Wi-Fi signal-based sensing method and device, electronic device, and storage medium

Abstract

The present application provides a Wi-Fi signal-based perception method and apparatus, electronic device, and storage medium. The method includes: performing a cleansing transform on the frequency-domain channel response of each antenna array element of each transceiver to obtain a corresponding cleaned channel impulse response; for each transceiver, selecting any cleaned channel impulse response from multiple cleaned channel impulse responses corresponding to the transceiver as the target channel impulse response, and conjugate-multiplying the other cleaned channel impulse responses with the target channel impulse response to obtain multiple products; constructing a specified vector based on the multiple products and determining the covariance matrix corresponding to the specified vector; performing eigenvalue decomposition on the covariance matrix to obtain the angle of arrival of the passive target relative to the transceiver; and determining the perception result of the passive target based on the angles of arrival corresponding to at least two transceivers. The present application solution can parse the angle of arrival from the Wi-Fi signal and accurately perceive the passive target based on the at least two angles of arrival.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a Wi-Fi signal sensing method and device, an electronic device, and a computer-readable storage medium. Background Art

[0002] A key development direction for next-generation wireless communication technology is the integration of communication, perception, and radar. Future Wi-Fi signals will not only transmit data but also sense passive targets (people or other objects without terminal devices). For example, they can leverage the channel estimation information from the Wi-Fi signal's long training sequence (LTF) to locate, track, and identify passive targets.

[0003] Using wireless signals to perceive the activities of passive targets can play an important role in smart home scenarios. Summary of the Invention

[0004] The present invention provides a method and apparatus, an electronic device, and a storage medium for detecting a Wi-Fi signal. The method is used to parse the angle of arrival (AoA) from Wi-Fi signals received and transmitted by at least two transceivers, and accurately detect passive targets based on the at least two AoA angles.

[0005] In one aspect, the present application provides a Wi-Fi signal-based sensing method, which is applied to a Wi-Fi transceiver system. The Wi-Fi transceiver system includes at least two transceivers, each transceiver includes at least three antenna elements, two of the at least three antenna elements have a transmitting function, and each of the at least three antenna elements has a receiving function. The method includes:

[0006] Performing a cleaning transformation on the frequency domain channel response of each antenna array element of each transceiver to obtain a corresponding cleaned channel impulse response;

[0007] For each transceiver, selecting any cleaned channel impulse response from a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and conjugate-multiplying the target channel impulse response with the other cleaned channel impulse responses to obtain a plurality of products;

[0008] constructing a specified vector based on the multiple products, and determining a covariance matrix corresponding to the specified vector;

[0009] performing eigenvalue decomposition on the covariance matrix to obtain an arrival angle of the passive target relative to the transceiver;

[0010] A perception result of the passive target is determined based on the arrival angles corresponding to the at least two transceivers.

[0011] In one embodiment, determining the perception result of the passive target based on the arrival angles corresponding to the at least two transceivers includes:

[0012] The target position of the passive target in the environmental coordinate system is determined based on the arrival angle of the passive target relative to at least two transceivers and the position information of each transceiver in the environmental coordinate system.

[0013] In one embodiment, determining the perception result of the passive target based on the arrival angles corresponding to the at least two transceivers includes:

[0014] constructing an angle-of-arrival-time spectrum based on the angles of arrival corresponding to the at least two transceivers at a plurality of observation moments;

[0015] A sub-spectrum image within a specified time period is cut from the arrival angle-time spectrum, and the sub-spectrum image is input into a trained behavior recognition model to obtain a behavior recognition result.

[0016] In one embodiment, before selecting, for each transceiver, any cleaned channel impulse response from a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and conjugate-multiplying the other cleaned channel impulse responses with the target channel impulse response to obtain a plurality of products, the method further includes:

[0017] For each transceiver, interpolation processing is performed based on at least two cleaned channel impulse responses corresponding to the transceiver to expand the number of cleaned channel impulse responses corresponding to the transceiver.

[0018] In one embodiment, performing a cleaning transformation on the frequency domain channel response of each antenna array element of each transceiver to obtain a corresponding cleaned channel impulse response includes:

[0019] determining, for each antenna array element of each transceiver, a frequency domain channel response corresponding to a power delay profile;

[0020] Searching for a sampling point with the maximum power in the power delay spectrum as a centroid sampling point, and intercepting and splicing several sampling points before the centroid sampling point to the back end of the power delay spectrum to obtain a target power delay spectrum;

[0021] A target sampling point is selected from the target power delay profile according to a front window of a preset first length and a rear window of a preset second length, and other sampling points other than the target sampling point are used as noise sampling points; wherein the front window is placed at the front end of the target power delay profile, and the rear window is placed at the rear end of the target power delay profile;

[0022] Determining a noise threshold power based on the power of multiple noise sampling points;

[0023] Filtering out target sampling points whose power exceeds the noise threshold power as designated sampling points;

[0024] Circularly connecting the front and rear ends of the target power delay profile, and determining whether the distance between the designated sampling point closest to the front end in the rear window and the centroid sampling point at the junction exceeds a preset sampling point number threshold;

[0025] If so, determine the designated sampling point closest to the front end in the rear window as the LOS sampling point, and the remaining designated sampling points as the NLOS sampling points;

[0026] In the channel impulse response corresponding to the frequency domain channel response, time domain channel estimation values ​​of sampling points other than the NLOS sampling point are set to zero to obtain a cleaned channel impulse response.

[0027] In one embodiment, the method further comprises:

[0028] If not, the centroid sampling point is determined to be the LOS sampling point, and the other designated sampling points are determined to be the NLOS sampling points;

[0029] Return to the step of setting the time domain channel estimation values ​​of the sampling points other than the NLOS sampling points in the channel impulse response corresponding to the frequency domain channel response to zero to obtain a cleaned channel impulse response.

[0030] In one embodiment, determining the noise threshold power based on the powers of the multiple noise sampling points includes:

[0031] Calculating an average of the powers of the multiple noise sampling points as a candidate noise threshold power;

[0032] Smoothing is performed on candidate noise threshold powers corresponding to a plurality of consecutive symbols transmitted by the Wi-Fi signal to obtain the noise threshold power.

[0033] On the other hand, the present application provides a Wi-Fi signal-based sensing device, which is applied to a Wi-Fi transceiver system, wherein the Wi-Fi transceiver system includes at least two transceivers, each transceiver includes at least three antenna array elements, two of the at least three antenna array elements have a transmitting function, and each of the at least three antenna array elements has a receiving function. The device includes:

[0034] A cleaning module, configured to perform a cleaning transformation on the frequency domain channel response of each antenna array element of each transceiver to obtain a corresponding cleaned channel impulse response;

[0035] a multiplication module configured to select, for each transceiver, any cleaned channel impulse response from a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and conjugate-multiply the other cleaned channel impulse responses by the target channel impulse response to obtain a plurality of products;

[0036] a determination module, configured to construct a specified vector based on the multiple products, and determine a covariance matrix corresponding to the specified vector;

[0037] a decomposition module, configured to perform eigenvalue decomposition on the covariance matrix to obtain an arrival angle of the passive target relative to the transceiver;

[0038] A perception module is used to determine a perception result of the passive target based on the arrival angles corresponding to the at least two transceivers.

[0039] Furthermore, the present application provides an electronic device, comprising:

[0040] processor;

[0041] a memory for storing processor-executable instructions;

[0042] The processor is configured to execute the above-mentioned Wi-Fi signal-based perception method.

[0043] In addition, the present application provides a computer-readable storage medium, which stores a computer program. The computer program can be executed by a processor to implement the above-mentioned Wi-Fi signal-based perception method.

[0044] The present application solution cleans and transforms the frequency domain channel response of each antenna array element of each transceiver in the Wi-Fi transceiver system, removing data from the noise channel and the LOS channel. The cleaned channel impulse response can then be used to determine the arrival angle of a passive target relative to the transceiver, thereby accurately sensing the passive target based on the arrival angles corresponding to at least two transceivers. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments of the present application.

[0046] Figure 1 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application;

[0047] Figure 2 A flowchart of a Wi-Fi signal sensing method according to an embodiment of the present application is provided.

[0048] Figure 3A schematic diagram of a Wi-Fi signal receiving and transmitting method of a transceiver provided in one embodiment of the present application;

[0049] Figure 4 A schematic diagram of an application scenario of a Wi-Fi signal sensing method according to an embodiment of the present application;

[0050] Figure 5 Provided for an embodiment of this application Figure 2 Detailed flow diagram of step 210;

[0051] Figure 6 A schematic diagram of a power delay spectrum provided in one embodiment of the present application;

[0052] Figure 7 A schematic diagram of a target power delay profile provided in one embodiment of the present application;

[0053] Figure 8 A schematic diagram of sampling point screening provided in one embodiment of the present application;

[0054] Figure 9 A block diagram of a Wi-Fi signal-based sensing device provided in accordance with an embodiment of the present application. DETAILED DESCRIPTION

[0055] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0056] Similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0057] like Figure 1 As shown, this embodiment provides an electronic device 1, including: at least one processor 11 and a memory 12, Figure 1 In the figure, a processor 11 is used as an example. The processor 11 and the memory 12 are connected via a bus 10. The memory 12 stores instructions that can be executed by the processor 11. The instructions are executed by the processor 11 so that the electronic device 1 can perform all or part of the process of the method in the following embodiment. In one embodiment, the electronic device 1 can be a transceiver in a Wi-Fi transceiver system, or a computing device connected to the Wi-Fi transceiver system, for executing the perception method based on Wi-Fi signals. The following describes the solution with the electronic device as the execution subject.

[0058] The memory 12 can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0059] The present application also provides a computer-readable storage medium, which stores a computer program. The computer program can be executed by the processor 11 to complete the Wi-Fi signal-based perception method provided in the present application.

[0060] See also Figure 2 , is a flow chart of a Wi-Fi signal sensing method according to an embodiment of the present application, such as Figure 2 As shown, the method may include the following steps 210 to 250.

[0061] Step 210: Perform a cleaning transformation on the frequency domain channel response of each antenna array element of each transceiver to obtain a corresponding cleaned channel impulse response.

[0062] The solution of the present application is applied to a Wi-Fi transceiver system, which includes at least two transceivers, each of which includes at least three antenna elements. The arrangement of the at least three antenna elements of each transceiver can be a one-dimensional uniform linear array (ULA), a square antenna array (UPA), or a two-dimensional array or other array form. Two antenna elements in the at least three antenna arrays of each transceiver have a transmitting function, and each antenna element has a receiving function. In one embodiment, the interval between adjacent antenna elements is half a wavelength. In one embodiment, if the transceiver includes three antenna elements, the three antenna elements can be a one-dimensional uniform linear array, and the first and last two antenna elements of the three antenna elements have a transmitting function. In one embodiment, if the transceiver includes four antenna elements, and the four antenna elements can be a one-dimensional uniform linear array, then two antenna elements (the first and last two, or the first and third, or the second and fourth) of the four antenna elements have a transmitting function. In one embodiment, if the transceiver includes four antenna array elements, and the four antenna array elements form a T-shaped two-dimensional array, then two non-adjacent antenna array elements among the four antenna array elements have a transmitting function.

[0063] See also Figure 3 , is a schematic diagram of a Wi-Fi signal receiving and transmitting method of a transceiver provided in an embodiment of the present application, such as Figure 3 As shown, the transceiver includes three antenna elements, Ant1, Ant2, and Ant4, and one virtual antenna element, Virtual Ant3. The transceiver can be considered to have four antenna elements, with the first antenna element, Ant1, and the fourth antenna element, Ant4, transmitting Wi-Fi signals, and each antenna element receiving Wi-Fi signals. In this case, Ant1 can transmit Wi-Fi signals to Ant2 and Ant4, respectively. Ant2 can receive RX12 from Ant1, and Ant4 can receive RX14 from Ant1. Meanwhile, Virtual Ant3 can be considered to receive RX13 from Ant1 (RX13 does not actually exist). Ant4 can transmit Wi-Fi signals to Ant1 and Ant2, respectively. Ant1 can receive RX41 from Ant4, and Ant2 can receive RX42 from Ant4. Meanwhile, Virtual Ant3 can be considered to receive RX43 from Ant4 (RX43 does not actually exist).

[0064] The purpose of setting up virtual antenna array elements is to reduce hardware costs and resources required in subsequent calculations. In actual applications, virtual antenna array elements may not be set up. Figure 3For example, you can replace the virtual antenna element with a hardware antenna element, or place the last antenna element in the place of the virtual antenna element. The number of antenna elements in different receivers can be the same or different.

[0065] For each antenna array element of the transceiver, the electronic device can determine the frequency domain channel response (CFR) in the frequency domain from the Wi-Fi signal received by the antenna array element through a channel estimation algorithm. According to the difference between the transmitting end and the receiving end of the Wi-Fi signal, the corresponding frequency domain channel response can be determined for different Wi-Fi signals. For example, Figure 3 For example, the corresponding frequency domain channel responses can be determined for RX12, RX14, RX41, and RX42 respectively. In one embodiment, the electronic device can perform windowing processing on the frequency domain channel response using a window function (such as a Hamming window) to concentrate the spectrum leakage and facilitate subsequent processing.

[0066] For each frequency-domain channel response, the electronic device can clean it, removing noise and LOS (Line of Sight) channel data, and transforming it into the corresponding cleaned channel impulse response (CIR). The cleaned channel impulse response only contains NLOS (Not Line of Sight) channel data.

[0067] When a passive target moves in an indoor scene, the change in the space it occupies will affect the indoor Wi-Fi signal, causing changes in the multipath channel. At this time, the frequency domain channel response, which serves as the channel state information (CSI), changes accordingly. The multipath channels indicated by the frequency domain channel response include LOS channels, NLOS channels, and noise channels. Since indoor static objects remain motionless and the LOS channel data is not affected by passive targets, the NLOS channel data can represent the impact of the passive target's activities on the wireless channel. The cleaned channel impulse response can then characterize the passive target's activities.

[0068] In one embodiment, after cleaning and transforming hardware antenna array elements to obtain cleaned channel impulse responses, the electronic device can perform interpolation processing for each transceiver based on at least two cleaned channel impulse responses corresponding to the transceiver to obtain the cleaned channel impulse response of the transceiver's virtual antenna array element. This measure can expand the number of cleaned channel impulse responses corresponding to the transceiver, making subsequent passive target perception results more accurate.

[0069] For example, Figure 3For example, after obtaining the cleaned channel impulse response h of the signal received by Ant2 from Ant1 (rx12) , and the cleaned channel impulse response h of the signal received by Ant4 from Ant1 (rx14) Afterwards, you can (rx12) and h (rx14) Perform interpolation to obtain h (rx13) , which is the cleaned channel impulse response of the signal received by the virtual antenna array element Virtual Ant3 from Ant1.

[0070] After obtaining the cleaned channel impulse response h of the signal received by Ant1 and Ant4 (rx41) , and the cleaned channel impulse response h of the signal received by Ant2 from Ant4 (rx42) Afterwards, you can (rx41) and h (rx42) Perform interpolation to obtain h (rx43) , which is the cleaned channel impulse response of the signal received by the virtual antenna element Virtual Ant3 at Ant4.

[0071] Step 220: For each transceiver, select any cleaned channel impulse response from the multiple cleaned channel impulse responses corresponding to the transceiver as the target channel impulse response, and conjugate-multiply the other cleaned channel impulse responses with the target channel impulse response to obtain multiple products.

[0072] For multiple cleaned channel impulse responses corresponding to the transceiver, the electronic device can select one of them as the target channel impulse response. For example, to ensure that the directionality of the phase change does not change during the calculation process and facilitate subsequent calculations, the cleaned channel impulse response corresponding to the Wi-Fi signal transmitted from the first antenna element to the second antenna element can be selected as the target channel impulse response. Alternatively, the cleaned channel impulse response corresponding to the Wi-Fi signal transmitted from the last antenna element to the second-to-last antenna element can be selected as the target channel impulse response.

[0073] The electronic device can conjugate-multiply the other cleaned channel impulse responses of the transceiver with the target channel impulse response. Multiplying any cleaned channel impulse response with the target channel impulse response can produce a product. Thus, multiple products can be obtained. Here, the other cleaned channel impulse responses are channel impulse responses other than the target channel impulse response.

[0074] by Figure 3 For example, if the impulse response h of multiple cleaned channels is (rx12) 、h (rx13) 、h (rx14) 、h (rx41) 、h(rx42) 、h (rx43) In the (rx12) As the target channel impulse response, multiple products can be calculated using the following formulas (1) to (5):

[0075] h1=h (rx13) ×conj(h (rx12) ) (1)

[0076] h2=h (rx14) ×conj(h (rx12) ) (2)

[0077] h3=h (rx41) ×conj(h (rx12) ) (3)

[0078] h4=h (rx42) ×conj(h (rx12) ) (4)

[0079] h5=h (rx43) ×conj(h (rx12) ) (5)

[0080] Among them, h1, h2, h3, h4, and h5 are all products.

[0081] Step 230: construct a specified vector based on the multiple products, and determine the covariance matrix corresponding to the specified vector.

[0082] After obtaining multiple products, a CIR spatial autocorrelation column vector is constructed using the multiple products as a specified vector. Figure 3 For example, the specified vector can be expressed as X = [h1,h2,h3,h4,h5] T .

[0083] The electronic device can calculate the covariance matrix corresponding to the specified vector using the following formula (6):

[0084] R XX =E{XX CT} (6)

[0085] Among them, R XX is the covariance matrix; E is the identity matrix; X is the specified vector.

[0086] Step 240: Perform eigenvalue decomposition on the covariance matrix to obtain the arrival angle of the passive target relative to the transceiver.

[0087] Electronic devices can perform eigenvalue decomposition on the covariance matrix through methods such as the MUSIC (multiple signal classification algorithm), the ESPRIT (Estimation of Signal Parameters using Rotational Invariance Techniques) algorithm, and the compressed sensing algorithm to obtain the angle of arrival (AOA) of the passive target relative to the transceiver.

[0088] When performing eigenvalue decomposition on the covariance matrix, multiple angles of arrival may be obtained. In this case, the angle of arrival needs to be selected based on the application scenario. The specific selection method is described below.

[0089] By executing the aforementioned steps 210 to 240 for each transceiver, the arrival angle corresponding to each transceiver can be obtained.

[0090] Step 250: Determine a perception result of the passive target based on the arrival angles corresponding to at least two transceivers.

[0091] The electronic device can sense the state of the passive target based on the arrival angle of the passive target relative to at least two transceivers in the Wi-Fi transceiver system, thereby obtaining a sensing result. Here, the sensing content may include tracking and locating the passive target, or identifying the behavior of the passive target, or both tracking and locating the passive target and identifying its behavior.

[0092] Through the above measures, after cleaning and transforming the frequency domain channel response of each antenna array element of each transceiver in the Wi-Fi transceiver system and removing data from the noise channel and the Loss of Sight channel (LOS) channel, the arrival angle of the passive target relative to the transceiver can be determined based on the cleaned channel impulse response. This allows accurate perception of the passive target based on the arrival angles corresponding to at least two transceivers.

[0093] In one embodiment, if the sensing content includes tracking and locating a passive target, it is necessary to predetermine the position information of at least two transceivers in an environmental coordinate system. The position information of each transceiver can be determined based on the actual placement of the transceiver in the application environment. The environmental coordinate system is a coordinate system established in the application environment.

[0094] After determining the arrival angle of the passive target relative to at least two transceivers, the electronic device can determine the target position of the passive target in the environmental coordinate system based on the arrival angle of the passive target relative to at least two transceivers and the position information of each transceiver in the environmental coordinate system.

[0095] See also Figure 4 , which is a schematic diagram of an application scenario of a Wi-Fi signal sensing method according to an embodiment of the present application, such as Figure 4 As shown, in the plane environmental coordinate system, the positions of the two transceivers TRX1 and TRX2 have been determined, and the arrival angle of the passive target relative to TRX1 and the arrival angle relative to TRX2 are known. Then, the intersection position of the line connecting the passive target and the two transceivers is the target position.

[0096] Figure 4 In the embodiment, the Wi-Fi system includes two transceivers. In actual applications, the Wi-Fi system may include more transceivers, and the target position of the passive target may be determined in the same manner.

[0097] When a passive target moves within an application environment, its movement has the greatest impact on the wireless channel. For example, if a person is walking and waving, the whole-body movement involved in walking will have the greatest impact on the multipath transmission of the Wi-Fi signal. Therefore, when the sensing content includes tracking and positioning, if multiple angles of arrival are decomposed from the covariance matrix during step 240, the largest angle of arrival can be selected for tracking and positioning.

[0098] By means of the above measures, the passive target can be accurately located at each observation moment by means of the arrival angles of at least two transceivers.

[0099] In one embodiment, if the sensing content includes behavior recognition of a passive target, there are two cases: one in which the sensing content includes both tracking and positioning and behavior recognition; the other in which the sensing content includes only behavior recognition. The specific content of behavior recognition can be determined based on the needs of the application scenario. For example, behavior recognition can include identifying the hand movements of the passive target (person), such as waving, clapping, or raising hands; or behavior recognition can include identifying the health status of the passive target (person), such as heart rate, breathing, or falls.

[0100] In the first case, after decomposing multiple angles of arrival from the covariance matrix during step 240, the largest angle of arrival can be selected for tracking and positioning, and the second largest angle of arrival can be selected for behavior recognition. In the second case, after decomposing multiple angles of arrival from the covariance matrix during step 240, the largest angle of arrival can be selected for tracking and positioning.

[0101] The electronic device can construct an angle-of-arrival (AoA)-time spectrum based on the arrival angles corresponding to at least two transceivers at multiple observation times. The vertical axis of the AoA-time spectrum represents the arrival angles corresponding to the at least two transceivers, and the horizontal axis represents time. The interval between adjacent observation times can be configured as needed. For example, each data packet sent by a Wi-Fi signal corresponds to one observation time.

[0102] The electronic device can crop a sub-spectral image within a specified time period from the arrival angle-time spectrum. The specified time period can be configured as needed. For example, in an application scenario requiring real-time behavior recognition of passive targets, where the single behavior to be recognized takes less than two seconds to complete, the specified time period can be within the last two seconds.

[0103] After cropping the sub-spectral images generated within a specified time period, the electronic device can input the sub-spectral images into a trained behavior recognition model, which processes the sub-spectral images to obtain behavior recognition results. The behavior recognition model can be trained using any network model used for classification, such as CNN (Convolutional Neural Networks), TCN (Temporal Convolutional Network), or a hybrid model of CNN and RNN (Recurrent Neural Networks).

[0104] Through the above measures, the behavior of passive targets can be identified based on the arrival angles corresponding to at least two transceivers at multiple observation times with the help of a machine learning model.

[0105] In one embodiment, see Figure 5 , provided in one embodiment of the present application Figure 2 The detailed flow chart of step 210 is as follows: Figure 5 As shown, when executing step 210, steps 211 to 218 may be specifically executed.

[0106] Step 211: For the frequency domain channel response of each antenna array element of each transceiver, determine a corresponding power delay profile for the frequency domain channel response.

[0107] At each observation moment, after obtaining the frequency domain channel response of each antenna array element of each transceiver, the electronic device can perform an inverse Fourier transform (IFFT) on the frequency domain channel response to obtain a channel impulse response. After obtaining the channel impulse response, the electronic device can calculate a power delay profile (PDP) based on the channel impulse response. In one embodiment, the same symbol of the Wi-Fi signal has multiple frequency domain channel responses on a transceiver, and multiple power delay profiles can be calculated. In this case, the average of the multiple power delay profiles can be calculated as the power delay profile of the symbol in subsequent processing.

[0108] Step 212: Search for the sampling point with the maximum power in the power delay spectrum as the centroid sampling point, and intercept and splice several sampling points before the centroid sampling point to the back end of the power delay spectrum to obtain the target power delay spectrum.

[0109] The electronic device can search for the sampling point with the highest power in the power delay profile and use this sampling point as the centroid sampling point. After determining the centroid sampling point, the electronic device can intercept several sampling points before the centroid sampling point and splice these intercepted sampling points to the end of the power delay profile to obtain the target power delay profile.

[0110] See also Figure 6 , is a schematic diagram of a power delay spectrum provided in an embodiment of the present application, such as Figure 6 As shown, the power delay spectrum includes 256 sampling points, and the rectangle in the lower left corner is the sampling point before the centroid sampling point.

[0111] See also Figure 7 , is a schematic diagram of a target power delay spectrum provided in an embodiment of the present application, such as Figure 7 As shown, Figure 6 The sampling points before the center-of-gravity sampling point are intercepted and spliced ​​at the back end of the power delay spectrum to obtain the target power delay spectrum.

[0112] Step 213: Filter out target sampling points in the target power delay profile based on a front window of a preset first length and a rear window of a preset second length, and use other sampling points other than the target sampling points as noise sampling points; wherein the front window is placed at the front end of the target power delay profile, and the rear window is placed at the rear end of the target power delay profile.

[0113] The first length can be obtained by multiplying the length of a cyclic prefix (CP) by a first coefficient, where the first coefficient is greater than one, and illustratively, the first coefficient is 2. The second length can be obtained by multiplying the length of the cyclic prefix by a second coefficient, where the second coefficient is less than one, and illustratively, the second coefficient is 0.5.

[0114] The electronic device can place the front window at the front end of the target power delay profile and the rear window at the rear end of the target power delay profile, and use the sampling points within the front and rear windows as target sampling points. Sampling points other than the target sampling points can be determined as noise sampling points.

[0115] See also Figure 8 , is a schematic diagram of sampling point screening provided by an embodiment of the present application, such as Figure 8 As shown, multiple sampling points in the front window are target sampling points, multiple sampling points in the rear window are target sampling points, and multiple sampling points between the front window and the rear window are noise sampling points.

[0116] Step 214: Determine a noise threshold power based on the powers of the multiple noise sampling points.

[0117] The electronic device may calculate an average value of powers of multiple noise sampling points and use the noise average value as the noise threshold power.

[0118] In one embodiment, when determining the noise threshold power, the average power of multiple noise sampling points can be calculated as a candidate noise threshold power. For multiple consecutive symbols transmitted by the Wi-Fi signal, a candidate noise threshold power corresponding to each symbol can be calculated. The multiple candidate noise threshold powers can then be smoothed to obtain the noise threshold power. The number of symbols used for smoothing can be configured as needed.

[0119] For example, the smoothing process can be performed by the following formula (7):

[0120] m l =α noise *n l +(1-α noise )*n l-1 (7)

[0121] Among them, n l represents the candidate noise threshold power corresponding to the lth symbol in the data packet; α noise represents the noise smoothing factor, which is greater than zero and less than one; n l-1 represents the candidate noise threshold power corresponding to the l-1th symbol in the data packet; m l Indicates the smoothed noise threshold power.

[0122] When smoothing is performed on the candidate noise threshold powers corresponding to two consecutive symbols, the noise threshold power can be obtained by smoothing directly using formula (7). If smoothing is performed on the noise threshold powers corresponding to at least three consecutive symbols, smoothing can be performed first based on the candidate noise threshold powers corresponding to the first two symbols, and then the smoothing result can be smoothed with the candidate noise threshold power corresponding to the next symbol, and so on, until the candidate noise threshold powers of all symbols are smoothed to obtain the noise threshold power.

[0123] By smoothing the candidate noise threshold powers corresponding to a plurality of symbols to obtain the noise threshold power, a more accurate noise threshold power can be obtained.

[0124] Step 215: Filter out target sampling points whose power exceeds the noise threshold power as designated sampling points.

[0125] The electronic device can check whether the power corresponding to each target sampling point exceeds the noise threshold power, thereby screening out the target sampling points whose power exceeds the noise threshold power. These screened out target sampling points are called designated sampling points.

[0126] Step 216: cyclically connect the front and rear ends of the target power delay profile, and determine whether the distance between the designated sampling point closest to the front end in the rear window and the centroid sampling point exceeds a preset sampling point number threshold.

[0127] Step 217: If yes, determine the designated sampling point closest to the front end in the rear window as the LOS sampling point, and the remaining designated sampling points as the NLOS sampling points.

[0128] The electronic device may cyclically connect the front and rear ends of the target power delay profile. In this case, the last sampling point of the target power delay profile is connected to the first sampling point. The electronic device may determine whether the distance between the designated sampling point closest to the front end in the rear window and the centroid sampling point exceeds a sampling point number threshold. The sampling point number threshold can be configured as needed; an exemplary sampling point number threshold is 2.

[0129] by Figure 8 For example, the designated sampling point closest to the front end in the rear window is the first designated sampling point from left to right. Check whether the distance between the designated sampling point and the center of gravity sampling point after passing the 256th sampling point from left to right exceeds the sampling point quantity threshold.

[0130] On the one hand, if yes, it means that the distance between the designated sampling point closest to the front end in the rear window and the centroid sampling point is large enough, and the power is not affected by the power of the centroid sampling point. In this case, it can be determined that the designated sampling point closest to the front end in the rear window is the LOS sampling point, and the remaining designated sampling points are NLOS sampling points.

[0131] On the other hand, if the value is not true, it indicates that the designated sampling point closest to the front end in the rear window is closer to the centroid sampling point, and its power may be affected by the power of the centroid sampling point. In this case, if other designated sampling points in the rear window are even closer to the centroid sampling point, they will also be affected by the centroid sampling point. Therefore, the centroid sampling point can be directly designated as the LOS sampling point, and the remaining designated sampling points can be designated as NLOS sampling points.

[0132] In addition, if there is no designated sampling point in the rear window, in other words, the power of all target sampling points in the rear window does not exceed the noise power threshold, the centroid sampling point can be directly determined as the LOS sampling point, and the remaining designated sampling points can be determined as NLOS sampling points.

[0133] Step 218: In the channel impulse response corresponding to the frequency domain channel response, the time domain channel estimation values ​​of the sampling points other than the NLOS sampling point are set to zero to obtain a cleaned channel impulse response.

[0134] After determining the NLOS sampling point, the electronic device can determine the NLOS sampling point in the channel impulse response corresponding to the frequency domain channel response based on the index of the NLOS sampling point, set the time domain channel estimation values ​​of other sampling points except the NLOS sampling point to zero, and retain the time domain channel estimation value corresponding to the NLOS sampling point, thereby obtaining a cleaned channel impulse response.

[0135] Through the above measures, the frequency domain channel response of each antenna array element of each transceiver can be effectively cleaned and transformed, and the time domain channel estimation values ​​of the noise channel and the LOS channel can be removed to obtain a cleaned channel impulse response that can accurately characterize the activity of the passive target, so that the activity of the passive target can be accurately perceived with the help of the cleaned channel impulse response.

[0136] Figure 9 FIG is a block diagram of a sensing device based on Wi-Fi signals according to an embodiment of the present invention. Figure 9 As shown, the device may include:

[0137] A cleaning module 910 is configured to perform a cleaning transformation on the frequency domain channel response of each antenna array element of each transceiver to obtain a corresponding cleaned channel impulse response;

[0138] a multiplication module 920 configured to, for each transceiver, select any cleaned channel impulse response from a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and conjugate-multiply the other cleaned channel impulse responses by the target channel impulse response to obtain a plurality of products;

[0139] A determination module 930 is configured to construct a specified vector based on the multiple products and determine a covariance matrix corresponding to the specified vector;

[0140] a decomposition module 940 configured to perform eigenvalue decomposition on the covariance matrix to obtain an arrival angle of the passive target relative to the transceiver;

[0141] The perception module 950 is configured to determine a perception result of the passive target based on the arrival angles corresponding to the at least two transceivers.

[0142] The implementation process of the functions and effects of each module in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned Wi-Fi signal-based perception method, and will not be repeated here.

[0143] In the several embodiments provided in this application, the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to the multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical functions. In some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0144] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0145] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

Claims

1. A Wi-Fi signal sensing method, applied to a Wi-Fi transceiver system, characterized in that: The Wi-Fi transceiver system includes at least two transceivers, each transceiver includes at least three antenna array elements, two of the at least three antenna array elements have a transmitting function, and each of the at least three antenna array elements has a receiving function. The method includes: Performing a cleaning transformation on the frequency domain channel response of each antenna array element of each transceiver to obtain a corresponding cleaned channel impulse response; For each transceiver, selecting any cleaned channel impulse response from a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and conjugate-multiplying the target channel impulse response with the other cleaned channel impulse responses to obtain a plurality of products; constructing a specified vector based on the multiple products, and determining a covariance matrix corresponding to the specified vector; performing eigenvalue decomposition on the covariance matrix to obtain an arrival angle of the passive target relative to the transceiver; A perception result of the passive target is determined based on the arrival angles corresponding to the at least two transceivers.

2. The method according to claim 1, characterized in that The determining, based on the arrival angles corresponding to the at least two transceivers, a perception result of the passive target, includes: The target position of the passive target in the environmental coordinate system is determined based on the arrival angle of the passive target relative to at least two transceivers and the position information of each transceiver in the environmental coordinate system.

3. The method according to claim 1 or 2, characterized in that The determining, based on the arrival angles corresponding to the at least two transceivers, a perception result of the passive target, includes: constructing an angle-of-arrival-time spectrum based on the angles of arrival corresponding to the at least two transceivers at a plurality of observation moments; A sub-spectrum image within a specified time period is cut from the arrival angle-time spectrum, and the sub-spectrum image is input into a trained behavior recognition model to obtain a behavior recognition result.

4. The method according to claim 1, wherein Before selecting, for each transceiver, any cleaned channel impulse response from a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and conjugate-multiplying the other cleaned channel impulse responses by the target channel impulse response to obtain a plurality of products, the method further includes: For each transceiver, interpolation processing is performed based on at least two cleaned channel impulse responses corresponding to the transceiver to expand the number of cleaned channel impulse responses corresponding to the transceiver.

5. The method according to claim 1, characterized in that The cleaning transformation is performed on the frequency domain channel response of each antenna array element of each transceiver to obtain a corresponding cleaned channel impulse response, including: determining, for each antenna array element of each transceiver, a frequency domain channel response corresponding to a power delay profile; Searching for a sampling point with the maximum power in the power delay spectrum as a centroid sampling point, and intercepting and splicing several sampling points before the centroid sampling point to the back end of the power delay spectrum to obtain a target power delay spectrum; A target sampling point is selected from the target power delay profile according to a front window of a preset first length and a rear window of a preset second length, and other sampling points other than the target sampling point are used as noise sampling points; wherein the front window is placed at the front end of the target power delay profile, and the rear window is placed at the rear end of the target power delay profile; Determining a noise threshold power based on the power of multiple noise sampling points; Filtering out target sampling points whose power exceeds the noise threshold power as designated sampling points; Circularly connecting the front and rear ends of the target power delay profile, and determining whether the distance between the designated sampling point closest to the front end in the rear window and the centroid sampling point at the junction exceeds a preset sampling point number threshold; If so, determine the designated sampling point closest to the front end in the rear window as the LOS sampling point, and the remaining designated sampling points as the NLOS sampling points; In the channel impulse response corresponding to the frequency domain channel response, time domain channel estimation values ​​of sampling points other than the NLOS sampling point are set to zero to obtain a cleaned channel impulse response.

6. The method according to claim 5, characterized in that The method further comprises: If not, the centroid sampling point is determined to be the LOS sampling point, and the other designated sampling points are determined to be the NLOS sampling points; Return to the step of setting the time domain channel estimation values ​​of the sampling points other than the NLOS sampling points in the channel impulse response corresponding to the frequency domain channel response to zero to obtain a cleaned channel impulse response.

7. The method according to claim 5, characterized in that The determining of the noise threshold power based on the powers of the plurality of noise sampling points includes: Calculating an average of the powers of the multiple noise sampling points as a candidate noise threshold power; Smoothing is performed on candidate noise threshold powers corresponding to a plurality of consecutive symbols transmitted by the Wi-Fi signal to obtain the noise threshold power.

8. A Wi-Fi signal sensing device, applied to a Wi-Fi transceiver system, characterized in that: The Wi-Fi transceiver system includes at least two transceivers, each transceiver includes at least three antenna array elements, two of the at least three antenna array elements have a transmitting function, and each of the at least three antenna array elements has a receiving function. The device includes: A cleaning module, configured to perform a cleaning transformation on the frequency domain channel response of each antenna array element of each transceiver to obtain a corresponding cleaned channel impulse response; a multiplication module configured to select, for each transceiver, any cleaned channel impulse response from a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and conjugate-multiply the other cleaned channel impulse responses by the target channel impulse response to obtain a plurality of products; a determination module, configured to construct a specified vector based on the multiple products, and determine a covariance matrix corresponding to the specified vector; a decomposition module, configured to perform eigenvalue decomposition on the covariance matrix to obtain an arrival angle of the passive target relative to the transceiver; A perception module is used to determine a perception result of the passive target based on the arrival angles corresponding to the at least two transceivers.

9. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing processor-executable instructions; The processor is configured to execute the Wi-Fi signal-based perception method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and the computer program can be executed by a processor to implement the Wi-Fi signal-based perception method according to any one of claims 1 to 7.

Images