Singularity and Error Analysis of a Simple Quaternion Estimator
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916234851778560 |
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| author | Peng, Caitong Choukroun, Daniel |
| author_facet | Peng, Caitong Choukroun, Daniel |
| contents | A novel single-frame quaternion estimator processing two vector observations is introduced. The singular cases are examined, and appropriate rotational solutions are provided. Additionally, an alternative method involving sequential rotation is introduced to manage these singularities. The simplicity of the estimator enables clear physical insights and a closed-form expression for the bias as a function of the quaternion error covariance matrix. The covariance could be approximated up to second order with respect to the underlying measurement noise assuming arbitrary probability distribution. The current note relaxes the second-order assumption and provides an expression for the error covariance that is exact to the fourth order, under the assumption of Gaussian distribution. A comprehensive derivation of the individual components of the quaternion additive error covariance matrix is presented. This not only provides increased accuracy but also alleviates issues related to singularity. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2403_01150 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Singularity and Error Analysis of a Simple Quaternion Estimator Peng, Caitong Choukroun, Daniel Methodology Systems and Control A novel single-frame quaternion estimator processing two vector observations is introduced. The singular cases are examined, and appropriate rotational solutions are provided. Additionally, an alternative method involving sequential rotation is introduced to manage these singularities. The simplicity of the estimator enables clear physical insights and a closed-form expression for the bias as a function of the quaternion error covariance matrix. The covariance could be approximated up to second order with respect to the underlying measurement noise assuming arbitrary probability distribution. The current note relaxes the second-order assumption and provides an expression for the error covariance that is exact to the fourth order, under the assumption of Gaussian distribution. A comprehensive derivation of the individual components of the quaternion additive error covariance matrix is presented. This not only provides increased accuracy but also alleviates issues related to singularity. |
| title | Singularity and Error Analysis of a Simple Quaternion Estimator |
| topic | Methodology Systems and Control |
| url | https://arxiv.org/abs/2403.01150 |