Mobile real time kinematic (rtk) / precise point positioning (ppp) enhancement with antenna pco/pcv compensation

An apparatus for global navigation satellite system (GNSS)-based positioning of a mobile device using a machine-learning model for antenna phase center compensation, comprising:

• a global navigation satellite system (GNSS) receiver that includes at least one receiver antenna;
• a memory;
• and
• one or more processors communicatively coupled with the GNSS receiver and the memory, wherein the one or more processors are configured to:
• obtain GNSS information associated with one or more satellite vehicles (SVs) available to provide GNSS signals to the mobile device;
• obtain attitude information of the mobile device based at least in part on sensor data obtained from one or more sensors of the mobile device;
• process the GNSS information and the attitude information of the mobile device using the machine-learning model to generate a measurement uncertainty prediction associated with the at least one receiver antenna;
• and
• execute at least one GNSS-based positioning operation that includes antenna phase center compensation based at least in part on the measurement uncertainty prediction generated by the machine-learning model.

An apparatus for global navigation satellite system (GNSS)-based positioning of a mobile device using a machine-learning model for antenna phase center compensation, the apparatus comprising:

• means for obtaining GNSS information associated with one or more satellite vehicles (SVs) available to provide GNSS signals to the mobile device;
• means for obtaining attitude information of the mobile device based at least in part on sensor data obtained from one or more sensors of the mobile device;
• means for processing the GNSS information and the attitude information of the mobile device using the machine-learning model to generate a measurement uncertainty prediction associated with at least one receiver antenna of the mobile device;
• and
• means for executing at least one GNSS-based positioning operation that includes antenna phase center compensation based at least in part on the measurement uncertainty prediction generated by the machine-learning model.