Wireless signal display method, device and computer readable storage medium

Abstract

The present invention relates to the field of communication technology, and discloses a wireless signal display method, device and computer-readable storage medium. The wireless signal display method comprises the following steps: parsing the wireless signal to obtain a signal amplitude matrix; performing data conversion on the signal amplitude matrix to obtain a conversion amplitude matrix; and displaying the conversion amplitude matrix in an image to obtain a wireless signal image. The present invention can improve the visibility of wireless signals and improve the intuitive expression ability of wireless signals.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a wireless signal display method, device and computer-readable storage medium. Background Art

[0002] At present, with the development of radio technology, wireless signals have certain applications in obtaining the laws of human activities, and wireless signals can be used to determine the number of human activities; however, the mapping relationship between wireless signals and the number of human activities is usually expressed as a one-dimensional time series signal; it is difficult to describe living organisms intuitively and visibly like visible light machine vision, and can only indirectly express the quantitative characteristics of human activities by analyzing limited one-dimensional time series signals. Summary of the invention

[0003] The main purpose of the present invention is to provide a wireless signal display method, device and computer-readable storage medium, aiming to improve the visibility and intuitive expression ability of wireless signals.

[0004] To achieve the above object, the present invention provides a wireless signal display method, the wireless signal display method comprising the following steps:

[0005] Analyze the wireless signal to obtain the signal amplitude matrix;

[0006] Performing data conversion on the signal amplitude matrix to obtain a conversion amplitude matrix;

[0007] The conversion amplitude matrix is ​​displayed graphically to obtain a wireless signal image.

[0008] Optionally, the step of performing data conversion on the signal amplitude matrix to obtain a conversion amplitude matrix includes:

[0009] Perform pixel conversion on each amplitude in the signal amplitude matrix to obtain a pixel value corresponding to each amplitude;

[0010] The pixel values ​​corresponding to each of the amplitudes are combined according to the position of each amplitude in the signal amplitude matrix to obtain a conversion amplitude matrix.

[0011] Optionally, the step of displaying the conversion amplitude matrix in a graphical form to obtain a wireless signal image includes:

[0012] Convert each pixel value in the conversion amplitude matrix into a pixel point;

[0013] The pixel points are arranged and displayed in sequence with the time in the conversion amplitude matrix as the x-axis and the channel in the conversion amplitude matrix as the y-axis to form a wireless signal image, wherein the pixel points correspond to the pixel values ​​one by one.

[0014] Optionally, the step of analyzing the wireless signal to obtain a signal amplitude matrix includes:

[0015] Analyze the wireless signal based on a channel state analysis program to obtain a matrix signal;

[0016] Performing high-frequency filtering on the matrix signal based on a Butterworth filtering program to obtain a processed denoised matrix signal;

[0017] Performing a dimensionality reduction operation on the noise reduction matrix signal based on a principal component analysis algorithm to obtain a dimensionality reduction matrix signal;

[0018] The amplitude in the dimension reduction matrix signal is extracted to form a signal amplitude matrix.

[0019] Optionally, the dimension reduction matrix signal ,in H t is the wireless signal vector obtained at time t, c is the total number of channels in the wireless signal, T is the transposition operation, is the wireless signal of channel c at time t;

[0020] in, ,in, is the amplitude of channel c at time t, is the phase of channel c at time t;

[0021] The signal amplitude matrix is ,in, .

[0022] Optionally, the step of performing high-frequency filtering on the matrix signal based on a Butterworth filter program to obtain a processed denoised matrix signal comprises:

[0023] Obtaining the sampling frequency, human body fluctuation frequency and filtering order of the wireless receiver;

[0024] Calculate the cutoff frequency according to the sampling frequency and the human body fluctuation frequency;

[0025] Performing high-frequency filtering on the signal amplitude in the matrix signal based on the cutoff frequency and the filtering order to obtain a filtering amplitude;

[0026] The signal amplitude in the matrix signal is replaced by the filtering amplitude to obtain a noise reduction matrix signal.

[0027] Optionally, performing a dimensionality reduction operation on the noise reduction matrix signal based on a principal component analysis algorithm to obtain a dimensionality reduction matrix signal includes:

[0028] Input the noise reduction matrix signal as a sample set into a principal component analysis algorithm, and perform centralization processing on each spatial sample point in the sample set;

[0029] Calculating the covariance matrix of the spatial sample points, and decomposing the covariance matrix to obtain the eigenvalue corresponding to each of the spatial sample points and the eigenvector corresponding to each of the spatial sample points;

[0030] Determining a minimum dimension reduction dimension according to a preset reconstruction threshold and the eigenvalue;

[0031] The eigenvalues ​​are arranged in descending order from large to small, and the eigenvectors corresponding to the eigenvalues ​​with the smallest dimensionality reduction dimension are selected to form a dimensionality reduction matrix signal.

[0032] Optionally, the sample set , the spatial sample points after centralization are , x i is a spatial sample point in the noise reduction matrix signal;

[0033] The minimum dimension reduction pass Calculated, where d is the dimension of the sample set, λ i is the eigenvalue, and t is the preset reconstruction threshold.

[0034] In addition, to achieve the above-mentioned purpose, the present invention also provides a wireless signal display device, which includes: a memory, a processor, and a wireless signal display program stored in the memory and executable on the processor, and when the wireless signal display program is executed by the processor, the steps of the wireless signal display method described above are implemented.

[0035] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, on which a wireless signal display program is stored, and when the wireless signal display program is executed by a processor, the steps of the wireless signal display method as described above are implemented.

[0036] The present invention provides a wireless signal display method, device and computer-readable storage medium, which analyzes the wireless signal to obtain a signal amplitude matrix; performs data conversion on the signal amplitude matrix to obtain a conversion amplitude matrix; and displays the conversion amplitude matrix in an image to obtain a wireless signal image. In the above manner, the present invention can improve the visibility of wireless signals and improve the intuitive expression ability of wireless signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1It is a schematic diagram of the terminal structure of the hardware operating environment involved in the embodiment of the present invention;

[0038] Figure 2 It is a flowchart of a first embodiment of a wireless signal display method of the present invention;

[0039] Figure 3 FIG. 4 is a flow chart of a second embodiment of a wireless signal display method according to the present invention.

[0040] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0041] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0042] The main solution of the embodiment of the present invention is: analyzing the wireless signal to obtain a signal amplitude matrix; performing data conversion on the signal amplitude matrix to obtain a conversion amplitude matrix; and visually displaying the conversion amplitude matrix to obtain a wireless signal image.

[0043] With the development of radio technology, wireless signals have certain applications in obtaining the laws of human activities. Wireless signals can be used to determine the number of human activities; however, the mapping relationship between wireless signals and the number of human activities is usually expressed as a one-dimensional time series signal; it is difficult to describe living organisms intuitively and visibly like visible light machine vision, and can only indirectly express the quantitative characteristics of human activities by analyzing limited one-dimensional time series signals.

[0044] The present invention aims to improve the visibility and intuitive expression capability of wireless signals.

[0045] like Figure 1 As shown, Figure 1 It is a schematic diagram of the terminal structure of the hardware operating environment involved in the embodiment of the present invention.

[0046] The terminal in the embodiment of the present invention may be a PC, or may be a mobile terminal device with a display function, such as a smart phone or a tablet computer.

[0047] like Figure 1As shown, the terminal may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0048] Preferably, the terminal may also include a camera, an RF (Radio Frequency) circuit, a sensor, an audio circuit, a WiFi module, and the like. Among them, sensors include light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display screen according to the brightness of the ambient light, and the proximity sensor may turn off the display screen and / or backlight when the mobile terminal is moved to the ear. As a type of motion sensor, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that identify the posture of the mobile terminal (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; of course, the mobile terminal may also be equipped with other sensors such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., which will not be repeated here.

[0049] Those skilled in the art will understand that Figure 1 The terminal structure shown in the figure does not constitute a limitation on the terminal, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0050] like Figure 1 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a wireless signal display program.

[0051] exist Figure 1 In the terminal shown, the network interface 1004 is mainly used to connect to the backend server and perform data communication with the backend server; the user interface 1003 is mainly used to connect to the client (user end) and perform data communication with the client; and the processor 1001 can be used to call the wireless signal display program stored in the memory 1005 and perform the following operations:

[0052] Analyze the wireless signal to obtain the signal amplitude matrix;

[0053] Performing data conversion on the signal amplitude matrix to obtain a conversion amplitude matrix;

[0054] The conversion amplitude matrix is ​​displayed graphically to obtain a wireless signal image.

[0055] Further, the processor 1001 may call the wireless signal display program stored in the memory 1005, and further perform the following operations:

[0056] Perform pixel conversion on each amplitude in the signal amplitude matrix to obtain a pixel value corresponding to each amplitude;

[0057] The pixel values ​​corresponding to each of the amplitudes are combined according to the position of each amplitude in the signal amplitude matrix to obtain a conversion amplitude matrix.

[0058] Further, the processor 1001 may call the wireless signal display program stored in the memory 1005, and further perform the following operations:

[0059] Convert each pixel value in the conversion amplitude matrix into a pixel point;

[0060] The pixel points are arranged and displayed in sequence with the time in the conversion amplitude matrix as the x-axis and the channel in the conversion amplitude matrix as the y-axis to form a wireless signal image, wherein the pixel points correspond to the pixel values ​​one by one.

[0061] Further, the processor 1001 may call the wireless signal display program stored in the memory 1005, and further perform the following operations:

[0062] Analyze the wireless signal based on a channel state analysis program to obtain a matrix signal;

[0063] Performing high-frequency filtering on the matrix signal based on a Butterworth filtering program to obtain a processed denoised matrix signal;

[0064] Performing a dimensionality reduction operation on the noise reduction matrix signal based on a principal component analysis algorithm to obtain a dimensionality reduction matrix signal;

[0065] The amplitude in the dimension reduction matrix signal is extracted to form a signal amplitude matrix.

[0066] Furthermore, the dimension reduction matrix signal ,in H t is the wireless signal vector obtained at time t, c is the total number of channels in the wireless signal, T is the transposition operation, is the wireless signal of channel c at time t;

[0067] in, ,in, is the amplitude of channel c at time t, is the phase of channel c at time t;

[0068] The signal amplitude matrix is ,in, .

[0069] Further, the processor 1001 may call the wireless signal display program stored in the memory 1005, and further perform the following operations:

[0070] Obtaining the sampling frequency, human body fluctuation frequency and filtering order of the wireless receiver;

[0071] Calculate the cutoff frequency according to the sampling frequency and the human body fluctuation frequency;

[0072] Performing high-frequency filtering on the signal amplitude in the matrix signal based on the cutoff frequency and the filtering order to obtain a filtering amplitude;

[0073] The signal amplitude in the matrix signal is replaced by the filtering amplitude to obtain a noise reduction matrix signal.

[0074] Further, the processor 1001 may call the wireless signal display program stored in the memory 1005, and further perform the following operations:

[0075] Input the noise reduction matrix signal as a sample set into a principal component analysis algorithm, and perform centralization processing on each spatial sample point in the sample set;

[0076] Calculating the covariance matrix of the spatial sample points, and decomposing the covariance matrix to obtain the eigenvalue corresponding to each of the spatial sample points and the eigenvector corresponding to each of the spatial sample points;

[0077] Determining a minimum dimension reduction dimension according to a preset reconstruction threshold and the eigenvalue;

[0078] The eigenvalues ​​are arranged in descending order from large to small, and the eigenvectors corresponding to the eigenvalues ​​with the smallest dimensionality reduction dimension are selected to form a dimensionality reduction matrix signal.

[0079] Furthermore, the sample set , the spatial sample points after centralization are , x i is a spatial sample point in the noise reduction matrix signal;

[0080] The minimum dimension reduction pass Calculated, where d is the dimension of the sample set, λ i is the eigenvalue, and t is the preset reconstruction threshold.

[0081] Based on the above hardware structure, an embodiment of a wireless signal display method of the present invention is proposed.

[0082] The present invention provides a wireless signal display method.

[0083] Reference Figure 2 , Figure 2 FIG. 4 is a flow chart of a first embodiment of a wireless signal display method according to the present invention.

[0084] In an embodiment of the present invention, the wireless signal display method is applied to a wireless signal display device, and the method includes:

[0085] Step S10, analyzing the wireless signal to obtain a signal amplitude matrix;

[0086] In this embodiment, in order to improve the visibility of wireless signals and improve the intuitive expression ability of wireless signals, the wireless signal display device analyzes the wireless signals to obtain a signal amplitude matrix, wherein the signal amplitude matrix is ​​a matrix formed by extracting the amplitude of the wireless signals.

[0087] Step S10 analyzes the wireless signal to obtain a signal amplitude matrix, which may include:

[0088] Step a: receiving a wireless signal from a wireless router based on a wireless receiver.

[0089] In this embodiment, before the wireless signal display device analyzes the wireless signal, it determines the number of human bodies based on the wireless signals related to human activity. A wireless router is set up in the human activity area. The wireless router is used to send wireless signals. After the wireless signals pass through the human bodies active in the space, they are received by the wireless receiver. The wireless signal display device receives the wireless signals sent by the wireless router based on the wireless receiver.

[0090] Step S20, performing data conversion on the signal amplitude matrix to obtain a conversion amplitude matrix;

[0091] In this embodiment, after obtaining the signal amplitude matrix, the wireless signal display device performs data conversion on the signal amplitude matrix, that is, converts the amplitudes in the signal amplitude matrix into pixel values ​​to obtain a conversion amplitude matrix.

[0092] Step S20 performs data conversion on the signal amplitude matrix to obtain a conversion amplitude matrix, which may include:

[0093] Step b1, performing pixel conversion on each amplitude in the signal amplitude matrix to obtain a pixel value corresponding to each amplitude;

[0094] In this embodiment, after obtaining the signal amplitude matrix, the wireless signal display device performs pixel conversion on each amplitude in the signal amplitude matrix to obtain a pixel value corresponding to each amplitude.

[0095] After obtaining the signal amplitude matrix, the signal amplitude matrix is ​​selected as the data to be converted, the amplitude in the signal amplitude matrix is ​​normalized to between [0,1], and then multiplied by 255 to change its range to [0,255], and the pixel value corresponding to each amplitude is obtained; the amplitude in the matrix is ​​made to correspond to the color value.

[0096] Step b2, combining the pixel values ​​corresponding to each of the amplitudes according to the position of each amplitude in the signal amplitude matrix to obtain a conversion amplitude matrix.

[0097] In this embodiment, after obtaining the pixel value corresponding to each amplitude, the wireless signal display device combines the pixel values ​​corresponding to each amplitude according to the position of each amplitude in the signal amplitude matrix to obtain a conversion amplitude matrix.

[0098] Step S30, displaying the conversion amplitude matrix in a graphical form to obtain a wireless signal image.

[0099] In this embodiment, after obtaining the conversion amplitude matrix, the wireless signal display device displays the conversion amplitude matrix in a graphical manner to obtain a wireless signal image.

[0100] Step S30 displays the conversion amplitude matrix in a graphical form to obtain a wireless signal image, which may include:

[0101] Step c1, converting each pixel value in the conversion amplitude matrix into a pixel point;

[0102] In this embodiment, after obtaining the conversion amplitude matrix, the wireless signal display device converts each pixel value in the conversion amplitude matrix into a corresponding pixel point.

[0103] Step c2, arranging and displaying the pixel points in sequence with the time in the conversion amplitude matrix as the x-axis and the channel in the conversion amplitude matrix as the y-axis to form a wireless signal image, wherein the pixel points correspond to the pixel values ​​one by one.

[0104] In this embodiment, after each pixel value in the conversion amplitude matrix of the wireless signal display device is converted into a pixel point, the pixel points are arranged and displayed in sequence with the time in the conversion amplitude matrix as the x-axis and the channel c in the conversion amplitude matrix as the y-axis, and the amplitude in the conversion amplitude matrix is ​​converted into a wireless signal image. The channel is a 3*30 subcarrier channel. Among them, the pixel points correspond to the pixel values ​​one by one. That is, after obtaining the conversion amplitude matrix, the wireless signal display device converts each of the pixel values ​​in the conversion amplitude matrix into a pixel point, and displays the pixel points in an image according to the position of the pixel value corresponding to the pixel point in the conversion amplitude matrix to form a wireless signal image.

[0105] In this embodiment, the wireless signal is analyzed through the above scheme to obtain a signal amplitude matrix; the signal amplitude matrix is ​​converted to obtain a conversion amplitude matrix; the conversion amplitude matrix is ​​displayed graphically to obtain a wireless signal image. Thus, the visibility of the wireless signal is improved and the intuitive expression ability of the wireless signal is improved.

[0106] Further, refer to Figure 3 , Figure 3 This is a flow chart of the second embodiment of the wireless signal display method of the present invention. Figure 2 In the embodiment shown, step S10 analyzes the wireless signal to obtain a signal amplitude matrix, which may include:

[0107] Step S11, analyzing the wireless signal based on a channel state analysis program to obtain a matrix signal;

[0108] In this embodiment, after receiving the wireless signal, the wireless signal display device analyzes the wireless signal according to the channel state analysis program to obtain a matrix signal. Taking one of the data as an example, the collected original signal is in dat format. After the channel state analysis program, the wireless signal is converted into a four-dimensional matrix signal. The matrix signal is a four-dimensional matrix of 3*3*30*n, where the first "3" represents the number of transmitting antennas, the second "3" represents the number of receiving lines, "30" represents 30 subcarriers on each channel, and n represents that the current data packet has n data, and each data is a 3*3*30-dimensional matrix.

[0109] Step S12, performing high-frequency filtering on the matrix signal based on a Butterworth filter program to obtain a processed denoised matrix signal;

[0110] In this embodiment, after obtaining the matrix signal, the wireless signal display device performs high-frequency filtering on the matrix signal based on the Butterworth filter program to obtain a processed noise-reduced matrix signal. In practical applications, due to the influence of environmental and equipment noise, these noises are mainly high-frequency signals, which makes the extracted CSI data very uneven and difficult to extract effective features. Therefore, it is necessary to first perform denoising on the CSI data. Through analysis, it is known that the impact of human activities on the link is mostly composed of low-frequency signals in the spectrum. However, the original CSI data summary contains a large amount of high-frequency noise. In order to prevent such a weak low-frequency signal of the human body from being overwhelmed by a large amount of high-frequency noise, it is necessary to use a filter to filter out these high-frequency noises in order to extract signals related to the number of people from the CSI data.

[0111] Step S12 performs high-frequency filtering on the matrix signal based on a Butterworth filter program to obtain a processed denoised matrix signal, which may include:

[0112] Step d1, obtaining the sampling frequency, human body fluctuation frequency and filter order of the wireless receiver;

[0113] In this embodiment, after acquiring the matrix signal, the wireless signal display device acquires the sampling frequency, human body fluctuation frequency and filtering order of the wireless receiver.

[0114] Step d2, calculating the cutoff frequency according to the sampling frequency and the human body fluctuation frequency;.

[0115] In this embodiment, after obtaining the sampling frequency of the wireless receiver and the human body fluctuation frequency, the wireless signal display device calculates the cutoff frequency according to the sampling frequency and the human body fluctuation frequency. ,in, f c is the human body vibration frequency, f s is the sampling frequency of the wireless receiver.

[0116] Step d3, performing high-frequency filtering on the signal amplitude in the matrix signal based on the cutoff frequency and the filtering order to obtain a filtering amplitude.

[0117] In this embodiment, after obtaining the cutoff frequency and the filter order, the wireless signal display device performs high-frequency filtering on the signal amplitude in the matrix signal based on the cutoff frequency and the filter order to obtain the filter amplitude. According to actual needs and computational complexity, the filter order is set to 9, that is, N=9. The low-pass filtering method of the Butterworth filter program requires the filter order N and the cutoff frequency representing the amplitude at -3dB passband. w cTwo parameters, the filter amplitude square function can be expressed as .

[0118] Step d4, replacing the signal amplitude in the matrix signal with the filtered amplitude to obtain a noise reduction matrix signal.

[0119] In this embodiment, after obtaining the filtering amplitude, the wireless signal display device replaces the signal amplitude in the matrix signal with the filtering amplitude to obtain a noise reduction matrix signal.

[0120] Step S13, performing a dimension reduction operation on the noise reduction matrix signal based on a principal component analysis algorithm to obtain a dimension reduction matrix signal;

[0121] In this embodiment, after obtaining the noise reduction matrix signal, the wireless signal display device performs a dimension reduction operation on the noise reduction matrix signal according to a principal component analysis algorithm to obtain a dimension reduction matrix signal.

[0122] Step S13 performs a dimension reduction operation on the denoised matrix signal based on a principal component analysis algorithm to obtain a dimension reduction matrix signal, which may include:

[0123] Step e1, inputting the noise reduction matrix signal as a sample set into a principal component analysis algorithm, and performing centralization processing on each spatial sample point in the sample set;

[0124] In this embodiment, after obtaining the noise reduction matrix signal, the wireless signal display device inputs the noise reduction matrix signal as a sample set into the principal component analysis algorithm, and performs centralization processing on each spatial sample point in the sample set. The principal component analysis algorithm (PCA) is a technology for analyzing and simplifying data sets. , which is the noise reduction matrix signal ; The spatial sample points after centralization are , x i is a spatial sample point in the denoised matrix signal.

[0125] Step e2, calculating the covariance matrix of the spatial sample points, and decomposing the covariance matrix to obtain the eigenvalue corresponding to each of the spatial sample points and the eigenvector corresponding to each of the spatial sample points;

[0126] In this embodiment, after the wireless signal display device performs centralization processing on the spatial sample points, it calculates the sample covariance matrix ZZ T , and decompose the covariance matrix to find the eigenvalue corresponding to each spatial sample point λ iAnd the feature vector corresponding to each of the spatial sample points w i . Among them, each eigenvalue corresponds to each eigenvector one by one.

[0127] Step e3, determining the minimum dimension reduction dimension according to a preset reconstruction threshold and the eigenvalue;

[0128] In this embodiment, after determining the eigenvalue corresponding to each of the spatial sample points and the eigenvector corresponding to each of the spatial sample points, the wireless signal display device reconstructs the eigenvalue according to the preset reconstruction threshold t and the eigenvalue. λ i , to select The minimum dimension reduction required d is the dimension of the sample set, which is also the dimension of the original sample set space. That is, according to the preset reconstruction threshold t and the eigenvalue λ i , to select The dimension of the projection space in which this is established.

[0129] Step e4, arranging the eigenvalues ​​in descending order from large to small, selecting the eigenvectors corresponding to the eigenvalues ​​with the smallest dimensionality reduction dimension, and forming a dimensionality reduction matrix signal.

[0130] In this embodiment, after determining the minimum dimension reduction, the wireless signal display device arranges the eigenvalues ​​in descending order from large to small, selects the eigenvectors corresponding to the number of eigenvalues ​​of the minimum dimension reduction, and forms a dimension reduction matrix signal. λ i , select the minimum dimension before dimensionality reduction The eigenvectors corresponding to the eigenvalues ​​constitute the projection matrix (dimensionality reduction matrix data) .

[0131] For example, assuming that the original space sample points are x i ,in i =1,2,3...n. Assume that the mean of the spatial sample points is , then the sample points after centering are: ; Assume that the new coordinate system is projected w 1 ,w 2 ,...,w d}, w i are the standard orthonormal basis vectors, , .assumed d represents the original dimension, represents the dimension after dimensionality reduction, then represents the projection of the sample point in the low-dimensional coordinate system, where Representative sample points The coordinates of the jth dimension in the low-dimensional space. Then Represents sample points Projection into low-dimensional space, where w ={ w 1 ,w 2 ,...,w d}. The calculated variance of the sample points after projection is , then we can use the formula , , represents the optimization objective function: After transformation, the formula ; The formula Substitution It can be found that the key problem is converted to finding the maximum eigenvalue, and each dimensional basis vector of the projection space w is the covariance matrix ZZ T The feature vector of .

[0132] Step S14, extracting the amplitude in the dimension reduction matrix signal to form a signal amplitude matrix.

[0133] In this embodiment, after obtaining the dimension reduction matrix signal, the wireless signal display device extracts the amplitude in the dimension reduction matrix signal to form a signal amplitude matrix. ,in H t is the wireless signal vector obtained at time t, C is the total number of channels in the wireless signal, T is the transposition operation, is the wireless signal of channel c at time t;

[0134] in, ,in, is the amplitude of channel c at time t, is the phase of channel c at time t; j is the dimension of the reduced matrix signal

[0135] The signal amplitude matrix is ,in, .

[0136] True Phase , is the measured phase, where f c is the frequency of channel c, represents the unknown time lag between the transmitter and the receiver, represents the phase shift due to signal propagation, βIndicates the unknown initial phase of the transmitted packet, represents the measurement noise;

[0137] To ensure that the phase measurement does not vary and β Change, define calibration parameters ;

[0138] Define calibration parameters ;

[0139] Phase after calibration ;

[0140] After calibration and preprocessing, the preprocessed phase measurement matrix can be obtained ;in, .

[0141] As an implementation method, the signal amplitude matrix , and the phase measurement matrix It is a matrix form of a radio image, with the time of the signal amplitude matrix as the x-axis and the channel c of the signal amplitude matrix as the y-axis, thereby converting the amplitude measurement value into a radio image.

[0142] Through the above scheme, this embodiment analyzes the wireless signal based on the channel state analysis program to obtain a matrix signal; performs high-frequency filtering on the matrix signal based on the Butterworth filter program to obtain a processed denoised matrix signal; performs dimensionality reduction operation on the denoised matrix signal based on the principal component analysis algorithm to obtain a reduced-dimensional matrix signal; extracts the amplitude in the reduced-dimensional matrix signal to form a signal amplitude matrix. In this way, high-frequency noise higher than the frequency of human activities in the wireless signal is removed, and the influence of environmental and equipment noise is eliminated.

[0143] The invention also provides a wireless signal display device.

[0144] The wireless signal display device of the present invention comprises: a memory, a processor and a wireless signal display program stored in the memory and executable on the processor. When the wireless signal display program is executed by the processor, the steps of the wireless signal display method described above are implemented.

[0145] Among them, the method implemented when the wireless signal display program running on the processor is executed can refer to the various embodiments of the wireless signal display method of the present invention, and will not be repeated here.

[0146] The present invention also provides a computer-readable storage medium.

[0147] A wireless signal display program is stored on the computer-readable storage medium of the present invention, and the wireless signal display program implements the steps of the wireless signal display method described above when executed by a processor.

[0148] Among them, the method implemented when the wireless signal display program running on the processor is executed can refer to the various embodiments of the wireless signal display method of the present invention, and will not be repeated here.

[0149] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0150] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0151] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0152] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A wireless signal display method, characterized in that: The wireless signal display method comprises the following steps: Analyze the wireless signal to obtain the signal amplitude matrix; Performing data conversion on the signal amplitude matrix to obtain a conversion amplitude matrix; Displaying the conversion amplitude matrix graphically to obtain a wireless signal image; The step of performing data conversion on the signal amplitude matrix to obtain a conversion amplitude matrix comprises: Perform pixel conversion on each amplitude in the signal amplitude matrix to obtain a pixel value corresponding to each amplitude; Combining the pixel values ​​corresponding to each of the amplitudes according to the position of each amplitude in the signal amplitude matrix to obtain a conversion amplitude matrix; The step of displaying the conversion amplitude matrix in a graphical form to obtain a wireless signal image comprises: Convert each pixel value in the conversion amplitude matrix into a pixel point; The pixel points are arranged and displayed in sequence with the time in the conversion amplitude matrix as the x-axis and the channel in the conversion amplitude matrix as the y-axis to form a wireless signal image, wherein the pixel points correspond to the pixel values ​​one by one.

2. The method according to claim 1, characterized in that: The step of analyzing the wireless signal to obtain a signal amplitude matrix includes: Analyze the wireless signal based on a channel state analysis program to obtain a matrix signal; Performing high-frequency filtering on the matrix signal based on a Butterworth filtering program to obtain a processed denoised matrix signal; Performing a dimensionality reduction operation on the noise reduction matrix signal based on a principal component analysis algorithm to obtain a dimensionality reduction matrix signal; The amplitude in the dimension reduction matrix signal is extracted to form a signal amplitude matrix.

3. The method according to claim 2, characterized in that The dimension reduction matrix signal ,in H t is the wireless signal vector obtained at time t, c is the total number of channels in the wireless signal, T is the transposition operation, is the wireless signal of channel c at time t; in, ,in, is the amplitude of channel c at time t, is the phase of channel c at time t; The signal amplitude matrix is ,in, .

4. The method according to claim 2, characterized in that: The step of performing high-frequency filtering on the matrix signal based on a Butterworth filtering program to obtain a processed denoised matrix signal comprises: Obtain the sampling frequency, human body fluctuation frequency and filter order of the wireless receiver; Calculate the cutoff frequency according to the sampling frequency and the human body fluctuation frequency; Performing high-frequency filtering on the signal amplitude in the matrix signal based on the cutoff frequency and the filtering order to obtain a filtering amplitude; The signal amplitude in the matrix signal is replaced by the filtering amplitude to obtain a noise reduction matrix signal.

5. The method according to claim 2, characterized in that: The performing a dimensionality reduction operation on the denoised matrix signal based on a principal component analysis algorithm to obtain a dimensionality reduction matrix signal comprises: Input the noise reduction matrix signal as a sample set into a principal component analysis algorithm, and perform centralization processing on each spatial sample point in the sample set; Calculating the covariance matrix of the spatial sample points, and decomposing the covariance matrix to obtain the eigenvalue corresponding to each of the spatial sample points and the eigenvector corresponding to each of the spatial sample points; Determining a minimum dimension reduction dimension according to a preset reconstruction threshold and the eigenvalue; The eigenvalues ​​are arranged in descending order from large to small, and the eigenvectors corresponding to the eigenvalues ​​with the smallest dimensionality reduction dimension are selected to form a dimensionality reduction matrix signal.

6. The method according to claim 5, characterized in that: The sample set , the spatial sample points after centralization are , x i is a spatial sample point in the noise reduction matrix signal; The minimum dimension reduction pass Calculated, where d is the dimension of the sample set, λ i is the eigenvalue, and t is the preset reconstruction threshold.

7. A wireless signal display device, characterized in that: The wireless signal display device includes: a memory, a processor, and a wireless signal display program stored in the memory and running on the processor. When the wireless signal display program is executed by the processor, the steps of the wireless signal display method according to any one of claims 1 to 6 are implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a wireless signal display program, and when the wireless signal display program is executed by a processor, the steps of the wireless signal display method according to any one of claims 1 to 6 are implemented.

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