Patent ID: 11943735
Assignee: nan
Field: Computer technology (Electrical engineering)
Classification: CPC G  H  Y | IPC G  H

Claim 0:
1. A method, comprising:
acquiring and preprocessing target camera serial interface (CSI) data of a to-be-positioned target; and
matching preprocessed target CSI data with fingerprints in a positioning fingerprint database to obtain coordinate information of the to-be-positioned target;
wherein:
a generation method of the positioning fingerprint database comprises:
collecting indoor WiFi signals by a software defined radio (SDR) platform to obtain indoor CSI data corresponding to the indoor WiFi signals, and preprocessing the indoor CSI data;
partitioning the preprocessed indoor CSI data into a plurality of data subsets through a clustering algorithm;
training an improved convolutional neural network (CNN) model by the plurality of data subsets to obtain a trained improved CNN model; and
generating the positioning fingerprint database by the trained improved CNN model and the preprocessed indoor CSI data;
wherein partitioning the preprocessed indoor CSI data into the plurality of data subsets through the clustering algorithm comprises:
dividing the preprocessed indoor CSI data into the plurality of data subsets by the clustering algorithm, and each data subset comprising a plurality of the indoor CSI data;
calculating a center of each data subset based on a k-means algorithm by following formula:, μ
       i
      
      =
      
       
        1
        
         
         
          C
          i
         
         
        
       
       ⁢
       
        
         ∑
          
        
        
         x
         ∈
         
          C
          i
         
        
       
       ⁢
       x
      
     
     ;
    
   
   
    
     (
     1
     )
    
   
  
 

where μi represents a center of an ith data subset, Ci represents the ith data subset, x represents the indoor CSI data i=1, . . . , k, where k is a number of data subsets;
calculating a square error of all data subsets based on the center of the ith data subset by following formula:

E=Σi=1kΣx∈Ci∥x−μi∥22  (2);

where E represents the square error of all data subsets; and
calculating a distance between the preprocessed indoor CSI data and the center of each data subset, re-partitioning the data subsets according to the distance until the square error is minimized, thereby obtaining a final data subset.