Unmanned intelligent biological threat monitoring method based on Internet

Abstract

The invention provides an unmanned intelligent biological threat monitoring method based on the Internet, and relates to the technical field of biological threat monitoring, and the method comprises the steps: collecting the physiological signal data of a human body through radar equipment, including various parameters of transmitting and receiving signals, such as the transmitting time, frequency, amplitude and phase, analyzing the radar signal data, and obtaining the data of the radar signal; generating a radar transmitting signal expression and a radar receiving signal expression, further analyzing the intermediate-frequency signal, analyzing and determining the relationship between the phase change of the intermediate-frequency signal and the breathing fluctuation of the chest of the human body, further collecting the environment temperature, analyzing a thermal noise signal generated by the temperature in the detection process, and determining the temperature of the human body. And generating a temperature noise index for reflecting the variable quantity of noise power caused by temperature change, generating an intermediate frequency phase jitter index for reflecting the jitter degree of the intermediate frequency signal phase caused by temperature, and outputting an evaluation accuracy level.

Description

Technical Field

[0001] The present invention relates to the technical field of biological threat monitoring, and in particular to an Internet-based unmanned intelligent biological threat monitoring method. Background Art

[0002] Biological threat monitoring is used to monitor and assess whether the human body is under biological threats. When the human body is under biological threats, it will cause respiratory disorders. When the human body is threatened by viruses and bacteria, the body temperature changes, and the responses of various organs change. Each organ has a strong connection with the heart, which will increase the burden on the heart, and the human body will show respiratory disorders externally. The monitoring process can monitor the changes in the chest cavity through radar signals and further generate the degree of respiratory disorder. In this process, data can be shared through the Internet, and equipment can be remotely controlled or data can be analyzed. Remote monitoring of respiratory disorders can be achieved to determine whether the human body is under biological threats from viruses and bacteria.

[0003] However, radar signals will be affected by external environmental factors during the monitoring process. When the temperature changes, thermal noise will be generated. Thermal noise is random noise caused by the thermal motion of electrons. When radar signals are received, the thermal noise signals caused by temperature will also be received, thus affecting the accuracy of radar signal reception. It is difficult for staff to judge the accuracy of the analysis results based on experience.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The purpose of the present invention is to provide an unmanned intelligent biological threat monitoring method based on the Internet to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] An unmanned intelligent biological threat monitoring method based on the Internet is used to monitor and evaluate whether the human body is exposed to respiratory disorders caused by biological threats. The specific steps include:

[0008] S1. transmitting a radar signal to a human chest cavity and collecting radar signal data, wherein the radar signal data includes a transmitting time, a minimum frequency, a maximum frequency, a frequency sweep period, an amplitude, and an initial phase of the transmitting signal and a receiving time, an amplitude, and an initial phase of the receiving signal;

[0009] S2. Perform correlation analysis on the minimum frequency and the maximum frequency of the transmitted signal to generate the transmitted signal bandwidth, perform correlation analysis on the transmitted signal bandwidth and radar signal data to generate a transmitted signal frequency expression;

[0010] S3. Analyze the frequency expression of the transmitted signal to generate the radar transmitted signal expression, perform correlation analysis on the radar transmitted signal expression and the transmitting time of the transmitted signal and the receiving time of the received signal to generate the radar received signal expression;

[0011] S4. After the transmission signal and the receiving signal are mixed and processed by a low-pass processor, an intermediate frequency signal is generated. The radar receiving signal expression and the radar transmitting signal expression are subjected to correlation analysis to generate the phase of the intermediate frequency signal. The phase of the intermediate frequency signal is analyzed to generate the chest cavity fluctuation variation d′(t). The chest cavity fluctuation variation d′(t) is used to reflect the degree of change of the human chest cavity over time. is the phase change of the intermediate frequency signal;

[0012] S5. Collect the temperature during measurement, and perform correlation analysis on the temperature and the transmission signal bandwidth to generate a temperature noise index, and further analyze and generate an intermediate frequency phase jitter index ΔΦ(t). The intermediate frequency phase jitter index ΔΦ(t) is used to reflect the degree of jitter of the intermediate frequency signal phase caused by temperature.

[0013] S6. Perform correlation analysis on the intermediate frequency phase jitter index ΔΦ(t) and the chest rise and fall variation d′(t) to generate a measurement evaluation accuracy index CPZ. The measurement evaluation accuracy index CPZ is used to reflect the accuracy of the chest rise and fall variation measured by the radar signal. A threshold is set, and the measurement evaluation accuracy index CPZ is compared with the accuracy threshold θ to output an accuracy level. Whether the chest rise and fall variation is accurate is outputted through the accuracy level. If it is accurate, the chest rise and fall variation is used for biological threat assessment. If it is inaccurate, repeat step 1.

[0014] Furthermore, in S1, a continuous wave radar signal is transmitted by a radar transmitting device, and the continuous wave radar signal is collected by a radar receiving device.

[0015] Furthermore, the minimum frequency f of the transmitted signal min , maximum frequency f max Correlation analysis is performed to generate the transmit signal bandwidth B, based on the formula:

[0016] B=f max -f min

[0017] Perform correlation analysis on the transmit signal bandwidth and radar signal data to generate the transmit signal frequency expression f (t) :

[0018]

[0019] Among them, T s is the frequency sweep period, and the frequency expression of the transmitted signal is f (t) It is used to reflect the relationship between the frequency of the transmitted signal and time. t is the time variable of the transmitted radar signal, and the starting point of the transmitted radar signal is taken as the zero point.

[0020] Furthermore, the frequency expression of the transmitted signal f (t) Perform analysis and generate the radar transmission signal expression x f (t), based on the formula:

[0021]

[0022] Where A is the amplitude of the transmitted signal, is the initial phase of the transmitted signal, and the radar transmitted signal expression x f (t) is used to reflect the relationship between the signal strength and time of the transmitted signal.

[0023] Furthermore, the radar transmission signal expression x f (t) and the transmission time t1 of the transmission signal, the reception time t2 of the reception signal, the amplitude A2 of the reception signal, the initial phase of the reception signal Perform correlation analysis to generate the radar receiving signal expression x j (t), based on the formula:

[0024]

[0025] Radar received signal expression x j (t) is used to reflect the relationship between the signal strength of the received signal and time, Δt=t2-t1.

[0026] Furthermore, the radar receiving signal expression x j (t), radar transmission signal expression x f (t) Perform correlation analysis to generate the intermediate frequency signal x i (t), based on the formula:

[0027]

[0028] Among them, s is an imaginary number, f3 is the frequency of the intermediate frequency signal, is the phase of the intermediate frequency signal, and the radar receiving signal expression x j (t), radar transmission signal expression x f (t), intermediate frequency signal x i(t), the phase of the intermediate frequency signal output by MATLAB software Where D is the distance between the human body and the radar, d(t) is the displacement of the human chest cavity in time, and c is the speed of light;

[0029] right Taking the derivative, we get That is, the chest cavity fluctuation change d'(t) is generated based on the formula: Among them, the chest cavity fluctuation change d′(t) is used to reflect the degree of change of the human chest cavity over time. is the phase change of the intermediate frequency signal.

[0030] Furthermore, the temperature T(t) is collected, and a correlation analysis is performed on the temperature T(t) and the transmission signal bandwidth B to generate the temperature noise index N(t), based on the following formula:

[0031] N(t)=k[T(t)+273.15]*B

[0032] Where k is the Boltzmann constant, temperature T(t) is the ambient temperature that changes with time during radar detection, and the temperature noise index N(t) is used to reflect the change in noise power caused by temperature changes;

[0033] Correlation analysis is performed on the temperature noise index N(t) to generate the intermediate frequency phase jitter index ΔΦ based on the formula:

[0034]

[0035] Among them, P1(t) is the signal power of the radar transmission signal that changes with time during radar detection, and the intermediate frequency phase jitter index ΔΦ(t) is used to reflect the degree of jitter of the intermediate frequency signal phase caused by temperature.

[0036] Furthermore, the correlation analysis is performed on the intermediate frequency phase jitter index ΔΦ(t) and the chest rise and fall variation d′(t) to generate the measurement evaluation accuracy index CPZ, based on the formula:

[0037]

[0038] in, is the phase change of the intermediate frequency signal The maximum value of the measurement evaluation accuracy index CPZ is used to reflect the accuracy of the chest rise and fall changes measured by the radar signal. t4 is the end time of the measurement;

[0039] The accuracy threshold θ is set to 1.39, and the measurement evaluation accuracy index CPZ is compared with the accuracy threshold θ. When CPZ>θ, the accuracy level of the chest rise and fall changes measured by the output radar signal is level two, and the chest rise and fall changes measured by the radar signal are inaccurate; when CPZ≤θ, the accuracy level of the chest rise and fall changes measured by the output radar signal is level one, and the chest rise and fall changes measured by the radar signal are accurate.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] The present invention collects physiological signal data of the human body through radar equipment, including various parameters of the transmitted and received signals, such as the transmission time, frequency, amplitude and phase, analyzes the radar signal data, generates a radar transmission signal expression and a radar reception signal expression, and further analyzes the intermediate frequency signal, analyzes and determines the relationship between the phase change of the intermediate frequency signal and the chest breathing fluctuation of the human body, and further collects the ambient temperature, analyzes the thermal noise signal generated by the temperature during the detection process, generates a temperature noise index for reflecting the change of noise power caused by temperature changes, and generates an intermediate frequency phase jitter index for reflecting the degree of jitter of the intermediate frequency signal phase caused by temperature, and performs correlation analysis on the intermediate frequency phase jitter index and the chest fluctuation change, generates a measurement evaluation accuracy index for reflecting the accuracy of the chest fluctuation change measured by the radar signal, and outputs the evaluation accuracy level. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic diagram of the overall method flow of the present invention. DETAILED DESCRIPTION

[0043] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0044] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include 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 may 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.

[0045] Example:

[0046] See also Figure 1 , the present invention provides a technical solution:

[0047] An unmanned intelligent biological threat monitoring method based on the Internet is used to monitor and evaluate whether the human body is threatened by biological threats and causes respiratory disorder. When the human body is threatened by viruses or bacteria, the temperature of the human body changes, and the responses of various organs change. Each organ has a strong connection with the heart, which will increase the burden on the heart, so that the human body will show respiratory disorder externally. Whether the human body is threatened by viruses or bacteria can be judged by monitoring whether the breathing is disordered. The data collected by the radar equipment of the present invention is shared based on the Internet, and the data can be received remotely. The more rapid the breathing frequency, the higher the degree of the human body's irritation reaction. The specific steps include:

[0048] Step 1, transmitting a radar signal to the human chest cavity and collecting radar signal data, the radar signal data including the transmitting time, minimum frequency, maximum frequency, sweep period, amplitude, initial phase of the transmitting signal and the receiving time, amplitude, initial phase of the receiving signal; transmitting a continuous wave radar signal through a radar transmitting device and collecting the continuous wave radar signal through a radar receiving device.

[0049] The radar transmits and receives signals, and collects radar signal data to generate expressions for transmit and receive signals. The process of analyzing the expressions is as follows:

[0050] Step 2: Perform correlation analysis on the minimum frequency and the maximum frequency of the transmitted signal to generate the transmitted signal bandwidth, perform correlation analysis on the transmitted signal bandwidth and radar signal data to generate a transmitted signal frequency expression;

[0051] Minimum frequency f for transmitted signal min , maximum frequency f max Correlation analysis is performed to generate the transmit signal bandwidth B, based on the formula:

[0052] B=f max -f min

[0053] Perform correlation analysis on the transmit signal bandwidth and radar signal data to generate the transmit signal frequency expression f (t) :

[0054]

[0055] Among them, T s is the frequency sweep period, and the frequency expression of the transmitted signal is f (t)It is used to reflect the relationship between the frequency of the transmitted signal and time. t is the time variable of the transmitted radar signal, and the starting point of the transmitted radar signal is taken as the zero point.

[0056] Step 3: In order to further analyze the transmission signal and the receiving signal, it is necessary to clarify the various parameters of their expressions. Therefore, the transmission signal frequency expression is analyzed, and the frequency domain conversion is performed to generate the radar transmission signal expression. The radar transmission signal expression and the transmission time of the transmission signal and the reception time of the reception signal are correlated and analyzed to generate the radar reception signal expression.

[0057] In order to facilitate calculation, frequency domain conversion is performed and the frequency expression of the transmitted signal f (t) Perform analysis and generate the radar transmission signal expression x f (t), based on the formula:

[0058]

[0059] Where A is the amplitude of the transmitted signal, is the initial phase of the transmitted signal, and the radar transmitted signal expression x f (t) is used to reflect the relationship between the signal strength and time of the transmitted signal.

[0060] The radar transmits the signal expression x f (t) and the time difference, amplitude and phase of the received signal to analyze and generate the radar receiving signal. The radar transmitting signal expression x f (t) and the transmission time t1 of the transmission signal, the reception time t2 of the reception signal, the amplitude A2 of the reception signal, the initial phase of the reception signal Perform correlation analysis to generate the radar receiving signal expression x j (t), based on the formula:

[0061]

[0062] Radar received signal expression x j (t) is used to reflect the relationship between the signal strength of the received signal and time, Δt=t2-t1.

[0063] Step 4: In order to determine the relationship between the chest fluctuation change and the radar transmission signal and the receiving signal, first analyze the intermediate frequency after the transmission signal and the receiving signal are mixed. After the transmission signal and the receiving signal are mixed, they are processed by a low-pass processor to generate an intermediate frequency signal. The radar reception signal expression and the radar transmission signal expression are correlated and analyzed to generate the phase of the intermediate frequency signal. The phase of the intermediate frequency signal is analyzed to generate the chest fluctuation change d′(t). The chest fluctuation change d′(t) is used to reflect the degree of change of the human chest over time. is the phase change of the intermediate frequency signal;

[0064] The expression of radar receiving signal x j (t), radar transmission signal expression x f (t) Perform correlation analysis to generate the intermediate frequency signal x i (t), based on the formula:

[0065]

[0066] Among them, s is an imaginary number, f3 is the frequency of the intermediate frequency signal, is the phase of the intermediate frequency signal, and the radar receiving signal expression x j (t), radar transmission signal expression x f (t), intermediate frequency signal x i (t), the phase of the intermediate frequency signal output by MATLAB software Where D is the distance between the human body and the radar, d(t) is the displacement of the human chest cavity in time, and c is the speed of light;

[0067] right Taking the derivative, we get That is, the chest cavity fluctuation change d'(t) is generated based on the formula: Among them, the chest cavity fluctuation change d′(t) is used to reflect the degree of change of the human chest cavity over time. is the phase change of the intermediate frequency signal. The phase change of the intermediate frequency signal is proportional to the change of the chest rise and fall. After determining the numerical relationship, the change of the chest rise and fall can be obtained by analyzing the phase change of the intermediate frequency signal.

[0068] Step 5: collect the temperature during measurement, and perform correlation analysis on the temperature and the transmission signal bandwidth to generate a temperature noise index, and further analyze and generate an intermediate frequency phase jitter index ΔΦ(t). The intermediate frequency phase jitter index ΔΦ(t) is used to reflect the degree of jitter of the intermediate frequency signal phase caused by temperature;

[0069] When the radar transmits and receives signals, the external temperature will interfere with the signal strength, thereby generating noise and affecting the measurement results. In order to analyze the impact of temperature on the measurement, the temperature T(t) is collected, and the correlation analysis between the temperature T(t) and the transmission signal bandwidth B is performed to generate the temperature noise index N(t). The formula is as follows:

[0070] N(t)=k[T(t)+273.15]*B

[0071] The degree of temperature noise is proportional to the temperature and the bandwidth of the transmitted signal, so it is calculated using the above formula, where k is the Boltzmann constant, temperature T(t) is the ambient temperature that changes with time during radar detection, and the temperature noise index N(t) is used to reflect the change in noise power caused by temperature changes;

[0072] The correlation analysis of the temperature noise index N(t) is performed to generate the intermediate frequency phase jitter index ΔΦ(t), based on the formula:

[0073]

[0074] The phase jitter of the intermediate frequency signal is proportional to the temperature noise. At the same time, the greater the signal power, the smaller the phase jitter will be, because a strong signal can better cover up the noise. Among them, P1(t) is the signal power of the radar transmission signal that changes with time during radar detection. The intermediate frequency phase jitter index ΔΦ(t) is used to reflect the degree of jitter of the intermediate frequency signal phase caused by temperature.

[0075] Step 6: Perform correlation analysis on the intermediate frequency phase jitter index ΔΦ(t) and the chest rise and fall variation d′(t) to generate a measurement evaluation accuracy index CPZ. The measurement evaluation accuracy index CPZ is used to reflect the accuracy of the chest rise and fall variation measured by the radar signal. A threshold is set, and the measurement evaluation accuracy index CPZ is compared with the accuracy threshold θ to output an accuracy level. The accuracy level is used to output whether the chest rise and fall variation is accurate. If it is accurate, the chest rise and fall variation is used for biological threat assessment. If it is inaccurate, repeat step 1.

[0076] The correlation analysis of the intermediate frequency phase jitter index ΔΦ(t) and the chest rise and fall variation d′(t) is performed to generate the measurement evaluation accuracy index CPZ, based on the following formula:

[0077]

[0078] in, is the phase change of the intermediate frequency signal The maximum value of t4 is the measurement end time, and the measurement evaluation accuracy index CPZ is used to reflect the accuracy of the chest rise and fall changes measured by the radar signal; the smaller the value of the measurement evaluation accuracy index CPZ, the smaller the influence of temperature on the chest rise and fall changes, and the higher the measurement accuracy.

[0079] The accuracy threshold θ is set to 1.39, and the measurement evaluation accuracy index CPZ is compared with the accuracy threshold θ. When CPZ>θ, the accuracy level of the chest rise and fall changes measured by the output radar signal is level two, and the chest rise and fall changes measured by the radar signal are inaccurate; when CPZ≤θ, the accuracy level of the chest rise and fall changes measured by the output radar signal is level one, and the chest rise and fall changes measured by the radar signal are accurate.

[0080] The present invention also provides a module for executing an Internet-based unmanned intelligent biological threat monitoring method, comprising:

[0081] A radar signal data acquisition module, used for acquiring radar signal data;

[0082] The transmission signal frequency analysis module is used to perform correlation analysis on the minimum frequency and maximum frequency of the transmission signal to generate the transmission signal bandwidth, perform correlation analysis on the transmission signal bandwidth and radar signal data, and generate the transmission signal frequency expression;

[0083] The signal analysis module is used to analyze the frequency expression of the transmitted signal to generate the radar transmitted signal expression, and to perform correlation analysis on the radar transmitted signal expression and the transmitting time of the transmitted signal and the receiving time of the received signal to generate the radar received signal expression;

[0084] The intermediate frequency signal analysis module is used to mix the transmission signal and the reception signal, and then generate the intermediate frequency signal after processing by the low-pass processor, perform correlation analysis on the radar reception signal expression and the radar transmission signal expression, generate the phase of the intermediate frequency signal, analyze the phase of the intermediate frequency signal, and generate the chest cavity fluctuation change;

[0085] The temperature analysis module is used to collect the temperature during measurement, and perform correlation analysis on the temperature and the transmission signal bandwidth to generate the temperature noise index, and further analyze and generate the intermediate frequency phase jitter index;

[0086] The comprehensive analysis module is used to perform correlation analysis on the intermediate frequency phase jitter index ΔΦ(t) and the chest rise and fall change d′(t), generate the measurement evaluation accuracy index CPZ, and the measurement evaluation accuracy index CPZ is used to reflect the accuracy of the chest rise and fall changes measured by the radar signal, and set a threshold, compare the measurement evaluation accuracy index CPZ with the accuracy threshold θ, and output the accuracy level.

[0087] The radar signal data collected by the present invention can be processed to generate the amount of change in the rise and fall of the human chest cavity. The degree of threat to the human body can be analyzed by identifying disease-related texts on the Internet (such as pathogen names and incidence rates). Geographic information can be automatically extracted and can be used to link multiple reports together. The dictionary of the system can be continuously expanded, initially including Chinese and English.

[0088] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0089] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0090] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0091] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. An unmanned intelligent biological threat monitoring method based on the Internet, used to monitor and evaluate whether the human body is exposed to respiratory disorders caused by biological threats, characterized in that: The specific steps include: S1. transmitting a radar signal to a human chest cavity and collecting radar signal data, wherein the radar signal data includes a transmitting time, a minimum frequency, a maximum frequency, a frequency sweep period, an amplitude, and an initial phase of the transmitting signal and a receiving time, an amplitude, and an initial phase of the receiving signal; S2. Perform correlation analysis on the minimum frequency and the maximum frequency of the transmitted signal to generate the transmitted signal bandwidth, perform correlation analysis on the transmitted signal bandwidth and radar signal data to generate a transmitted signal frequency expression; S3. Analyze the frequency expression of the transmitted signal to generate the radar transmitted signal expression, perform correlation analysis on the radar transmitted signal expression and the transmitting time of the transmitted signal and the receiving time of the received signal to generate the radar received signal expression; S4. After mixing the transmission signal and the reception signal, the intermediate frequency signal is generated after being processed by a low-pass processor. The radar reception signal expression and the radar transmission signal expression are subjected to correlation analysis to generate the phase of the intermediate frequency signal. The phase of the intermediate frequency signal is analyzed to generate the chest cavity fluctuation variation. , chest cavity rise and fall variation Used to reflect the degree of change of the human chest cavity over time. is the phase change of the intermediate frequency signal; S5. Collect the temperature during measurement, and perform correlation analysis on the temperature and the transmission signal bandwidth to generate the temperature noise index, and further analyze and generate the intermediate frequency phase jitter index. , IF phase jitter index Used to reflect the degree of jitter of the intermediate frequency signal phase caused by temperature; S6, intermediate frequency phase jitter index and chest rise and fall Correlation analysis is performed to generate the measurement evaluation accuracy index CPZ, which is used to reflect the accuracy of chest fluctuation changes measured by radar signals, and to set a threshold. The measurement evaluation accuracy index CPZ is compared with the accuracy threshold. A comparison is performed and an accuracy level is output. The accuracy level is used to output whether the chest rise and fall variation is accurate. If it is accurate, the chest rise and fall variation is used for biological threat assessment. If it is inaccurate, step 1 is repeated.

2. The method of an Internet-based unmanned intelligent biological threat monitoring method according to claim 1, characterized in that: In S1, a continuous wave radar signal is transmitted by a radar transmitting device, and a continuous wave radar signal is received by a radar receiving device.

3. The method of an Internet-based unmanned intelligent biological threat monitoring method according to claim 2, characterized in that: Minimum frequency of transmitted signal , Maximum frequency Correlation analysis is performed to generate the transmit signal bandwidth B, based on the formula: Perform correlation analysis on the transmit signal bandwidth and radar signal data to generate the transmit signal frequency expression : in, is the frequency sweep period, and the frequency expression of the transmitted signal is It is used to reflect the relationship between the transmission signal frequency and time. is the time variable of transmitting radar signal, and the starting point of transmitting radar signal is taken as the zero point.

4. Among them, A is the amplitude of the transmitted signal, is the initial phase of the transmitted signal, and the radar transmitted signal expression is Used to reflect the relationship between the signal strength and time of the transmitted signal.

5. The method of an Internet-based unmanned intelligent biological threat monitoring method according to claim 4, characterized in that: Radar transmission signal expression and the time at which the signal is transmitted , the time of receiving the received signal , the amplitude of the received signal , the initial phase of the received signal Perform correlation analysis to generate radar receiving signal expression , the formula based on is: Radar received signal expression It is used to reflect the relationship between the signal strength and time of the received signal. .

6. The method of an Internet-based unmanned intelligent biological threat monitoring method according to claim 5, characterized in that: Expression for radar receiving signal 、Radar transmission signal expression Perform correlation analysis to generate intermediate frequency signals , the formula based on is: Among them, s is an imaginary number, is the frequency of the intermediate frequency signal, is the phase of the intermediate frequency signal, and the combined radar receiving signal expression is 、Radar transmission signal expression , intermediate frequency signal , output the phase of the intermediate frequency signal through matlabe software , where D is the distance between the human body and the radar, is the fluctuation displacement of the human chest cavity in time, and c is the speed of light; right Taking the derivative, we get , that is, to generate the chest cavity fluctuation variation , the formula based on is: , where the chest rise and fall variation Used to reflect the degree of change of the human chest cavity over time. is the phase change of the intermediate frequency signal.

7. The method of an Internet-based unmanned intelligent biological threat monitoring method according to claim 6, characterized in that: Collection temperature , for temperature Correlation analysis is performed with the transmit signal bandwidth B to generate the temperature noise index , the formula based on is: Where k is the Boltzmann constant, temperature is the ambient temperature that changes with time during radar detection, the temperature noise index Used to reflect the change in noise power caused by temperature changes; Noise Index vs. Temperature Perform correlation analysis to generate IF phase jitter index The formula is: in, The signal power of the radar transmission signal changing with time during radar detection, the intermediate frequency phase jitter index It is used to reflect the degree of jitter of the intermediate frequency signal phase caused by temperature.

8. The method of an Internet-based unmanned intelligent biological threat monitoring method according to claim 7, characterized in that: Phase jitter index for intermediate frequency and chest rise and fall Correlation analysis is performed to generate the measurement evaluation accuracy index CPZ, based on the formula: in, is the phase change of the intermediate frequency signal The maximum value of the measurement evaluation accuracy index CPZ is used to reflect the accuracy of the chest rise and fall changes measured by the radar signal. is the measurement end time; Setting accurate thresholds is 1.39, and the accuracy index CPZ and the accuracy threshold are measured and evaluated. For comparison, when When , the accuracy level of chest fluctuation measured by the output radar signal is level 2, and the chest fluctuation measured by the radar signal is inaccurate; when When , the accuracy level of the chest cavity fluctuation changes measured by the output radar signal is level one, and at this time, the chest cavity fluctuation changes measured by the radar signal are accurate.

Images