Abstract

We combine accelerometer and asynchronous high-rate GNSS data to retrieve dynamic displacements. The method adopts relative GNSS positioning with observations of different sampling rates at rover and reference stations. The objective is to examine the feasibility of downsampling GNSS data at reference stations and thus, verify whether permanent GNSS networks collecting low-rate observations can serve as reference sites. The performance is assessed using a shake table to induce displacement waveforms. We show that the combined GNSS and accelerometer solution improves displacement accuracy by half compared to the GNSS-only one. Further accuracy improvement is obtained by applying the Rauch Tung Striebel (RTS) smoother. Consequently, it is reasonable to downsample high-rate GNSS data at the reference station even to a 2 s interval and preserve the displacement error below 1 mm. The results also reveal that a fusion of GNSS with accelerometer and RTS smoothing helps to mitigate the ephemeris error. With the assessment in the time–frequency domain, we show that the combined solution better recovers displacement waveforms than GNSS-only. For the former solution, the detected peak frequencies agree very well with those of the Linear Variable Differential Transformer responsible for providing the ground truth displacements, and the amplitude error does not exceed 0.5 mm. We conclude that the proposed approach based on asynchronous GNSS observations provides millimeter-level precision results and is better for reconciling dynamic displacements than a GNSS-only solution or simply integrating accelerometer data.

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