CN116669174A - Sensing method and device based on Wi-Fi signals, electronic equipment and storage medium - Google Patents
Sensing method and device based on Wi-Fi signals, electronic equipment and storage medium Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
- H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
- H04W84/10—Small scale networks; Flat hierarchical networks
- H04W84/12—WLAN [Wireless Local Area Networks]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The application provides a sensing method and device based on Wi-Fi signals, electronic equipment and storage media, wherein the sensing method comprises the following steps: cleaning and transforming 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 one of a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and performing conjugate multiplication on other cleaned channel impulse responses and the target channel impulse response respectively to obtain a plurality of products; constructing a specified vector based on a plurality of 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; and determining a perception result of the passive target based on the corresponding arrival angles of the at least two transceivers. According to the scheme, the arrival angle can be resolved from the Wi-Fi signals, and the passive target can be accurately perceived based on at least two arrival angles.
Description
Technical Field
The present application relates to the field of wireless communications technologies, and in particular, to a Wi-Fi signal based sensing method and apparatus, an electronic device, and a computer readable storage medium.
Background
An important development direction of the next generation wireless communication technology is communication sensing/radar integration, and future Wi-Fi signals will have not only a data transmission function but also a sensing function on passive targets (people not carrying terminal devices or other targets). For example, the channel estimation information of the LTF long training sequence of the Wi-Fi signal is utilized to locate, track, identify the behavior of the passive target, and the like.
The wireless signal is utilized to sense the activity condition of the passive target, so that the method can play an important role in the intelligent home scene.
Disclosure of Invention
The embodiment of the application aims to provide a sensing method and device based on Wi-Fi signals, electronic equipment and storage medium, which are used for analyzing arrival angles from Wi-Fi signals received and transmitted by at least two transceivers and accurately sensing a passive target based on the at least two arrival angles.
In one aspect, the present application provides a sensing method based on Wi-Fi signals, 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 elements, two antenna elements of the at least three antenna elements have a transmitting function, and each antenna element of the at least three antenna elements has a receiving function, and the method includes:
Cleaning and transforming 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 one of a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and performing conjugate multiplication on other cleaned channel impulse responses and the target channel impulse response respectively to obtain a plurality of products;
constructing a specified vector based on the products, and determining a covariance matrix corresponding to the specified vector;
performing eigenvalue decomposition on the covariance matrix to obtain an arrival angle of a passive target relative to the transceiver;
and determining a perception result of the passive target based on the arrival angles corresponding to the at least two transceivers.
In an embodiment, the determining the perceived result of the passive target based on the arrival angles corresponding to the at least two transceivers includes:
a target location of the passive target in an environmental coordinate system is determined based on an angle of arrival of the passive target relative to at least two transceivers, and location information of each transceiver in the environmental coordinate system.
In an embodiment, the determining the perceived result of the passive target based on the arrival angles corresponding to the at least two transceivers includes:
constructing an arrival angle-time spectrum based on arrival angles corresponding to the at least two transceivers at a plurality of observation moments;
and cutting a sub-spectrum image in a specified time period from the arrival angle-time spectrum, and inputting the sub-spectrum image into a trained behavior recognition model to obtain a behavior recognition result.
In an embodiment, before selecting, for each transceiver, any one of the cleaned channel impulse responses from the plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and performing conjugate multiplication on other cleaned channel impulse responses and the target channel impulse response respectively 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.
In an embodiment, the performing a cleaning transform on the frequency domain channel response of each antenna element of each transceiver to obtain a corresponding cleaned channel impulse response includes:
Determining a corresponding power delay spectrum for the frequency domain channel response of each antenna element of each transceiver;
searching a sampling point with the maximum power in the power time delay spectrum as a gravity center sampling point, and intercepting and splicing a plurality of sampling points in front of the gravity center sampling point to the rear end of the power time delay spectrum to obtain a target power time delay spectrum;
screening out target sampling points from the target power delay spectrum according to a front window with a preset first length and a rear window with a preset second length, and taking other sampling points except the target sampling points as noise sampling points; the front window is arranged at the forefront end of the target power time delay spectrum, and the rear window is arranged at the rearmost end of the target power time delay spectrum;
determining a noise threshold power based on the power of the plurality of noise sampling points;
screening out target sampling points with power exceeding the noise threshold power as designated sampling points;
circularly connecting the front end and the rear end of the target power delay spectrum, judging whether the distance between the designated sampling point closest to the front end in the rear window and the center-of-gravity sampling point at the joint is beyond a preset sampling point number threshold value;
If yes, determining a designated sampling point closest to the front end in the rear window as an LOS sampling point, and determining the rest designated sampling points as NLOS sampling points;
and setting the time domain channel estimation values of sampling points except NLOS sampling points in the channel impulse response corresponding to the frequency domain channel response to zero to obtain the channel impulse response after cleaning.
In an embodiment, the method further comprises:
if not, determining the gravity center sampling point as an LOS sampling point, and the rest specified sampling points as NLOS sampling points;
and returning to the step of setting the time domain channel estimation values of sampling points except NLOS sampling points in the channel impulse response corresponding to the frequency domain channel response to obtain the channel impulse response after cleaning.
In an embodiment, the determining the noise threshold power based on the power of the plurality of noise sampling points includes:
calculating the average power of the plurality of noise sampling points to be used as candidate noise threshold power;
and carrying out smoothing processing based on candidate noise threshold power corresponding to a plurality of continuous symbols transmitted by the Wi-Fi signal to obtain the noise threshold power.
In another aspect, the present application provides a sensing device based on Wi-Fi signals, which is applied to a Wi-Fi transceiver system, where the Wi-Fi transceiver system includes at least two transceivers, each transceiver includes at least three antenna elements, two antenna elements of the at least three antenna elements have a transmitting function, and each antenna element of the at least three antenna elements has a receiving function, and the device includes:
The cleaning module is used for cleaning and transforming 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 one of a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and perform conjugate multiplication on other cleaned channel impulse responses and the target channel impulse response, respectively, to obtain a plurality of products;
the determining module is used for constructing a specified vector based on the products and determining a covariance matrix corresponding to the specified vector;
the decomposition module is used for carrying out eigenvalue decomposition on the covariance matrix to obtain an arrival angle of the passive target relative to the transceiver;
and the perception module is used for determining a perception result of the passive target based on the arrival angles corresponding to the at least two transceivers.
Further, the present application provides an electronic device, including:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the Wi-Fi signal based sensing method described above.
Furthermore, the present application provides a computer-readable storage medium storing a computer program executable by a processor to perform the above Wi-Fi signal-based sensing method.
According to the scheme, after the frequency domain channel response of each antenna array element of each transceiver of the Wi-Fi transceiver system is cleaned and transformed and the data of a noise channel and the data of an LOS channel are removed, the arrival angle of a passive target relative to the transceivers can be determined according to the cleaned channel impulse response, so that the passive target is accurately perceived according to the arrival angles corresponding to at least two transceivers.
Drawings
In order to more clearly illustrate the technical solution of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below.
Fig. 1 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
fig. 2 is a flow chart of a Wi-Fi signal-based sensing method according to an embodiment of the present application;
fig. 3 is a schematic diagram of a Wi-Fi signal transceiving mode of a transceiver according to an embodiment of the present application;
fig. 4 is a schematic diagram of an application scenario of a Wi-Fi signal-based sensing method according to an embodiment of the present application;
FIG. 5 is a detailed flowchart of step 210 of FIG. 2 according to an embodiment of the present application;
FIG. 6 is a schematic diagram of a power delay spectrum according to an embodiment of the present application;
FIG. 7 is a schematic diagram of a target power delay spectrum according to an embodiment of the present application;
FIG. 8 is a schematic diagram of sampling point screening according to an embodiment of the present application;
fig. 9 is a block diagram of a sensing device based on Wi-Fi signals according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application.
Like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
As shown in fig. 1, the present embodiment provides an electronic apparatus 1 including: at least one processor 11 and a memory 12, one processor 11 being exemplified in fig. 1. The processor 11 and the memory 12 are connected by a bus 10, and the memory 12 stores instructions executable by the processor 11, which instructions are executed by the processor 11, so that the electronic device 1 may perform all or part of the flow of the method in the embodiments described below. In an embodiment, the electronic device 1 may be a transceiver in a Wi-Fi transceiver system or a computing device interfacing with a Wi-Fi transceiver system for performing a Wi-Fi signal based sensing method. The following describes a scenario with an electronic device as an execution subject.
The Memory 12 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as static random access Memory (Static Random Access Memory, SRAM), electrically erasable Programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), erasable Programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), programmable Read-Only Memory (PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk.
The present application also provides a computer readable storage medium storing a computer program executable by the processor 11 to perform the Wi-Fi signal based sensing method provided by the present application.
Referring to fig. 2, a flow chart of a Wi-Fi signal based sensing method according to an embodiment of the present application is shown in fig. 2, and the method may include the following steps 210 to 250.
Step 210: and cleaning and transforming the frequency domain channel response of each antenna array element of each transceiver to obtain a corresponding cleaned channel impulse response.
The scheme of the application is applied to a Wi-Fi receiving and transmitting system, and the Wi-Fi receiving and transmitting system comprises at least two transceivers, and each transceiver comprises at least three antenna array elements. The arrangement of the at least three antenna elements of each transceiver may be in the form of a one-dimensional uniform linear array (Uniform Linear Array, ULA), or a square antenna array (Uniform Planar Array, UPA), or a two-dimensional array. Two antenna elements in at least three antenna arrays of each transceiver have a transmitting function and each antenna element has a receiving function. In one embodiment, adjacent antenna elements are spaced apart by half a wavelength. In an embodiment, if the transceiver includes three antenna elements, the three antenna elements may be a one-dimensional uniform linear array, and two of the three antenna elements have a transmitting function. In an embodiment, if the transceiver comprises four antenna elements, and the four antenna elements may be one-dimensional uniform linear arrays, 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 an embodiment, if the transceiver includes four antenna elements and the four antenna elements form a "T" shaped two-dimensional array, two non-adjacent antenna elements of the four antenna elements have a transmitting function.
Referring to fig. 3, a schematic diagram of a Wi-Fi signal transceiving manner of a transceiver according to an embodiment of the present application is shown in fig. 3, where the transceiver includes three antenna elements Ant1, ant2, and Ant4, and one Virtual antenna element Virtual Ant3, the transceiver may be regarded as having four antenna elements, and the first antenna element Ant1 and the fourth antenna element Ant4 have a function of transmitting Wi-Fi signals, and each antenna element has a function of receiving Wi-Fi signals. In this case, ant1 may transmit signals to Ant2 and Ant4, respectively, wi-Fi, ant2 may receive RX12 from Ant1, ant4 may receive RX14 from Ant1, while Virtual Ant3 may be considered to receive RX13 from Ant1 (RX 13 is not actually present). Ant4 may transmit signals to Ant1 and Ant2, respectively, wi-Fi, ant1 may receive RX41 from Ant4, ant2 may receive RX42 from Ant4, while Virtual Ant3 may be considered to receive RX43 from Ant4 (RX 43 is not actually present).
The purpose of setting the virtual antenna elements is to reduce hardware cost and resources required in the subsequent calculation process. In practical applications, a virtual antenna element may not be set, and taking fig. 3 as an example, the virtual antenna element may be replaced by an antenna element of hardware, or the last antenna element may be placed at the position of the virtual antenna element. The number of antenna elements may be the same or different for different receivers.
For each antenna element of the transceiver, the electronic device may determine a frequency domain channel response (Channel Frequency Response, CFR) in the frequency domain from Wi-Fi signals received by the antenna element by a channel estimation algorithm. According to the difference between the transmitting end and the receiving end of Wi-Fi signals, corresponding frequency domain channel responses can be determined for different Wi-Fi signals respectively. Illustratively, taking fig. 3 as an example, corresponding frequency domain channel responses may be determined for RX12, RX14, RX41, RX42, respectively. In one embodiment, the electronic device may window the frequency domain channel response by a window function (e.g., a hamming window), so that spectrum leakage is more concentrated and convenient for subsequent processing.
For each frequency domain channel response, the electronic device may clean it to remove noise data and LOS (Line of Sight) channel data, and transform to obtain a corresponding cleaned channel impulse response (Channel Impulse Response, CIR). The cleaned channel impulse response contains only the data of the NLOS (Not Line of Sight, non-line of sight transmission) channel.
When a passive target is active in an indoor scene, the passive target can influence indoor Wi-Fi signals due to the change of occupied space, so that multipath channels are changed. At this time, the frequency domain channel response as channel state information (Channel State Information, CSI) changes accordingly. The multipath channels indicated by the frequency domain channel response include LOS channels, NLOS channels, noise channels. Because the indoor static object is kept still, and the data of the LOS channel is not influenced by the passive target, the data of the NLOS channel can represent the influence of the activity of the passive target on the wireless channel, and the channel impulse response after cleaning can represent the activity condition of the passive target.
In an embodiment, after the cleaned channel impulse response is obtained by cleaning and transforming the antenna array element which is hardware, for each transceiver, the electronic device may perform interpolation processing based on at least two cleaned channel impulse responses corresponding to the transceiver, so as to obtain the cleaned channel impulse response of the virtual antenna array element of the transceiver. By the aid of the method, the number of channel impulse responses after cleaning corresponding to the transceiver can be increased, and the subsequent perception result aiming at the passive target is more accurate.
Illustratively, taking FIG. 3 as an example, the channel impulse response h after cleaning is obtained for the signal of Ant2 received Ant1 (rx12) And Ant4 receives the cleaned channel impulse response h of the signal of Ant1 (rx14) Thereafter, can be applied to h (rx12) And h (rx14) Interpolation processing is carried out to obtain h (rx13) As the channel impulse response after cleaning of the Virtual antenna element Virtual Ant3 receiving the signal of Ant 1.
Post-cleaning channel impulse response h for obtaining Ant1 received Ant4 signal (rx41) And the cleaned channel impulse response h of the signal of Ant2 receiving Ant4 (rx42) Thereafter, can be applied to h (rx41) And h (rx42) Interpolation processing is carried out to obtain h (rx43) As the channel impulse response after cleaning of the Virtual antenna element Virtual Ant3 receiving the signal of Ant 4.
Step 220: for each transceiver, selecting any one of the cleaned channel impulse responses from a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and performing conjugate multiplication on other cleaned channel impulse responses and the target channel impulse response respectively to obtain a plurality of products.
For a plurality of cleaned channel impulse responses corresponding to the transceiver, the electronic device can select one cleaned channel impulse response from the plurality of cleaned channel impulse responses as a target channel impulse response. For example, to ensure that the directivity of the phase change is not changed in the calculation process, so as to facilitate the subsequent calculation, the channel impulse response after cleaning corresponding to the Wi-Fi signal sent from the first antenna element to the second antenna element can be selected as the target channel impulse response; or, the cleaned channel impulse response corresponding to the Wi-Fi signal sent from the last antenna element to the next-to-last antenna element can be selected as the target channel impulse response.
The electronic device may conjugate and multiply other cleaned channel impulse responses of the transceiver with the target channel impulse response, respectively, and any cleaned channel impulse response may be multiplied with the target channel impulse response, so as to obtain a product, and thus, a plurality of products may be obtained. Here, the other post-cleaning channel impulse responses are channel impulse responses other than the target channel impulse response.
Taking fig. 3 as an example, if the channel impulse response h is cleaned from a plurality of (rx12) 、h (rx13) 、h (rx14) 、h (rx41) 、h (rx42) 、h (rx43) In which h is selected (rx12) As a target channel impulse response. A plurality of products can be calculated by the following formulas (1) to (5):
h 1 ＝h (rx13) ×conj(h (rx12) ) (1)
h 2 ＝h (rx14) ×conj(h (rx12) ) (2)
h 3 ＝h (rx41) ×conj(h (rx12) ) (3)
h 4 ＝h (rx42) ×conj(h (rx12) ) (4)
h 5 ＝h (rx43) ×conj(h (rx12) ) (5)
wherein h is 1 、h 2 、h 3 、h 4 、h 5 Are all products.
Step 230: and constructing a specified vector based on the products, and determining a covariance matrix corresponding to the specified vector.
After the multiple products are obtained, the CIR spatial autocorrelation column vectors are constructed with the multiple products as specified vectors. Taking fig. 3 as an example, the specified vector may be expressed as x= [ h ] 1 ,h 2 ,h 3 ,h 4 ,h 5 ] T 。
The electronic device may calculate the covariance matrix corresponding to the specified vector by the following formula (6):
R XX ＝E{XX CT } (6)
wherein R is XX Is covariance matrix; e is an identity matrix; x is a specified vector.
Step 240: and performing eigenvalue decomposition on the covariance matrix to obtain the arrival angle of the passive target relative to the transceiver.
The electronic device may perform eigenvalue decomposition on the covariance matrix by means of MUSIC (multiple signal classification algorithm) algorithm, ESPRIT (Estimation of Signal Parameters using Rotational Invariance Techniques) algorithm, compressed sensing algorithm, etc., so as to obtain an Angle of Arrival (AOA) of the passive target relative to the transceiver.
When eigenvalue decomposition is performed on the covariance matrix, a plurality of arrival angles may be obtained, in which case the arrival angle needs to be selected from among them according to the needs of the application scene. Specific selection means are described in detail below.
The foregoing steps 210 to 240 are performed for each transceiver, and an arrival angle corresponding to each transceiver can be obtained.
Step 250: and determining a perception result of the passive target based on the corresponding arrival angles of the at least two transceivers.
The electronic device can sense the state of the passive target according to the arrival angle of the passive target relative to at least two transceivers in the Wi-Fi transceiver system, so as to obtain a sensing result. Here, the perceived content may include tracking and locating the passive target, or performing behavior recognition on the passive target, or performing tracking and locating and behavior recognition on the passive target at the same time.
Through the measures, after the frequency domain channel response of each antenna element of each transceiver of the Wi-Fi transceiver system is cleaned and transformed and the data of the noise channel and the data of the LOS channel are removed, the arrival angle of the passive target relative to the transceivers can be determined according to the cleaned channel impulse response, so that the passive target can be accurately perceived according to the arrival angles corresponding to at least two transceivers.
In an embodiment, if the perceived content includes tracking and locating passive targets, then the location information of at least two transceivers in the environment coordinate system needs to be predetermined, and the location information of each transceiver may be determined according to the actual placement location of the transceiver in the application environment. The environment coordinate system is a coordinate system established in the application environment.
After determining the angle of arrival of the passive object with respect to the at least two transceivers, the electronic device may determine the object location of the passive object in the ambient coordinate system based on the angle of arrival of the passive object with respect to the at least two transceivers, and the location information of each transceiver in the ambient coordinate system.
Referring to fig. 4, a schematic diagram of an application scenario of a Wi-Fi signal-based sensing method according to an embodiment of the present application is shown in fig. 4, where, on a planar environmental coordinate system, positions of two transceivers TRX1 and TRX2 have been determined, and an arrival angle of a passive target relative to TRX1 and an arrival angle relative to TRX2 are known, then a position of an intersection between a passive target and a connection of the two transceivers is a target position.
In fig. 4, the Wi-Fi system includes two transceivers, and in practical applications, the Wi-Fi system may include more transceivers, and the target position of the passive target may be determined in the same manner.
When a passive target moves in an application environment, the influence of the movement of the passive target on a wireless channel is greatest, for example, when the passive target is a person and walks while waving hands, the passive target can have the greatest influence on the multipath transmission of Wi-Fi signals due to the fact that the walking involves whole body movement. Thus, where the perceived content includes tracking locations, if multiple angles of arrival are resolved from the covariance matrix when step 240 is performed, the largest angle of arrival may be selected for tracking locations.
By means of the measures, the passive target can be accurately positioned by means of the arrival angles of at least two transceivers at each observation time.
In one embodiment, if the perceived content includes behavior recognition of passive targets, then two cases are separated: firstly, sensing content, including tracking positioning and behavior recognition; secondly, the perceived content includes only behavior recognition. The specific content of the behavior recognition can be determined according to the requirements of the application scene, and the behavior recognition can be exemplified by recognition of hand actions of a passive target (person), such as hand waving, hand clapping, hand lifting and the like; alternatively, behavior recognition may be the recognition of the health status of a passive target (person), such as heart rate, respiration, fall, etc.
For the first case, after decomposing the arrival angles from the covariance matrix at the execution of step 240, the largest arrival angle may be selected for tracking positioning and the second largest arrival angle is selected for behavior recognition. For the second case, after decomposing out the multiple angles of arrival from the covariance matrix when step 240 is performed, the largest angle of arrival may be selected for tracking positioning.
The electronic device may construct an angle of arrival-time spectrum based on angles of arrival corresponding to at least two transceivers at a plurality of observation times. The vertical axis of the angle of arrival-time spectrum is the angle of arrival corresponding to at least two transceivers, and the horizontal axis is time. The interval between adjacent observation times may be configured as needed, and each data packet sent by the Wi-Fi signal corresponds to an observation time, for example.
The electronic device may crop sub-spectrum images from the angle-of-arrival-time spectrum for a specified period of time. Here, the specified time period may be configured according to needs, for example, in an application scenario, real-time behavior recognition needs to be performed on a passive target, and a single completion time of the behavior to be recognized is within two seconds, then the specified time period may be within the last two seconds.
After the sub-spectrum images generated in the specified time period are cut, the electronic device can input the sub-spectrum images into a trained behavior recognition model, and the behavior recognition model is used for processing the sub-spectrum images, so that a behavior recognition result is obtained. The behavior recognition model can be obtained by training any network model for classification, such as a CNN (Convolutional Neural Networks, convolutional neural network), a TCN (Temporal Convolutional Network, time domain convolutional network) or a mixed model of the CNN and the RNN (Recurrent Neural Networks, cyclic neural network).
By means of the measures, the passive target can be identified by means of a machine learning model based on the corresponding arrival angles of at least two transceivers at a plurality of observation moments.
In an embodiment, referring to fig. 5, a detailed flowchart of step 210 in fig. 2 is provided for an embodiment of the present application, and as shown in fig. 5, steps 211 to 218 may be specifically performed when step 210 is performed.
Step 211: for the frequency domain channel response of each antenna element of each transceiver, a corresponding power delay profile is determined for the frequency domain channel response.
After obtaining the frequency domain channel response of each antenna element of each transceiver at each observation time instant, the electronic device may perform an inverse fourier transform (Inverse Fast Fourier Transform, IFFT) on the frequency domain channel response to obtain a channel impulse response. After deriving the channel impulse response, the electronic device may calculate a power delay profile (Power Delay Profile, PDP) based on the channel impulse response. In an embodiment, the same symbol of the Wi-Fi signal has multiple frequency domain channel responses on one transceiver, and multiple power delay spectrums can be calculated, in which case, an average value can be calculated for the multiple power delay spectrums as the power delay spectrum of the symbol in subsequent processing.
Step 212: searching a sampling point with the maximum power in the power delay spectrum, taking the sampling point as a gravity center sampling point, and splicing a plurality of sampling points in front of the gravity center sampling point to the rear end of the power delay spectrum to obtain a target power delay spectrum.
The electronic equipment can search the sampling point with the maximum power in the power time delay spectrum, and the searched sampling point is used as the gravity center sampling point. After the gravity center sampling point is determined, the electronic device can intercept a plurality of sampling points in front of the gravity center sampling point, splice the intercepted sampling points to the rear end of the power delay spectrum, and therefore obtain the target power delay spectrum.
Referring to fig. 6, a schematic diagram of a power delay spectrum according to an embodiment of the present application is shown in fig. 6, where the power delay spectrum includes 256 sampling points, and a sampling point before a center of gravity sampling point is located in a lower left rectangle.
Referring to fig. 7, a schematic diagram of a target power delay spectrum provided by an embodiment of the present application is shown in fig. 7, and after a sampling point before a center of gravity sampling point in fig. 6 is intercepted, the sampling point is spliced at a rear end of the power delay spectrum, so as to obtain the target power delay spectrum.
Step 213: screening out target sampling points in a target power delay spectrum according to a front window with a preset first length and a rear window with a preset second length, and taking other sampling points except the target sampling points as noise sampling points; the front window is placed at the forefront end of the target power delay spectrum, and the rear window is placed at the rearmost end of the target power delay spectrum.
The first length may be obtained by multiplying a first coefficient by a length of a Cyclic Prefix (CP), the first coefficient being greater than one, and exemplary, the first coefficient being 2. The second length may be multiplied by a second coefficient, which is less than one, and is illustratively 0.5, based on the length of the cyclic prefix.
The electronic device may place the front window at the forefront end of the target power delay spectrum, place the rear window at the rearmost end of the target power delay spectrum, and use the sampling points in the front window and the rear window as target sampling points. And sampling points other than the target sampling point may be determined as noise sampling points.
Referring to fig. 8, a schematic diagram of sampling point screening according to an embodiment of the present application is shown in fig. 8, where a plurality of sampling points in a front window are target sampling points, a plurality of sampling points in a rear window are target sampling points, and a plurality of sampling points between the front window and the rear window are noise sampling points.
Step 214: a noise threshold power is determined based on the power of the plurality of noise sampling points.
The electronic device may calculate an average of the power of the plurality of noise sampling points and take the average of the noise as the noise threshold power.
In one embodiment, in determining the noise threshold power, an average of the powers of a plurality of noise sampling points may be calculated as the candidate noise threshold power. For a plurality of continuous symbols transmitted by Wi-Fi signals, candidate noise threshold power corresponding to each symbol can be calculated respectively, and the plurality of candidate noise threshold powers can be smoothed, so that the noise threshold power is obtained. Here, the number of symbols used for the smoothing process may be configured as needed.
By way of example, the smoothing process may be performed by the following formula (7):
m l ＝α noise *n l +(1-α noise )*n l-1 (7)
wherein n is l Representing candidate noise threshold power corresponding to the first symbol in the data packet; alpha noise Representing a noise smoothing factor, the noise smoothing factor being greater than zero and less than one; n is n l-1 Representing candidate noise threshold power corresponding to the first-1 symbol in the data packet; m is m l Representing the smoothed noise threshold power.
When the smoothing processing is performed by the candidate noise threshold power corresponding to two continuous symbols, the noise threshold power can be obtained by directly performing the smoothing processing by the formula (7). If the smoothing is performed by continuously performing the smoothing on the noise threshold power corresponding to at least three symbols, the smoothing may be performed based on the candidate noise threshold powers corresponding to the two first symbols, and then the smoothing result and the candidate noise threshold power corresponding to the next symbol are smoothed, and so on until the candidate noise threshold powers of all the symbols are smoothed, so as to obtain the noise threshold power.
The noise threshold power is obtained through smoothing the candidate noise threshold power corresponding to the plurality of symbols, and more accurate noise threshold power can be obtained.
Step 215: and screening out target sampling points with power exceeding the noise threshold power as designated sampling points.
The electronic device may check whether the power corresponding to each target sampling point exceeds the noise threshold power, thereby screening out target sampling points with power exceeding the noise threshold power, where the screened target sampling points are referred to as designated sampling points.
Step 216: and circularly connecting the front end and the rear end of the target power time delay spectrum, and judging whether the distance between the designated sampling point closest to the front end in the rear window and the sampling point passing through the joint is beyond a preset sampling point number threshold value.
Step 217: if yes, determining the appointed sampling point closest to the front end in the rear window as an LOS sampling point, and the rest appointed sampling points as NLOS sampling points.
The electronic device may connect the front and back ends of the target power delay profile in a loop, in which case the last sample point of the target power delay profile is connected to the first sample point. The electronic device may determine whether a specified sampling point in the rear window closest to the front end exceeds a sampling point count threshold at a distance between the passing junction and the center of gravity sampling point. Here, the sampling point number threshold may be configured as needed, with an exemplary sampling point number threshold of 2.
Taking fig. 8 as an example, the designated sampling point closest to the front end in the rear window is the first designated sampling point in the left-to-right direction, and whether the distance between the designated sampling point and the center-of-gravity sampling point after passing through the 256 th sampling point from left to right exceeds the threshold value of the number of sampling points is detected.
On the one hand, if the distance between the designated sampling point closest to the front end in the rear window and the gravity center sampling point is large enough, the power is not affected by the power of the gravity center sampling point, in this case, the designated sampling point closest to the front end in the rear window can be determined to be the LOS sampling point, and the rest of the designated sampling points are NLOS sampling points.
On the other hand, if not, it is indicated that the distance between the designated sampling point closest to the front end and the center of gravity sampling point in the rear window is small, and the power may be affected by the power of the center of gravity sampling point. In this case, if other specified sampling points exist in the rear window, the distance from the center of gravity sampling point is smaller, and the influence of the center of gravity sampling point is also received. Therefore, it is possible to directly determine the center of gravity sampling point as the LOS sampling point and determine the remaining specified sampling points as the NLOS sampling points.
In addition, if no specified sampling point exists 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 gravity center sampling point can be directly determined to be an LOS sampling point, and the rest specified sampling points are determined to be NLOS sampling points.
Step 218: and setting the time domain channel estimation values of sampling points except NLOS sampling points in the channel impulse response corresponding to the frequency domain channel response to zero to obtain the channel impulse response after cleaning.
After determining the NLOS sampling points, the electronic device may determine the NLOS sampling points in the channel impulse response corresponding to the frequency domain channel response according to the indexes of the NLOS sampling points, set the time domain channel estimation values of other adopted points except the NLOS sampling points to zero, and reserve the time domain channel estimation values corresponding to the NLOS sampling points, thereby obtaining the channel impulse response after cleaning.
By the measures, the frequency domain channel response of each antenna array element of each transceiver can be effectively subjected to cleaning transformation, the time domain channel estimation values of a noise channel and an LOS channel are removed, and the cleaned channel impulse response which can accurately represent the activity condition of the passive target is obtained, so that the activity condition of the passive target can be accurately perceived by means of the cleaned channel impulse response in the follow-up process.
Fig. 9 is a block diagram of a sensing device based on Wi-Fi signals according to an embodiment of the present invention, and as shown in fig. 9, the device may include:
the cleaning module 910 is configured to perform cleaning transformation for the frequency domain channel response of each antenna element of each transceiver to obtain a corresponding cleaned channel impulse response;
a multiplication module 920, configured to select, for each transceiver, any one of the cleaned channel impulse responses from a plurality of cleaned channel impulse responses corresponding to the transceiver, as a target channel impulse response, and perform conjugate multiplication on other cleaned channel impulse responses and the target channel impulse response, respectively, to obtain a plurality of products;
A determining module 930, configured to construct a specified vector based on the multiple products, and determine a covariance matrix corresponding to the specified vector;
a decomposition module 940, configured to decompose eigenvalues of the covariance matrix to obtain an arrival angle of the passive target relative to the transceiver;
and a sensing module 950, configured to determine a sensing result of the passive target based on the arrival angles corresponding to the at least two transceivers.
The implementation process of the functions and actions of each module in the device is specifically shown in the implementation process of the corresponding steps in the Wi-Fi signal-based sensing method, and will not be described herein.
In the several embodiments provided in the present application, the disclosed apparatus and method may be implemented in other manners. The apparatus embodiments described above are merely illustrative, for example, of the flowcharts and block diagrams in the figures that illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored on a computer readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Claims (10)
1. The sensing method based on Wi-Fi signals is applied to a Wi-Fi receiving and transmitting system, and is characterized in that the Wi-Fi receiving and transmitting system comprises at least two transceivers, each transceiver comprises at least three antenna array elements, two antenna array elements in the at least three antenna array elements have a transmitting function, and each antenna array element in the at least three antenna array elements has a receiving function, and the method comprises the following steps:
Cleaning and transforming 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 one of a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and performing conjugate multiplication on other cleaned channel impulse responses and the target channel impulse response respectively to obtain a plurality of products;
constructing a specified vector based on the products, and determining a covariance matrix corresponding to the specified vector;
performing eigenvalue decomposition on the covariance matrix to obtain an arrival angle of a passive target relative to the transceiver;
and determining a perception result of the passive target based on the arrival angles corresponding to the at least two transceivers.
2. The method of claim 1, wherein the determining a perceived result of the passive target based on the corresponding angles of arrival of the at least two transceivers comprises:
a target location of the passive target in an environmental coordinate system is determined based on an angle of arrival of the passive target relative to at least two transceivers, and location information of each transceiver in the environmental coordinate system.
3. The method according to claim 1 or 2, wherein the determining the perceived result of the passive target based on the corresponding angles of arrival of the at least two transceivers comprises:
constructing an arrival angle-time spectrum based on arrival angles corresponding to the at least two transceivers at a plurality of observation moments;
and cutting a sub-spectrum image in a specified time period from the arrival angle-time spectrum, and inputting the sub-spectrum image into a trained behavior recognition model to obtain a behavior recognition result.
4. The method of claim 1, wherein before selecting, for each transceiver, any one of the cleaned channel impulse responses from the 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, respectively, to obtain a plurality of products, the method further comprises:
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 of claim 1, wherein performing a cleaning transform on the frequency domain channel response of each antenna element of each transceiver to obtain a corresponding cleaned channel impulse response comprises:
Determining a corresponding power delay spectrum for the frequency domain channel response of each antenna element of each transceiver;
searching a sampling point with the maximum power in the power time delay spectrum as a gravity center sampling point, and intercepting and splicing a plurality of sampling points in front of the gravity center sampling point to the rear end of the power time delay spectrum to obtain a target power time delay spectrum;
screening out target sampling points from the target power delay spectrum according to a front window with a preset first length and a rear window with a preset second length, and taking other sampling points except the target sampling points as noise sampling points; the front window is arranged at the forefront end of the target power time delay spectrum, and the rear window is arranged at the rearmost end of the target power time delay spectrum;
determining a noise threshold power based on the power of the plurality of noise sampling points;
screening out target sampling points with power exceeding the noise threshold power as designated sampling points;
circularly connecting the front end and the rear end of the target power delay spectrum, judging whether the distance between the designated sampling point closest to the front end in the rear window and the center-of-gravity sampling point at the joint is beyond a preset sampling point number threshold value;
If yes, determining a designated sampling point closest to the front end in the rear window as an LOS sampling point, and determining the rest designated sampling points as NLOS sampling points;
and setting the time domain channel estimation values of sampling points except NLOS sampling points in the channel impulse response corresponding to the frequency domain channel response to zero to obtain the channel impulse response after cleaning.
6. The method of claim 5, wherein the method further comprises:
if not, determining the gravity center sampling point as an LOS sampling point, and the rest specified sampling points as NLOS sampling points;
and returning to the step of setting the time domain channel estimation values of sampling points except NLOS sampling points in the channel impulse response corresponding to the frequency domain channel response to obtain the channel impulse response after cleaning.
7. The method of claim 5, wherein determining the noise threshold power based on the power of the plurality of noise sampling points comprises:
calculating the average power of the plurality of noise sampling points to be used as candidate noise threshold power;
and carrying out smoothing processing based on candidate noise threshold power corresponding to a plurality of continuous symbols transmitted by the Wi-Fi signal to obtain the noise threshold power.
8. A sensing device based on Wi-Fi signals, which is applied to a Wi-Fi transceiver system, wherein the Wi-Fi transceiver system comprises at least two transceivers, each transceiver comprises at least three antenna elements, two antenna elements of the at least three antenna elements have a transmitting function, and each antenna element of the at least three antenna elements has a receiving function, the device comprises:
The cleaning module is used for cleaning and transforming 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 one of a plurality of cleaned channel impulse responses corresponding to the transceiver as a target channel impulse response, and perform conjugate multiplication on other cleaned channel impulse responses and the target channel impulse response, respectively, to obtain a plurality of products;
the determining module is used for constructing a specified vector based on the products and determining a covariance matrix corresponding to the specified vector;
the decomposition module is used for carrying out eigenvalue decomposition on the covariance matrix to obtain an arrival angle of the passive target relative to the transceiver;
and the perception module is used for determining a perception result of the passive target based on the arrival angles corresponding to the at least two transceivers.
9. An electronic device, the electronic device comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the Wi-Fi signal based sensing method of any one of claims 1-7.
10. A computer readable storage medium, wherein the storage medium stores a computer program executable by a processor to perform the Wi-Fi signal based sensing method of any one of claims 1-7.
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| CN117538854B (en) * | 2024-01-09 | 2024-04-09 | 腾讯科技（深圳）有限公司 | Ranging method, ranging apparatus, computer device, and computer-readable storage medium |
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