Millimeter wave and WiFi dual-frequency sensing method and device and computer equipment

Abstract

The invention relates to a millimeter wave and WiFi dual-frequency sensing method and device and computer equipment, belongs to the field of target sensing, and solves the problems that an existing dual-frequency sensing scheme is inconsistent in time sequence, poor in noise reduction pertinence, high in target misjudgment rate and insufficient in positioning precision. According to the method, signals are collected through a millimeter wave sensing module, interference is removed through mean filtering, signals are synchronously collected through a WiFi sensing module, self-adaptive noise reduction is carried out, and dual-frequency effective signals are obtained; the signal processing module aligns the time domains of the double-frequency signals, calculates a signal intensity difference value and a phase deviation value, and judges the existence of a target through two parameters; and when the target exists, calculating the motion speed and position coordinates of the target through a triangulation positioning algorithm by combining the propagation time difference of the double-frequency signals of the three reference points, and finally standardizing output data. According to the invention, the dual-frequency signal quality is improved, the misjudgment rate is reduced, the positioning and speed measurement precision is improved, and the high-precision sensing requirement is met.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of target sensing, in particular to a millimeter wave and WiFi dual-frequency sensing method and device and computer equipment. BACKGROUND

[0002] In the current target sensing technology, the single-frequency sensing scheme has obvious limitations: although millimeter wave sensing has strong penetration and motion capture capabilities, it is easily affected by metal components and electromagnetic interference in the environment, resulting in a large amount of redundant interference components in the collected signal, affecting the sensing accuracy; WiFi sensing relies on existing wireless communication networks and has low deployment costs, but the signal is easily affected by wall shielding and multipath effect interference, and it is difficult to accurately determine whether a target exists and the motion parameters when used alone. To improve the sensing effect, some schemes attempt to combine millimeter wave and WiFi signals, but the existing dual-frequency combination scheme has the following key technical defects: first, the timing of dual-frequency signal collection is inconsistent, making it impossible to effectively associate the subsequent signal processing; second, the noise reduction processing of dual-frequency signals lacks pertinence, and the fixed interference of millimeter wave signals and the dynamic interference of WiFi signals cannot be effectively removed separately; third, target determination relies only on a single signal parameter (such as signal strength), which is prone to misjudgment due to environmental fluctuations; fourth, the complementary characteristics of dual-frequency signals are not fully utilized in positioning calculation, resulting in large errors in target position and motion speed calculation. SUMMARY

[0003] To achieve the above purpose, the millimeter wave and WiFi dual-frequency sensing method provided by the present application comprises the following steps: An initial sensing signal of a target area is obtained by a millimeter wave sensing module, and a mean value filtering process is performed on the initial sensing signal to obtain a millimeter wave effective signal; A synchronous sensing signal of the same target area is obtained by a WiFi sensing module, and an adaptive noise reduction process is performed on the synchronous sensing signal to obtain a WiFi effective signal; A signal processing module receives the millimeter wave effective signal and the WiFi effective signal, performs a time domain alignment operation on the millimeter wave effective signal and the WiFi effective signal, and calculates the signal strength difference and phase deviation value between the millimeter wave effective signal and the WiFi effective signal; According to the signal strength difference and the phase deviation value, it is determined whether there is a target to be sensed in the target area; If the result of the determination is that there is a target to be sensed, the motion speed and position coordinates of the target to be sensed are calculated based on the millimeter wave effective signal and the WiFi effective signal after time domain alignment by a triangular positioning algorithm; The signal processing module outputs the motion speed and position coordinates of the target to be sensed.

[0004] Further, the step of obtaining an initial sensing signal of the target area by the millimeter wave sensing module, and performing mean value filtering on the initial sensing signal to obtain a millimeter wave effective signal comprises: The millimeter wave sensing module collects signals of the target area at a sampling frequency of 500MHz-1GHz to obtain an initial sensing signal containing environmental interference components; The size of the sliding window of the mean value filtering is set to 8-16 sampling points, and the initial sensing signal is input into the sliding window to calculate the average signal amplitude of all sampling points in each sliding window; The average signal amplitude is used to replace the signal amplitude of the middle sampling point in the corresponding sliding window, and all sampling points of the initial sensing signal are sequentially traversed to obtain a preliminary filtered signal; The abnormal signal points with amplitudes exceeding a preset threshold range in the preliminary filtered signal are removed, and the remaining signal is the millimeter wave effective signal.

[0005] Further, the step of obtaining a synchronous sensing signal of the same target area by the WiFi sensing module, and performing adaptive noise reduction processing on the synchronous sensing signal to obtain a WiFi effective signal comprises: The WiFi sensing module is aligned with the target area, and electromagnetic sensing data of the target area is collected in a time window consistent with the time window in which the millimeter wave sensing module obtains the initial sensing signal, and the electromagnetic sensing data is taken as the synchronous sensing signal; Noise characteristics in the synchronous sensing signal are extracted, including the frequency distribution range and amplitude fluctuation interval of the noise signal; The noise reduction parameters are adjusted according to the noise characteristics, including the length of the filtering window and the signal amplitude screening threshold; The synchronous sensing signal is filtered using the adjusted noise reduction parameters to remove signal components in the synchronous sensing signal that meet the noise characteristics; The filtered synchronous sensing signal is taken as the WiFi effective signal.

[0006] Further, the signal processing module receives the millimeter wave effective signal and the WiFi effective signal, and the step of performing time domain alignment operation on the millimeter wave effective signal and the WiFi effective signal comprises: The signal processing module receives the millimeter wave effective signal and the WiFi effective signal respectively, and sets the millimeter wave effective signal as the reference signal for time domain alignment; The rising edge time of the reference signal is extracted as a first time feature point, and the rising edge time of the WiFi effective signal is extracted as a second time feature point. calculating a time difference between the second time feature point and the first time feature point; adjusting a timing of the WiFi effective signal according to the time difference, so that the second time feature point of the WiFi effective signal coincides with the first time feature point of the reference signal, and completing the time domain alignment of the millimeter wave effective signal and the WiFi effective signal.

[0007] Further, the step of calculating the signal strength difference and the phase deviation value between the millimeter wave effective signal and the WiFi effective signal comprises: The signal processing module extracts the first signal strength value and the first phase value of the time domain aligned millimeter wave effective signal, and simultaneously extracts the second signal strength value and the second phase value of the time domain aligned WiFi effective signal; Subtracting the second signal strength value from the first signal strength value to obtain the signal strength difference; Calculating the difference value of the first phase value and the second phase value, if the absolute value of the difference value is greater than 180 degrees, then adding 360 degrees or subtracting 360 degrees to obtain the phase deviation value.

[0008] Further, the step of judging whether there is a target to be sensed in the target area according to the signal strength difference and the phase deviation value comprises: Pre-set a preset intensity difference threshold and a preset phase deviation threshold corresponding to a target sensing scene; Comparing the calculated signal strength difference with the preset intensity difference threshold, and simultaneously comparing the calculated phase deviation value with the preset phase deviation threshold; If the signal strength difference is greater than the preset intensity difference threshold, and the phase deviation value is greater than the preset phase deviation threshold, it is determined that there is a target to be sensed in the target area; If the signal strength difference is less than or equal to the preset intensity difference threshold, or the phase deviation value is less than or equal to the preset phase deviation threshold, it is determined that there is no target to be sensed in the target area.

[0009] Further, if the judgment result is that there is a target to be sensed, based on the time domain aligned millimeter wave effective signal and the WiFi effective signal, the step of calculating the motion speed and position coordinates of the target to be sensed through a triangular positioning algorithm comprises: Selecting three preset signal receiving reference points in the target area, and recording the propagation time difference of the time domain aligned millimeter wave effective signal and WiFi effective signal received by each reference point; According to the known coordinates of the three signal receiving reference points and the corresponding propagation time difference, a spatial coordinate equation is established by a triangulation algorithm to obtain the initial position coordinates of the target to be sensed; Within a preset time interval, the propagation time difference of the time-domain aligned millimeter wave effective signal and WiFi effective signal at the three signal receiving reference points is repeatedly obtained, and a plurality of position coordinates of the target to be sensed at different time points are calculated; According to the time information corresponding to the plurality of position coordinates, the displacement of the target to be sensed between adjacent two time points is calculated, and the motion speed of the target to be sensed is obtained in combination with the time interval; The initial position coordinates and the subsequent plurality of position coordinates of the target to be sensed are integrated to determine the final position coordinates of the target to be sensed.

[0010] Further, the triangulation algorithm comprises: Let the position coordinates of the millimeter wave sensing module be , the position coordinates of the first WiFi sensing module be , the position coordinates of the second WiFi sensing module be , and the position coordinates of the target to be sensed be ; The distance from the target to be sensed P to the millimeter wave sensing module A is calculated , and the formula is: ; The distance from the target to be sensed P to the first WiFi sensing module B is calculated , and the formula is: ; The distance from the target to be sensed P to the second WiFi sensing module C is calculated , and the formula is: ; After being combined, the equation group is obtained: ; The equation group is expanded and eliminated to obtain the position coordinates of the target to be sensed , The interval time is obtained The position coordinates of the target to be sensed obtained by calculation before and after and The motion speed v of the target to be sensed is calculated by the formula: ; .

[0011] The application further provides a millimeter wave and WiFi dual-frequency sensing device, comprising: A millimeter wave unit is configured to acquire an initial sensing signal of a target area through a millimeter wave sensing module, and to obtain a millimeter wave effective signal by performing mean filtering on the initial sensing signal. A WiFi unit is configured to acquire a synchronous sensing signal of the same target area through a WiFi sensing module, and to obtain a WiFi effective signal by performing adaptive noise reduction on the synchronous sensing signal. An alignment unit is configured to receive the millimeter wave effective signal and the WiFi effective signal by a signal processing module, to perform time domain alignment on the millimeter wave effective signal and the WiFi effective signal, and to calculate a signal strength difference and a phase deviation between the millimeter wave effective signal and the WiFi effective signal. A judgment unit is configured to judge whether a target to be sensed exists in the target area according to the signal strength difference and the phase deviation. A calculation unit is configured to calculate a motion speed and a position coordinate of the target to be sensed by a triangulation algorithm based on the millimeter wave effective signal and the WiFi effective signal after time domain alignment, if the judgment result is that the target to be sensed exists. An output unit is configured to output the motion speed and the position coordinate of the target to be sensed by the signal processing module.

[0012] The application further provides a computer device including a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the millimeter wave and WiFi dual-frequency sensing method when executing the computer program.

[0013] The application further provides a computer readable storage medium storing a computer program, and the computer program implementing the steps of the millimeter wave and WiFi dual-frequency sensing method when executed by a processor.

[0014] The millimeter wave and WiFi dual-frequency sensing method, device and computer device provided by the application have the following beneficial effects: The processing methods are designed according to the characteristics of dual-frequency signals: the millimeter wave signal is processed by mean filtering combined with abnormal point elimination to effectively remove fixed environmental interference; the WiFi signal is processed by adaptive noise reduction based on noise characteristics to specifically suppress dynamic interference, and the quality of dual-frequency effective signals is significantly improved; The time sequence consistency of millimeter wave and WiFi signals is ensured by time domain alignment, which provides a reliable basis for subsequent parameter calculation and target judgment, and avoids correlation errors caused by time sequence deviation; The existence of a target is judged based on the signal strength difference and the phase deviation, which is stronger in anti-environment fluctuation ability and improves the target recognition accuracy compared with single parameter judgment; The triangular positioning algorithm combines the time difference of the propagation of the dual-frequency signals, fully utilizes the complementary characteristics of the strong penetration of the millimeter wave signal and the wide coverage of the WiFi signal, and controls the position calculation error of the target within 0.5 meters and the motion speed calculation error within 0.1 m / s, so as to meet the high-precision sensing demand. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a flowchart of a millimeter wave and WiFi dual-frequency sensing method in an embodiment of the present application; Figure 2 is a structural block diagram of a millimeter wave and WiFi dual-frequency sensing device in an embodiment of the present application; Figure 3 is a structural schematic block diagram of a computer device in an embodiment of the present application.

[0016] The implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application.

[0018] Reference Figure 1 is a flowchart of a millimeter wave and WiFi dual-frequency sensing method in an embodiment of the present application, including the following steps: S1, obtaining an initial sensing signal of a target area through a millimeter wave sensing module, performing mean filtering processing on the initial sensing signal to obtain a millimeter wave effective signal; S2, obtaining a synchronous sensing signal of the same target area through a WiFi sensing module, performing adaptive noise reduction processing on the synchronous sensing signal to obtain a WiFi effective signal; S3, a signal processing module receives the millimeter wave effective signal and the WiFi effective signal, performs time domain alignment operation on the millimeter wave effective signal and the WiFi effective signal, and calculates the signal strength difference and the phase deviation value between the millimeter wave effective signal and the WiFi effective signal; S4, judging whether there is a target to be sensed in the target area according to the signal strength difference and the phase deviation value; S5, if the judgment result is that there is a target to be sensed, calculating the motion speed and position coordinates of the target to be sensed based on the millimeter wave effective signal and the WiFi effective signal after time domain alignment through a triangular positioning algorithm; S6, the signal processing module outputs the motion speed and position coordinates of the target to be sensed.

[0019] In step S1, an initial sensing signal of a target area is obtained by a millimeter wave sensing module, and a mean filtering process is performed on the initial sensing signal to obtain a millimeter wave effective signal, comprising: The millimeter wave sensing module collects signals of the target area at a sampling frequency of 500MHz-1GHz to obtain an initial sensing signal containing environmental interference components; The size of the sliding window of the mean filtering is set to 8-16 sampling points, the initial sensing signal is input into the sliding window, and the average signal amplitude of all sampling points in each sliding window is calculated; The average signal amplitude is used to replace the signal amplitude of the middle sampling point in the corresponding sliding window, and all sampling points of the initial sensing signal are sequentially traversed to obtain a preliminary filtered signal; The abnormal signal points in the preliminary filtered signal with amplitudes exceeding a preset threshold range are removed, the preset threshold range is 0.5-1.5 times the overall amplitude mean value of the preliminary filtered signal, and the remaining signal is the millimeter wave effective signal.

[0020] Specifically, the millimeter wave sensing module starts the signal collection function, and the sampling frequency is set to 500MHz-1GHz. The selection of the frequency range is based on the sensing requirements of the target area. It can ensure the capture accuracy of the subtle signal changes in the target area, avoid incomplete signal sampling and missing of key signal characteristics generated by target movement due to too low sampling frequency, and avoid excessive redundant data caused by too high frequency, thereby reducing the computational burden of the subsequent signal processing module. At this time, the initial sensing signal collected will inevitably contain environmental interference components, which mainly come from millimeter wave reflection signals of metal furniture in the target area, electromagnetic radiation signals generated by surrounding electrical equipment during operation, etc., which are all unrelated to the target to be sensed and need to be removed through filtering processing. Then, the mean filtering processing link is entered, and the sliding window size is set to 8-16 sampling points. The window size is verified through multiple scene experiments. If the window size is less than 8 sampling points, the smoothing effect on the continuously distributed environmental interference is insufficient, and the interference influence cannot be effectively weakened. If the window size is greater than 16 sampling points, the time resolution of the signal will decrease, and the signal edge details brought by the target to be sensed will be lost. After the initial sensing signal is sequentially input into the sliding window, the average value of the signal amplitude of all sampling points in each window is calculated. The average value can represent the overall characteristics of the local signal in the window, and the signal amplitude of the middle sampling points in the window is replaced with the average value. The influence of a single interference sampling point on the overall signal can be weakened through local statistical averaging. Then, the sliding window is moved in sequence from the beginning to the end of the signal, and the above calculation and replacement operations are repeated to obtain the preliminary filtered signal. A small number of transient burst interference points still exist in the preliminary filtered signal, such as transient electromagnetic pulses generated by the sudden start and stop of nearby equipment. The amplitude of the interference points deviates far from the normal signal range, and if it is retained, it will interfere with the use of subsequent effective signals. Therefore, it is necessary to remove abnormal points. Specifically, the average value of the amplitudes of all sampling points of the preliminary filtered signal is calculated, and the preset threshold range is set to 0.5-1.5 times the average value. The determination of the range is based on the amplitude distribution law of the effective signal in different indoor scenes. It can exclude invalid noise points with an amplitude less than 0.5 times the average value and burst interference points with an amplitude greater than 1.5 times the average value, and can also ensure that the effective signal components corresponding to the target to be sensed are not deleted. After removing the abnormal signal points that exceed the threshold range, the remaining signal is the millimeter wave effective signal that removes most of the environmental interference and can accurately reflect the related characteristics of the target to be sensed in the target area.

[0021] In step S2, the synchronous sensing signal of the same target area is obtained by the WiFi sensing module, and the adaptive noise reduction processing is performed on the synchronous sensing signal to obtain the WiFi effective signal. The step includes: The WiFi sensing module is aligned with the target area, and in a time window consistent with the time window in which the millimeter wave sensing module acquires an initial sensing signal, electromagnetic sensing data of the target area is collected, and the electromagnetic sensing data is taken as a synchronous sensing signal; Noise characteristics in the synchronous sensing signal are extracted, the noise characteristics including a frequency distribution range and an amplitude fluctuation interval of a noise signal; The noise reduction parameters are adjusted according to the noise characteristics, the noise reduction parameters including a time length of a filtering window and a signal amplitude screening threshold; The synchronous sensing signal is filtered by using the adjusted noise reduction parameters, and signal components in the synchronous sensing signal that meet the noise characteristics are removed; The filtered synchronous sensing signal is taken as a WiFi effective signal.

[0022] Specifically, the WiFi sensing module is aligned with the target area to ensure that the collection range accurately covers the space range to be sensed, avoiding irrelevant electromagnetic signals (such as wireless device signals in adjacent rooms) outside the target area from being mixed due to the deviation of the collection angle. At the same time, the WiFi sensing module and the millimeter wave sensing module acquire electromagnetic sensing data in a time window consistent with the initial sensing signal. The purpose of this time synchronization design is to enable the dual-frequency signals to have a correlatable basis in the time dimension. Since the WiFi signal is easily affected by other wireless devices (such as Bluetooth devices, other WiFi hotspots), wall reflection, and other factors in the environment during transmission, the synchronized sensing signal inevitably contains a large amount of noise components unrelated to the target to be sensed. Therefore, the noise characteristics in the synchronized sensing signal need to be extracted first. The frequency distribution range of the noise signal can be obtained through frequency spectrum analysis, for example, if there is a Bluetooth device operating in the 2.4 GHz frequency band in the environment, the noise frequency will be concentrated near this frequency band, and the amplitude fluctuation interval is determined by statistics of the amplitude range of the synchronized sensing signal in the no-target state. These two characteristics can accurately define the noise. Based on the extracted noise characteristics, the noise reduction parameters need to be adjusted dynamically according to the actual characteristics of the noise. If the noise frequency distribution is concentrated and fluctuates frequently, the length of the filter window needs to be set to a short interval (such as 10-20 ms) to avoid long window filtering out short-time effective signals generated by target movement. If the noise amplitude fluctuation interval is stable between -85 dBm and -75 dBm, the signal amplitude filtering threshold is set to -80 dBm to ensure that only noise components falling within this amplitude interval are removed. Based on the parameter adjustment method based on noise characteristics, unlike the traditional noise reduction method with fixed parameters, the noise reduction effect and effective signal preservation can be more accurately balanced, avoiding the problem of excessive noise reduction leading to target information loss or incomplete noise reduction still storing interference. Then, the synchronized sensing signal is filtered using the adjusted noise reduction parameters to remove signal components within the noise frequency distribution range through frequency filtering and remove noise points exceeding the set threshold through amplitude screening, achieving targeted noise removal. After this filtering process, the remaining components in the synchronized sensing signal are mainly the WiFi signal changes caused by the movement of the target to be sensed, obtaining the WiFi effective signal.

[0023] In one embodiment of step S3, the signal processing module receives the millimeter wave effective signal and the WiFi effective signal, and the step of performing time domain alignment operation on the millimeter wave effective signal and the WiFi effective signal includes: The signal processing module receives the millimeter wave effective signal and the WiFi effective signal respectively, and sets the millimeter wave effective signal as the reference signal for time domain alignment. The rising edge time of the reference signal is extracted as the first time feature point, and the rising edge time of the WiFi effective signal is extracted as the second time feature point. calculating a time difference between the second time feature point and the first time feature point; According to the time difference, adjusting the timing of the WiFi effective signal to make the second time feature point of the WiFi effective signal coincide with the first time feature point of the reference signal, completing the time domain alignment of the millimeter wave effective signal and the WiFi effective signal.

[0024] Specifically, WiFi signals are susceptible to multi-path effects and transmission delay fluctuations caused by wall obstructions. Millimeter wave signals have shorter wavelengths and stronger directivity, and their time characteristics are more stable when propagating in the same target area. The starting and changing moments of their signals are easier to capture accurately. When entering the time feature point extraction stage, the rising edge moment of the signal is selected as the feature point. Because the rising edge represents the mutation stage of the signal from the low amplitude state to the high amplitude state, the signal change rate is the largest and the characteristics are the most prominent. Compared with the signal peak (which is susceptible to amplitude fluctuations) or the falling edge (which has a slower change trend), the detection accuracy of the rising edge moment is higher. The rising edge moment of the millimeter wave effective signal can be extracted as the first time feature point, and the rising edge moment of the WiFi effective signal can be extracted as the second time feature point through the edge detection algorithm built-in the signal processing module, to ensure that the two feature points can accurately reflect the key time nodes of the respective signals. Next, the time difference between the second time feature point and the first time feature point is calculated, specifically by subtracting the time stamp corresponding to the first time feature point from the time stamp corresponding to the second time feature point. This difference directly quantifies the timing offset of the WiFi effective signal relative to the reference signal. If the difference is positive, it means that the WiFi effective signal lags behind the millimeter wave effective signal. If the difference is negative, it means that the WiFi effective signal leads the millimeter wave effective signal. Finally, according to the calculated time difference, the timing of the WiFi effective signal is adjusted. For example, when the difference is 1.2 ms (i.e., the WiFi signal lags), the signal processing module adjusts the timing of the WiFi effective signal by 1.2 ms through the built-in timing adjustment unit, so that the second time feature point of the WiFi effective signal coincides with the first time feature point of the millimeter wave effective signal on the time axis. The essence of this adjustment process is to eliminate the timing difference caused by the differences in hardware response of the acquisition module and the slight differences in propagation path, so that the millimeter wave signal and the WiFi signal used in subsequent calculations of signal strength difference and phase deviation value correspond to the same time node.

[0025] In a further embodiment of step S3, the step of calculating the signal strength difference and the phase deviation value between the millimeter wave effective signal and the WiFi effective signal comprises: The signal processing module extracts a first signal strength value and a first phase value of the time-domain aligned millimeter wave effective signal, and extracts a second signal strength value and a second phase value of the time-domain aligned WiFi effective signal; The first signal strength value is subtracted by the second signal strength value to obtain the signal strength difference value; The difference between the first phase value and the second phase value is calculated, and if the absolute value of the difference is greater than 180 degrees, the difference is added by 360 degrees or subtracted by 360 degrees to obtain the phase deviation value.

[0026] Specifically, the signal processing module first extracts a first signal strength value and a first phase value from the time-domain aligned millimeter wave effective signal through the built-in signal analysis unit. The first signal strength value reflects the energy attenuation degree of the millimeter wave signal after passing through the target area, and its size is related to the reflection characteristics and distance of the target. The first phase value reflects the phase change of the millimeter wave signal in the propagation process, which is significantly affected by target shielding and path length. When calculating the signal strength difference value, the first signal strength value is directly subtracted by the second signal strength value. The physical meaning of this difference value is to quantify the energy attenuation difference of two different frequency signals under the action of the same target. When the target area has a target to be sensed, due to the different reflection and absorption characteristics of the target to millimeter wave and WiFi signals, the difference value will deviate significantly from the baseline value under the no-target state. For example, the human body reflects millimeter waves strongly and absorbs WiFi signals more obviously, which will make the difference value present a specific range of positive values.

[0027] For the calculation of the phase deviation value, first, the difference between the first phase value and the second phase value is calculated. At this time, the periodicity of the phase needs to be considered. The phase value usually cycles with a period of 0-360 degrees. If the difference is directly taken, the result will not match the actual physical meaning (for example, the first phase value is 350 degrees and the second phase value is 10 degrees. The direct difference is 340 degrees, but the actual phase deviation should be -20 degrees). Therefore, when the absolute value of the calculated difference is greater than 180 degrees, the difference is adjusted by adding 360 degrees or subtracting 360 degrees (for example, 340 degrees minus 360 degrees to get -20 degrees), so that the final phase deviation value falls within the reasonable range of -180 degrees to 180 degrees. This range can truly reflect the physical meaning of the phase difference of the two signals, avoid the deviation caused by periodicity, and ensure the accuracy of subsequent target judgment based on the phase parameter. The signal strength difference value and the phase deviation value obtained through the above processing together constitute a two-dimensional feature parameter for judging whether a target exists. Compared with a single parameter, it can resist environmental interference and improve sensing reliability.

[0028] In step S4, according to the signal strength difference value and the phase deviation value, the step of judging whether a target to be sensed exists in the target area includes: The preset intensity difference threshold and the preset phase deviation threshold corresponding to the target sensing scene are set in advance; The calculated signal intensity difference is compared with the preset intensity difference threshold, and the calculated phase deviation value is compared with the preset phase deviation threshold; If the signal intensity difference is greater than the preset intensity difference threshold, and the phase deviation value is greater than the preset phase deviation threshold, it is determined that there is a target to be sensed in the target region; If the signal intensity difference is less than or equal to the preset intensity difference threshold, or the phase deviation value is less than or equal to the preset phase deviation threshold, it is determined that there is no target to be sensed in the target region.

[0029] Specifically, the preset intensity difference threshold and the preset phase deviation threshold corresponding to the target sensing scene are set. The two thresholds are not fixed values, but are calibrated through a large number of experiments in combination with specific application scenarios (such as smart home living room, office, security monitoring area, etc.); In the target scene, first, a blank test without a target to be sensed is performed, and the signal intensity difference and the phase deviation value in this state are collected as a reference, then a known target (such as a human body, a specific object) is introduced for multiple tests, and the minimum effective value of the two parameters when the target exists is counted. Finally, the preset intensity difference threshold is set to 1.2-1.5 times the maximum reference value in the blank state, and the preset phase deviation threshold is set to 1.3-1.6 times the maximum reference value in the blank state, to ensure that the threshold can effectively distinguish between the presence of a target and the absence of a target, and can also resist common environmental fluctuations in the scene (such as slight signal drift caused by temperature changes, and phase disturbance caused by slight vibration of the device).

[0030] Subsequently, the signal processing module compares the signal intensity difference calculated in step S3 with the preset intensity difference threshold, and compares the phase deviation value with the preset phase deviation threshold. The design of double-parameter comparison is because single-parameter judgment is easy to be affected by environmental interference and lead to misjudgment; for example, if only the signal intensity difference is relied on, the intensity difference will abnormally increase due to sudden electromagnetic interference (such as microwave oven working for a short time), and a misjudgment will be made. If only the phase deviation value is relied on, a misjudgment will be made due to the sudden contact failure of the device line. Through the double conditions of "the signal intensity difference is greater than the preset intensity difference threshold" and "the phase deviation value is greater than the preset phase deviation threshold", the complementary nature of the two parameters to the target response (the intensity attenuation and phase change of millimeter wave and WiFi signal to the same target have correlation but are not synchronized) can be utilized, and the probability of misjudgment caused by single interference factor can be greatly reduced.

[0031] When the two conditions are met at the same time, it indicates that the signal change in the target area is both in the energy attenuation dimension beyond the normal range of environmental interference and in the phase change dimension presents characteristics consistent with the target action, so it is determined that there is a target to be inducted; otherwise, if the signal intensity difference does not exceed the preset threshold (meaning that the energy change does not reach the characteristics of the target existence), or the phase deviation value does not exceed the preset threshold (meaning that the phase change does not conform to the law of target action), it is determined that there is no target to be inducted.

[0032] In step S5, if the judgment result is that there is a target to be inducted, based on the time-domain aligned millimeter wave effective signal and the WiFi effective signal, the step of calculating the motion speed and position coordinates of the target to be inducted by a triangular positioning algorithm includes: Selecting three preset signal receiving reference points in the target area, and recording the propagation time difference of the time-domain aligned millimeter wave effective signal and the WiFi effective signal received by each reference point; According to the known coordinates of the three signal receiving reference points and the corresponding propagation time difference, a spatial coordinate equation is established by a triangular positioning algorithm to obtain the initial position coordinates of the target to be inducted; Within a preset time interval, the propagation time difference of the time-domain aligned millimeter wave effective signal and the WiFi effective signal at the three signal receiving reference points is repeatedly obtained, and a plurality of position coordinates of the target to be inducted at different time points are calculated; According to the time information corresponding to the plurality of position coordinates, the displacement of the target to be inducted between adjacent two time points is calculated, and the motion speed of the target to be inducted is obtained in combination with the time interval; The initial position coordinates and the subsequent plurality of position coordinates of the target to be inducted are integrated to determine the final position coordinates of the target to be inducted.

[0033] Specifically, after determining that there is a target to be inducted, based on the time-domain aligned millimeter wave effective signal and the WiFi effective signal, the specific process of measuring the motion speed and position coordinates of the target to be inducted by a triangular positioning algorithm is as follows: selecting three preset non-collinear signal receiving reference points in the target area, recording the propagation time difference of the dual-frequency signal received by each reference point, and using the complementary characteristics of the dual-frequency signal to reduce the measurement deviation of a single frequency signal; according to the known coordinates of the three reference points and the corresponding propagation time difference, a spatial coordinate equation is established by a triangular positioning algorithm to obtain the initial position coordinates of the target to be inducted; within a preset time interval, the propagation time difference of the dual-frequency signal at each reference point is repeatedly obtained, and a plurality of position coordinates of the target at different time points are calculated; the displacement between adjacent time points is calculated according to the position coordinates, and the motion speed of the target is obtained in combination with the time interval; the initial position coordinates and the subsequent plurality of coordinates are integrated to determine the final position coordinates of the target to be inducted by a processing method of weakening random error.

[0034] The triangular positioning algorithm comprises: The position coordinates of the millimeter wave sensing module are The position coordinates of the first WiFi sensing module are The position coordinates of the second WiFi sensing module are The position coordinates of the target to be sensed are ; The distance between the target to be sensed P and the millimeter wave sensing module A is calculated , and the formula is ; The distance between the target to be sensed P and the first WiFi sensing module B is calculated , and the formula is ; The distance between the target to be sensed P and the second WiFi sensing module C is calculated , and the formula is ; By combining the above, the equation group is obtained: ; The equation group is expanded and eliminated, and the position coordinates of the target to be sensed are solved , The interval time is obtained The position coordinates of the target to be sensed obtained by the two times of calculation are and The formula is: ; The motion speed v of the target to be sensed is calculated.

[0035] In step S6, the signal processing module outputs the motion speed and position coordinates of the target to be sensed. The signal processing module first carries out format standardization processing on the calculated motion speed (unit unified as m / s, numerical value reserved two decimal places) and position coordinates (three-dimensional coordinates x, y, z, unit unified as meters, numerical value reserved two decimal places), so as to ensure that the data format is adapted to the receiving requirements of a subsequent application end (such as an intelligent home gateway or a security monitoring host); then, according to the application scene requirements, a corresponding output interface is selected; a UART interface is used in a short-distance transmission scene, and an Ethernet interface is used in a long-distance transmission scene, and the interface communication rate is set as 9600 bps-100 Mbps according to the data volume; before data transmission, the motion speed and position coordinate data are subjected to integrity checking through a CRC checking algorithm, if the checking is passed, data sending is started, if the checking fails, the effective data calculated in the previous sequence is re-called and checked again; after the data sending is completed, the signal processing module outputs a feedback signal, prompting that the application end has received complete data, and the application end can execute subsequent operations (such as intelligent home device linkage or target trajectory display) based on the motion speed and position coordinates.

[0036] Reference is made to the accompanying drawings Figure 2 A schematic diagram of a millimeter wave and WiFi dual-frequency sensing device is provided in the present application, and the device comprises: A millimeter wave unit is configured to acquire an initial sensing signal of a target area through a millimeter wave sensing module, and to obtain a millimeter wave effective signal by performing mean filtering processing on the initial sensing signal. A WiFi unit is configured to acquire a synchronous sensing signal of the same target area through a WiFi sensing module, and to obtain a WiFi effective signal by performing adaptive noise reduction processing on the synchronous sensing signal. An alignment unit is configured to receive the millimeter wave effective signal and the WiFi effective signal by a signal processing module, to perform time domain alignment operation on the millimeter wave effective signal and the WiFi effective signal, and to calculate a signal strength difference value and a phase deviation value between the millimeter wave effective signal and the WiFi effective signal. A judgment unit is configured to judge whether there is a target to be sensed in the target area according to the signal strength difference value and the phase deviation value. A calculation unit is configured to calculate the motion speed and position coordinates of the target to be sensed by a triangulation algorithm based on the millimeter wave effective signal and the WiFi effective signal after time domain alignment, if the judgment result is that there is a target to be sensed. An output unit is configured to output the motion speed and position coordinates of the target to be sensed by the signal processing module.

[0037] Reference is made to the accompanying drawings Figure 3 In the embodiments of the present application, a computer device is also provided, which can be a server, and the internal structure thereof can be as shown in Figure 3The computer device shown in the figure includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in the embodiment. The network interface of the computer device is used to communicate with the external terminal through the network connection. The computer program is executed by the processor to implement the above method.

[0038] Those skilled in the art can understand that, Figure 3 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the application, and does not constitute a limitation on the computer device to which the scheme of the application is applied.

[0039] The embodiment of the application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by the processor to implement the above method. It can be understood that the computer readable storage medium in the embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0040] To sum up, the application discloses a millimeter wave and WiFi dual-frequency induction method, which belongs to the technical field of target induction and is suitable for intelligent home, security monitoring and the like. The method solves the problems of inconsistent timing, poor noise reduction pertinence, high target misjudgment rate and insufficient positioning accuracy of the existing dual-frequency induction scheme. The method collects signals through a millimeter wave induction module and removes interference through mean filtering, synchronously collects signals through a WiFi induction module and adaptively reduces noise, and obtains dual-frequency effective signals. A signal processing module aligns the time domain of the dual-frequency signals, calculates a signal strength difference value and a phase deviation value, and determines the existence of a target through dual parameters. When the target exists, the motion speed and position coordinates of the target are calculated through a triangular positioning algorithm combined with the time difference of the dual-frequency signals of three reference points, and finally the data is standardized and output. The application improves the quality of dual-frequency signals, reduces the misjudgment rate, improves the positioning and speed measurement accuracy, and meets the high-precision induction demand.

[0041] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiment methods. Any reference to memory, storage, database or other medium provided by the present application and used in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM, etc.

[0042] It should be noted that in this document, the terms "comprising", "including", or any other variant thereof are intended to cover a non-exclusive inclusion, such that a process, device, article or method that comprises a list of elements does not only include those elements, but can also include other elements not expressly listed or inherent to the process, device, article or method. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, device, article or method that includes the element.

[0043] The above description is only the preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation, or direct or indirect application in other related technical fields, based on the content of the present application specification and drawings, are also included in the patent protection scope of the present application.

Claims

1. A dual-band induction method for millimeter wave and WiFi, characterized in that, The method comprises the following steps: acquiring initial sensing signals of a target area through a millimeter wave sensing module, performing mean filtering processing on the initial sensing signals to obtain millimeter wave effective signals; acquiring synchronous sensing signals of the same target area through a WiFi sensing module, performing adaptive noise reduction processing on the synchronous sensing signals to obtain WiFi effective signals; a signal processing module receives the millimeter wave effective signals and the WiFi effective signals, performs time domain alignment operation on the millimeter wave effective signals and the WiFi effective signals, and calculates signal strength difference and phase deviation between the millimeter wave effective signals and the WiFi effective signals; judging whether there is a target to be sensed in the target area according to the signal strength difference and the phase deviation; if the result of the judgment is that there is a target to be sensed, calculating the motion speed and position coordinates of the target to be sensed through a triangular positioning algorithm based on the millimeter wave effective signals and the WiFi effective signals after time domain alignment; the signal processing module outputs the motion speed and position coordinates of the target to be sensed. 2.The dual-band millimeter wave and WiFi sensing method of claim 1, wherein, The step of acquiring initial sensing signals of a target area through a millimeter wave sensing module and performing mean filtering processing on the initial sensing signals to obtain millimeter wave effective signals comprises: the millimeter wave sensing module collects signals of the target area at a sampling frequency of 500MHz-1GHz to obtain initial sensing signals containing environmental interference components; the size of the sliding window of mean filtering is set to 8-16 sampling points, the initial sensing signals are input into the sliding window, and the average signal amplitude of all sampling points in each sliding window is calculated; the average signal amplitude is used to replace the signal amplitude of the middle sampling point in the corresponding sliding window, and all sampling points of the initial sensing signals are sequentially traversed to obtain a preliminary filtered signal; abnormal signal points with amplitudes exceeding a preset threshold range are removed from the preliminary filtered signal, the preset threshold range is 0.5-1.5 times the average amplitude of the preliminary filtered signal as a whole, and the remaining signals are the millimeter wave effective signals. 3.The dual-band millimeter wave and WiFi sensing method of claim 1, wherein, The step of acquiring synchronous sensing signals of the same target area through a WiFi sensing module and performing adaptive noise reduction processing on the synchronous sensing signals to obtain WiFi effective signals comprises: the WiFi sensing module is aligned with the target area, and electromagnetic sensing data of the target area is collected in a time window consistent with the time window in which the millimeter wave sensing module acquires initial sensing signals, and the electromagnetic sensing data is taken as synchronous sensing signals; noise characteristics in the synchronous sensing signals are extracted, the noise characteristics including the frequency distribution range and amplitude fluctuation interval of noise signals; noise reduction parameters are adjusted according to the noise characteristics, the noise reduction parameters including the length of the filtering window and the signal amplitude screening threshold; the synchronous sensing signals are filtered using the adjusted noise reduction parameters to remove signal components in the synchronous sensing signals that meet the noise characteristics; the filtered synchronous sensing signals are taken as WiFi effective signals.

4. The dual-band mmWave and WiFi sensing method of claim 1, wherein, The signal processing module receives the millimeter-wave effective signal and the WiFi effective signal, and performs a time-domain alignment operation on the millimeter-wave effective signal and the WiFi effective signal, including: The signal processing module receives the millimeter-wave effective signal and the WiFi effective signal respectively, and sets the millimeter-wave effective signal as a time-domain aligned reference signal; The rising edge of the reference signal is extracted as the first time feature point, and the rising edge of the valid WiFi signal is extracted as the second time feature point. Calculate the time difference between the second time feature point and the first time feature point; Based on the time difference, the timing of the WiFi valid signal is adjusted so that the second time feature point of the WiFi valid signal coincides with the first time feature point of the reference signal, thereby completing the time domain alignment of the millimeter wave valid signal and the WiFi valid signal. 5.The dual-band millimeter wave and WiFi induction method of claim 1 or 4, wherein, The steps for calculating the signal strength difference and phase deviation between the effective millimeter-wave signal and the effective WiFi signal include: The signal processing module extracts the first signal strength value and the first phase value of the time-domain aligned millimeter-wave effective signal, and simultaneously extracts the second signal strength value and the second phase value of the time-domain aligned WiFi effective signal. The signal strength difference is obtained by subtracting the second signal strength value from the first signal strength value. Calculate the difference between the first phase value and the second phase value. If the absolute value of the difference is greater than 180 degrees, add 360 degrees to the difference or subtract 360 degrees to obtain the phase deviation value.

6. The dual-band mmWave and WiFi sensing method of claim 1, wherein, The step of determining whether a target to be sensed exists within the target area based on the signal strength difference and the phase deviation value includes: Pre-set the preset intensity difference threshold and preset phase deviation threshold corresponding to the target sensing scene; The calculated signal strength difference is compared with the preset strength difference threshold, and the calculated phase deviation value is compared with the preset phase deviation threshold. If the signal strength difference is greater than the preset strength difference threshold and the phase deviation is greater than the preset phase deviation threshold, then it is determined that there is a target to be sensed in the target area. If the signal strength difference is less than or equal to the preset strength difference threshold, or the phase deviation value is less than or equal to the preset phase deviation threshold, then it is determined that there is no target to be sensed in the target area.

7. The dual-band mmWave and WiFi sensing method of claim 1, wherein, If the determination result indicates the existence of a target to be sensed, the steps of calculating the motion speed and position coordinates of the target to be sensed using a triangulation algorithm based on the time-domain aligned millimeter-wave effective signal and the WiFi effective signal include: Three preset signal receiving reference points are selected within the target area, and the propagation time difference between the time-domain aligned millimeter wave effective signal and the WiFi effective signal received at each reference point is recorded respectively. Based on the known coordinates of the three signal receiving reference points and the corresponding propagation time difference, a spatial coordinate equation is established using a triangulation algorithm, and the initial position coordinates of the target to be sensed are obtained by solving the equation. The propagation time difference between the time-domain aligned millimeter wave effective signal and the WiFi effective signal at the three signal receiving reference points is repeatedly obtained within a preset time interval, and a plurality of position coordinates of the target to be sensed at different time points are calculated; According to the time information corresponding to the plurality of position coordinates, the displacement of the target to be sensed between two adjacent time points is calculated, and the motion speed of the target to be sensed is obtained in combination with the time interval; The initial position coordinate and the subsequent plurality of position coordinates of the target to be sensed are integrated to determine the final position coordinate of the target to be sensed. 8.The dual-band inductive method of millimeter wave and WiFi according to claim 1 or 7, characterized in that, The triangular positioning algorithm comprises: The position coordinates of the millimeter wave sensing module are , the position coordinates of the first WiFi sensing module are , the position coordinates of the second WiFi sensing module are , and the position coordinates of the target to be sensed are ; The distance from the target P to be induced to the millimeter wave induction module A is calculated The formula is: ； Calculate the distance from the target P to the first WiFi sensing module B The formula is: ； Calculate the distance from the target P to the second WiFi sensing module C The formula is: ； After simultaneous solution, the equation group is obtained: ； Solving the equation set by expansion and elimination, the position coordinates of the target to be induced are obtained , Acquisition interval time The target position coordinates obtained by the previous and subsequent calculations And By the formula: ； The motion speed v of the target to be sensed is calculated.

9. A dual-band mmWave and WiFi sensing device, characterized in that, It comprises: A millimeter wave unit is configured to obtain an initial sensing signal of a target area through a millimeter wave sensing module, and to obtain a millimeter wave effective signal by performing mean filtering on the initial sensing signal; A WiFi unit is configured to obtain a synchronous sensing signal of the same target area through a WiFi sensing module, and to obtain a WiFi effective signal by performing adaptive noise reduction on the synchronous sensing signal; An alignment unit is configured to receive the millimeter wave effective signal and the WiFi effective signal by a signal processing module, to perform time-domain alignment on the millimeter wave effective signal and the WiFi effective signal, and to calculate the signal strength difference and the phase deviation between the millimeter wave effective signal and the WiFi effective signal; A judgment unit is configured to determine whether there is a target to be sensed in the target area according to the signal strength difference and the phase deviation; A calculation unit is configured to calculate the motion speed and the position coordinate of the target to be sensed by a triangular positioning algorithm based on the time-domain aligned millimeter wave effective signal and the WiFi effective signal if the result of the judgment is that there is a target to be sensed; An output unit is configured to output the motion speed and the position coordinate of the target to be sensed by the signal processing module. 10.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-9. The processor executes the computer program to realize the steps of the millimeter wave and WiFi dual-frequency sensing method in any one of claims 1 to 8.

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