Multi-base-station wireless positioning method based on full convolutional neural network

• Main Authors: CHEN YANGZHUO, CHEN DAIZHU, MO YAJIE, LI ZEXIAN, ZHU SHUANGXIN, CHEN ANQI, PENG SHASHA, CAI CHENGLIN, FAN SHUO
• Format: Patent
• Language: Chinese; English
• Published: 22.03.2022
• Subjects: ANALOGOUS ARRANGEMENTS USING OTHER WAVES; CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION ORRERADIATION OF RADIO WAVES; MEASURING; PHYSICS; RADIO DIRECTION-FINDING; RADIO NAVIGATION; TESTING

The invention discloses a multi-base-station wireless positioning method based on a full convolutional neural network. The method comprises the following steps: step 1, respectively collecting distance data between labels in a plurality of spaces and each base station; 2, generating a signal space score graph according to the collected distance data and coordinates and system error parameters of each base station, and labeling the whole graph to form a training data set; 3, designing a full convolutional neural network, and training the full convolutional neural network by using the training data set in the step 2; and step 4, outputting the generated signal space score map by using the trained full convolutional neural network to obtain a label position space score map, and obtaining position information of the label in the space. The positioning method provided by the invention is convenient to use, can quantify the uncertainty of the positioning result, supports data input of any multiple base stations, an