A deep learning regression fusion positioning method based on signal strength

Abstract

The invention provides a deep learning regression fusion positioning method based on signal strength, and relates to the field of positioning methods based on signal strength. The present invention comprises the following steps: Step 1, establish a fingerprint library in the environment to be positioned; Step 2, preprocess the data in the fingerprint library; Step 3, input the preprocessed data into the automatic coding model for pre-training; step 4. Construct the DNN model on the basis of the auto-encoding model, and then train the DNN model; step 5, construct the CNN model and input the preprocessed data into the CNN model for training; step 6, train the DNN model according to the DS evidence fusion theory Fusion with the output probability value of the CNN model to calculate the prediction result; step 7, adjust the DNN model and CNN model according to the error value between the model estimated result and the real result; step 8, perform real-time positioning according to the adjusted classification model. The present invention utilizes the complementary advantages of DNN and CNN to comprehensively extract features and improve the positioning accuracy.

Description

technical field [0001] The invention relates to the field of positioning methods based on signal strength, in particular to a deep learning regression fusion positioning method based on signal strength. Background technique [0002] With the rapid development of the big data era, the demand for positioning technology is also growing rapidly, and its main driving force is the huge application and commercial potential that positioning services can bring. Through location-based services, users can determine their location in large supermarkets, find a product in a specific store, and find the facilities they need in public service places such as airports or train stations. The hospital confirms the location information of medical personnel or medical equipment, and the fire department locates the firefighters, etc. Therefore, positioning technology in complex environments is the core technology of several key issues of the Internet of Things. [0003] Literature M.Nowicki and...

AI Technical Summary

Problems solved by technology

[0004] The object of the present invention is to provide a deep learning regression fusion positioning method based on signal strength in order to solve the problem that the existence of the following three problems leads to inaccurate source location estimation results in complex environments: (1) classification model positioning The error is easily affected by the grid point spacing when the offline fingerprint database is established. (2) The feature extraction of the signal strength by the single deep learning model DNN is not comprehensive, and the signal strength distribution characteristics between the single training data cannot be learned. (3) If the model When locating grid points, the uncertainty is strong, directly using the label corresponding to the maximum value of the output layer as the positioning result will lead to a large positioning error

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