Asynchronous multirate multisensor information fusion algorithm

Lin, Yan; Liu, B.S.; Zhou, Donghua

doi:10.1109/taes.2007.4383603

Cited by 89 publications

(27 citation statements)

References 20 publications

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“…The objective of information fusion is to obtain more information than is present in any individual information source by combining information from different sources [17]. In practice, this means that by utilizing the complementary properties of the different information sources, the information fusion algorithm in a navigation application aims to reduce ambiguities in the measured information and thereby expand the spatial and temporal coverage in which the navigation system works.…”

Section: Information Fusionmentioning

confidence: 99%

Indoor Positioning by Ultrawide Band Radio Aided Inertial Navigation

Angelis

Nilsson

Skog

et al. 2010

Metrology and Measurement Systems

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-In this paper, a research activity aimed at developing an indoor positioning system is presented. The realized system prototype uses sensor fusion techniques to combine information from two sources: a local Ultra-Wideband (UWB) radio based distance-measuring system infrastructure and an Inertial Navigation System (INS). The UWB system provides a measure of distance between two transceivers by measuring the time-of-flight of pulses. Its principle of operation is briefly described, together with the main features of its architecture. Furthermore, the main characteristics of the INS and of the Extended Kalman Filter information fusion approach are presented. Finally, some experimental results are provided, relative to static and dynamic position measurements.

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Section: Information Fusionmentioning

confidence: 99%

Indoor Positioning by Ultrawide Band Radio Aided Inertial Navigation

Angelis

Nilsson

Skog

et al. 2010

Metrology and Measurement Systems

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“…Here, data generally arrives at the fusion center at multiple rates asynchronously. Publications on asynchronous data fusion for discrete time systems include approaches based on multiscale system theory [7][8][9][10], batch process methods [11], algorithms based on multirate filter banks [12], etc. Although the Kalman filter (KF) output is in discrete time, the dynamics is often described in continuous time.…”

Section: Introductionmentioning

confidence: 99%

“…For sensors having different sampling rates at different scales, multiscale system theory is a useful tool. Our work stems from multiscale system theory but provides a new multiscale modeling architecture that is not limited to the wavelet [10,11,33]. In [11], the state at a coarser scale is modeled by the moving average of states at the finest scale; in [11] and [33], the backward model and the forward model were presented, respectively, through certain modifications of the moving average model.…”

Section: Introductionmentioning

confidence: 99%

Modeling and estimation of asynchronous multirate multisensor system with unreliable measurements

Yan

Xia

et al. 2015

IEEE Trans. Aerosp. Electron. Syst.

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This paper is concerned with state estimation of a linear system by fusion of asynchronous, multirate, multisensor data. The system is described at the finest scale with multiple sensors observing a common thing independently at different scales with different sampling rates. Unreliable measurements are available. The main results are: the multiscale system is properly formulated, a credibility measure is constructed and used to determine whether the measurement is normal or faulty, and an optimal recursive fusion algorithm is presented. The effectiveness and stability of the algorithm under unreliable measurements are analyzed. A Manuscript

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“…Hong [11] proposed an algorithm for multi-resolutional distributed filtering with the wavelet transform as a linking mechanism between different resolution sensor domains. Yan et al [27] presented a novel fusion algorithm for multiple asynchronous multi-rate sensors by establishing state-space models for each scale and recursively fusing the data from many sensors, where the ratio between the sampling rates of different sensors is allowed to be any positive integer. Alouani et al [1] proposed a general sensor-to-sensor-track fusion algorithm for multiple sensors that are asynchronous and have arbitrary communication rates.…”

Section: Introductionmentioning

confidence: 99%