2021
DOI: 10.3390/s21124164
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The Interacting Multiple Model Filter and Smoother on Boxplus-Manifolds

Abstract: Hybrid systems are subject to multiple dynamic models, or so-called modes. To estimate the state, the sequence of modes has to be estimated, which results in an exponential growth of possible sequences. The most prominent solution to handle this is the interacting multiple model filter, which can be extended to smoothing. In this paper, we derive a novel generalization of the interacting multiple filter and smoother to manifold state spaces, e.g., quaternions, based on the boxplus-method. As part thereof, we p… Show more

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Cited by 4 publications
(3 citation statements)
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“…With two kinematic models available for each filter, we plan on developing an invariant-IMM based on [15] or multiplemodel particle filter to embed the geometric models into more complex tracking algorithms.…”
Section: A Future Workmentioning
confidence: 99%
“…With two kinematic models available for each filter, we plan on developing an invariant-IMM based on [15] or multiplemodel particle filter to embed the geometric models into more complex tracking algorithms.…”
Section: A Future Workmentioning
confidence: 99%
“…A single dynamic model in estimating motion parameters cannot accurately describe all of the unpredictable maneuvering behaviors of an underwater passive vehicle. The performance of motion estimation techniques within a single model may be significantly affected if the state equation and the actual movements of the target do not match [7]. The most comprehensive and effective motion prediction models are those which calculate the statistical equations of object kinematics at each moment of the turning path [8].…”
Section: Introductionmentioning
confidence: 99%
“…Multimodal systems based on tactile and kinesthetic fusion feedback have emerged to display more realistic haptic feedback for operators in virtual environments [24]. Multimodal fusion technology refers to the integration and fusion of information from different sensors and modalities to improve the performance and effectiveness of the system, including sensor fusion, data fusion, and information fusion [25][26][27]. Luo Shan et al [28] presented a method called Iterative Closest Labeled Point (iCLAP) to link kinesthetic and tactile modalities to achieve integrated perception of the touched object.…”
Section: Introductionmentioning
confidence: 99%