Abstract
Multilateration tracking systems (MLTSs) are used in industrial three-dimensional (3D) coordinate measuring applications. For high-precision measurement, system parameters must be calibrated properly in advance. For an MLTS using absolute distance measurement (ADM), the conventional self-calibration method significantly reduces estimation efficiency because all system parameters are estimated simultaneously using a complicated residual function. This paper presents a novel self-calibration method that optimizes ADM to reduce the number of system parameters via highly precise and separate estimations of dead paths. Therefore, the residual function to estimate the tracking station locations can be simplified. By applying a suitable mathematical procedure and solving the initial guess problem without the aid of an external device, estimation accuracy of the system parameters is significantly improved. In three self-calibration experiments, with ADM repeatability of approximately 3.4 µm, the maximum deviation of the system parameters estimated by the proposed self-calibration method was 68.6 µm, while the maximum deviation estimated by the conventional self-calibration method was 711.9 µm. Validation of 3D coordinate measurements in a 1000 mm × 1000 mm × 1000 mm volume showed good agreement between the proposed ADM-based MLTS and a commercial laser tracker, where the maximum difference based on the standard deviation was 17.7 µm. Conversely, the maximum difference was 98.8 µm using the conventional self-calibration method. These results confirmed the efficiency and feasibility of the proposed self-calibration method.
Highlights
In recent decades, the demand for accurate measurement of large structures has increased considerably
With the aim of providing a solution to the above-mentioned issues, this paper presents a novel self-calibration method for an Multilateration tracking systems (MLTSs) using absolute distance measurement (ADM), in which the advantages of ADM are effectively optimized to improve the efficiency of the self-calibration process and provide good initial guesses for least squares estimation
A small number of system parameters are estimated in each step, which reduces the complexity of the original residual function
Summary
The demand for accurate measurement of large structures has increased considerably. Sensors 2020, 20, 7288 large-volume measurement [7] Efforts to reduce this error have led to the use of multilateration tracking systems (MLTSs), in which angle measurement is entirely removed and only multi-distance information is used for three-dimensional (3D) coordinate measurement [8]. To the best of our knowledge, there have been no reports of a custom-designed self-calibration method for ADM-based MLTSs, which could implement advantages of ADM to provide high-precision estimation of system parameters (i.e., dead paths and tracking station locations). By using the roughly estimated elevation angle offset, the initial guess problem can be solved automatically without the aid of any external device This enables improvement of the on-site calibration of tracking station locations.
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