Multisensor fusion and integration: approaches, applications, and future research directions

TLDR

Multisensor fusion and integration is a rapidly evolving field that draws on control theory, signal processing, AI, probability, and statistics, and offers more reliable and accurate information by leveraging redundant, complementary, or timely data. This paper reviews current sensor technologies, the paradigm of multisensor fusion and integration, fusion techniques across levels, and outlines future research directions such as microsensors, smart sensors, and adaptive fusion. The authors describe how multisensor fusion is achieved through various techniques at different fusion levels and discuss its applications in robotics, biomedical systems, equipment monitoring, remote sensing, and transportation.

Abstract

Multisensor fusion and integration is a rapidly evolving research area and requires interdisciplinary knowledge in control theory, signal processing, artificial intelligence, probability and statistics, etc. The advantages gained through the use of redundant, complementary, or more timely information in a system can provide more reliable and accurate information. This paper provides an overview of current sensor technologies and describes the paradigm of multisensor fusion and integration as well as fusion techniques at different fusion levels. Applications of multisensor fusion in robotics, biomedical system, equipment monitoring, remote sensing, and transportation system are also discussed. Finally, future research directions of multisensor fusion technology including microsensors, smart sensors, and adaptive fusion techniques are presented.