Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency

Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency

The paradigm of multisensor data fusion has been evolved from a centralized architecture to a decentralized or distributed architecture along with the advancement in sensor and communication technologies. These days, distributed state estimation and data fusion has been widely explored in diverse fields of engineering and control due to its superior performance over the centralized one in terms...

Multisensor Data Fusion

Multisensor Data Fusion

IMultisensor data fusion refers to the acquisition, processing and synergistic combination of information gathered by various knowledge sources and sensors to provide a better understanding of a phenomenon. It is a fascinating and rapidly evolving field that has generated a lot of excitement in the research and development community. These concepts are being applied to a wide variety of fields ...

Multisensor Parallel Largest Ellipsoid Distributed Data Fusion with Unknown Cross-Covariances

As the largest ellipsoid (LE) data fusion algorithm can only be applied to two-sensor system, in this contribution, parallel fusion structure is proposed to introduce the LE algorithm into a multisensor system with unknown cross-covariances, and three parallel fusion structures based on different estimate pairing methods are presented and analyzed. In order to assess the influence of fusion str...

An Improved Algorithm under Error Correlation in Distributed Data Fusion

In distributed data fusion, the correlation between every local estimate makes an impact on the result of fusion. This paper introduces a scalar of correlation coefficient to present the correlation between local estimates, and estimate a covariance matrix in the limit of correlation. The improved algorithm put forward to use the form of Bar shalom-Campo algorithm and partly estimate the limit ...