Motion detection counting system based on millimeter wave radar technology

Abstract

The invention provides a millimeter wave radar technology-based motion detection counting system, which comprises the following steps of: firstly, detecting human body activity in a target area in real time through a low-power-consumption human body detection module, and sending a trigger signal to a main controller processing module to activate a radar system module when the human body activity is detected; a frequency modulation continuous wave signal is transmitted to a target area through the radar system module, the received echo signal and the transmitted signal are subjected to frequency mixing to generate an intermediate frequency signal, and the main controller processing module performs motion posture detection and counting according to the intermediate frequency signal to obtain a corresponding motion detection counting result; the motion detection counting result is controlled to be displayed and stored, and finally the obtained motion detection counting result is sent to mobile terminal equipment through the wireless receiving and transmitting module. According to the invention, through distance measurement, speed measurement and angle measurement functions of the millimeter wave radar, automatic detection, counting and analysis of motion actions are realized, and the detection precision, the real-time performance and the user experience are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of radar systems, and in particular to a motion detection and counting system based on millimeter wave radar technology. Background Art

[0002] In the existing motion posture detection and counting methods, the following technical means are usually used: One is the camera monitoring system. The system relies on a high-frame rate camera to capture the dynamics of human jumping, and uses image processing technology to achieve the purpose of motion recognition and counting. However, this technology has many disadvantages: on the one hand, it is easily restricted by ambient light. Once in an outdoor environment or a venue with poor lighting conditions, the clarity of the image captured by the camera will be greatly reduced, which will lead to a decline in detection accuracy and a significant increase in errors. On the other hand, its demand for computing resources is considerable. The image processing process requires a lot of computing power and places strict requirements on the response time of the entire system, which undoubtedly increases the operating cost and complexity of the system. In addition, from the perspective of information acquisition, it is difficult to accurately grasp the three-dimensional position and angle details of the human body with only a single camera, and it is difficult to meet the needs of all-round analysis of motion postures.

[0003] The second is the wearable sensor solution. This method uses sensors such as accelerometers and gyroscopes to collect human motion data, and then realizes jump recognition and counting functions through data analysis. However, this technology also has obvious shortcomings: first, it is not easy to wear. Users need to equip sensors in many parts of their bodies, which will interfere with their normal training rhythm to a certain extent and have an adverse effect on athletic performance. Secondly, sensors face a high risk of failure. During exercise, sweat erosion, violent movement impact and even accidental falls occur frequently. These factors can easily cause data loss or even physical damage to the sensor, seriously affecting the reliability of detection and counting. Summary of the invention

[0004] In view of the shortcomings of the prior art mentioned above, the purpose of the present invention is to provide a motion detection and counting system based on millimeter wave radar technology, which is used to solve the technical problems that the existing motion counting detection mainly relies on manual recording, high frame rate cameras or wearable devices for analysis, and has insufficient real-time performance, convenience or accuracy.

[0005] To achieve the above-mentioned purpose and other related purposes, the present invention provides a motion detection and counting system based on millimeter wave radar technology, the system comprising: a low-power human body detection module, a radar system module, a main controller processing module, a wireless transceiver module and a result display module; wherein the low-power human body detection module is used to detect human activities in a target area in real time, and send a trigger signal to the radar system module when human activities are detected; the radar system module is connected to the low-power human body detection module, and is used to transmit a frequency modulated continuous wave signal to the target area after receiving the trigger signal, and mix the received echo signal with the transmission signal to generate an intermediate frequency signal; the main controller processing module is connected to the radar system module, and is used to perform target motion posture detection and counting according to the generated intermediate frequency signal to obtain corresponding motion detection and counting results, and control the display and storage of the motion detection and counting results; the wireless transceiver module is connected to the main controller processing module, and is used to send the obtained motion detection and counting results to a mobile terminal device; the result display module is connected to the main controller processing module, and is used to display the motion detection and counting results.

[0006] In one embodiment of the present invention, the low-power human detection module is used to detect whether there is a human body in the target area based on the human body detection data collected in real time. When the presence of a human body is detected, it is determined whether there is currently human activity in the target area based on a preset human motion detection threshold, and a trigger signal is sent to the radar system module when human activity is detected.

[0007] In one embodiment of the present invention, the target motion posture detection and counting based on the generated intermediate frequency signal to obtain the corresponding motion detection counting result includes: calculating the key motion information of each frame based on the generated intermediate frequency signal; performing target motion judgment on the key motion information of each frame collected within a specific time period, and counting to obtain the corresponding motion detection counting result.

[0008] In one embodiment of the present invention, the calculation of the key motion information of each frame according to the generated intermediate frequency signal includes: performing 1D Fourier transform and 2D Fourier transform on the intermediate frequency signal frame by frame, obtaining the energy of each speed unit corresponding to each distance unit, and storing them as elements in the distance-speed unit energy matrix, and each element is set with a corresponding speed unit subscript based on the close radar subscript range and the far radar subscript range; wherein the number of elements set in the horizontal direction of the distance-speed unit energy matrix is ​​the number of speed units involved, and the number of elements set in the vertical direction of the matrix is ​​the number of distance units involved; determining each distance in the distance-speed unit energy matrix The element with the largest energy corresponding to the unit, and record the corresponding energy and the speed unit subscript corresponding to the energy; count the number of elements that meet the conditions of moving away from the radar speed and the conditions of moving close to the radar among the elements with the largest energy corresponding to each distance unit; based on the number of elements that meet the conditions of moving away from the radar speed and the conditions of moving close to the radar, calculate the number of distance units with similar speed directions and typical similar speed values, as well as the number of distance units with the same speed direction and typical moving away speed values; based on the number of distance units with similar speed directions and typical similar speed values, as well as the number of distance units with the same speed direction and typical moving away speed values, calculate the key motion information of the current frame.

[0009] In one embodiment of the present invention, determining the element with the largest energy corresponding to each distance unit in the distance-speed unit energy matrix and recording the corresponding energy and the speed unit subscript corresponding to the energy includes: using a maximum value calculation formula or a constant false alarm detection algorithm to calculate the maximum energy corresponding to each distance unit in the distance-speed unit energy matrix and the speed unit subscript corresponding to the energy.

[0010] In one embodiment of the present invention, the counting of the number of elements that meet the far-from-radar speed condition and the approaching radar speed condition in the elements with the maximum energy corresponding to each distance unit includes: based on the far-from-radar speed condition set by the speed tolerance threshold, the energy access threshold, and the far-from-radar subscript range, determining the number of elements that meet the far-from-radar speed condition in the elements with the maximum energy corresponding to each distance unit; based on the approaching radar condition set by the speed tolerance threshold, the energy access threshold, and the approaching radar subscript range, determining the number of elements that meet the approaching radar speed condition in the elements with the maximum energy corresponding to each distance unit.

[0011] In one embodiment of the present invention, the key motion information of the current frame is calculated based on the number of distance units with similar speed directions and typical similar speed values ​​and the number of distance units with the same speed direction and typical distant speed values, including: comparing the number of distance units with similar speed directions and the number of distance units with the same speed direction, taking the maximum value of the two as the first motion significance parameter and taking the minimum value of the two as the second motion significance parameter; judging whether valid motion occurs based on the first motion significance parameter, the second motion significance parameter and the set threshold, and recording the corresponding ternary key motion information.

[0012] In one embodiment of the present invention, the target motion judgment is performed on the key motion information of each frame collected within a specific time period, and the corresponding motion detection count result is obtained by counting, which includes: periodically intercepting the ternary key motion information of each frame within the most recent specific time period, and arranging them in reverse chronological order; using machine learning methods and / or expert system calculation methods to output the corresponding motion detection count results based on the arranged ternary key motion information of each frame.

[0013] In one embodiment of the present invention, an expert system calculation method is used to output corresponding motion detection count results based on the ternary key motion information of each arranged frame, including: judging whether there is a target motion report based on the ternary key motion information of each frame, and recording the corresponding initial distance when it is judged that there is a target motion report, and determining the target motion judgment parameters based on the ternary key motion information of each frame, and making a target motion judgment according to the effective motion condition, and outputting the corresponding motion detection count results; wherein, the target motion judgment parameters include: falling start frame, falling start distance, rising end frame, rising end distance, rising start frame, and rising start distance.

[0014] In one embodiment of the present invention, the use of machine learning to output the corresponding motion detection count result according to the ternary key motion information of each arranged frame includes: inputting the ternary key motion information of each frame into the trained machine learning model, and directly outputting the corresponding motion detection count result; using machine learning and expert system calculation methods to output the corresponding motion detection count result according to the ternary key motion information of each arranged frame includes: judging whether there is a target motion report based on the ternary key motion information of each frame, and recording the corresponding initial distance when it is judged that there is a target motion report, and determining the target motion judgment parameter based on the ternary key motion information of each frame, and inputting the target motion judgment parameter into the trained machine learning model, and outputting the corresponding motion detection count result.

[0015] As described above, the present invention is a motion detection and counting system based on millimeter wave radar technology, which has the following beneficial effects: the present invention first detects human activities in the target area in real time through a low-power human detection module, and sends a trigger signal to the main controller processing module to activate the radar system module when human activities are detected, and then transmits a frequency modulated continuous wave signal to the target area through the radar system module, and mixes the received echo signal with the transmission signal to generate an intermediate frequency signal. The main controller processing module performs motion posture detection and counting according to the intermediate frequency signal to obtain the corresponding motion detection counting result, and controls the display and storage of the motion detection counting result, and finally sends the obtained motion detection counting result to the mobile terminal device through the wireless transceiver module. The present invention realizes automatic detection, counting and analysis of motion movements through the ranging, speed and angle measurement functions of the millimeter wave radar, thereby improving detection accuracy, real-time performance and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the flow of a motion detection and counting system based on millimeter wave radar technology in one embodiment of the present invention.

[0017] Figure 2 Shown is a schematic diagram of a human body detection process of a low-power human body detection module in an embodiment of the present invention.

[0018] Figure 3 Shown is a schematic diagram of the radar system module installation position in an embodiment of the present invention.

[0019] Figure 4 Shown is a schematic diagram of the process of calculating key motion information in one embodiment of the present invention.

[0020] Figure 5 Shown is a schematic diagram of a target motion determination process in an embodiment of the present invention.

[0021] Figure 6 FIG. 4 is a schematic diagram showing the structure of an electronic terminal in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0023] It should be noted that in the following description, reference is made to the accompanying drawings, which describe several embodiments of the present invention. It should be understood that other embodiments may also be used, and that mechanical composition, structural, electrical and operational changes may be made without departing from the spirit and scope of the present invention. The following detailed description should not be considered restrictive, and the scope of the embodiments of the present invention is limited only by the claims of the published patents. The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. Spatially related terms, such as "upper", "lower", "left", "right", "below", "below", "lower", "above", "upper", etc., may be used in the text to facilitate the description of the relationship between an element or feature shown in the figure and another element or feature.

[0024] Throughout the specification, when a part is said to be "connected" to another part, this includes not only the case of "direct connection" but also the case of "indirect connection" by placing other elements therebetween. In addition, when a part is said to "include" a certain constituent element, unless otherwise stated, it does not exclude other constituent elements, but means that other constituent elements may be included.

[0025] The terms first, second and third mentioned herein are used to describe various parts, components, regions, layers and / or segments, but are not limited thereto. These terms are only used to distinguish a certain part, component, region, layer or segment from other parts, components, regions, layers or segments. Therefore, the first part, component, region, layer or segment described below may refer to the second part, component, region, layer or segment within the scope of the present invention.

[0026] Furthermore, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless there is an indication to the contrary in the context. It should be further understood that the terms "comprise", "include" indicate the presence of the described features, operations, elements, components, items, kinds, and / or groups, but do not exclude the presence, occurrence or addition of one or more other features, operations, elements, components, items, kinds, and / or groups. The terms "or" and "and / or" used herein are interpreted as inclusive, or mean any one or any combination. Therefore, "A, B or C" or "A, B and / or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B and C". Exceptions to this definition will only occur when the combination of elements, functions or operations is inherently mutually exclusive in some way.

[0027] The present invention provides a motion detection and counting system based on millimeter wave radar technology. First, a low-power human body detection module is used to detect human activities in a target area in real time, and a trigger signal is sent to the main controller processing module to activate the radar system module when human activities are detected. Then, a frequency modulated continuous wave signal is transmitted to the target area through the radar system module, and the received echo signal is mixed with the transmission signal to generate an intermediate frequency signal. The main controller processing module performs motion posture detection and counting according to the intermediate frequency signal to obtain the corresponding motion detection counting result, and controls the display and storage of the motion detection counting result. Finally, the obtained motion detection counting result is sent to the mobile terminal device through the wireless transceiver module. The present invention realizes automatic detection, counting and analysis of motion actions through the ranging, speed and angle measurement functions of the millimeter wave radar, and improves detection accuracy, real-time performance and user experience.

[0028] The following is a detailed description of the embodiments of the present invention with reference to the accompanying drawings so that those skilled in the art can easily implement the present invention. The present invention can be embodied in many different forms and is not limited to the embodiments described herein.

[0029] like Figure 1 A structural schematic diagram of a motion detection and counting system based on millimeter wave radar technology in an embodiment of the present invention is shown.

[0030] The system includes: a low-power human body detection module 1, a radar system module 2, a main controller processing module 3, a wireless transceiver module 4 and a result display module 5; wherein, The low-power human body detection module 1 is used to detect human body activities in the target area in real time, and send a trigger signal to the radar system module when human body activities are detected; The radar system module 2 is used to transmit a frequency-modulated continuous wave signal to the target area after activation, and mix the received echo signal with the transmitted signal to generate an intermediate frequency signal; the radar system module 2 adopts FMCW (Frequency-Modulated Continuous-Wave) radar. FMCW radar technology has become a feasible solution for motion detection because of its accurate distance measurement, speed measurement and angle measurement capabilities, as well as strong anti-interference characteristics. FMCW radar transmits a continuous wave signal whose frequency changes linearly with time, and receives the signal reflected by the target for analysis. The basic principles of its distance measurement, speed measurement and angle measurement are as follows: The frequency of the signal emitted by the FMCW radar changes linearly with time, and the received signal will have a frequency difference with the transmitted signal due to propagation delay, namely the beat frequency. By calculating this frequency difference, combined with the swept waveform configuration and information such as the speed of light, the distance between the target and the radar can be obtained. The moving target will produce a Doppler frequency shift. By analyzing the Doppler frequency shift of the received signal, the radar can calculate the radial velocity of the target. Angle measurement principle: Calculate the azimuth or elevation angle of the target through the phase difference in the multi-antenna array.

[0031] The main controller processing module 3 is connected to the low-power human body detection module 1 and the radar system module 2, and is used to activate the radar system module 2 to work when receiving a trigger signal from the low-power human body detection module; it is also used to perform motion posture detection and counting according to the intermediate frequency signal generated by the radar system module 2 to obtain corresponding motion detection counting results, and control the display and storage of the motion detection counting results.

[0032] The wireless transceiver module 4 is responsible for data transmission and interaction with the mobile device. The wireless transceiver module 4 is connected to the main controller processing module 3, and is used to send the obtained motion detection counting results to the mobile device; specifically, the wireless transceiver module 4 may include: a WIFI transceiver module, and the motion detection counting results are sent to the mobile device for management via the WIFI module. A Bluetooth transceiver module, and the motion detection counting results are sent to the mobile terminal for management via the Bluetooth module. A command interaction module is responsible for data interaction between the WIFI / BT module and the main controller processing module 3.

[0033] The result display module 5 is connected to the main controller processing module 3 and is used to display the motion detection counting result; specifically, the result display module 5 can be a screen that displays the motion detection counting result on the screen, or it can be a voice playback device that is used to broadcast the corresponding motion detection counting result by voice.

[0034] In one embodiment, the main function of the low-power human detection module 1 is to wake up and switch the radar motion counting function through the trigger signal of the control circuit when detecting human activity in the target area through a passive infrared sensor (PIR) or a low-power radar. The low-power human detection module 1 is used to detect whether there is a human body in the target area according to the real-time collected human detection data, and when the presence of a human body is detected, determine whether there is human activity in the target area based on a preset human motion detection threshold, and send a trigger signal to the main controller processing module 3 when human activity is detected.

[0035] In a preferred embodiment, the low-power human body detection module 1 uses a low-power radar, and the specific detection process is as follows: like Figure 2 , the low-power radar is powered on and initialized, including setting the human motion detection threshold. After power-on initialization, the low-power radar is always in working state. When the radar transmits continuous wave or frequency modulated continuous wave signal, if the human body is moving relative to the radar, the signal reflected from the human body will shift in frequency due to the Doppler effect. The human body movement is detected by analyzing the changes in the signal. When the detected value exceeds the human motion detection threshold, a trigger signal is sent and the radar system module enters the motion detection and counting working mode.

[0036] In one embodiment, the radar system module 2 is set to be placed at a certain height, and the selection of this height is usually based on specific detection requirements. For example, it is determined based on factors such as the size of the target area, the surrounding environment, and the desired detection effect. A higher position may help expand the detection coverage and reduce the impact of obstructions on detection, thereby enabling a more comprehensive monitoring of the target area. For example Figure 3 The location displayed.

[0037] The radar system module 2 starts when receiving a trigger signal and completes the necessary initialization operations; the radar transmitter periodically transmits / receives a frequency modulated continuous wave sweep signal, mixes the received echo signal with the transmission signal to generate an intermediate frequency signal, and converts it into a digital signal through an analog-to-digital converter (ADC) and stores it. A typical frequency modulated continuous wave signal transmission method is that the transmitter transmits several groups of FMCW signals in a period (Tframe), each group of frequency modulated continuous wave signals contains multiple chirps, and each chirp scans a certain bandwidth. A group of periodically transmitted FMCW signals is called a frame.

[0038] Preferably, after the radar system module 2 is initialized, a radar calibration mark is read from a non-volatile memory. If the radar system module 2 has not been calibrated, a radar calibration program is entered and calibration parameters are saved in the non-volatile memory. If the radar system module 2 has been calibrated, the calibration value is directly read from the non-volatile memory. Calibration is performed according to the obtained calibration value, and subsequent motion posture detection and counting are performed after calibration.

[0039] In one embodiment, the main controller processing module 3 performs motion posture detection and counting according to the generated intermediate frequency signal to obtain corresponding motion detection and counting results, including: Step 1: Calculate the key motion information of each frame based on the generated intermediate frequency signal; Step 2: Target motion judgment is performed on the key motion information of each frame collected within a specific time period, and the corresponding motion detection counting result is obtained by counting.

[0040] In one embodiment, if Figure 4 , step 1 includes: Step 11: Perform 1D Fourier transform and 2D Fourier transform on the intermediate frequency signal frame by frame to obtain the energy of each speed unit corresponding to each distance unit, and store them as elements in the distance-speed unit energy matrix, and each element is set with a corresponding speed unit subscript based on the close radar subscript range and the far radar subscript range; Specifically, the space detected by the radar is divided into distance units, which are like concentric ring areas centered on the radar. For each such distance unit, different speed units are further subdivided to represent the different speed states that the target may have at that distance. According to the basic principle of the FMCW radar receiver, the 1D / 2D Fourier transform is performed frame by frame on the intermediate frequency signal to obtain the energy of each speed unit corresponding to each distance unit, and store them as elements in the range-speed unit (Range-Doppler-Bin) energy matrix; through the above transformation, the energy of different speed units in each distance unit can be known. This energy value reflects the possibility of the target appearing at the corresponding distance and speed state or the strength of the target reflection signal.

[0041] The energy db of each speed unit corresponding to each distance unit is stored in an N*M matrix, the number of elements M set in the vertical direction is the number of distance units involved, and the number of elements N set in the horizontal direction is the number of speed units involved, denoted as: P(m, n) where m∈[0, M-1], n∈[0, N-1]; Each element is set with a corresponding speed unit subscript based on the subscript range close to the radar and the subscript range far from the radar; in particular, for the speed unit subscript of zero Doppler (that is, no motion), it is recorded as n0 = N / 2. On this basis, the speed unit far from the radar is defined as [0, n0 - 1], which can be understood as the speed direction corresponding to these units in the speed dimension is to make the target away from the radar; and the speed unit close to the radar is [n0 + 1, N - 1], which means that the speed direction corresponding to these units is to make the target close to the radar. If the initial situation does not meet the requirements of such speed unit subscript setting in the actual signal processing or data storage process, this goal can also be achieved through the operation of Fourier transform shift (FFT shift), so as to ensure that the speed unit subscript setting of the entire distance-speed unit energy matrix complies with the established rules, so as to facilitate the subsequent accurate analysis and judgment of the target's distance, speed and direction of movement based on this information.

[0042] Step 12: Determine the element with the largest energy corresponding to each distance unit in the distance-speed unit energy matrix, and record the corresponding energy and the speed unit subscript corresponding to the energy.

[0043] Step 13: Count the number of elements that meet the speed condition of being away from the radar and the number of elements that meet the speed condition of being close to the radar among the elements with the largest energy corresponding to each distance unit.

[0044] Step 14: Based on the number of elements meeting the conditions of the speed away from the radar and the conditions of the speed close to the radar, the number of distance cells with similar speed directions and typical similar speed values ​​and the number of distance cells with the same speed directions and typical speed away values ​​are calculated.

[0045] Step 15: Calculate the key motion information of the current frame based on the number of distance units with similar speed directions and typical similar speed values ​​and the number of distance units with the same speed directions and typical distant speed values.

[0046] In one embodiment, step 12 includes: using a maximum value calculation formula or a constant false alarm detection algorithm to calculate the maximum energy corresponding to each distance unit in the distance-speed unit energy matrix and the speed unit subscript corresponding to the energy; Specifically, for each element in P(m, n), Pv(m) and Iv(m) are calculated, where Pv(m) represents the maximum energy in distance unit m; Iv(m) represents the speed unit subscript corresponding to the maximum energy in distance unit m.

[0047] Methods for calculating Pv(m) and Iv(m) using the maximum value calculation formula include: P(m,n); (1) P(m,n); (2)

[0048] In addition, the Constant False Alarm Rate (CFAR) algorithm is used to calculate Pv(m) and Iv(m). Its core purpose is to detect the target signal as accurately as possible from the complex background noise and interference while keeping the false alarm probability constant. The methods include: 1) When no valid CFAR detection point is found in a given distance unit m after constant false alarm detection, it is recorded as Pv(m) = 0, Iv(m) = -1; 2) When the distance unit m includes a valid CFAR detection point signal, the energy of the detection point signal is recorded as Pv(m), and the detection point velocity unit is marked as Iv(m); 3) When the distance unit m includes multiple valid CFAR detection point signals, Pv(m) and Iv(m) are regarded as queues containing multiple elements, and the energy of the detection point signals is recorded one by one as Pv(m), and the corresponding speed units are recorded one by one as Iv(m).

[0049] The above-mentioned constant false alarm detection technology can be used in the speed dimension alone or in the distance-speed dimension.

[0050] In one embodiment, step 13 includes: counting the number of elements that meet the speed condition of being away from the radar and the number of elements that meet the speed condition of being close to the radar among the elements with the largest energy corresponding to each distance unit; Based on the radar-away speed condition set by the speed tolerance threshold, the energy access threshold, and the radar-away subscript range, the number of elements that meet the radar-away speed condition among the elements with the largest energy corresponding to each distance unit is determined; Specifically, traverse all Iv(m) records and count the number of elements that simultaneously meet the following conditions of speed away from the radar: cnt(n) : ; (3) ; (4) Iv(m) ∈[0, n0-1]; (5) Wherein, in formula (3), n is a reference speed unit subscript for comparison, Nthreshold is the speed tolerance threshold; P threshold is the energy admission threshold, which is a non-negative threshold; abs is the calculation for the absolute value; Based on the approaching radar condition set by the speed tolerance threshold, the energy access threshold, and the approaching radar subscript range, the number of elements that meet the approaching radar speed condition among the elements with the largest energy corresponding to each distance unit is determined.

[0051] Traverse all Iv(m) records and count the number of elements R that simultaneously meet the following conditions for the speed close to the radar: Ncnt(n) : ; (6) ; (7) Iv(m) ∈[n0+1, N-1]; (8) It should be noted that if Pv(m) and Iv(m) are queues containing multiple elements, the above operations act on each element of the Pv(m) and Iv(m) queues.

[0052] In one embodiment, step 14 includes: Based on the number of elements that meet the conditions of speed away from the radar and the conditions of approaching the radar RP cnt(n) and R Ncnt(n) , calculate the number of distance units P with similar velocity directions cnt,max and typical similar speed value P v,max And the number of distance units N with the same velocity direction cnt,max and the typical value of the runaway velocity N v,max , and its calculation formula includes: (9) (10) (11) (12) Formula (9) is to count the number of elements with the largest number under the condition of speed far from the radar, which provides a key quantitative index for analyzing the speed distribution of the target in the direction far from the radar; Formula (10) is to find the speed unit subscript when the speed condition far from the radar is met and the number of elements is the largest as the typical similar speed value, which helps to grasp the speed characteristics of the target in this direction; Formula (11) is to count the number of elements with the largest number under the condition of speed close to the radar, which provides an important quantitative reference index for analyzing the speed distribution of the target in the direction close to the radar; Formula (12) is to find the speed unit subscript when the speed condition close to the radar is met and the number of elements is the largest as the typical similar speed value, which helps to grasp the speed characteristics of the target in this direction.

[0053] It should be noted that if RP cnt(n) If all elements in P are 0, then v,max = -1; if RNcnt(n) If all elements in N are 0, then v,max = -1.

[0054] In one embodiment, step 15 includes: Compare the number of distance cells with similar velocity directions And the number of distance units with the same velocity direction , taking the maximum value of the two as the first motion significance parameter CM and taking the minimum value of the two as the second motion significance parameter CN; Based on the first motion significance parameter CM, the second motion significance parameter CN and the set threshold C threshold and D threshold Determine whether valid motion occurs and record the corresponding ternary key motion information; Specifically, when analyzing the target (such as the human body) squatting, jumping and other movements, from the perspective of radar detection, there will be multiple distance units with similar speeds and the same speed direction. When the movement in these main directions is significant enough, it can be determined that there is a valid movement in the current frame of radar detection. The "significance" here refers to the use of specific parameters to measure whether the characteristics of the target movement in terms of speed and distance unit distribution are prominent enough to determine whether it is a truly meaningful movement.

[0055] Therefore, the significance parameter is defined as: CM = Max(P cnt,max , N cnt,max ) ; (13) CN = Min(P cnt,max , N cnt,max ); (14) Among them, P cnt,max is the number of distance units with similar velocity directions obtained previously by calculation, N cnt,max is the number of distance cells with the same velocity direction.

[0056] If the saliency parameters meet the following conditions, the frame is considered to have a valid motion: CM > Cthreshold; (15) CM > D threshold ×CN; (16) Among them, C threshold and D threshold are two non-negative thresholds respectively.

[0057] If there is valid motion in this frame, the frame records the ternary key motion information according to the following rules: ; (17) ; (18) ; (19) Among them, CMN is regarded as a quantitative representation of relative significance; V can be understood as representing the more dominant typical speed value under the current effective motion situation; the determination of R comprehensively considers multiple factors such as the energy of the distance unit, the speed direction, and the speed tolerance with the typical speed value; in formula (19), The absolute value of the difference with V must be less than the speed tolerance threshold , the maximum energy Pv(m) in the distance unit m must be greater than the energy admission threshold , and (Iv(m)-n0)×(V-n0)>0 m This condition is limited from the perspective of speed direction consistency, ensuring that the selected distance unit is consistent with the typical speed value V determined previously in the speed direction.

[0058] If there is no valid motion in this frame, the frame records the ternary key motion information according to the following rules: CMN = 0; (20) V = -1; (21) R = -1; (22) Directly assigning CMN a value of 0 means that when there is no effective motion in the current frame, its relative significance quantization value is 0. Using -1 to represent the value of V means that when there is no effective motion, there is no corresponding typical speed value, which is used to mark this state of no effective motion. Similarly, assigning R a value of -1 means that when there is no effective motion, there is no specific distance unit that meets the relevant conditions to be recorded, which reflects the state of missing relevant information when there is no effective motion.

[0059] In one embodiment, if Figure 5 , step 2 includes: Step 21: periodically intercepting the ternary key motion information of each frame in the recent specific time period and arranging them in reverse time order; Specifically, we need to periodically capture the ternary key motion information of each frame within the recent specific time period. The specific time period can be set according to the needs, such as S seconds; the S seconds here is a set time window. By focusing on the data within this relatively short time period, we can capture the recent motion state changes of the target more timely, while avoiding the problem of too much data causing the analysis to be too complicated. For the ternary key motion information of each frame i within these S seconds,<CMN, V,R> The triplets are arranged in reverse time order, denoted as cmn[i], v[i] and r[i], where i∈[0,k-1]; k represents the number of triplets collected in the last S seconds, that is, the number of triplets corresponding to the number of frames contained in this time window. Arranging and storing in reverse time order means that the latest data will be stored at position i=0, and the earlier data will be stored in turn, with the earliest data stored at position i=k-1.

[0060] Step 22: Using a machine learning method and / or an expert system calculation method, output corresponding counting results according to the arranged ternary key motion information of each frame.

[0061] In one embodiment, the output of the corresponding motion detection count results according to the arranged ternary key motion information of each frame by using an expert system calculation method includes: Based on the ternary key motion information of each frame, determine whether there is a target motion report, and record the corresponding initial distance if it is determined that there is a target motion report, and determine the target motion judgment parameters based on the ternary key motion information of each frame, and make target motion judgments according to valid target motion conditions, and output the corresponding motion detection count results; wherein the target motion judgment parameters include: falling start frame, falling start distance, rising end frame, rising end distance, rising start frame, and rising start distance.

[0062] Specifically, the target movement can be jumping or squatting. During the jumping and squatting process, the human body Doppler velocity changes from approaching (n∈[0, m0]) to moving away (n∈[m0+1, M-1]), and the human body distance radar also has a far-near-far operation. During the squatting process, the human body Doppler velocity changes from moving away (n∈[m0+1, M-1]) to moving closer (n∈[0, m0]), and the human body distance radar also has a near-far-near operation. The jump decision process is now described: Based on the velocity information v(0) of the latest frame (i.e. the frame corresponding to v(0)), we can preliminarily judge whether there is a jump report. If v(0) is -1, it means that there is no typical velocity value related to effective motion, or v(0) is close information (v[0]∈[0,m0]). In this case, it is determined that there is no jump report for this frame. Otherwise, the initial distance at this time is recorded as Rfall_end , this distance information can be used as an initial reference value for subsequent judgment of position changes during the jump process.

[0063] First, determine the falling start frame and the falling start distance. The specific method is as follows: Start searching for v from i = 0, looking back at the data in the past M frames; here, a basic judgment condition for effective falling is set: among these M frames, there are greater than or equal to N frames where v[i] is within the range of away information (v[i] ∈ [m0 + 1, M - 1]), and there is no frame where v[i] is within the range of close information (v[i] ∈ [0, m0]), then it is considered that an effective fall is recorded.

[0064] After meeting the above preliminary judgment conditions for effective falling, next, further accurately determine the specific frame subscript at which the fall starts and the corresponding position information. Specifically: Continuously search for the largest v[t] within the range M <= t < K, and v[t] also needs to meet the following additional limiting conditions: 1) Among v[i] (0 <= i < t), the number of records where v[i] is -1 is less than or equal to C v0 ; 2) Among v[i] (0 <= i < t), the number of records where v[i] is close information is less than or equal to C v1 ; 3) v[t] itself is away information; And when the conditions are met, the value t is the falling start frame, denoted as F dn_start， At this time, the distance record is R fn_start .

[0065] Next, determine the rising end frame and the rising end position. The specific method is as follows: Start from i = F dn_start + 1 and search for the largest v[t] within the range F dn_start < t < K, and v[t] also needs to meet the following additional limiting conditions: 1) Among v[i] (Fdn_start < i < t), the number of records where v[i] is not -1 is less than or equal to Cv2; 2) V[t] = -1; And when the conditions are met, the value t is the rising end frame, denoted as Fup_end, and the distance record at this time is Rup_end.

[0066] Next, determine the rising start frame and the rising start distance. The methods include: Start searching from i = Fup_end + 1 for the largest v[t] within the range Fup_end < t < K, and the following additional constraints need to be satisfied: 1) Among v[i] (Fup_end < i < t), the number of records where v[i] is -1 is less than or equal to Cv3; 2) Among v[i] (Fup_end < i < t), the number of records where v[i] is far - away information is less than or equal to Cv4; 3) v[t] itself is close - in information; And when the conditions are met, the value t is the starting frame of the rise, denoted as F up_start At this time, the distance record is R up_start； It should be noted that the C v0、 C v1、 C v2、 C v3、 C v4 is a non - negative integer and is related to the frame rate; generally speaking, the larger the frame rate, the larger the above values need to be correspondingly.

[0067] Finally, calculate the average value Amn of cmn[i] (0 <= i <= Fup_start); According to the relationship among F fall_start、 R fall_start、 F up_end、 R up_end、 F up_start,、 R up_start、 R fall_end、 A series of criteria can be defined to determine whether there is a valid jump, including some or all of the following criteria: 1) The total jump time should be greater than a given threshold: F up_start > Threshold ，1 ; 2) The jump - up time should be greater than a given threshold: F up_start -F up_end >Threshold ,2 ; 3) The time of staying in the air, forming zero speed, should not be too long: F up_end -F fall_start <Threshold ,3 ; 4) The landing time should be greater than a given threshold: F fall_start >Threshold ,4 ; 5) When staying in the air and forming zero speed, the distance should not change suddenly: abs(R up_end -R fall_start )< Threshold ,5 ; 6) The take-off and landing heights should not change suddenly: abs(R up_start -R fall_end ) < Threshold ,6 ; 7) Abnormal disturbances should not be too much mn < Threshold ,7 ; If it is determined to be a valid jump, record F up_start The sampling time t corresponding to the frame is different for two recorded sampling times, which is considered as a new jump; otherwise, it is considered as a repeated record of a jump.

[0068] It should be noted that the squatting process is the reverse operation of the jumping operation, which means that during the squatting process, the human body will show the opposite change characteristics in speed and distance relative to the radar. During the jumping process, the human body first approaches the radar (the corresponding speed direction is in the close information range), and then moves away from the radar (the corresponding speed direction is in the far information range). For the squatting process, the reverse process is to start from the speed state away from the radar, and then change to the speed state close to the radar, which is derived based on the opposite logic of the jump in the speed direction. During the squatting process, the human body will show a change from near-far-near. That is, at the beginning, the distance to the radar is relatively close, then gradually becomes farther, and finally returns to a relatively close position, which is exactly the opposite of the distance change during the jump. Therefore, based on the detailed processing methods of each stage of the above-mentioned jumping process, the reverse logic of the above-mentioned speed and distance changes can be used to infer how to determine the processing methods of key stages such as the start and end of squatting during the squatting process. This will not be elaborated. For example, in the process of jumping, the falling start frame is determined by judging that the speed direction continues to move away within a certain number of frames, and in the process of squatting, the relevant frame information of the squatting start is determined by judging that the speed direction continues to move closer within a certain number of frames. For example, in the process of jumping, the rising end frame is determined according to the speed value of -1 and other conditions, and when squatting, the squatting end frame may be determined according to similar but reverse speed-related conditions. In addition, for operations such as recording the distance of the corresponding stage, reasonable settings and reasoning can be made according to the reverse situation of the distance change, so as to construct a complete squatting process processing method, which is used to analyze the manifestation of squatting as a human movement behavior in radar detection data and related feature judgments.

[0069] In one embodiment, when analyzing human body motion, in addition to the expert system calculation method based on rules and conditional judgment mentioned above, a machine learning method can also be used. The core idea is to directly use the three-element key motion information of each frame arranged in sequence.<CMN,V, R> As input data, it is provided to the trained machine learning model, and the model automatically analyzes these data features and outputs the corresponding counting results, that is, the statistics of the target movement (such as the number of jumps and squats, etc.) are completed. In this embodiment, a classifier can be used to machine learn and classify the ternary key motion information of each frame, and a judgment criterion can be given. The classifier can use a support vector machine (SVM), logistic regression, and a long short-term memory neural network (LSTM).

[0070] In one embodiment, when analyzing the target motion and obtaining the target motion judgment parameters, a method combining machine learning and expert system calculation is adopted. Although both are based on machine learning technology, they differ in the use of data features. Instead of directly using the triple sequence mentioned above,<CMN,V,R> As learning features, a series of target motion judgment parameters recorded by expert system are selected, including: F fall_start、 R fall_start、 F up_end、 R up_end、 F up_start,、 R up_start、 R fall_end、 A mn Data. These data are used as input data to provide to the trained machine learning model, which automatically analyzes these data features and outputs the corresponding counting results, that is, completing the statistics of the target movement (such as the number of jumps and squats, etc.).

[0071] In one embodiment, after obtaining the motion detection counting result, it is determined whether it is necessary to exit the pedometer mode. If it is not necessary to exit, the next frame signal is transmitted and subsequent processing is performed.

[0072] The motion detection and counting system based on millimeter wave radar technology provided in the embodiment of the present invention can be implemented on the terminal side or the server side. As for the hardware structure of the electronic terminal, please refer to Figure 6, which is an optional hardware structure diagram of a motion detection and counting terminal 1000 of the millimeter wave radar technology provided in an embodiment of the present invention. The terminal 1000 may be a mobile phone, a computer device, a tablet device, a personal digital processing device, a factory background processing device, etc. The terminal 1000 includes: at least one processor 1001, a memory 1002, at least one network interface 10010 and a user interface 1009. The various components in the device are coupled together through a bus system 1005. It can be understood that the bus system 1005 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 1005 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, in Figure 6 In the specification, various buses are labeled as bus systems.

[0073] The user interface 1009 may include a display, a keyboard, a mouse, a trackball, a click gun, keys, buttons, a touch pad or a touch screen.

[0074] It is understood that the memory 1002 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), which is used as an external cache. By way of exemplary but not limiting explanation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM). The memory described in the embodiments of the present invention is intended to include but is not limited to these and any other suitable categories of memory.

[0075] The memory 1002 in the embodiment of the present invention is used to store various categories of data to support the operation of the terminal 1000. Examples of these data include: any executable program for operating on the terminal 1000, such as an operating system 10021 and an application 10022; the operating system 10021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application 10022 may include various applications, such as a media player (MediaPlayer), a browser (Browser), etc., for implementing various application services. The motion detection and counting system based on millimeter wave radar technology provided in the embodiment of the present invention may be included in the application 10022.

[0076] The method disclosed in the above embodiment of the present invention can be applied to the processor 1001, or implemented by the processor 1001. The processor 1001 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 1001 or the instruction in the form of software. The above processor 1001 may be a general processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 1001 can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiment of the present invention. The general processor 1001 can be a microprocessor or any conventional processor, etc. In combination with the steps of the accessory optimization method provided in the embodiment of the present invention, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0077] In an exemplary embodiment, the terminal 1000 may be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD) to execute the aforementioned method.

[0078] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to the computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

[0079] In the embodiments provided in the present application, the computer readable and writable storage medium may include a read-only memory, a random access memory, an EEPROM, a CD-ROM or other optical disk storage device, a disk storage device or other magnetic storage device, a flash memory, a USB flash drive, a mobile hard disk, or any other medium that can be used to store the desired program code in the form of an instruction or data structure and can be accessed by a computer. In addition, any connection can be appropriately referred to as a computer-readable medium. For example, if the instruction is sent from a website, a server or other remote source using a coaxial cable, an optical fiber cable, a twisted pair, a digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, the coaxial cable, optical fiber cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of the medium. However, it should be understood that computer readable and writable storage media and data storage media do not include connections, carriers, signals, or other temporary media, but are intended to be non-temporary, tangible storage media. Disk and disc, as used in this application, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers.

[0080] Compared with the prior art, the present invention has the following advantages:

[0081] 1. Provide a low-power and millimeter-wave radar collaborative solution: Low-power radar can always maintain operation and continuously monitor the surrounding environment due to its excellent low-energy consumption characteristics. In comparison, millimeter-wave radar consumes relatively high energy during operation, so a selective working mechanism is adopted to start only when necessary. By cleverly using low-power radar as a trigger source to activate the millimeter-wave radar to work, the two complement each other, effectively overcoming the problem of excessive overall power consumption and providing a solid guarantee for the continuous and stable operation of the system.

[0082] 2. Non-contact precise measurement: Relying on cutting-edge millimeter-wave radar technology, this invention has achieved non-contact precise detection of human body movements. This innovative measure completely eliminates the inconvenience and discomfort that may be caused by traditional contact measurement methods, comprehensively improves the comfort of the movement detection process, and greatly simplifies the operation process, giving users a more convenient and efficient use experience.

[0083] 3. Efficient data transmission and intelligent management: The system integrates an advanced data transmission module, which is like a bridge that seamlessly connects the internal detection system with various external devices. Whether it is a convenient mobile phone APP or a powerful computer terminal, sports data can be transmitted to these external devices in real time and stably, allowing users to conduct comprehensive and accurate real-time control of sports information anytime and anywhere, fully meeting diverse usage needs.

[0084] 4. Multivariate motion counting algorithm system: The present invention constructs a comprehensive, multi-level motion counting algorithm architecture. Among them, the single-frame judgment mechanism based on the unit maximum statistical principle can accurately capture key information at the single-frame data level; the jump / squat judgment strategy based on the expert system fully draws on the knowledge of experts in the field to conduct in-depth analysis of complex motion states; and the cutting-edge machine learning technology based on abstract features, with the help of big data training models, intelligently identifies various motion patterns. The three work together to ensure the high accuracy of motion counting.

[0085] 5. Wide application: The present invention has excellent cross-domain adaptability and is deeply integrated into multiple key fields such as medical health, sports, and school education. Whether it is to assist in motion monitoring in the process of medical rehabilitation, or to provide accurate data feedback for sports training, or to achieve quantitative management of students' sports status in campus education scenarios, it has demonstrated incomparable practical value, injected new vitality into the development of various industries, and created broad prospects.

[0086] In summary, the motion detection and counting system based on millimeter wave radar technology of the present invention first detects human activities in the target area in real time through a low-power human detection module, and sends a trigger signal to the main controller processing module to activate the radar system module when human activities are detected, and then transmits a frequency-modulated continuous wave signal to the target area through the radar system module, and mixes the received echo signal with the transmission signal to generate an intermediate frequency signal. The main controller processing module performs motion posture detection and counting according to the intermediate frequency signal to obtain the corresponding motion detection counting result, and controls the display and storage of the motion detection counting result, and finally sends the obtained motion detection counting result to the mobile terminal device through the wireless transceiver module. The present invention realizes automatic detection, counting and analysis of motion movements through the ranging, speed measurement and angle measurement functions of the millimeter wave radar, and improves detection accuracy, real-time performance and user experience. Therefore, the present invention effectively overcomes the various shortcomings in the prior art and has a high industrial utilization value.

[0087] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A motion detection and counting system based on millimeter wave radar technology, characterized in that: The system includes: a low-power human body detection module, a radar system module, a main controller processing module, a wireless transceiver module and a result display module; wherein, The low-power human detection module is used to detect human activities in the target area in real time and send a trigger signal to the radar system module when human activities are detected; The radar system module is used to transmit a frequency modulated continuous wave signal to the target area after being activated, and mix the received echo signal with the transmitted signal to generate an intermediate frequency signal; The main controller processing module is connected to the low-power human body detection module and the radar system module, and is used to activate the radar system module to work after receiving the trigger signal; it is also used to detect and count the target motion posture according to the generated intermediate frequency signal to obtain the corresponding motion detection counting result, and control the display and storage of the motion detection counting result; The wireless transceiver module is connected to the main controller processing module and is used to send the obtained motion detection counting results to the mobile terminal device; The result display module is connected to the main controller processing module and is used to display the motion detection counting result.

2. The motion detection and counting system based on millimeter wave radar technology according to claim 1, characterized in that: The low-power human detection module is used to detect whether there is a human body in the target area based on the human body detection data collected in real time. When the presence of a human body is detected, it is determined whether there is currently human activity in the target area based on a preset human motion detection threshold, and a trigger signal is sent to the radar system module when human activity is detected.

3. The motion detection and counting system based on millimeter wave radar technology according to claim 1, characterized in that: The method of performing target motion posture detection and counting according to the generated intermediate frequency signal to obtain corresponding motion detection counting results includes: Calculate key motion information of each frame based on the generated intermediate frequency signal; The target motion judgment is performed on the key motion information of each frame collected within a specific time period, and the corresponding motion detection counting result is obtained by counting.

4. The motion detection and counting system based on millimeter wave radar technology according to claim 3, characterized in that: Calculating the key motion information of each frame according to the generated intermediate frequency signal includes: Perform 1D Fourier transform and 2D Fourier transform on the intermediate frequency signal frame by frame to obtain the energy of each speed unit corresponding to each distance unit, and store them as elements in the distance-speed unit energy matrix, and each element is set with a corresponding speed unit subscript based on the close radar subscript range and the far radar subscript range; wherein the number of elements set in the horizontal direction of the distance-speed unit energy matrix is ​​the number of speed units involved, and the number of elements set in the vertical direction of the matrix is ​​the number of distance units involved; Determine the element with the largest energy corresponding to each distance unit in the distance-speed unit energy matrix, and record the corresponding energy and the speed unit subscript corresponding to the energy; Count the number of elements that meet the speed condition of being away from the radar and the number of elements that meet the speed condition of being close to the radar among the elements with the largest energy corresponding to each distance unit; Based on the number of elements meeting the condition of moving away from the radar speed and the number of elements meeting the condition of moving towards the radar, the number of distance cells with similar speed directions and typical similar speed values ​​and the number of distance cells with the same speed directions and typical moving away speed values ​​are calculated; The key motion information of the current frame is calculated based on the number of distance units with similar velocity directions and typical similar velocity values ​​and the number of distance units with the same velocity directions and typical distant velocity values.

5. The motion detection and counting system based on millimeter wave radar technology according to claim 4, characterized in that: The step of determining the element with the largest energy corresponding to each distance unit in the distance-speed unit energy matrix and recording the corresponding energy and the speed unit subscript corresponding to the energy includes: The maximum energy corresponding to each distance unit in the distance-speed unit energy matrix and the speed unit subscript corresponding to the energy are calculated using a maximum value calculation formula or a constant false alarm detection algorithm.

6. The motion detection and counting system based on millimeter wave radar technology according to claim 4, characterized in that: The number of elements that meet the speed condition of being away from the radar and the speed condition of being close to the radar among the elements with the largest energy corresponding to each distance unit is counted as follows: Based on the radar-away speed condition set by the speed tolerance threshold, the energy access threshold, and the radar-away subscript range, the number of elements that meet the radar-away speed condition among the elements with the largest energy corresponding to each distance unit is determined; Based on the approaching radar condition set by the speed tolerance threshold, the energy access threshold, and the approaching radar subscript range, the number of elements that meet the approaching radar speed condition among the elements with the largest energy corresponding to each distance unit is determined.

7. The motion detection and counting system based on millimeter wave radar technology according to claim 4, characterized in that: The key motion information of the current frame is calculated based on the number of distance units with similar speed directions and typical similar speed values ​​and the number of distance units with the same speed directions and typical far-away speed values, including: Comparing the number of distance units with similar speed directions and the number of distance units with the same speed direction, taking the maximum value of the two as the first motion significance parameter and taking the minimum value of the two as the second motion significance parameter; Based on the first motion significance parameter, the second motion significance parameter and the set threshold, it is determined whether effective motion occurs, and the corresponding ternary key motion information is recorded.

8. The motion detection and counting system based on millimeter wave radar technology according to claim 7, characterized in that: The step of performing target motion judgment on key motion information of each frame collected within a specific time period and performing counting to obtain corresponding motion detection counting results includes: Periodically capture the ternary key motion information of each frame in the recent specific time period and arrange them in reverse time order; By using a machine learning method and / or an expert system calculation method, the corresponding motion detection counting result is output according to the arranged ternary key motion information of each frame.

9. The motion detection and counting system based on millimeter wave radar technology according to claim 8, characterized in that: The expert system calculation method is used to output the corresponding motion detection counting results according to the arranged ternary key motion information of each frame, including: Based on the ternary key motion information of each frame, determine whether there is a target motion report, and record the corresponding initial distance if it is determined that there is a target motion report. Determine the target motion judgment parameters based on the ternary key motion information of each frame, and make target motion judgment according to the effective motion conditions, and output the corresponding motion detection count result; wherein the target motion judgment parameters include: falling start frame, falling start distance, rising end frame, rising end distance, rising start frame, and rising start distance.

10. The motion detection and counting system based on millimeter wave radar technology according to claim 9, characterized in that: The method of outputting the corresponding motion detection counting result according to the arranged ternary key motion information of each frame by using a machine learning method comprises: inputting the ternary key motion information of each frame into a trained machine learning model, and directly outputting the corresponding motion detection counting result; Using machine learning and expert system calculation methods, the corresponding motion detection count results are output according to the arranged ternary key motion information of each frame, including: judging whether there is a target motion report based on the ternary key motion information of each frame, and recording the corresponding initial distance when it is judged that there is a target motion report, and determining the target motion judgment parameters based on the ternary key motion information of each frame, and inputting the target motion judgment parameters into the trained machine learning model to output the corresponding motion detection count results.

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