The main motivation of this study is to assess the accuracy performance of the real-time global GNSS PPP positioning service, i.e. Trimble CenterPoint RTX, and online PPP post-processing service, i.e. CSRS-PPP, in Çorum Province of Turkey. Within this scope, a geodetic point was established and GNSS data were logged in static mode at a measurement interval of 1 Hz. At the same time, the real-time coordinates of each measurement epoch were determined with the Trimble CenterPoint RTX positioning service using L-band geostationary satellite delivery. The collected GNSS data were also sent to the CSRS-PPP service and the coordinates of each measurement epoch were calculated. According to comparison of the coordinates obtained from CenterPoint RTX to the known coordinates, it was concluded that the 3D real-time positioning achieved at centimeter-level of accuracy within convergence time of a few minutes. On the other hand, CSRS-PPP also provided centimeter-level accurate positioning with post-processing mode. The overall results show that, the attainable accuracy with both approaches provided the requirements of the many scientific and practical surveying applications.

The real world phenomena being observed by sensors are generally non-stationary in nature. The classical linear techniques for analysis and modeling natural time-series observations are inefficient and should be replaced by non-linear techniques of whose theoretical aspects and performances are varied. In this manner adopting the most appropriate technique and strategy is essential in evaluating sensors’ data. In this study, two different time-series analysis approaches, namely least squares spectral analysis (LSSA) and wavelet analysis (continuous wavelet transform, cross wavelet transform and wavelet coherence algorithms as extensions of wavelet analysis), are applied to sea-level observations recorded by tide-gauge sensors, and the advantages and drawbacks of these methods are reviewed. The analyses were carried out using sea-level observations recorded at the Antalya-II and Erdek tide-gauge stations of the Turkish National Sea-Level Monitoring System. In the analyses, the useful information hidden in the noisy signals was detected, and the common features between the two sea-level time series were clarified. The tide-gauge records have data gaps in time because of issues such as instrumental shortcomings and power outages. Concerning the difficulties of the time-frequency analysis of data with voids, the sea-level observations were preprocessed, and the missing parts were predicted using the neural network method prior to the analysis. In conclusion the merits and limitations of the techniques in evaluating non-stationary observations by means of tide-gauge sensors records were documented and an analysis strategy for the sequential sensors observations was presented.