Singh

Year: 2006 Journal:   IEEE Transactions on Knowledge and Data Engineering Vol: 18 (12)Pages: 1696-1710   Publisher: IEEE Computer Society

Abstract

The tracking of objects using distributed multiple sensors is an important field of work in the application areas of autonomous robotics, military applications, and mobile systems. In this survey, we review a number of computationally intelligent methods that are used for developing robust tracking schemes through sensor data fusion. The survey discusses the application of the various algorithms at different layers of the JDL model and highlights the weaknesses and strengths of the approaches in the context of different applications.

Keywords:
Sensor fusion Computer science Strengths and weaknesses Robotics Artificial intelligence Context (archaeology) Field (mathematics) Tracking (education) Mobile robot Data mining Machine learning Data science Robot

Metrics

369
Cited By
19.26
FWCI (Field Weighted Citation Impact)
205
Refs
0.99
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Distributed Sensor Networks and Detection Algorithms
Physical Sciences →  Computer Science →  Computer Networks and Communications
Neural Networks and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence

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