When surveying national reference points using a global positioning system (GPS), appropriate work regulations pertaining to the surveying time must be observed. However, such data can be modified easily, so identifying non-compliance with work regulations and forgeries is challenging. If such incidents occur in cadastral surveys, it may result in financial damages to stakeholders, such as citizens and the state. Therefore, it is necessary to improve the reliability by ensuring the integrity of the GPS positioning data and allowing anyone to track them. In this study, a prototype system was developed to record GPS data and the corrections generated during survey processes using the Ethereum blockchain network. Blockchain is a distributed ledger system that prevents the manipulation of uploaded data without the need for a centralized institution by allowing anyone to check the data. Unlike in the past, the proposed system improves the data integrity and reliability for the entire survey process through blockchain, thereby ensuring transparency of the checks using smart contract addresses.

Binary Offset Carrier (BOC) modulation is used in the Global Navigation Satellite System (GNSS). Unlike Binary Phase Shift Keying (BPSK) in the Global Positioning System, BOC-modulated signals have side-peaks in the autocorrelation function (ACF) leading to positioning errors in multipath channels. This paper introduces a two-stage BOC first arrival path detection network (BOC-FPDNet). This includes side-peaks cancellation (SC) and multipath time delay estimation (MDE) for BOC modulation. The SC is a deep learning-based method that cancels side-peaks without added computational load or noise increase. The MDE uses Multi-head attention to extract ACF output features and consists of two heads, positive and negative sample detector, for time delay estimation. The effectiveness of BOC-FPDNet is demonstrated by comparing it to super-resolution and other deep learning detection techniques in various multipath channel simulations and real urban data. Results show BOC-FPDNet provides superior side-peak cancellation and accurate BOC-modulated signal detection.