Investigation of the trade-off between the complexity of the accelerometer bias model and the state estimation accuracy in INS/GNSS integration
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Gilles Teodori
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Hans Neuner
Abstract
The integration of Inertial Navigation Systems and Global Navigation Satellite Systems (GNSS) represents the core navigation unit for mobile platforms in open sky environments. A realistic assessment of the accuracy of the navigation solution depends on the accurate modelling of inertial sensor errors. Sensor noise and biases contribute most to short-term navigation errors. For the latter, different models can be used, varying in complexity. This paper investigates how the use of two different models for the accelerometer bias affects the accuracy of the state estimate in an extended Kalman filter. For this purpose, the Allan variance technique is applied to a data sequence from a specific inertial sensor to identify and quantify the underlying noise processes. The estimated noise parameters are used to characterise a bias model for the accelerometers that in addition to the static bias model takes non-white noise processes of the inertial sensor under investigation into account. This detailed accelerometer bias model is compared to a classical modelling approach that only considers static biases. Both approaches are evaluated based on simulation studies for continuous and intermittent GNSS coverages. The results show no significant difference between the two modelling approaches in terms of horizontal position and attitude precision. Furthermore, the correctness of the accelerometer bias estimates is not significantly affected by the modelling approach. All in all, it can be concluded that a detailed bias model of the accelerometers does not outperform the classical modelling approach.
Funding source: Österreichische Forschungsförderungsgesellschaft
Award Identifier / Grant number: 37082870
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Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: This work was carried out within the framework of the ZAP-ALS project funded by the Austrian Research Promotion Agency (FFG). ZAP-ALS is short for Zuverlässiger, Automatischer und Präziser: integrierte Schätzung von Trajektorien und Punktwolken aus GNSS, INS und ALS. The authors acknowledge TU Wien Bibliothek for financial support through its Open Access Funding Programme.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
Appendix A: Power spectral densities of noise processes
The power spectral density (PSD) of a random walk process defined by Eq. (6) is given by [2, Eq. (4.49) p. 127]
where H(⋅) denotes the transfer function of Eq. (6) [17] and j refers to the imaginary unit. S K refers to the PSD of the driving noise w K(t) of the random walk process z K(t).
Using the first line of Eq. (22) and the transfer function of Eq. (7) [17, p. 13], the PSD of a first-order Gauss-Markov process z B(t) results in
S B refers to the PSD of the driving noise w B(t) of the first-order Gauss–Markov process z B(t).
The rate PSD of quantization noise’ z A (t) is [12, Eq. (C.13)]
where S A = A 2 and A denotes the quantization noise coefficient. t 0 refers to the fixed and uniform sampling interval of the IMU.
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© 2022 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Review
- Investigation of the trade-off between the complexity of the accelerometer bias model and the state estimation accuracy in INS/GNSS integration
- Original Research Articles
- Solution for ill-posed EIV model regularization attending to its decreasing regularization characteristic
- Trajectory evaluation using repeated rail-bound measurements
- Global geopotential models evaluation based on terrestrial gravity data over Ethiopia
- A calculation method for GNSS positioning precision based on the posteriori unit weight variance
- Accuracy and reliability of BeiDou clocks
- Positioning performance with dual-frequency low-cost GNSS receivers
- Estimating 3D displacement vectors from line-of-sight observations with application to MIMO-SAR
- Determination of the height reference surface for the Republic of Albania by using global geopotential models
- An integrated adaptive Kalman filter for improving the reliability of navigation systems
Artikel in diesem Heft
- Frontmatter
- Review
- Investigation of the trade-off between the complexity of the accelerometer bias model and the state estimation accuracy in INS/GNSS integration
- Original Research Articles
- Solution for ill-posed EIV model regularization attending to its decreasing regularization characteristic
- Trajectory evaluation using repeated rail-bound measurements
- Global geopotential models evaluation based on terrestrial gravity data over Ethiopia
- A calculation method for GNSS positioning precision based on the posteriori unit weight variance
- Accuracy and reliability of BeiDou clocks
- Positioning performance with dual-frequency low-cost GNSS receivers
- Estimating 3D displacement vectors from line-of-sight observations with application to MIMO-SAR
- Determination of the height reference surface for the Republic of Albania by using global geopotential models
- An integrated adaptive Kalman filter for improving the reliability of navigation systems
