## 1 Introduction  
Integrated measurement methods are usually employed for various surveying engineering jobs, such as monitoring land surface displacements or structure deformation [1, 2, 3, 4, 5, 6, 7]. Classical (terrestrial) surveying techniques are usually based on control networks referred to as a local (national) system of coordinates [8, 9]. Survey results are usually processed by a simultaneous adjustment of classical observations (angles and distances) and GNSS vectors in a common mathematical space [5]. Integrated networks may be adjusted on the GRS'80 (Geodetic Reference System '80) reference ellipsoid surface or a horizontal projection plane in a local system. It is necessary to pre-process the observations in both cases. This process can include the projection of GNSS vectors onto an ellipsoid (calculating the length of a geodetic line and its original azimuth), projection of classical observations (horizontal distances) onto the surface of an ellipsoid (calculating the projection corrections), or transformation of GNSS vectors (\(\Delta X\), \(\Delta Y\), \(\Delta Z\)) onto a horizontal plane [10, 11, 12, 13]. The determination of the height of the GNSS network points (e.g., calculation of ellipsoidal heights and their conversion into values referenced to the local model of geoid) is a separate computational stage [14, 15, 16, 17]. All the pre-processing is rather labour-intensive and requires practical experience and knowledge [13, 18, 19]. What is more, one cannot avoid errors resulting from the transforming of the original observations into pseudo-observations on a common plane of reference (such as projection errors or errors of the geoid model). Integrated networks are proposed to be used if satellite signal exposure is insufficient (in forests or difficult topography). It is then that classical observations can be used to improve the GNSS vector network. Detailed investigations into integrated geodetic networkscan be found in many available publications [6; 14; 20; 21; 22]. For example, [PERSON] [8] showed a method for adjusting a GNSS network as a linear (trilateration) network. He proved that slope distances measured with any surveying method can be adjusted in any reference system (cf. [23]). [PERSON] [24] proposed an alternative adjustment method whereby both distances and angles between GNSS vectors are calculated in a geocentric spatial system (\(XYZ\)). A resulting set of linear-angular non-reduced pseudo-observations can be adjusted in reference to a local reference system. Land-surveying measurements are adjusted because they are burdened with random errors (cf. [8; 25]). The errors are treated like normally distributed random variables (Gauss distribution, Figure 1). The error of measurement (\(\epsilon\)) exhibits normal distribution if the error's density function \(f(\epsilon)\) can be expressed as:  
\[f(\epsilon)=\frac{1}{\sqrt{2\pi}}\cdot e^{-\frac{\epsilon^{2}}{2}}=\frac{1}{ \sqrt{2\pi}}\cdot\exp\left(-\frac{\epsilon^{2}}{2}\right) \tag{1}\]  
where: \(\epsilon\)--the base of a natural logarithm. The probability that the measurement error \(\epsilon\) (as a random variable) will take a value from the interval \((\epsilon_{1};\epsilon_{2})\) can be expressed in the form (Figure 1):  
\[P(\epsilon\in\langle\epsilon_{1};\epsilon_{2}\rangle)=\frac{1}{\sqrt{2\pi}} \cdot\int\limits_{\epsilon_{1}}^{\epsilon_{2}}\exp\left(\frac{-\epsilon^{2}} {2}\right)d\epsilon \tag{2}\]  
where: \(d\epsilon\)--the differential of \(\epsilon\). As the actual values of errors of measurement \(\epsilon\) are unknown, they are replaced with observation corrections \(v\), to be determined during adjustment. The goal of adjusting observations with the least-squares method is to select such correction values \(v\) that the sum of their squares multiplied by the weights (\(p\)) is the smallest.