WO2023005821A1 - Procédé de détection d'être vivant, terminal et support de stockage - Google Patents

Procédé de détection d'être vivant, terminal et support de stockage Download PDF

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Publication number
WO2023005821A1
WO2023005821A1 PCT/CN2022/107272 CN2022107272W WO2023005821A1 WO 2023005821 A1 WO2023005821 A1 WO 2023005821A1 CN 2022107272 W CN2022107272 W CN 2022107272W WO 2023005821 A1 WO2023005821 A1 WO 2023005821A1
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Prior art keywords
distance
dimension data
distance detection
target
index
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PCT/CN2022/107272
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English (en)
Chinese (zh)
Inventor
尹学良
秘石
包红燕
张昆
秦屹
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森思泰克河北科技有限公司
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Publication of WO2023005821A1 publication Critical patent/WO2023005821A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/04—Systems determining presence of a target
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • G01S13/08—Systems for measuring distance only
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications

Definitions

  • the present application belongs to the technical field of life detection, and in particular relates to a life detection method, a terminal and a computer-readable storage medium.
  • the internal temperature of the car can reach the critical value of heat stroke within 15 minutes. If there is a living body in the car at this time, such as an infant, its life safety will be seriously threatened.
  • life detection sensors mainly include infrared detectors, ultrasonic radars, and cameras.
  • Active infrared detectors are easily interfered by various heat sources and sunlight sources.
  • passive infrared detectors the infrared radiation of the human body is easily blocked and not easily received by the alarm; especially when the ambient temperature is close to the temperature of the human body, the detection ability and sensitivity of the passive infrared detector will drop significantly, and in severe cases, short-term Failure situation.
  • the resolution of ultrasonic radar is poor, and the detection effect is poor in complex environments; especially at high temperatures, the sensitivity of ultrasonic radar will drop sharply.
  • Cameras have extremely high requirements on light, are easily affected by dust, are expensive, and are not conducive to protecting the privacy of passengers.
  • the present application provides a living body detection method, a terminal and a storage medium, which can improve the precision of living body detection.
  • the first aspect of the present application provides a living body detection method, the method is applied to millimeter wave radar and includes:
  • the acquiring the distance dimension data of the millimeter-wave radar includes:
  • the intermediate frequency signal corresponding to the echo signal is obtained through signal processing, and the intermediate frequency signal is fast Fourier transformed to obtain the corresponding signal of the receiving antenna.
  • the distance dimension data wherein, one transmitting antenna of the millimeter-wave radar transmits a group of chirp signals, and the echo signals received by multiple receiving antennas of the millimeter-wave radar are echoes corresponding to the chirp signals wave signal;
  • the distance dimension data of the millimeter-wave radar is acquired through the distance dimension data corresponding to at least one receiving antenna.
  • the acquiring the distance dimension data of the millimeter wave radar includes:
  • the distance dimension data corresponding to at least two receiving antennas are coherently accumulated to obtain the distance dimension data of the millimeter wave radar.
  • the method further includes:
  • the amplitude difference of the distance dimension data at the kth time and the k-1th time is filtered.
  • the determining whether there is a target at the Nth moment according to the frequency spectrum corresponding to the n distance detection units includes:
  • any distance detection unit search for a maximum value within the preset frequency range, and obtain an index number corresponding to the maximum value
  • the index number corresponding to the maximum value obtain an index range of a preset size centered on the index number of the maximum value
  • the distance detection unit corresponds to The eigenvalues for include:
  • the characteristic value conf corresponding to the distance detection unit is obtained through a preset formula, and the preset formula is:
  • the judging whether there is a target at the Nth moment according to the eigenvalues corresponding to the n distance detection units includes:
  • the feature values corresponding to the n distance detection units are all greater than or equal to a preset threshold, it is determined that there is a target at the Nth moment.
  • the method further includes:
  • the target exists at R time points among the M time points, it is determined that the target exists, and R is greater than or equal to a preset value.
  • the present application provides a terminal, including a memory, a processor, and a computer program stored in the memory and operable on the processor.
  • the processor executes the computer program, the above-mentioned Steps in the method described in one aspect or any possible implementation manner of the first aspect.
  • the present application provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, any one of the above first aspect or the first aspect is implemented. Possible implementations of the steps of the method.
  • This application provides a living body detection method, terminal and storage medium, which can detect the target position through millimeter-wave radar, and calculate the range-dimension signal amplitude of the target position at a certain moment; after continuously accumulating amplitude changes at multiple moments, the data Carry out frequency domain analysis; then use the frequency domain features to judge whether there is a frequency that matches the micro-movement characteristics of the living body, and finally identify whether there is a target living body in the detected space.
  • the living body detection method provided in the present application can accurately identify the micro-movement characteristics of the living body, and improves the detection accuracy of the living body.
  • Fig. 1 is the implementation flowchart of the living body detection method provided by one embodiment of the present application
  • FIG. 2 is a flow chart of the implementation of a living body detection method provided by another embodiment of the present application.
  • Fig. 3 is a schematic structural diagram of a living body detection device provided by an embodiment of the present application.
  • FIG. 4 is a schematic diagram of a terminal provided by an embodiment of the present application.
  • FIG. 1 shows a flow chart of an implementation of a living body detection method provided by an embodiment of the present application.
  • the living body detection method includes step S101 to step S105. Each step is described in detail below.
  • the living body detection method provided in this application can be applied to millimeter wave radar.
  • Millimeter wave radar uses a large bandwidth signal, which has extremely high detection accuracy and is not affected by light, temperature, dust, etc.
  • the millimeter wave radar can have multiple receiving antennas.
  • the intermediate frequency signal corresponding to the echo signal can be obtained through signal processing; and then the intermediate frequency signal is subjected to fast Fourier transform to obtain the corresponding distance dimension data.
  • one transmitting antenna of the millimeter-wave radar can transmit a group of chirp signals; the echo signals received by multiple receiving antennas of the millimeter-wave radar are echo signals corresponding to the chirp signals.
  • the distance dimension data of the millimeter wave radar described in step S101 includes distance dimension data corresponding to at least one receiving antenna.
  • the distance dimension data corresponding to one or more receiving antennas may be selected as the distance dimension data of the millimeter wave radar.
  • the millimeter-wave radar can adopt the method of single transmission and multiple reception, that is, one transmitting antenna can be selected to transmit a group of chirp signals (ie, chirp signals), and correspondingly multiple receiving antennas can receive them. After these receiving antennas receive the echo signals, they convert the echo signals into intermediate frequency signals through signal processing technology; then perform FFT (fast Fourier transform) on the intermediate frequency signals to obtain distance dimension data.
  • one transmitting antenna can be selected to transmit a group of chirp signals (ie, chirp signals), and correspondingly multiple receiving antennas can receive them.
  • FFT fast Fourier transform
  • the distance dimension data corresponding to at least two receiving antennas can be coherently accumulated to obtain the millimeter wave radar The distance dimension data of .
  • the distance dimension data corresponding to two or more receiving antennas are coherently accumulated to improve the signal-to-noise ratio of echo data in a certain direction, thereby improving the detection capability in this direction.
  • coherent accumulation is a well known technique in the art.
  • the space to be detected may be the interior space of a car, or other spaces where life detection is required, which is not limited in this application.
  • the preset effective distance range can be expressed as [RangeStart, RangeEnd], which can be reasonably set according to the actual situation of the detected space, the range to be detected, and the layout position of the millimeter-wave radar.
  • the distance dimension data obtained in step S101 is intercepted according to the effective distance range.
  • the obtained intercepted data includes a plurality of distance detection units, and each distance detection unit corresponds to a target index targetIndex.
  • the approximate distance of the micro-moving target can be determined.
  • step S103 determines the neighborhood range of the distance detection unit corresponding to the target index, that is, [targetIndex - binIndex, targetIndex + binIndex]; where the size of binIndex can be set in advance.
  • the neighborhood range namely [targetIndex - binIndex, targetIndex + binIndex]
  • n adjacent distance detection units can be obtained.
  • the magnitude difference between the distance dimension data at the kth moment and the k-1th moment of each distance detection unit can be obtained sequentially through the first formula; the first formula is:
  • diffA m,k represents the amplitude difference of the m-th distance detection unit at time k
  • a m,k represents the range dimension data amplitude of the m-th distance detection unit at time k
  • a m,k-1 represents the time k-1
  • any distance detection unit in order to filter out clutter and further improve the accuracy of life detection, any distance detection unit can be processed as follows:
  • the amplitude difference of the distance dimension data at the kth time and the k-1th time is filtered.
  • the preset frequency may be the movement frequency of the chest and abdominal cavity when the human body breathes in a state of deep sleep.
  • frequency filtering may be performed on the amplitude difference diffA m,k of the m-th distance detection unit obtained at time k.
  • the preset frequency range can be set to 0.1-0.6 Hz.
  • the main micro-movement feature comes from the change of the chest and abdominal cavity during breathing, and the frequency of this change is generally 0.1-0.6Hz.
  • a Butterworth IIR Bandpass filter can be used to implement filtering.
  • the cutoff frequency of the filter is set to a preset frequency range, such as 0.1-0.6Hz. In this way, the interference caused by out-of-band clutter can be filtered out to a certain extent.
  • the filtered data at time k can be put into the data buffer buffer corresponding to the distance detection unit. Multi-time data accumulation can be carried out in the data buffer buffer.
  • step S104 performs windowing and FFT processing on the time-domain data in the data buffer buffer, so as to obtain the frequency spectrum corresponding to the n distance detection units within the target neighborhood.
  • windowing and Fourier transform are well-known technologies in the art.
  • step S105 according to the frequency spectrums corresponding to the n distance detection units, it can be judged whether there is a frequency conforming to the breathing characteristics of the human body, so as to judge whether there is a human body in the detected space.
  • the life detection method shown in Figure 1 can detect the target position through the millimeter-wave radar, and calculate the range dimension signal amplitude of the target position at a certain moment; after continuously accumulating amplitude changes at multiple moments, the data Carry out frequency domain analysis; then use the frequency domain features to judge whether there is a frequency that matches the micro-movement characteristics of the living body, and finally identify whether there is a target living body in the detected space.
  • the above detection method can accurately identify the micro-movement characteristics of the living body, and improves the detection accuracy of the living body.
  • Fig. 2 shows a flow chart of implementing a method for detecting a living body provided by another embodiment of the present application.
  • the living body detection method includes step S201 to step S204. Each step is described in detail below.
  • the distance detection unit can be obtained by intercepting the distance dimension data of the millimeter wave radar.
  • the frequency spectrum of the distance detection unit can be obtained by performing fast Fourier transform on the relevant data corresponding to the distance detection unit.
  • step S201 after obtaining the frequency spectrum corresponding to n distance detection units at the Nth time, analyze the frequency spectrum characteristics of each distance detection unit at this time.
  • Each distance detection unit corresponds to an index number.
  • this step obtains the eigenvalues in the following way:
  • the characteristic value conf corresponding to the distance detection unit is obtained through a preset formula; the preset formula is:
  • step S204 count the eigenvalues in the frequency domain corresponding to the n distance detection units in the target neighborhood at the Nth moment; if the eigenvalues in the frequency domain corresponding to the n distance detection units in the target neighborhood all meet the preset
  • the decision-making condition can judge that there is a target at the Nth moment, otherwise there is no target.
  • the aforementioned preset decision-making condition is: at the Nth moment, the feature values corresponding to the n distance detection units are all greater than or equal to a preset threshold Threshold.
  • the detection method provided by this embodiment can also use the following decision-making method: judge whether there is a target at each time in the M consecutive moments after the Nth moment including the Nth moment; , if there is a target at R times, it is judged that there is a target; R is greater than or equal to the preset value.
  • the life detection method shown in Figure 2 can obtain the characteristic value of each distance detection unit at the Nth moment through the frequency spectrum corresponding to each distance detection unit, and judge whether there is a target based on this; the detection method can Effective detection of living organisms in the detected space, such as the remaining members of the car; especially for infants and children in a deep sleep state, even if they do not have large-scale movements of their limbs, they can also be detected due to the micro-movement characteristics of the thorax and abdomen. , are accurately identified by millimeter-wave radar.
  • FIG. 3 is a schematic structural diagram of a living body detection device provided by the present application. For ease of description, FIG. 3 only shows the parts related to the present application. The living body detection device provided by the present application will be described in detail below.
  • the living body detection device 3 includes a distance dimension data acquisition unit 31 , a target index acquisition unit 32 , an amplitude difference acquisition unit 33 , a frequency spectrum acquisition unit 34 and a discrimination unit 35 .
  • the distance-dimension data acquiring unit 31 is configured to execute the aforementioned step S101, that is, to acquire the distance-dimension data of the millimeter-wave radar.
  • the target index acquisition unit 32 is configured to perform the aforementioned step S102, that is, intercept the distance dimension data of the millimeter-wave radar according to the preset effective distance range, and acquire the target index corresponding to the maximum peak value in the intercepted data.
  • the spectrum acquisition unit 34 is used to execute the aforementioned step S104, that is, perform windowing and fast Fourier transform on the amplitude difference corresponding to any distance detection unit to obtain the spectrum corresponding to the distance detection unit.
  • the judging unit 35 is configured to execute the aforementioned step S105, that is, judging whether there is a target at the Nth moment according to the frequency spectrum corresponding to the n distance detection units.
  • the distance-dimension data acquisition unit 31 may also be used to: perform signal processing on the echo signal received by any one of the plurality of receiving antennas of the millimeter-wave radar, to obtain the echo signal corresponding to the echo signal intermediate frequency signal; and perform fast Fourier transform on the intermediate frequency signal to obtain corresponding distance dimension data; wherein, one transmitting antenna of the millimeter wave radar transmits a group of chirp signals, and a plurality of receiving antennas of the millimeter wave radar receive The received echo signal is an echo signal corresponding to the chirp signal.
  • the distance dimension data of the millimeter wave radar includes distance dimension data received by at least one receiving antenna.
  • the distance dimension data acquiring unit 31 may also be configured to: perform coherent accumulation of distance dimension data corresponding to at least two receiving antennas to obtain the distance dimension data of the millimeter wave radar.
  • the life detection device 3 further includes: a filtering unit 36 .
  • the filtering unit 36 is configured to filter the amplitude difference between the distance dimension data at the kth moment and the k -1th moment according to a preset frequency range.
  • the judging unit 35 can also be used to perform the aforementioned steps S201 to S204, namely:
  • any distance detection unit search for a maximum value within the preset frequency range, and obtain an index number corresponding to the maximum value
  • the index number corresponding to the maximum value obtain an index range of a preset size centered on the index number of the maximum value
  • the discrimination unit 35 can also be used for:
  • the characteristic value conf corresponding to the distance detection unit is obtained through a preset formula; the preset formula is:
  • the judging unit 35 can also be used to: judge at the Nth moment, whether the feature values corresponding to the n distance detection units are all greater than or equal to a preset threshold; if so, judge that there is a target at the Nth moment .
  • the judging unit 35 may also be used for: judging whether there is a target at each moment in consecutive M moments after the Nth moment including the Nth moment;
  • the target exists at R time points among the M time points, it is determined that the target exists, and R is greater than or equal to a preset value.
  • the life detection device provided by this application can use the detection method provided by this application to detect whether there is life in a certain space, that is, the life detection device provided by this application can detect the target position through millimeter wave radar, and calculate the target position.
  • Fig. 4 is a schematic diagram of a terminal provided by the present application.
  • the terminal 4 includes a processor 40 , a memory 41 and a computer program 42 stored in the memory 41 and executable on the processor 40 .
  • the processor 40 executes the computer program 42, the steps of the living body detection method provided by the above method embodiments are implemented, for example, steps S101 to S105 shown in FIG. 1 .
  • the processor 40 executes the computer program 42, it realizes the functions of the modules/units in the above-mentioned device embodiments, such as the functions of the units 31 to 36 shown in FIG. 3 .
  • the computer program 42 can be divided into one or more modules/units. These modules/units are stored in the memory 41 and executed by the processor 40 to realize the inventive concept of the present application. These modules/units may be a series of computer program instruction segments capable of accomplishing specific functions, and these instruction segments are used to describe the execution process of the computer program 42 in the terminal 4 .
  • computer program 42 may be divided into units 31 to 36 shown in FIG. 3 .
  • the terminal 4 may be a computing device such as a desktop computer, a notebook, a palmtop computer, or a cloud server.
  • the terminal 4 may include, but not limited to, a processor 40 and a memory 41 .
  • FIG. 4 is only an example of the terminal 4 and does not constitute a limitation on the terminal 4 .
  • Terminal 4 may include more or fewer components than shown, or combine certain components, or different components.
  • the terminal 4 may also include an input and output device, a network access device, a bus, and the like.
  • the processor 40 can be a central processing unit (Central Processing Unit, CPU), and can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application-specific integrated circuits (Application Specific Integrated Circuit, ASIC), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • a general-purpose processor may be a microprocessor or any conventional processor or the like.
  • the storage 41 may be an internal storage unit of the terminal 4, such as a hard disk or a memory of the terminal 4.
  • the memory 41 can also be an external storage device of the terminal 4, such as a plug-in hard disk equipped on the terminal 4, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash memory card (Flash Card) wait.
  • the memory 41 may also include both an internal storage unit of the terminal 4 and an external storage device.
  • the memory 41 is used to store the computer program 42 and other programs and data required by the terminal 4 .
  • the memory 41 can also be used to temporarily store data that has been output or will be output.
  • the present application also provides a computer-readable storage medium, in which a computer program is stored.
  • a computer program is stored.
  • the steps shown in FIG. 1 and/or FIG. 2 can be implemented to complete the detection of living bodies existing in the space.
  • the disclosed device/terminal and method may be implemented in other ways, and the above-described device/terminal embodiments are only illustrative.
  • the division of the modules or units is only a logical function division, and there may be other division methods in actual implementation; for example, multiple units or components can be combined or integrated into another system, or some features can be ignored, or not.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separate.
  • Components shown as units may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the corresponding embodiment.
  • the integrated module/unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the implementation of all or part of the processes in the methods of the above-mentioned embodiments in the present application may also be completed by instructing related hardware through computer programs.
  • the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, the steps of the above-mentioned embodiments of the living body detection method can be realized.
  • the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form.
  • the computer readable medium may be: any entity or device capable of carrying the computer program code, recording medium, U disk, removable hard disk, magnetic disk, optical disk, computer memory, read-only memory (Read-Only Memory, ROM) , random access memory (Random Access Memory, RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable Excluding electrical carrier signals and telecommunication signals.

Abstract

Procédé de détection d'être vivant, terminal (4) et support de stockage lisible par ordinateur. Le procédé est appliqué à un radar à ondes millimétriques, et consiste : à obtenir des données de dimension de distance du radar à ondes millimétriques (S101) ; à intercepter les données de dimension de distance en fonction d'une plage de distance effective prédéfinie, et à obtenir un indice cible correspondant à la valeur de pic maximale dans les données interceptées (S102) ; à obtenir, en fonction de l'indice cible, n unités de mesure de distance adjacentes centrées sur une unité de mesure de distance correspondant à l'indice cible, et à obtenir séquentiellement une différence d'amplitude entre les données de dimension de distance de chaque unité de mesure de distance à un kième instant et à un (k-1)ème instant parmi N instants consécutifs (S103) ; à réaliser un fenêtrage et une transformée de Fourier rapide pour la différence d'amplitude correspondant à une unité de mesure de distance quelconque afin d'obtenir un spectre correspondant à l'unité de mesure de distance (S104) ; et à déterminer, en fonction des spectres correspondant aux n unités de mesure de distance, si une cible existe à un Nième instant (S105). Le procédé de détection d'être vivant peut améliorer la précision de détection d'être vivant.
PCT/CN2022/107272 2021-07-26 2022-07-22 Procédé de détection d'être vivant, terminal et support de stockage WO2023005821A1 (fr)

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