Wireless receive signal strength indicator (rssi)-based positioning

An apparatus comprising:

• at least one processing device configured to:
• receive wireless fingerprint data associated with a specified area, the wireless fingerprint data identifying (i) multiple locations within the specified area and (ii) for each location, one or more signal strength values associated with wireless signals received at the location from one or more of multiple wireless transmitters, wherein the wireless fingerprint data is missing signal strength values for one or more of the wireless transmitters at one or more specific locations within the specified area;
• generate a first training dataset by adding filler signal strength values in place of at least some of the signal strength values that are missing from the wireless fingerprint data;
• train a first machine learning model using the first training dataset, the first machine learning model trained to receive a specified location as input and generate predicted signal strength values as outputs;
• and
• use the trained first machine learning model to generate additional signal strength values, at least some of the additional signal strength values to be used in place of at least a portion of the signal strength values that are missing from the wireless fingerprint data.

A non-transitory computer readable medium containing instructions that when executed cause at least one processor to:

• receive wireless fingerprint data associated with a specified area, the wireless fingerprint data identifying (i) multiple locations within the specified area and (ii) for each location, one or more signal strength values associated with wireless signals received at the location from one or more of multiple wireless transmitters, wherein the wireless fingerprint data is missing signal strength values for one or more of the wireless transmitters at one or more specific locations within the specified area;
• generate a first training dataset by adding filler signal strength values in place of at least some of the signal strength values that are missing from the wireless fingerprint data;
• train a first machine learning model using the first training dataset, the first machine learning model trained to receive a specified location as input and generate predicted signal strength values as outputs;
• and
• use the trained first machine learning model to generate additional signal strength values, at least some of the additional signal strength values to be used in place of at least a portion of the signal strength values that are missing from the wireless fingerprint data.

A method comprising:

• obtaining, by a mobile electronic device, signal strength values associated with wireless signals received at the mobile electronic device;
• providing the obtained signal strength values as input to a trained location prediction machine learning model;
• using the trained location prediction machine learning model to generate a predicted location of the mobile electronic device;
• and
• presenting the predicted location of the mobile electronic device on a display of the mobile electronic device;
• wherein the trained location prediction machine learning model is trained using (i) wireless fingerprint data collected within a specified area and (ii) imputed or augmented signal strength values generated using a trained generator machine learning model.