US 12,422,566 B2
Integer ambiguity validation with machine learning
Min Wang, Tustin, CA (US); and Songwon Jee, San Jose, CA (US)
Assigned to QUALCOMM Incorporated, San Diego, CA (US)
Filed by QUALCOMM Incorporated, San Diego, CA (US)
Filed on Jun. 14, 2023, as Appl. No. 18/334,837.
Prior Publication US 2024/0418869 A1, Dec. 19, 2024
Int. Cl. G01S 19/44 (2010.01)
CPC G01S 19/44 (2013.01) 24 Claims
OG exemplary drawing
 
1. An apparatus comprising:
one or more memories;
one or more receivers; and
one or more processors communicatively coupled to the one or more memories and the one or more receivers, the one or more processors being configured to:
obtain, in conjunction with the one or more receivers, a plurality of feature values that are based on satellite signals received by a mobile device;
determine an integer ambiguity vector indicative of integer numbers of carrier phase cycles of the satellite signals between the apparatus and respective satellites;
determine a probability of the integer ambiguity vector being correct by using the integer ambiguity vector in a machine learning algorithm; and
determine whether the integer ambiguity vector is correct based on the probability of the integer ambiguity vector being correct and an integer ambiguity vector probability threshold.