A human presence detection method, device, readable storage medium and terminal device

Abstract

The present application belongs to the field of human body detection technology, and in particular relates to a method, apparatus, computer-readable storage medium, and terminal device for detecting the presence of a human body. The method comprises obtaining a target radar intermediate frequency signal; wherein the target radar intermediate frequency signal is the radar intermediate frequency signal at the current moment; performing a distance-dimensional fast Fourier transform on the target radar intermediate frequency signal to obtain a target fast Fourier transform spectrum signal; calculating the degree of consistency between the target fast Fourier transform spectrum signal and a reference spectrum signal; wherein the reference spectrum signal is a fast Fourier transform spectrum signal obtained at a reference moment, and the reference moment is before the current moment; and determining a human presence detection result at the current moment based on the degree of consistency.

Description

Technical Field

[0001] The present application belongs to the field of human body detection technology, and in particular relates to a method, apparatus, computer-readable storage medium, and terminal device for detecting the presence of a human body. Background Art

[0002] With the development of intelligent technology, smart homes are gradually entering thousands of households, bringing numerous conveniences to people's lives. In this field, frequency-modulated continuous wave (FMCW) millimeter wave radar has a wide range of applications for close-range human presence detection. For example, a smart toilet can keep the lid open when a person is detected near it, or a smart desk lamp can automatically turn on the light when a person is detected near it.

[0003] Currently, when using FMCW millimeter-wave radar for human presence detection, it is usually necessary to perform three-dimensional fast Fourier transform calculations on the radar signal, which consumes a lot of time and computing power, resulting in low efficiency of the human presence detection method. Summary of the Invention

[0004] In view of this, embodiments of the present application provide a human presence detection method, apparatus, computer-readable storage medium, and terminal device to solve the problem of low efficiency of human presence detection methods in the prior art.

[0005] A first aspect of the embodiments of the present application provides a method for detecting the presence of a human body, which may include:

[0006] Acquire a target radar intermediate frequency signal; wherein the target radar intermediate frequency signal is the radar intermediate frequency signal at the current moment;

[0007] Performing a range-dimensional fast Fourier transform on the target radar intermediate frequency signal to obtain a target fast Fourier transform spectrum signal;

[0008] Calculating the consistency between the target fast Fourier transform spectrum signal and a reference spectrum signal; wherein the reference spectrum signal is a fast Fourier transform spectrum signal obtained at a reference time, and the reference time is before the current time;

[0009] Based on the consistency level, a human presence detection result at the current moment is determined.

[0010] A second aspect of the embodiments of the present application provides a human presence detection device, which may include:

[0011] A radar intermediate frequency signal acquisition module is used to acquire a target radar intermediate frequency signal; wherein the target radar intermediate frequency signal is the radar intermediate frequency signal at the current moment;

[0012] A fast Fourier transform module is used to perform a range-dimensional fast Fourier transform on the target radar intermediate frequency signal to obtain a target fast Fourier transform spectrum signal;

[0013] a consistency calculation module, configured to calculate the consistency between the target fast Fourier transform spectrum signal and a reference spectrum signal; wherein the reference spectrum signal is a fast Fourier transform spectrum signal obtained at a reference time, the reference time being before the current time;

[0014] The detection result determination module is used to determine the human presence detection result at the current moment based on the consistency level.

[0015] A third aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of any of the above-mentioned human presence detection methods are implemented.

[0016] The fourth aspect of an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the above-mentioned human presence detection methods when executing the computer program.

[0017] A fifth aspect of the embodiments of the present application provides a computer program product, which, when executed on a terminal device, enables the terminal device to execute the steps of any one of the above-mentioned human presence detection methods.

[0018] Compared with the prior art, the embodiments of the present application have the following advantages: the embodiments of the present application obtain a target radar intermediate frequency signal; wherein the target radar intermediate frequency signal is the radar intermediate frequency signal at the current moment; the target radar intermediate frequency signal is subjected to a range-dimensional fast Fourier transform to obtain a target fast Fourier transform spectrum signal; the consistency degree between the target fast Fourier transform spectrum signal and a reference spectrum signal is calculated; wherein the reference spectrum signal is a fast Fourier transform spectrum signal obtained at a reference moment, and the reference moment is before the current moment; based on the consistency degree, a human presence detection result at the current moment is determined. Through the embodiments of the present application, a range-dimensional fast Fourier transform can be performed on the radar intermediate frequency signal, and the consistency degree between the spectrum signal obtained after the fast Fourier transform and the reference spectrum signal obtained at a previous time is calculated. Based on the consistency degree, a human presence detection result can be determined. Compared with the existing solution that requires a three-dimensional fast Fourier transform, the embodiments of the present application only require a one-dimensional fast Fourier transform, which can greatly improve the efficiency of the human presence detection method, help save resources and computing power, and improve the scene adaptability of the human presence detection method. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 This is a flow chart of an embodiment of a method for detecting the presence of a human body in an embodiment of the present application;

[0021] Figure 2 It is a schematic diagram of radar detection signal and radar echo signal;

[0022] Figure 3 is a schematic diagram of a difference sequence between a fast Fourier transform spectrum signal and a reference spectrum signal at a certain moment;

[0023] Figure 4 This is a structural diagram of an embodiment of a human presence detection device in an embodiment of the present application;

[0024] Figure 5 This is a schematic block diagram of a terminal device in an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the purpose, features, and advantages of the invention of this application more obvious and easy to understand, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the embodiments described below are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0026] It will be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0027] It should also be understood that the terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0028] It should be further understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0029] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0030] In addition, in the description of the present application, the terms "first", "second", "third", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0031] With the development of intelligent technology, smart homes are gradually entering thousands of households, bringing numerous conveniences to people's lives. In this field, frequency-modulated continuous wave (FMCW) millimeter wave radar has many applications for close-range human presence detection. For example, if a person is detected near a smart toilet, the toilet lid will remain open. Another example is that if a person is detected near a smart desk lamp, the light will automatically turn on the light.

[0032] Currently, when using FMCW millimeter-wave radar for human presence detection, it is usually necessary to perform three-dimensional fast Fourier transform calculations on the radar signal. The calculation process involves multiple filtering and predictions, which consumes a lot of time and computing power, resulting in low efficiency of human presence detection methods.

[0033] In view of this, embodiments of the present application provide a human presence detection method, apparatus, computer-readable storage medium, and terminal device to solve the problem of low efficiency of human presence detection methods in the prior art.

[0034] It should be noted that the executor of the method of this application is a terminal device, which may include but is not limited to common smart home devices such as smart desk lamps, smart toilets, smart beds, smart door locks, and smart sofas.

[0035] See also Figure 1 In an embodiment of the present application, a method for detecting the presence of a human body may include:

[0036] Step S101: Acquire target radar intermediate frequency signal.

[0037] The target radar intermediate frequency signal is the radar intermediate frequency signal at the current moment.

[0038] In the embodiment of the present application, the terminal device may be pre-installed with an FMCW millimeter wave radar for real-time close-range detection. During close-range detection, the FMCW millimeter wave radar may be used to transmit radar detection signals to the monitoring area according to a preset detection cycle. At the same time, the feedback radar echo signal may be collected, such as Figure 2 By mixing the currently collected radar echo signal with the currently transmitted radar detection signal, an intermediate frequency signal can be obtained; based on this intermediate frequency signal, the distance information between each object in the monitoring area and the FMCW millimeter wave radar can be determined.

[0039] In an embodiment of the present application, at the current moment, an FMCW millimeter-wave radar can be used to transmit a group of radar detection signals to the monitoring area; wherein, a group of radar detection signals can include a preset number of individual radar detection signals; at the same time, a group of radar echo signals can also be collected, and a group of radar echo signals can also include the same number of individual radar echo signals as the radar detection signals; wherein, the specific value of the preset number can be concretized and situationally set according to actual needs, and this application does not limit this; here, the specific value of the preset number can preferably be set to 32, that is, a group of radar detection signals can include 32 radar detection signals, and a group of radar echo signals can include 32 radar echo signals.

[0040] Afterwards, the radar echo signal collected at the current moment can be mixed with the radar detection signal emitted at the current moment to obtain the radar intermediate frequency signal at the current moment (called the target radar intermediate frequency signal).

[0041] In a specific implementation of an embodiment of the present application, in order to facilitate analysis, the target radar intermediate frequency signal can also be filtered to obtain a filtered target radar intermediate frequency signal, and subsequent human presence detection can be performed based on the filtered target radar intermediate frequency signal.

[0042] Step S102: Perform a range-dimensional fast Fourier transform on the target radar intermediate frequency signal to obtain a target fast Fourier transform spectrum signal.

[0043] In an embodiment of the present application, a range-dimensional fast Fourier transform can be performed on the target radar intermediate frequency signal, so that the target radar intermediate frequency signal can be converted from a time domain signal to a frequency domain signal to obtain a target fast Fourier transform spectrum signal.

[0044] By using the target fast Fourier transform spectrum signal, the characteristics of the target radar intermediate frequency signal in the frequency domain and the distance dimension information can be efficiently analyzed while saving computing power and time.

[0045] Step S103: Calculate the consistency between the target fast Fourier transform spectrum signal and the reference spectrum signal.

[0046] Normally, radar detection signals can pass through non-metallic obstacles (such as ceramic toilet seats, plastic or wooden shells, etc.) and will spontaneously decay in the air.

[0047] If at a certain moment (for example, the first second), there is no human body in the monitoring area, the collected radar echo signal is usually a noise signal, or a severely attenuated signal obtained after multipath reflection from distant obstacles. Therefore, when there is no human body in the monitoring area, the radar echo signal has a large difference in the change trend at each frequency point and is more random. If there is still no human body in the monitoring area for a short period of time thereafter (for example, the first 1.5 seconds), the fast Fourier transform spectrum signal obtained in the first 1.5 seconds will also be a noise signal or a severely attenuated signal. The fast Fourier transform spectrum signal will also have the problem of large difference in change trend and strong randomness. If the fast Fourier transform spectrum signal obtained in the first second is subtracted from the fast Fourier transform spectrum signal obtained in the first 1.5 seconds, the obtained sequences will be disorganized and have poor consistency with each other. Figure 3 As shown in the figure; if there is a human body in the monitoring area at both the 1st second and the 1.5th second, the radar echo signals collected at the two moments will usually be stronger, and the changing trends of the radar echo signals at each frequency point will be similar, showing obvious consistency; if the fast Fourier transform spectrum signal obtained at the 1st second is subtracted from the fast Fourier transform spectrum signal obtained at the 1.5th second, the obtained sequences will be relatively similar, showing obvious consistency.

[0048] In this embodiment of the present application, a fast Fourier transform spectrum signal obtained at a time prior to the current moment (referred to as a reference moment) can be selected as a reference spectrum signal, and the degree of consistency between the target fast Fourier transform spectrum signal and the reference spectrum signal can be calculated. Because the fast Fourier transform spectrum signals obtained at both the reference moment and the current moment will show significant consistency (high consistency) only when a human body is present in the monitoring area, the human presence detection result can be determined based on the degree of consistency between the fast Fourier transform spectrum signals obtained at both moments.

[0049] In the embodiment of the present application, the target fast Fourier transform spectrum signal The transform spectrum data sequence may include a preset number of sequences , each transformed spectrum data sequence A radar intermediate frequency signal is obtained by fast Fourier transform, which can be recorded as ;in, for The number of transformed spectrum data sequences included in , that is, the number of radar detection signals included in a group of radar detection signals.

[0050] Specifically, since a group of radar detection signals includes various radar detection signals, corresponding intermediate frequency signals can be obtained; by performing fast Fourier transform on each intermediate frequency signal, various transformation spectrum data sequences can be obtained; and based on the various transformation spectrum data sequences, the target fast Fourier transform spectrum signal can be assembled.

[0051] For example, a group of radar detection signals includes 32 radar detection signals; based on this, 32 intermediate frequency signals can be obtained. By performing fast Fourier transform on the 32 intermediate frequency signals respectively, the corresponding transform spectrum data sequence (a total of 32 transform spectrum data sequences) can be obtained, and based on the 32 transform spectrum data sequences, the target fast Fourier transform spectrum signal can be constructed.

[0052] Each transform spectrum data sequence can include individual transform spectrum data. Each transform spectrum data is the spectrum energy corresponding to a range gate, which is recorded as ;in, is the number of range gates that the FMCW millimeter wave radar can detect, The specific value of can be determined by the detection range of the FMCW millimeter wave radar.

[0053] For example, the distance resolution of FMCW millimeter wave radar is 10 cm, and a total of 64 range gates can be detected, that is, is 64; therefore, it can be seen that the maximum distance that the FMCW millimeter wave radar can detect is 640 cm (10 cm * 64), so the transformed spectrum data sequence The spectrum energy corresponding to each of the 64 range gates can be included, which is recorded as ,in, for The spectrum energy corresponding to the 10th centimeter, for The spectral energy corresponding to the 20th centimeter... for The spectral energy corresponding to the 640th centimeter.

[0054] In an embodiment of the present application, a moment before the current moment can be used as a reference moment, and the fast Fourier transform spectrum signal obtained at the reference moment can be used as a reference spectrum signal. Any transformed spectrum data sequence in the reference spectrum signal can also be used as a reference spectrum data sequence in the reference spectrum signal.

[0055] For example, 0.5 seconds before the current moment can be used as the reference moment, and the fast Fourier transform spectrum signal obtained at the reference moment can be used as the reference spectrum signal; since the reference spectrum signal includes 32 transform spectrum data sequences, the first transform spectrum data sequence among the 32 transform spectrum data sequences can be used as the reference spectrum data sequence in the reference spectrum signal.

[0056] Here, the transformed spectrum data corresponding to the preset detection distance in the reference spectrum data sequence can also be used as the reference spectrum data. The detection distance can be specific and contextually set based on actual needs and radar performance, and this application does not limit this. For example, if the detection distance is 1 meter and the FMCW millimeter wave radar has a range resolution of 10 centimeters, the first 10 transformed spectrum data in the reference spectrum data sequence can be used as the reference spectrum data.

[0057] Similarly, the transformed spectrum data corresponding to the detection distance in the transformed spectrum data sequence can also be used as effective spectrum data.

[0058] In an embodiment of the present application, the difference between the effective spectrum data and the reference spectrum data in each transformed spectrum data sequence in the target fast Fourier transform spectrum signal can be calculated respectively to obtain a corresponding difference sequence.

[0059] Afterwards, the differences between the corresponding maximum spectrum data and minimum spectrum data in each difference sequence can be calculated respectively to obtain the differences of each spectrum data; among which, the maximum spectrum data is the maximum value of each difference in the difference sequence, and the minimum spectrum data is the minimum value of each difference in the difference sequence.

[0060] Here, the differences between the various spectral data can also be summed to obtain the target sum; in addition, the difference between the target maximum spectral data and the target minimum spectral data can also be calculated to obtain the target difference; among them, the target maximum spectral data is the maximum value among the various maximum spectral data, and the target minimum spectral data is the minimum value among the various minimum spectral data.

[0061] Based on the target difference and the target sum, the degree of consistency between the target fast Fourier transform spectrum signal and the reference spectrum signal can be determined; specifically, the ratio between the target sum and the target difference can be calculated, and then the degree of consistency between the target fast Fourier transform spectrum signal and the reference spectrum signal can be determined based on the ratio.

[0062] If the ratio is larger, it means that the difference between the target fast Fourier transform spectrum signal and the reference spectrum signal is greater, that is, the consistency between the target fast Fourier transform spectrum signal and the reference spectrum signal is smaller; if the ratio is smaller, it means that the difference between the target fast Fourier transform spectrum signal and the reference spectrum signal is smaller, that is, the consistency between the target fast Fourier transform spectrum signal and the reference spectrum signal is greater.

[0063] For ease of understanding, the calculation process of the consistency degree between the target fast Fourier transform spectrum signal and the reference spectrum signal in this application will be described below with reference to specific embodiments.

[0064] In this embodiment, a group of radar detection signals may include 32 radar detection signals, that is, N is 32; the range resolution of the FMCW millimeter wave radar is 10 cm, and a total of 64 range gates can be detected; that is, the target fast Fourier transform spectrum signal ; Each transformed spectrum data sequence can include the spectrum energy corresponding to 64 range gates; that is, .

[0065] Here, the detection distance can be set to 1 meter. Based on this, the spectrum energy corresponding to the first 10 range gates in each transformed spectrum data sequence can be set as the effective spectrum data. For example, for the first transformed spectrum data sequence In terms of in as effective spectrum data.

[0066] In addition, the 0.5 second before the current moment can be used as the reference moment, and the fast Fourier transform spectrum signal obtained at the reference moment can be used as the reference spectrum signal; and any transformed spectrum data sequence in the reference spectrum signal can be used as the reference spectrum data sequence; for example, the first transformed spectrum data sequence of the reference spectrum signal can be used as the reference spectrum data sequence, which is recorded as , since the detection distance is 1 meter, it can be The first 10 transformed spectrum data (i.e., ) as reference spectrum data.

[0067] Afterwards, the differences between the effective spectrum data and the reference spectrum data in each transformed spectrum data sequence in the target fast Fourier transform spectrum signal can be calculated respectively to obtain a corresponding difference sequence.

[0068] Take the first transform spectrum data sequence in the target fast Fourier transform spectrum signal For example, we can calculate in and in The difference between in and in The difference between... in and in The absolute value of the difference between The corresponding difference sequence is calculated as follows:

[0069] ,

[0070] in, for The corresponding difference sequence. The other transformed spectrum data sequences in the target fast Fourier transform spectrum signal can be calculated according to the above method to obtain the respective difference sequences.

[0071] Afterwards, the difference between the corresponding maximum spectrum data and minimum spectrum data in each difference sequence can be calculated to obtain each spectrum data difference, where the maximum spectrum data is the maximum value of each difference in the difference sequence, and the minimum spectrum data is the minimum value of each difference in the difference sequence.

[0072] Transform spectrum data sequence The corresponding difference sequence For example, if The maximum value of each difference is , the minimum value is , then you can Determined The maximum spectrum data ,Will Determined Minimum spectrum data ; Afterwards, the maximum spectrum data can be calculated With minimum spectrum data The difference between them, get the difference sequence The corresponding spectral data difference .

[0073] The other transformed spectrum data sequences in the target fast Fourier transform spectrum signal can be calculated according to the above method to obtain the spectrum data difference, that is, 、 、 .

[0074] Afterwards, the difference values of each spectrum data can be summed to obtain the target sum. The specific calculation formula is:

[0075]

[0076] in, For the goal and is the transformed spectrum data sequence The corresponding difference sequence The maximum spectrum data, is the transformed spectrum data sequence The corresponding difference sequence The minimum spectrum data.

[0077] Here, the maximum value and minimum value of each maximum spectrum data can also be determined, and the maximum value can be determined as the target maximum spectrum data, and the minimum value can be determined as the target minimum spectrum data. , target minimum spectrum data Afterwards, the target maximum spectrum data can be calculated With the target minimum spectrum data The difference between the two gets the target difference .

[0078] Based on goals and Difference from target , determine the degree of consistency; specifically, the target and Difference from target The ratio between ,Afterwards, the consistency degree between the target fast Fourier transform spectrum signal and the reference spectrum signal can be determined according to the ratio.

[0079] In a specific implementation, The reciprocal of is taken as the value of the consistency degree.

[0080] Step S104: Determine the human presence detection result at the current moment based on the consistency level.

[0081] In an embodiment of the present application, if the degree of consistency is less than or equal to a preset degree threshold, it can be considered that the degree of consistency between the target fast Fourier transform spectrum signal and the reference spectrum signal is small. At this time, it can be determined that the human presence detection result at the current moment is that there is no human body.

[0082] If the consistency degree is greater than the degree threshold, it can be considered that the consistency degree between the target fast Fourier transform spectrum signal and the reference spectrum signal is large. At this time, it can be determined that the human presence detection result at the current moment is that a human body exists.

[0083] Among them, the above-mentioned degree threshold can be specifically set according to actual needs, and this application does not limit this.

[0084] Based on this, human presence detection can be performed efficiently and conveniently without performing complex three-dimensional fast Fourier transform, which can greatly save computing power and cost, and reduce the performance requirements for the processor, so that the human presence detection method of the embodiment of the present application has stronger usability, and can help expand the application scenarios of FMCW millimeter wave radar (such as human micro-motion detection, human standing detection), and improve the scene adaptability of FMCW millimeter wave radar.

[0085] In an embodiment of the present application, the reference spectrum signal can also be updated based on a preset time interval; wherein, the update time interval can be specific and situational according to actual needs, and this application does not limit this.

[0086] Specifically, each reference spectrum signal update moment can be determined according to a preset time interval, and at each reference spectrum signal update moment, the fast Fourier transform spectrum signal obtained at the corresponding reference spectrum signal update moment can be determined as the reference spectrum signal. For example, the update time interval may be 0.4 seconds, that is, the reference spectrum signal is updated every 0.4 seconds. Based on this, the update times of the reference spectrum signal can be determined to be 0.4 seconds, 0.8 seconds, 1.2 seconds, etc. At 0.4 seconds, the radar intermediate frequency signal obtained at 0.4 seconds can be subjected to a range-dimensional fast Fourier transform to obtain a fast Fourier transform spectrum signal, and this fast Fourier transform spectrum signal can be determined as the reference spectrum signal. At 0.8 seconds, the radar intermediate frequency signal obtained at 0.8 seconds can be subjected to a range-dimensional fast Fourier transform to obtain a fast Fourier transform spectrum signal, and this fast Fourier transform spectrum signal can be determined as the reference spectrum signal. At 1.2 seconds, the radar intermediate frequency signal obtained at 1.2 seconds can be subjected to a range-dimensional fast Fourier transform to obtain a fast Fourier transform spectrum signal, and this fast Fourier transform spectrum signal can be determined as the reference spectrum signal.

[0087] Based on this, it can be guaranteed that timely and valuable reference spectrum signals are provided for the target radar intermediate frequency signals.

[0088] In a specific implementation of the embodiment of the present application, the human body detection state can also be determined based on the human body presence detection result; specifically, if the human body presence detection result at the current moment is that a human body exists, the human body detection state can be determined to be the first state; wherein the first state is the state in which a human body exists; if the human body presence detection result at the current moment is that a human body does not exist, the human body detection state can be determined to be the second state; wherein the second state is the state in which a human body does not exist; and according to the human body detection state, the terminal device can perform corresponding operations; for example, if the terminal device is a smart desk lamp, if the human body detection state is that a human body exists, the desk lamp can be automatically turned on; if the human body detection state is that a human body does not exist, the desk lamp can be automatically turned off. For another example, if the terminal device is a smart toilet, if the human body detection state is that a human body exists, the toilet lid can be automatically opened; if the human body detection state is that a human body does not exist, the toilet lid can be automatically closed.

[0089] In another specific implementation of the embodiment of the present application, if the human presence detection state changes too frequently, it may cause the operation of the terminal device to be too abrupt, thereby affecting the user experience. Therefore, in order to maintain a relatively stable human presence detection state, a timer may be set. After each reset, the timer can keep counting for a preset period of time. During this period, the human presence detection state can be maintained in a certain state, thereby reducing the frequent changes in the human presence detection state. If the human presence detection result at the current moment is that a human is present, the timer can be reset and the human presence detection state can be determined to be the first state. If the human presence detection result at the current moment is that a human is not present and the timer keeps counting, it can be determined that a human presence was detected a short time before the current moment. It can be considered that the current detection of human absence is likely a false positive, and the human presence detection state can be maintained in the first state. If the human presence detection result at the current moment is that a human is not present, but the timer does not count, it can be determined that a human was not detected a short time before the current moment. In this case, the human presence detection state can be determined to be the second state. Accordingly, each time a human presence is detected, the human presence detection state can be maintained in the first state for a period of time, reducing the frequent changes in the human presence detection state and improving the user experience.

[0090] In summary, the embodiment of the present application obtains a target radar intermediate frequency signal; wherein the target radar intermediate frequency signal is the radar intermediate frequency signal at the current moment; performs a distance-dimensional fast Fourier transform on the target radar intermediate frequency signal to obtain a target fast Fourier transform spectrum signal; calculates the consistency between the target fast Fourier transform spectrum signal and a reference spectrum signal; wherein the reference spectrum signal is a fast Fourier transform spectrum signal obtained at a reference moment, and the reference moment is before the current moment; based on the consistency, determines the human presence detection result at the current moment. Through the embodiment of the present application, the radar intermediate frequency signal can be subjected to a distance-dimensional fast Fourier transform, and the consistency between the spectrum signal obtained after the fast Fourier transform and the reference spectrum signal obtained a period of time before is calculated. Based on the consistency, the human presence detection result can be determined. Compared with the existing solution that requires a three-dimensional fast Fourier transform, the embodiment of the present application only requires a one-dimensional fast Fourier transform, which can greatly improve the efficiency of the human presence detection method, help save resources and computing power, and improve the scene adaptability of the human presence detection method.

[0091] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0092] Corresponding to the human presence detection method described in the above embodiment, Figure 4A structural diagram of an embodiment of a human presence detection device provided in an embodiment of the present application is shown.

[0093] In an embodiment of the present application, a human presence detection device may include:

[0094] The radar intermediate frequency signal acquisition module 401 is used to acquire the target radar intermediate frequency signal; wherein the target radar intermediate frequency signal is the radar intermediate frequency signal at the current moment;

[0095] A fast Fourier transform module 402 is configured to perform a range-dimensional fast Fourier transform on the target radar intermediate frequency signal to obtain a target fast Fourier transform spectrum signal;

[0096] A consistency calculation module 403 is configured to calculate a consistency between the target fast Fourier transform spectrum signal and a reference spectrum signal; wherein the reference spectrum signal is a fast Fourier transform spectrum signal obtained at a reference time, the reference time being before the current time;

[0097] The detection result determination module 404 is configured to determine a human presence detection result at a current moment based on the consistency level.

[0098] In a specific implementation of the embodiment of the present application, the radar intermediate frequency signal acquisition module includes:

[0099] The radar echo signal acquisition submodule is used to obtain the radar echo signal collected at the current moment;

[0100] The mixing processing submodule is used to mix the radar echo signal collected at the current moment with the radar detection signal transmitted at the current moment to obtain the target radar intermediate frequency signal.

[0101] In a specific implementation of the embodiment of the present application, the target fast Fourier transform spectrum signal includes various transform spectrum data sequences, each of the transform spectrum data sequences includes various transform spectrum data, the reference spectrum signal includes a reference spectrum data sequence, the reference spectrum data sequence includes various reference spectrum data, and the reference spectrum data is spectrum data corresponding to a preset detection distance in the reference spectrum data sequence;

[0102] The consistency degree calculation module includes:

[0103] a difference calculation submodule, configured to respectively calculate the difference between the effective spectrum data in each of the transformed spectrum data sequences and the reference spectrum data to obtain a corresponding difference sequence; wherein the effective spectrum data is the transformed spectrum data in the transformed spectrum data sequence corresponding to the detection distance;

[0104] The consistency level determination submodule is configured to determine the consistency level based on each of the difference value sequences.

[0105] In a specific implementation of the embodiment of the present application, the consistency level determination submodule includes:

[0106] a spectrum data difference calculation unit, configured to respectively calculate the difference between the corresponding maximum spectrum data and minimum spectrum data in each difference sequence to obtain each spectrum data difference; wherein the maximum spectrum data is the maximum value of each difference in the difference sequence, and the minimum spectrum data is the minimum value of each difference in the difference sequence;

[0107] a difference summing unit, configured to sum the differences of the spectrum data to obtain a target sum;

[0108] a target difference calculation unit, configured to calculate the difference between the target maximum spectrum data and the target minimum spectrum data to obtain a target difference; wherein the target maximum spectrum data is the maximum value among the maximum spectrum data, and the target minimum spectrum data is the minimum value among the minimum spectrum data;

[0109] A consistency level determination unit is configured to determine the consistency level based on the target difference and the target sum.

[0110] In a specific implementation of the embodiment of the present application, the detection result determination module includes:

[0111] a human body absence determination submodule, configured to determine that the human body presence detection result at the current moment is that a human body does not exist if the consistency level is less than or equal to a preset level threshold;

[0112] The human body presence determination submodule is configured to determine that the human body presence detection result at the current moment is that a human body exists if the consistency level is greater than the level threshold.

[0113] In a specific implementation of the embodiment of the present application, the apparatus further includes:

[0114] a first state determination module, configured to reset a timer and determine the human body detection state as a first state if the human body presence detection result at the current moment is that a human body is present; wherein the timer keeps counting for a preset period of time after being reset, and the first state is a state in which a human body is present;

[0115] a second state determination module, configured to determine the human body detection state as the first state if the human body presence detection result at the current moment is that no human body exists and the timer keeps counting;

[0116] The third state determination module is used to determine the human body detection state as the second state if the human body presence detection result at the current moment is that there is no human body and the timer is not timing; wherein the second state is a state where no human body is detected.

[0117] In a specific implementation of the embodiment of the present application, the apparatus further includes:

[0118] An update time determination module, configured to determine the update time of each reference spectrum signal based on a preset time interval;

[0119] The reference spectrum signal updating module is used to update the reference spectrum signal at each reference spectrum signal updating moment.

[0120] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices, modules and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0121] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0122] Figure 5 A schematic block diagram of a terminal device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0123] like Figure 5 As shown, the terminal device 5 of this embodiment includes: a processor 50, a memory 51, and a computer program 52 stored in the memory 51 and executable on the processor 50. When the processor 50 executes the computer program 52, the steps in the above-mentioned embodiments of the human presence detection method are implemented, such as Figure 1 Alternatively, when the processor 50 executes the computer program 52, the functions of the modules / units in the above-mentioned device embodiments are realized, for example, Figure 4 Functions of modules 401 to 404 are shown.

[0124] Exemplarily, the computer program 52 may be divided into one or more modules / units, which are stored in the memory 51 and executed by the processor 50 to implement the present application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 52 in the terminal device 5.

[0125] Those skilled in the art will understand that Figure 5It is only an example of the terminal device 5 and does not constitute a limitation on the terminal device 5. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal device 5 may also include input and output devices, network access devices, buses, etc.

[0126] The processor 50 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0127] The memory 51 can be an internal storage unit of the terminal device 5, such as a hard drive or memory of the terminal device 5. The memory 51 can also be an external storage device of the terminal device 5, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Furthermore, the memory 51 can include both an internal storage unit of the terminal device 5 and an external storage device. The memory 51 is used to store the computer program and other programs and data required by the terminal device 5. The memory 51 can also be used to temporarily store data that has been output or is about to be output.

[0128] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0129] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0130] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0131] In the embodiments provided in this application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0132] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0133] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0134] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application can implement all or part of the process steps in the above-mentioned method embodiments by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable storage medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal, and software distribution medium. It should be noted that the content of the computer-readable storage medium can be appropriately increased or decreased based on the requirements of legislation and patent practice in a jurisdiction. For example, in some jurisdictions, based on legislation and patent practice, computer-readable storage media do not include electric carrier signals and telecommunication signals.

[0135] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for detecting the presence of a human body, characterized in that: include: Acquire a target radar intermediate frequency signal; wherein the target radar intermediate frequency signal is the radar intermediate frequency signal at the current moment; The obtaining of the target radar intermediate frequency signal comprises: Get the radar echo signal collected at the current moment; Mixing the radar echo signal collected at the current moment with the radar detection signal transmitted at the current moment to obtain the target radar intermediate frequency signal; Performing a range-dimensional fast Fourier transform on the target radar intermediate frequency signal to obtain a target fast Fourier transform spectrum signal; Calculating the degree of consistency between the target fast Fourier transform spectrum signal and the reference spectrum signal; wherein the reference spectrum signal is a fast Fourier transform spectrum signal obtained at a reference moment, and the reference moment is a moment before the current moment; the target fast Fourier transform spectrum signal includes various transform spectrum data sequences, each of the transform spectrum data sequences includes various transform spectrum data, the reference spectrum signal includes a reference spectrum data sequence, the reference spectrum data sequence includes various reference spectrum data, and the reference spectrum data is spectrum data in the reference spectrum data sequence corresponding to a preset detection distance; Calculating the consistency between the target fast Fourier transform spectrum signal and the reference spectrum signal includes: Calculating the difference between the effective spectrum data in each of the transformed spectrum data sequences and the reference spectrum data to obtain a corresponding difference sequence; wherein the effective spectrum data is the transformed spectrum data in the transformed spectrum data sequence corresponding to the detection distance; Determining the degree of consistency based on each of the difference sequences; The determining the consistency level based on each of the difference value sequences includes: Calculating the difference between the corresponding maximum spectrum data and minimum spectrum data in each difference sequence respectively to obtain each spectrum data difference; wherein the maximum spectrum data is the maximum value of each difference in the difference sequence, and the minimum spectrum data is the minimum value of each difference in the difference sequence; Summing the differences of the spectral data to obtain a target sum; Calculating the difference between the target maximum spectrum data and the target minimum spectrum data to obtain a target difference; wherein the target maximum spectrum data is the maximum value of each of the maximum spectrum data, and the target minimum spectrum data is the minimum value of each of the minimum spectrum data; determining the degree of consistency based on the target difference and the target sum; Based on the consistency level, a human presence detection result at the current moment is determined.

2. The method for detecting human presence according to claim 1, wherein: Determining a human presence detection result at a current moment based on the consistency level includes: If the consistency level is less than or equal to a preset level threshold, determining that the human presence detection result at the current moment is that no human body exists; If the consistency level is greater than the level threshold, it is determined that the human body presence detection result at the current moment is that a human body exists.

3. The method for detecting human presence according to claim 2, wherein: After determining the human presence detection result at the current moment based on the consistency level, the method further includes: If the human presence detection result at the current moment is that a human body is present, the timer is reset and the human body detection state is determined to be a first state; wherein the timer keeps timing for a preset period after being reset, and the first state is a state in which a human body is present; If the human presence detection result at the current moment is that no human body exists and the timer keeps counting, the human body detection state is determined to be the first state; If the human presence detection result at the current moment is that no human body exists and the timer is not counting, the human body detection state is determined to be a second state; wherein the second state is a state in which no human body is detected.

4. The method for detecting human presence according to any one of claims 1 to 3, wherein: Also includes: Determining the update time of each reference spectrum signal based on a preset time interval; At each reference spectrum signal update moment, the reference spectrum signal is updated.

5. A human presence detection device, characterized in that: include: A radar intermediate frequency signal acquisition module is configured to acquire a target radar intermediate frequency signal; wherein the target radar intermediate frequency signal is the radar intermediate frequency signal at the current moment; acquiring the target radar intermediate frequency signal includes: acquiring a radar echo signal collected at the current moment; mixing the radar echo signal collected at the current moment with the radar detection signal transmitted at the current moment to obtain the target radar intermediate frequency signal; A fast Fourier transform module is used to perform a range-dimensional fast Fourier transform on the target radar intermediate frequency signal to obtain a target fast Fourier transform spectrum signal; A consistency calculation module is used to calculate the consistency between the target fast Fourier transform spectrum signal and the reference spectrum signal; wherein, the reference spectrum signal is the fast Fourier transform spectrum signal obtained at a reference moment, and the reference moment is a moment before the current moment; the target fast Fourier transform spectrum signal includes various transform spectrum data sequences, each of the transform spectrum data sequences includes various transform spectrum data, the reference spectrum signal includes a reference spectrum data sequence, the reference spectrum data sequence includes various reference spectrum data, and the reference spectrum data is the spectrum data corresponding to the preset detection distance in the reference spectrum data sequence; the calculation of the consistency between the target fast Fourier transform spectrum signal and the reference spectrum signal includes: respectively calculating the difference between the effective spectrum data in each of the transform spectrum data sequences and the reference spectrum data to obtain a corresponding difference sequence; wherein, the effective spectrum data is The transformed spectrum data corresponding to the detection distance in the transformed spectrum data sequence; determining the degree of consistency based on each of the difference sequences; determining the degree of consistency based on each of the difference sequences, including: respectively calculating the difference between the corresponding maximum spectrum data and minimum spectrum data in each of the difference sequences to obtain each spectrum data difference; wherein the maximum spectrum data is the maximum value of each difference in the difference sequence, and the minimum spectrum data is the minimum value of each difference in the difference sequence; summing up each of the spectrum data differences to obtain a target sum; calculating the difference between the target maximum spectrum data and the target minimum spectrum data to obtain a target difference; wherein the target maximum spectrum data is the maximum value of each of the maximum spectrum data, and the target minimum spectrum data is the minimum value of each of the minimum spectrum data; determining the degree of consistency based on the target difference and the target sum; The detection result determination module is used to determine the human presence detection result at the current moment based on the consistency level.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the human presence detection method according to any one of claims 1 to 4 are implemented.

7. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the human presence detection method according to any one of claims 1 to 4 are implemented.

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