Indoor positioning method based on global and local joint constraint transfer learning
A transfer learning and indoor positioning technology, applied in the field of indoor positioning based on global and local joint constraint transfer learning, can solve the problems of difficult to form accurate, real-time, stable positioning, insufficient knowledge, etc., to achieve high positioning accuracy, improve Good accuracy and robustness
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[0023] 1. Experimental Site Layout
[0024] The experimental environment is 308.4m 2 In the library environment, there are chairs, benches and bookshelves in the room. The number of WiFi access points that can be detected in the positioning area is 448. First, the site is divided into 230 grid points.
[0025] 2. Acquire data and form RSS fingerprint database
[0026] Place the mobile device in each grid point in turn, record the grid point number and the RSS value from each access point to form an RSS vector here n s is the number of all RSS samples marked for a known position, and the corresponding position mark is denoted as c i ∈{1,2,...,C}, C=230 is the number of grid points. RSS values with corresponding location markers form a database of fingerprints, i.e. source domains in,
[0027] 3. Collect the RSS value of the device to be located
[0028] Collect the RSS value of the mobile device requesting location to form the target domain here Target domain d...
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