Maintaining a trained neural network for mobile device RSS fingerprint based indoor navigation
US10655971B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | May 1, 2019 |
| Grant date | May 19, 2020 |
| Priority date | — |
| Expiry date | May 1, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and system of maintaining a trained neural network for mobile device indoor navigation and positioning. The method comprises: determining, in the processor, at a first location relative to a wireless signal source at a second location, a set of received signal strength (RSS) input parameters in accordance with a postulated RSS model, the processor implementing an input layer of a neural network, the set of RSS input parameters providing an RSS input feature to the input layer of the neural network; receiving a set of RSS measured parameters acquired at a mobile device positioned at the first location from the wireless signal source at the second location; computing, at an output layer of the trained neural network, an output error based on comparing the RSS input feature to an RSS output feature generated at the output layer, the RSS output feature being generated at least in part based on a matrix of weights associated with at least a first neural network layer; and if the output error exceeds a threshold value, re-training the neural network based at least in part upon re-initializing the matrix of weights associated with the at least a first neural network layer.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.