## 4 Analysis, Comparison and Discussion of the Results  
As we mentioned with regard to the purpose of our research, we performed dynamic response measurements using three different methods. For further analysis of the results for the purpose of determining the dynamic response, it was necessary to determine the frequency, dominant frequency and amplitude parameters. In the case of the RTS method, which is understood to be a non-invasive method and one used for determining the response in places where other methods are not used, the results of the measurements must be further analysed. From the obtained results, we can only determine the vertical displacement versus the loading time, which is useful for static analyses. In order to determine the frequency, dominant frequency and amplitude, we have to further process the data from the geodesic measurements. Measurements in most scientific and engineering fields are characterised by the periodic signal of the measured object, the periodicity of which is identified using spectral analysis techniques. Spectral analysis or spectrum analysis is thus a method of analysis employing mathematical parameterisation, where the selected object is studied in terms of frequencies or other directly related quantities, such as energy, eigenvalues and the like. The most widely used and widely represented technique in the field of spectral analysis is the Fourier-transform method, which is applicable to both continuous and linear signals. The main limitation in the appropriate use of the Fourier transform is the requirement for a constant (equivalent) measurement time interval [64]. The Fourier transform is an extremely powerful mathematical tool that is used in a wide range of fields. The main reason for the widespread use of this method is that the Fourier transform converts the complicated operations of subtraction and convolution into simple multiplication and, as such, it is an important tool in the solution of differential equations. In the field of physical science, the method is most commonly used for the determination of so-called frequency spectra of oscillations with the presence of a certain amount of noise and where the acquisition of the data is, in principle, uniform. In today's practice, uniform sampling is basically only possible with more advanced automated measurement systems, such as accelerometers or strain gauges. In contrast to this situation, in our work with surveying methods, we are confronted with the problem of non-uniformity in the acquisition of measured data obtained at unequal or irregular time intervals. Incorrect registration intervals and, consequently, sampling errors occur in the wake of technical shortcomings in surveying instruments. The errors are visually reflected as so-called coarse errors, which are caused by the insufficient frequency range of a device, partial automation, noise and mechanical interruption of the measurement [64]. The Fourier transform, whether discrete or fast, becomes practically useless when we want to take into account the different, temporally unequal measurement data that can be obtained from different surveying instruments, such as RTSs, in an analysis. The Lomb periodogram method was introduced in 1976 by [PERSON] and [PERSON] as a means to incorporate and account for sampling irregularities in data processing. The Lomb periodogram can, therefore, be used for spectral analysis of both irregularly and correctly sampled measurement data [65]. The Lomb or Lomb-Scargle periodogram is a mathematical method based on the least-squares principle for estimating the frequency spectra of arbitrary oscillations and the periodicity of uniform and non-uniform sampling. The procedure is based on the fitting of sinusoidal shape functions [64]:  
\[h(t)=a\cdot\cos\left(\frac{2\pi}{T}.(t-\tau)\right)+b\cdot\sin\left(\frac{2\pi }{T}\cdot(t-\tau)\right) \tag{1}\]  
The Lomb periodogram \(P(t)\) describes the dimensionless value used to express the power spectrum and is defined for a time period \(T\) as [64]:\[P(T)=\frac{1}{2\sigma^{2}}.