Living body detection method and device, electronic equipment and vehicle

Abstract

The invention relates to the field of radar detection, and provides a living body detection method and device, electronic equipment and a vehicle, and the method comprises the steps: receiving a living body detection instruction, and outputting a living body detection signal; receiving an echo signal corresponding to the living body detection signal, and determining an initial signal-to-noise ratio corresponding to the echo signal; performing signal-to-noise ratio enhancement processing on the initial signal-to-noise ratio to obtain a target signal-to-noise ratio; determining an echo amplitude corresponding to the echo signal according to the target signal-to-noise ratio; and in response to the echo amplitude being greater than a preset threshold, determining that a living body exists at a position corresponding to the echo signal. The signal-to-noise ratio of the echo signal is enhanced, so that the signal-to-noise ratio of the signal corresponding to the living body detected at a relatively far position is improved, and the difference of the echo signal between the relatively far living body and the non-living body is distinguished. And when the echo amplitude is determined to be greater than the preset threshold value, it is indicated that the living body exists at the position corresponding to the echo signal at the moment, accurate detection of the living body at a relatively long distance is realized, and the problem of missing alarm of the living body at the relatively long distance is avoided.

Description

Technical Field

[0001] The present disclosure relates to the field of radar detection, and in particular to a living body detection method, device, electronic equipment and vehicle. Background Art

[0002] With the rapid development of vehicle technology, vehicles have become an important means of transportation in people's daily lives. Vehicles are usually equipped with detection radars to detect living things in the car. When the driver forgets to check the living things, the radars can detect the living things and notify the driver to reduce safety hazards.

[0003] The beam of the current liveness detection radar is divergent, strong in the center and gradually weakened at the outside. As a result, when the radar detects live objects at a distance, the detection results are almost the same as when there are no live objects at all. This leads to low accuracy in liveness detection at a distance and is prone to missed alarms. Summary of the invention

[0004] In view of this, the purpose of the present disclosure is to propose a living body detection method, device, electronic device and vehicle to solve the problem that during current radar detection, the detection results for living bodies at a farther distance are almost the same as those when there are no living bodies, resulting in low detection accuracy for living bodies at a farther distance and easy missed alarms.

[0005] Based on the above objectives, the first aspect of the present disclosure provides a living body detection method, the method comprising:

[0006] Receiving a liveness detection instruction, and outputting a liveness detection signal;

[0007] receiving an echo signal corresponding to the living body detection signal, and determining an initial signal-to-noise ratio corresponding to the echo signal;

[0008] Performing signal-to-noise ratio enhancement processing on the initial signal-to-noise ratio to obtain a target signal-to-noise ratio;

[0009] Determining an echo amplitude corresponding to the echo signal according to the target signal-to-noise ratio;

[0010] In response to the echo amplitude being greater than a preset threshold, it is determined that a living body exists at a position corresponding to the initial echo signal.

[0011] Based on the same inventive concept, the second aspect of the present disclosure proposes a living body detection device, comprising:

[0012] The command receiving module is configured to receive a liveness detection command and output a liveness detection signal;

[0013] an initial signal-to-noise ratio determination module, configured to receive an echo signal corresponding to the living body detection signal, and determine an initial signal-to-noise ratio corresponding to the echo signal;

[0014] a signal-to-noise ratio enhancement module, configured to perform signal-to-noise ratio enhancement processing on the initial signal-to-noise ratio to obtain a target signal-to-noise ratio;

[0015] an echo amplitude determination module, configured to determine the echo amplitude corresponding to the echo signal according to the target signal-to-noise ratio;

[0016] The living body detection module is configured to determine that a living body exists at a position corresponding to the initial echo signal in response to the echo amplitude being greater than a preset threshold.

[0017] Based on the same inventive concept, the third aspect of the present disclosure proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor implements the liveness detection method as described above when executing the computer program.

[0018] Based on the same inventive concept, the fourth aspect of the present disclosure proposes a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to execute the living body detection method as described above.

[0019] Based on the same inventive concept, the fifth aspect of the present disclosure provides a vehicle, comprising the liveness detection device described in the second aspect or the electronic device described in the third aspect or the storage medium described in the fourth aspect.

[0020] As can be seen from the above, the present disclosure proposes a method, device, electronic device and vehicle for detecting living things, which receive a living thing detection instruction and output a living thing detection signal, wherein the living thing detection signal is used to detect living things in the vehicle. An echo signal corresponding to the living thing detection signal is received, an initial signal-to-noise ratio corresponding to the echo signal is determined, and the initial signal-to-noise ratio is subjected to signal-to-noise ratio enhancement processing to obtain a target signal-to-noise ratio. By enhancing the signal-to-noise ratio of the echo signal, the signal-to-noise ratio of the signal corresponding to the living thing detected at a farther distance is improved to distinguish the difference between the echo signals of living things at a farther distance and those without living things. The echo amplitude corresponding to the echo signal is determined according to the target signal-to-noise ratio, and in response to the echo amplitude being greater than a preset threshold, it is determined that there is a living thing at the position corresponding to the echo signal. When it is determined that the echo amplitude is greater than the preset threshold, it means that there is a living thing at the position corresponding to the echo signal, thereby achieving accurate detection of living things at a farther distance and avoiding the problem of missed alarms of living things at a farther distance. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the present disclosure or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 is a flow chart of a liveness detection method according to an embodiment of the present disclosure;

[0023] Figure 2 is a structural block diagram of a living body detection device according to an embodiment of the present disclosure;

[0024] Figure 3 It is a schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0025] In order to make the objectives, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0026] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure should be understood by people with ordinary skills in the field to which the present disclosure belongs. The "first", "second" and similar words used in the embodiments of the present disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0027] The terms used in this disclosure are explained as follows:

[0028] FFT: Fast Fourier transform, Fourier transform is one of the most basic methods in time domain to frequency domain transformation analysis.

[0029] FMCW: Frequency Modulated Continuous Wave, FMCW technology and pulse radar technology are two technologies used in high-precision radar ranging. The basic principle is that the transmitted wave is a high-frequency continuous wave, and its frequency changes over time according to the law of triangular waves.

[0030] SNR: Signal-to-Noise Ratio (SNR) is an important parameter to measure signal quality, which represents the ratio of the power of the useful signal to the power of the background noise. SNR is widely used in communications, audio processing, video processing and other electronic signal processing fields.

[0031] With the rapid development of vehicle technology, vehicles have become an important means of transportation in people's daily lives. Vehicles are usually equipped with detection radars to detect living things in the car. When the driver forgets to check the living things, the radars can detect the living things and notify the driver to reduce safety hazards.

[0032] The beam of the current liveness detection radar is divergent, strong in the center and gradually weakened at the outside. The larger the beam angle and the farther the distance, the lower the gain of the transmitting and receiving antennas, resulting in weaker position characteristics at large angles. Therefore, when detecting the remaining live bodies at the farthest seat, the received power value corresponding to the live bodies at a farther distance is almost the same as the received power value corresponding to the absence of live bodies, resulting in lower detection accuracy for live bodies at a farther distance and prone to missed alarms.

[0033] Based on the above description, this embodiment proposes a living body detection method, such as Figure 1 As shown, the method includes:

[0034] Step 101: receiving a liveness detection instruction and outputting a liveness detection signal.

[0035] In specific implementation, when a live body detection instruction is received, it means that a live body in the vehicle needs to be detected. A detection instruction is sent to a radar detection module in the vehicle, so that the radar detection module outputs a live body detection signal after receiving the detection instruction, wherein the live body detection signal is a radar detection signal, such as a millimeter wave detection signal.

[0036] The radar detection module uses the human body's unique micro-movements (such as breathing, heartbeat, etc.) as identification features. These micro-movements appear as weak frequency changes in the radar signal. The preset signal processing algorithm can extract the identification features and then determine whether the target is alive.

[0037] Step 102: Receive an echo signal corresponding to the living body detection signal, and determine an initial signal-to-noise ratio corresponding to the echo signal.

[0038] In specific implementation, when performing live body detection by radar, it is necessary to detect the target by emitting electromagnetic waves and receiving their reflected signals. Therefore, after outputting the live body detection signal, the corresponding reflected signal, that is, the echo signal corresponding to the live body detection signal, is received.

[0039] Step 103: Perform signal-to-noise ratio enhancement processing on the initial signal-to-noise ratio to obtain a target signal-to-noise ratio.

[0040] In a specific implementation, the initial signal-to-noise ratio is subjected to signal-to-noise ratio enhancement processing, wherein the signal-to-noise ratio enhancement method includes at least one of the following: enhancing signal strength, reducing noise interference, filtering processing, or enhancing using signal processing technology.

[0041] Signal strength can be enhanced by increasing the transmission power or optimizing the receiving sensitivity. Increasing the transmission power means that at the radar signal transmitting end, by increasing the power of the transmitter in the radar detection module, the transmission distance and strength of the signal can be increased, thereby improving the signal-to-noise ratio. Optimizing the receiving sensitivity means that at the signal receiving end, by optimizing the design of the receiver and improving its sensitivity, the receiving ability of weak signals can be enhanced, thereby improving the signal-to-noise ratio.

[0042] Reducing noise interference can be achieved by selecting low-noise components, optimizing equipment layout or controlling environmental noise.

[0043] In this embodiment, the enhancement of signal strength can be adopted in the early stage of vehicle model development, but in the later use process, because the vehicle system has been determined and completed, it is not convenient to enhance the signal strength. At the same time, since the environment in which the vehicle is located is a variable value, the environment in which different vehicles are located is different, and the vehicle cannot eliminate the noise in the environment. Therefore, in this embodiment, the signal-to-noise ratio enhancement processing is preferably performed by filtering or using signal processing technology.

[0044] Step 104: determining an echo amplitude corresponding to the echo signal according to the target signal-to-noise ratio.

[0045] In specific implementation, after the signal-to-noise ratio enhancement processing, the signal-to-noise ratio of the echo signal is made to be the target signal-to-noise ratio, and the echo amplitude corresponding to the target signal is calculated according to the target signal-to-noise ratio.

[0046] Step 105: In response to the echo amplitude being greater than a preset threshold, determining that a living body exists at the position corresponding to the echo signal.

[0047] In specific implementation, the obtained echo amplitude is compared with a preset threshold value. If the echo amplitude is greater than the preset threshold value, it indicates that there is a living body at the radar detection position corresponding to the echo signal. If the echo amplitude is less than or equal to the preset threshold value, it indicates that there is no living body at the radar detection position corresponding to the echo signal.

[0048] In this embodiment, the living body refers to an object with vital signs, and the living body specifically includes humans, animals, plants, etc.

[0049] Through the above scheme, a live body detection instruction is received, and a live body detection signal is output, and the live body detection signal is used to detect live bodies in the vehicle. An echo signal corresponding to the live body detection signal is received, and the initial signal-to-noise ratio corresponding to the echo signal is determined. The initial signal-to-noise ratio is subjected to signal-to-noise ratio enhancement processing to obtain a target signal-to-noise ratio. By enhancing the signal-to-noise ratio of the echo signal, the signal-to-noise ratio of the signal corresponding to the live body detected at a farther distance is improved to distinguish the difference between the echo signals of the live body at a farther distance and the echo signals of the live body without the live body at a farther distance. The echo amplitude corresponding to the echo signal is determined according to the target signal-to-noise ratio, and in response to the echo amplitude being greater than a preset threshold, it is determined that there is a live body at the position corresponding to the echo signal. When it is determined that the echo amplitude is greater than the preset threshold, it means that there is a live body at the position corresponding to the echo signal, thereby achieving accurate detection of live bodies at a farther distance and avoiding the problem of missed alarms of live bodies at a farther distance.

[0050] In some embodiments, step 103 specifically includes:

[0051] Step 1031, obtaining a preset signal time width, performing matched filtering on the echo signal according to the preset signal time width, and obtaining a matched filtering gain;

[0052] Step 1032: Add the initial signal-to-noise ratio and the matched filter gain to obtain a target signal-to-noise ratio.

[0053] In a specific implementation, a preset signal time width is obtained, wherein the preset signal time width is a signal time width value set by a user, and the preset signal time width is greater than the time width of the echo signal itself. Matched filtering is performed on the echo signal according to the preset signal time width. Matched filtering is an effective method for detecting known signals in a noisy environment. By convolving the received signal with a known signal template, the signal-to-noise ratio is maximized, thereby improving the accuracy of signal detection.

[0054] The echo signal is matched filtered according to the preset signal time width to obtain a matched filter gain, and the initial signal-to-noise ratio and the matched filter gain are added together to obtain a sum value that is the target signal-to-noise ratio. In this embodiment, the specific method for determining the matched filter gain includes:

[0055] Step A, determining the signal bandwidth of the echo signal;

[0056] Step B: obtaining a matched filter gain based on the signal bandwidth and the preset signal time width.

[0057] Specifically, the signal bandwidth of the echo signal is determined, and the signal bandwidth is multiplied by the preset signal time width, and the obtained product value is the matched filter gain.

[0058] The matched filter gain is described by a formula: the signal bandwidth is B, the preset signal time width is T, and the calculated time-bandwidth product is D′=B*T. The matched filter gain is the same as the time-bandwidth product, that is, the value of the matched filter gain is B*T.

[0059] For example, the signal bandwidth is 4 GHz, the signal time width of the received echo signal is 32 us, and the preset signal time width is 64 us. Then, the signal bandwidth is multiplied by the signal time width of the received echo signal, and the time-width-bandwidth product is 128. The signal bandwidth is multiplied by the preset signal time width, and the time-width-bandwidth product is 256. The enhanced target signal-to-noise ratio is at least 2 times higher than the initial signal-to-noise ratio.

[0060] Through the above scheme, matched filtering is performed by taking a preset signal time width, and then the initial signal-to-noise ratio and the obtained matched filter gain are added to obtain the target signal-to-noise ratio. Since the value of the matched filter gain is the time-width-bandwidth product, the matched filter gain will also increase when the time width increases. After adding the initial signal-to-noise ratio, the signal-to-noise ratio of the echo signal is improved, and the echo signal of a living body at a distance is distinguished from the echo signal when there is no living body, so as to achieve accurate detection of a living body at a distance, and avoid the problem of missed alarm of a living body at a distance.

[0061] In some embodiments, before step 1031, the method further includes:

[0062] Step 10A, determining a target background mean estimate corresponding to the echo signal reception time;

[0063] Step 10B: performing clutter suppression on the echo signal according to the target background mean estimation to obtain a target echo signal.

[0064] In the specific implementation, the preset exponential weighting coefficient and the historical background mean estimate corresponding to the moment before the echo signal is received are obtained, and the target background mean estimate corresponding to the echo signal reception moment is calculated using the exponential weighting coefficient and the historical background mean estimate, wherein the target background mean estimate is expressed by the formula:

[0065] y k =a×y k-1 +(1-a)×x k

[0066] Among them, y k is the target background mean estimate, a is the exponential weighting coefficient, y k-1 is the historical background mean estimate, x kIn this embodiment, the value range of a is (0, 1), and by selecting different exponential weighting coefficients, the change of the background can be automatically used, so that it can have better moving target indication performance for radial and non-radial moving targets.

[0067] The echo signal is subjected to clutter suppression according to the determined target background mean estimation, and the clutter is removed by cancellation processing to obtain the target echo signal. Specifically, the echo signal is subjected to difference processing with the target background mean estimation to obtain the target echo signal, wherein the target echo signal is expressed by the formula:

[0068] s k =x k -y k

[0069] Among them, s k is the target echo signal.

[0070] In some embodiments, step 1031 specifically includes:

[0071] A preset signal time width is acquired, and matched filtering is performed on the target echo signal according to the preset signal time width to obtain a matched filtering gain.

[0072] In specific implementation, the echo signal is firstly subjected to clutter suppression, and then a preset signal time width is obtained. The echo signal is matched filtered according to the preset signal time width to obtain a matched filter gain. The initial signal-to-noise ratio and the matched filter gain are added together, and the sum obtained is the target signal-to-noise ratio.

[0073] Through the above scheme, clutter suppression is performed through a background cancellation algorithm of continuous multiple frames, the influence of strong reflections in the environment is eliminated, the influence of strong reflections on liveness detection is avoided, and the accuracy of subsequent liveness detection is improved.

[0074] In some embodiments, step 103 specifically includes:

[0075] Step 103A, determining a receiving speed of the echo signal, performing coherent integration based on the receiving speed, and obtaining a coherent integration gain;

[0076] Step 103B: Add the initial signal-to-noise ratio and the coherent accumulation gain to obtain a target signal-to-noise ratio.

[0077] In specific implementation, in signal theory, coherence is also called coherence, which is defined as a certain phase relationship between pulses. Simply put, the phases of pulses can be compared with each other, and knowing one phase can lead to knowing the other. The significance of coherent processing is to improve the signal-to-noise ratio when pulses are accumulated and improve the accuracy of the Doppler frequency.

[0078] Radar signal processing usually superimposes ("accumulates") multiple data samples to improve the signal-to-noise ratio (SNR). Two important accumulation methods include coherent accumulation and non-coherent accumulation. When the signal is complex data, the accumulation needs to consider coherence, so that both the amplitude information and the phase information of the signal can be used.

[0079] The receiving speed of the echo signal is determined, and coherent accumulation is performed based on the receiving speed to obtain a coherent accumulation gain. The sum of the initial signal-to-noise ratio and the coherent accumulation gain is calculated, and the sum is the target signal-to-noise ratio.

[0080] In some embodiments, the process of determining the coherent accumulation gain in step 103A specifically includes:

[0081] Step a, determining the receiving speed of the echo signal;

[0082] Step b, performing an integral transformation on the echo signal according to the receiving speed to obtain an echo signal spectrum;

[0083] Step c, obtaining the number of pulse periods corresponding to the echo signal, performing coherent accumulation on the echo signal spectrum according to the number of pulse periods, and obtaining a coherent accumulation gain.

[0084] In specific implementation, the specific method of coherent accumulation is to accumulate n echo signals. Since the noise is random, the result of accumulation is that the signal becomes stronger, while the noise is random, so the intensity becomes smaller, so the signal-to-noise ratio is improved. In coherent accumulation, the phase relationship between multiple pulses is fixed and clear, so theoretically the signal-to-noise ratio can be increased to n times after accumulation.

[0085] Determine the receiving speed of the echo signal, perform integral transformation on the echo signal according to the receiving speed, and obtain the echo signal spectrum. Obtain the number of pulse periods corresponding to the echo signal, perform coherent accumulation on the echo signal spectrum according to the number of pulse periods, and obtain the coherent accumulation gain. In this embodiment, the integral transformation is a two-dimensional Fourier transform.

[0086] The gain of coherent accumulation comes from the in-phase addition of N callback signals. The gain of signal component energy is N squared, while the gain of noise accumulation is only N. During accumulation, coherent superposition is achieved after compensating the phase modulated signal, thereby increasing the SNR by N times.

[0087] In this embodiment, a two-dimensional Fourier transform is performed through coherent accumulation of the velocity dimension to improve the signal-to-noise ratio. Preferably, a Fourier transform of 128 points is performed. Theoretically, the target signal-to-noise ratio can be increased by 128 times compared to the initial signal-to-noise ratio.

[0088] Through the above scheme, by taking coherent accumulation in the velocity dimension and performing a two-dimensional Fourier transform to improve the signal-to-noise ratio, the echo signal of a living body at a distance can be distinguished from the echo signal when there is no living body, thereby achieving accurate detection of living bodies at a distance and avoiding the problem of missed alarms of living bodies at a distance.

[0089] In some embodiments, step 104 specifically includes:

[0090] Step 1041, obtaining a receiver bandwidth and a receiver noise coefficient, performing product processing on the receiver bandwidth, the receiver noise coefficient and the target signal-to-noise ratio, and obtaining a receiving power corresponding to the echo signal;

[0091] Step 1042: perform an integral transformation on the received power to obtain an echo amplitude corresponding to the echo signal.

[0092] In a specific implementation, the receiver bandwidth, the receiver noise coefficient and the Boltzmann constant are obtained, the thermodynamic temperature of the vehicle environment is determined, and the receiver bandwidth, the receiver noise coefficient, the Boltzmann constant, the target signal-to-noise ratio and the corresponding thermodynamic temperature are multiplied to obtain the receiver sensitivity. The receiver sensitivity is expressed by the formula:

[0093]

[0094] Among them, S min is the receiver sensitivity, k is the Boltzmann constant, B is the receiver bandwidth, F is the receiver noise factor, T is the thermodynamic temperature, is the target signal-to-noise ratio.

[0095] In this embodiment, the received power corresponding to the echo signal is determined to be the same as the receiver sensitivity so that the corresponding radar operating range is maximized. That is, the received power corresponding to the echo signal is expressed by the formula:

[0096]

[0097] Among them, p r is the received power corresponding to the echo signal.

[0098] In this embodiment, according to the received power corresponding to the echo signal, it can be known that the received power is proportional to the target signal-to-noise ratio, and thus when the target signal-to-noise ratio is increased, the received power of the corresponding echo signal is also increased accordingly.

[0099] The receiving power is subjected to an integral transformation to obtain an echo amplitude corresponding to the echo signal. In this embodiment, the integral transformation is a Fourier transform.

[0100] It should be noted that the method of the embodiment of the present disclosure can be performed by a single device, such as a computer or a server. The method of the present embodiment can also be applied in a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present disclosure, and the multiple devices will interact with each other to complete the described method.

[0101] It should be noted that the above describes some embodiments of the present disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0102] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present disclosure further provides a living body detection device.

[0103] refer to Figure 2 , Figure 2 The living body detection device of the embodiment includes:

[0104] The instruction receiving module 201 is configured to receive a liveness detection instruction and output a liveness detection signal;

[0105] The initial signal-to-noise ratio determination module 202 is configured to receive the echo signal corresponding to the living body detection signal and determine the initial signal-to-noise ratio corresponding to the echo signal;

[0106] The signal-to-noise ratio enhancement module 203 is configured to perform signal-to-noise ratio enhancement processing on the initial signal-to-noise ratio to obtain a target signal-to-noise ratio;

[0107] The echo amplitude determination module 204 is configured to determine the echo amplitude corresponding to the echo signal according to the target signal-to-noise ratio;

[0108] The living body detection module 205 is configured to determine that a living body exists at the position corresponding to the echo signal in response to the echo amplitude being greater than a preset threshold.

[0109] In some embodiments, the signal-to-noise ratio enhancement module 203 specifically includes:

[0110] a matched filter gain determination unit, configured to obtain a preset signal time width, perform matched filtering on the echo signal according to the preset signal time width, and obtain a matched filter gain;

[0111] The target signal-to-noise ratio determination unit is configured to add the initial signal-to-noise ratio and the matched filter gain to obtain a target signal-to-noise ratio.

[0112] In some embodiments, the matched filter gain determination unit is specifically configured to:

[0113] determining a signal bandwidth of the echo signal;

[0114] A matched filter gain is obtained based on the signal bandwidth and the preset signal time width.

[0115] In some embodiments, the signal-to-noise ratio enhancement module 203 further includes a clutter suppression unit, and the clutter suppression unit is specifically configured as follows:

[0116] Determine the target background mean estimate corresponding to the echo signal reception time;

[0117] The echo signal is subjected to clutter suppression according to the target background mean estimation to obtain a target echo signal.

[0118] In some embodiments, the matched filter gain determination unit is specifically configured to:

[0119] A preset signal time width is acquired, and matched filtering is performed on the target echo signal according to the preset signal time width to obtain a matched filtering gain.

[0120] In some embodiments, the signal-to-noise ratio enhancement module 203 specifically includes:

[0121] a coherent accumulation gain determination unit, configured to determine a receiving speed of the echo signal, perform coherent accumulation based on the receiving speed, and obtain a coherent accumulation gain;

[0122] The target signal-to-noise ratio determination unit is configured to add the initial signal-to-noise ratio and the coherent accumulation gain to obtain a target signal-to-noise ratio.

[0123] In some embodiments, the coherent accumulation gain determination unit is specifically configured to:

[0124] determining a receiving speed of the echo signal;

[0125] Performing an integral transformation on the echo signal according to the receiving speed to obtain an echo signal spectrum;

[0126] The number of pulse periods corresponding to the echo signal is obtained, and the frequency spectrum of the echo signal is coherently accumulated according to the number of pulse periods to obtain a coherent accumulation gain.

[0127] In some embodiments, the echo amplitude determination module 204 is specifically configured to:

[0128] Acquire a receiver bandwidth and a receiver noise coefficient, and perform product processing on the receiver bandwidth, the receiver noise coefficient, and the target signal-to-noise ratio to obtain a received power corresponding to the echo signal;

[0129] The received power is integrally transformed to obtain an echo amplitude corresponding to the echo signal.

[0130] For the convenience of description, the above devices are described in terms of functions divided into various modules. Of course, when implementing the present disclosure, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0131] The device of the above embodiment is used to implement the corresponding living body detection method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0132] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the liveness detection method described in any of the above embodiments is implemented.

[0133] Figure 3 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 in the device.

[0134] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0135] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0136] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0137] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0138] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0139] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0140] The electronic device of the above embodiment is used to implement the corresponding living body detection method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0141] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present disclosure also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the liveness detection method described in any of the above embodiments.

[0142] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0143] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the liveness detection method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0144] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides a vehicle, including the liveness detection device in the above-mentioned embodiments, the electronic device in the above-mentioned embodiments, and the computer-readable storage medium in the above-mentioned embodiments, and the vehicle equipment implements the liveness detection method described in any of the above embodiments.

[0145] The vehicle of the above embodiment is used to implement the living body detection method described in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0146] It is understandable that before using the technical solutions of each embodiment of the present disclosure, the type, scope of use, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner, and the user's authorization will be obtained.

[0147] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly remind the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can independently choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0148] As an optional but non-limiting implementation, in response to receiving the user's active request, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0149] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0150] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present disclosure (including the claims) is limited to these examples. Based on the concept of the present disclosure, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present disclosure as described above, which are not provided in detail for the sake of simplicity.

[0151] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present disclosure difficult to understand, the known power / ground connections to the integrated circuit (IC) chips and other components may or may not be shown in the provided figures. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present disclosure difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the present disclosure will be implemented (that is, these details should be fully within the scope of understanding of those skilled in the art). Where specific details (e.g., circuits) are set forth to describe exemplary embodiments of the present disclosure, it is apparent to those skilled in the art that the embodiments of the present disclosure can be implemented without these specific details or with changes in these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0152] Although the present disclosure has been described in conjunction with specific embodiments of the present disclosure, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0153] The embodiments of the present disclosure are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A method for detecting a living body, characterized in that: include: Receiving a liveness detection instruction, and outputting a liveness detection signal; receiving an echo signal corresponding to the living body detection signal, and determining an initial signal-to-noise ratio corresponding to the echo signal; Performing signal-to-noise ratio enhancement processing on the initial signal-to-noise ratio to obtain a target signal-to-noise ratio; Determining an echo amplitude corresponding to the echo signal according to the target signal-to-noise ratio; In response to the echo amplitude being greater than a preset threshold, it is determined that a living body exists at a position corresponding to the echo signal.

2. The method according to claim 1, characterized in that The performing signal-to-noise ratio enhancement processing on the initial signal-to-noise ratio to obtain a target signal-to-noise ratio includes: Acquire a preset signal time width, and perform matched filtering on the echo signal according to the preset signal time width to obtain a matched filtering gain; The initial signal-to-noise ratio and the matched filter gain are added together to obtain a target signal-to-noise ratio.

3. The method according to claim 2, characterized in that The performing matched filtering on the echo signal according to the preset signal time width to obtain a matched filtering gain includes: determining a signal bandwidth of the echo signal; A matched filter gain is obtained based on the signal bandwidth and the preset signal time width.

4. The method according to claim 2, characterized in that: Before obtaining the preset signal time width, it also includes: Determine the target background mean estimate corresponding to the echo signal reception time; performing clutter suppression on the echo signal according to the target background mean estimation to obtain a target echo signal; The step of acquiring a preset signal time width and performing matched filtering on the echo signal according to the preset signal time width to obtain a matched filtering gain includes: A preset signal time width is acquired, and matched filtering is performed on the target echo signal according to the preset signal time width to obtain a matched filtering gain.

5. The method according to claim 1, characterized in that The performing signal-to-noise ratio enhancement processing on the initial signal-to-noise ratio to obtain a target signal-to-noise ratio includes: Determining a receiving speed of the echo signal, performing coherent integration based on the receiving speed, and obtaining a coherent integration gain; The initial signal-to-noise ratio and the coherent accumulation gain are added together to obtain a target signal-to-noise ratio.

6. The method according to claim 5, characterized in that The determining the receiving speed of the echo signal, performing coherent accumulation based on the receiving speed, and obtaining a coherent accumulation gain includes: determining a receiving speed of the echo signal; Performing an integral transformation on the echo signal according to the receiving speed to obtain an echo signal spectrum; The number of pulse periods corresponding to the echo signal is obtained, and the frequency spectrum of the echo signal is coherently accumulated according to the number of pulse periods to obtain a coherent accumulation gain.

7. The method according to claim 1, characterized in that The step of determining the echo amplitude corresponding to the echo signal according to the target signal-to-noise ratio includes: Acquire a receiver bandwidth and a receiver noise coefficient, and perform product processing on the receiver bandwidth, the receiver noise coefficient, and the target signal-to-noise ratio to obtain a received power corresponding to the echo signal; The received power is integrally transformed to obtain an echo amplitude corresponding to the echo signal.

8. A living body detection device, characterized in that: include: The command receiving module is configured to receive a liveness detection command and output a liveness detection signal; an initial signal-to-noise ratio determination module, configured to receive an echo signal corresponding to the living body detection signal, and determine an initial signal-to-noise ratio corresponding to the echo signal; a signal-to-noise ratio enhancement module, configured to perform signal-to-noise ratio enhancement processing on the initial signal-to-noise ratio to obtain a target signal-to-noise ratio; an echo amplitude determination module, configured to determine the echo amplitude corresponding to the echo signal according to the target signal-to-noise ratio; The living body detection module is configured to determine that a living body exists at a position corresponding to the echo signal in response to the echo amplitude being greater than a preset threshold.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A vehicle, characterized in that: The vehicle includes the electronic device according to claim 9.

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