Abstract
A measurement data self-calibration fusion method was proposed. Self-recognition self-calibration formulas and computational procedures of the systematic error (unknown input) in measurement data were given, enabling to automatically identify, estimate, compensate and correct the systematic error, so as to reduce its influence. Formulas and computational procedures of multi-sensor data fusion were established to further reduce the influence of random errors. The linear system and the non-linear system were discussed in detail respectively, and a large number of examplifications and simulations were carried out. It can be seen in two examples that the relative error of the proposed method is at least 45% less than that of the traditional method, and the calculation is simple, and well-suited for engineering applications.
| Translated title of the contribution | Measurement data self-calibration fusion method |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 1759-1763 |
| Number of pages | 5 |
| Journal | Hangkong Dongli Xuebao/Journal of Aerospace Power |
| Volume | 34 |
| Issue number | 8 |
| DOIs | |
| State | Published - 1 Aug 2019 |
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