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Non-contact multi-target positioning method

A multi-target positioning and non-contact technology, which is applied in the field of non-contact multi-target positioning, can solve the problems of a large amount of time, the influence of positioning accuracy, and large positioning errors, etc., to achieve enhanced extraction capabilities, solve insufficient accuracy, and enrich positioning methods Effect

Active Publication Date: 2022-01-11
ZHENGZHOU UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Defect: Due to the need to establish a location fingerprint database, it takes a lot of time and manpower to manually collect fingerprints of each location in the environment in the offline stage
[0009] Defect: The positioning accuracy of this type of method is directly affected by the accuracy of parameter estimation. Whether it is using the MUSIC algorithm or the SAGE algorithm, it is an estimate of the actual parameters.
Due to the use of estimated parameter values ​​​​substituting into the equation system calculation, it will produce a large positioning error

Method used

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Experimental program
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Embodiment 1

[0047] Such as image 3As shown, this embodiment provides a non-contact multi-target positioning method, including parameter estimation processing, CBR module processing and classifier module processing.

[0048] Parameter estimation processing

[0049] Including the step of mathematical modeling, the step of constructing the spatial spectrum function, the step of solving the peak-to-peak value of the spectrum and the step of generating the heat map; considering the high-resolution advantages of the JADE-MUSIC algorithm, this algorithm is used for parameter estimation;

[0050] The parameter estimation process includes:

[0051] Mathematical modeling steps: take the MA root antenna as the signal receiving array, the distance between the antenna arrays is d, and the receiving signal is continuously sampled at the rate of 1 / T during the signal collection, T is the sampling period; the spatial and temporal The sample numbers are respectively MA and MT=[Twin / T];

[0052] Use ma...

Embodiment 2

[0083] This embodiment provides a terminal, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the computer program, the non- The steps of the contact multi-target positioning method are to obtain the result of multi-target behavior recognition.

[0084] It should be noted that, for the convenience and brevity of description, for the specific working process of the terminal, reference may be made to the corresponding process of the method described in the above-mentioned embodiment 1, which will not be repeated here.

[0085] It should be noted that the terminal in this embodiment may be a terminal device such as a PC, a mobile phone, or a tablet.

[0086] In particular, the terminal can be used as a care terminal. At present, our country has entered an aging society. Due to the limitation of medical resources, home care for the elderly has become very important, and its related re...

Embodiment 3

[0088] This embodiment provides a computer-readable storage medium, on which computer instructions are stored. When the computer instructions are executed by a processor, the steps of the above-mentioned non-contact multi-target positioning method are implemented, and the result of multi-target behavior recognition is obtained. .

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Abstract

The invention provides a non-contact multi-target positioning method, which comprises the steps of parameter estimation processing, including a mathematical modeling step, a spatial spectrum function construction step, a spectrum peak value solving step and a heat map generation step; performing CBR module processing, taking the heat map obtained in the parameter estimation processing as model input, and performing processing by adopting a plurality of CBR modules; and using the classifier module for processing, taking the data processed by the CBR module as input, taking a Softmax method for classification, and obtaining a prediction result of final position information. According to the method, the position information parameters (AoA value and ToF value) of multi-target positioning are estimated by adopting the MUSIC algorithm, and the parameter information is converted into a heat map form to be input into the convolutional neural network, so that the feature extraction capability is greatly enhanced. On the basis of strong position feature extraction capability, the technical scheme provided by the invention realizes an indoor multi-target high-precision positioning function.

Description

technical field [0001] The invention relates to a non-contact multi-target positioning method, which belongs to the field of WIFI behavior recognition. Background technique [0002] In recent years, with the rapid development of the Internet of Things technology, convenient and high-precision location information services have become an important support for human-computer interaction and have attracted widespread attention. At present, indoor positioning technology based on computer vision, physical sensors and other methods has been relatively mature and has been widely used in various practical scenarios. However, these methods have certain limitations. The positioning method based on computer vision is easily affected by object occlusion and illumination in indoor complex environments, and has poor privacy; the indoor positioning method based on physical sensors is expensive to deploy and inconvenient to carry, which limits its scope of use. [0003] With the rapid gro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W4/02H04W4/021H04W4/33G06K9/62
CPCH04W4/023H04W4/021H04W4/33G06F18/2415Y02D30/70
Inventor 段鹏松曹仰杰王超叶彪
Owner ZHENGZHOU UNIV
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