High-precision GNSS faces several error sources: satellite orbit and clock deviations, ionospheric and tropospheric delays, multipath, and receiver noise. RTK and PPP correct many of these via real-time or post-processed data. Atmospheric errors are reduced using dual-frequency measurements and network models. Multipath remains a challenge, especially in urban environments — requiring careful antenna placement and filtering. Awareness of these factors is key to designing robust systems and interpreting performance limits realistically.
High-precision GNSS faces several error sources: satellite orbit and clock deviations, ionospheric and tropospheric delays, multipath, and receiver noise. RTK and PPP correct many of these via real-time or post-processed data. Atmospheric errors are reduced using dual-frequency measurements and network models. Multipath remains a challenge, especially in urban environments — requiring careful antenna placement and filtering. Awareness of these factors is key to designing robust systems and interpreting performance limits realistically.
High-precision GNSS faces several error sources: satellite orbit and clock deviations, ionospheric and tropospheric delays, multipath, and receiver noise. RTK and PPP correct many of these via real-time or post-processed data. Atmospheric errors are reduced using dual-frequency measurements and network models. Multipath remains a challenge, especially in urban environments — requiring careful antenna placement and filtering. Awareness of these factors is key to designing robust systems and interpreting performance limits realistically.