Low-energy consumption location of movable objects

Abstract

Low-energy consumption techniques for locating a movable object using a global navigation satellite system (GNSS) are provided. A mobile station attached to or included in a movable object can communicate bidirectionally with a fixed base station to determine a location of the movable object. The mobile station may communicate an estimated position to the base station and receive from the base station a set of GNSS satellites that are visible to the mobile station. The mobile station can acquire satellite timing information from GNSS signals from the set of satellites and communicate minimally-processed satellite timing information to the base station. The base station can determine the position of the mobile station and communicate the position back to the mobile station. By offloading much of the processing to the base station, energy consumption of the mobile station is reduced.

1 . (canceled) 
     
     
         2 . A system for analyzing satellite acquisition data, the system comprising:
 non-transitory data storage configured to store satellite acquisition data related to attempts by mobile stations capable of moving in a tracking area to acquire signals from global navigation satellite system (GNSS) satellites; and   a hardware processor in communication with the non-transitory data storage, the hardware processor programmed to:
 analyze the satellite acquisition data using a machine learning algorithm; and 
 perform one or more of the following based at least in part on the machine learning analysis:
 update a model of the tracking area in which the mobile stations are capable of moving, or 
 update GNSS satellite selection criteria for the mobile stations. 
 
   
     
     
         3 . The system of  claim 2 , wherein the hardware processor is programmed to learn, from the machine learning analysis, a presence of an obstacle that inhibits reception of GNSS satellite signals (1) at a particular position in the tracking area or (2) in a particular direction relative to the tracking area. 
     
     
         4 . The system of  claim 3 , wherein the hardware processor is programmed to:
 access geographic information system (GIS) geospatial data; and   determine the obstacle was not present in the GIS geospatial data.   
     
     
         5 . The system of  claim 3 , wherein the model of the tracking area comprises a position of the obstacle. 
     
     
         6 . The system of  claim 3 , wherein the hardware processor is programmed to not list, in ranked lists of satellites communicated to a mobile station, satellites in the particular direction relative to the tracking area in which presence of the obstacle inhibits reception of GNSS satellite signals. 
     
     
         7 . The system of  claim 2 , wherein the machine learning algorithm comprises a neural network, a decision tree, a support vector machine, a probabilistic method, a Bayesian network, or a data mining algorithm. 
     
     
         8 . The system of  claim 2 , wherein the mobile stations are attached in or on a shopping cart or in or on a wheel of a shopping cart. 
     
     
         9 . The system of  claim 8 , wherein the tracking area comprises a portion of a parking lot associated with a retail store. 
     
     
         10 . The system of  claim 2 , wherein the satellite acquisition data comprises an indication that a GNSS satellite failed to be acquired by a mobile station. 
     
     
         11 . The system of  claim 10 , wherein the satellite acquisition data comprises an indication that a width of a peak in a correlator output exceeds a threshold. 
     
     
         12 . The system of  claim 2 , wherein the hardware processor is programmed to determine, from the machine learning analysis of the satellite acquisition data, that a mobile station is malfunctioning. 
     
     
         13 . The system of  claim 12 , wherein the hardware processor is programmed to flag the malfunctioning mobile station for maintenance. 
     
     
         14 . The system of  claim 2 , wherein each of the mobile stations comprise:
 a radio frequency (RF) mobile communication system configured to operate an RF link having an RF link frequency in an RF band that is not licensed for cellular communications;   a mobile GNSS receiver; and   a dead reckoning system including a non-GNSS sensor, the dead reckoning system configured to use measurements from the non-GNSS sensor to provide an estimated position for the mobile station.