CN114063067A - Object state sensing detection method and system - Google Patents

Object state sensing detection method and system Download PDF

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CN114063067A
CN114063067A CN202111358176.0A CN202111358176A CN114063067A CN 114063067 A CN114063067 A CN 114063067A CN 202111358176 A CN202111358176 A CN 202111358176A CN 114063067 A CN114063067 A CN 114063067A
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张强
李晨曲
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Shenzhen Feirui Intelligent Co ltd
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Abstract

The invention relates to the technical field of induction recognition, in particular to an object state induction detection method and system. The method comprises the following steps: acquiring intermediate frequency data, and obtaining the speed component of the current intermediate frequency data through fast Fourier transform; analyzing and judging the obtained velocity components, and clustering the velocity components and analyzing the value positions to judge a target object corresponding to the velocity components; detecting the energy maximum value of each speed component of the target object, comparing the energy maximum value with a preset energy value interval, and judging the distance and the action amplitude of the target object corresponding to the energy maximum value; and outputting a sensing detection result according to the distance and the action amplitude of the target object. The invention can judge the category of the target object and judge the action amplitude of the target object by calculating the energy maximum value of the velocity component, and can detect whether the target object is in a large action, a micro action or a static state.

Description

Object state sensing detection method and system
Technical Field
The invention relates to the technical field of induction recognition, in particular to an object state induction detection method and system for object detection.
Background
At present, an infrared sensor is mainly adopted in the market to detect an application scene so as to judge whether a person exists. However, when the infrared sensor is used for sensing detection, the infrared sensor is often affected by objects with strong light and high temperature, so that the human body cannot be effectively detected, and the target cannot be accurately detected. Moreover, when the infrared sensor is used for detection, only one point or a certain angle range can be detected, the detection range is small, and the sensing detection requirements in various application scenes cannot be met.
And the microwave sensor is a device for detecting some physical quantity using the characteristics of microwaves. There are two modulation methods currently used in the industry for microwave sensors: FMCW and CW, wherein CW modulation is also called Continuous Wave (CW) modulation, and is a continuous wave signal, in fact a sine wave as a carrier wave, and CW may include linear modulation (AM, DSB, SSB, VSB, etc.), nonlinear modulation (FM, PM), digital modulation (ASK, FSK, etc.). Since CW modulation can only detect dynamic objects, it cannot detect micromotion and static states. Therefore, it is desirable to provide a method and system for object condition sensing detection.
Disclosure of Invention
In order to solve the problem that the existing modulation can only detect dynamic objects and cannot detect micromotion and static states, the invention constructs an object state induction detection method and system, adopts the advantages of a microwave sensor, can detect large-motion, micromotion and static-state objects, and has a large detection range.
The invention is realized by adopting the following technical scheme:
an object state sensing detection method comprises the following steps:
acquiring intermediate frequency data, and obtaining the speed component of the current intermediate frequency data through fast Fourier transform;
analyzing and judging the obtained velocity components, and clustering the velocity components and analyzing the value positions to judge a target object corresponding to the velocity components;
detecting the energy maximum value of each speed component of the target object, comparing the energy maximum value with a preset energy value interval, and judging the distance and the action amplitude of the target object corresponding to the energy maximum value;
and outputting a sensing detection result according to the distance and the action amplitude of the target object.
As a further aspect of the present invention, a method for obtaining a velocity component of the current intermediate frequency data includes:
capturing intermediate frequency data;
removing direct current from the captured intermediate frequency data, and adding a Hanning window;
and obtaining the velocity component of the current intermediate frequency data through fast Fourier transform.
Further, the intermediate frequency data is a waveform obtained by transmitting an electromagnetic wave with a fixed frequency by the sensor, reflecting the electromagnetic wave by the object, receiving the signal by the sensor, and mixing the signal, and the mixing formula of the intermediate frequency data is as follows:
Ifmixing of＝sin[(ω1-ω2)]
Wherein, ω is1For transmitting frequency, omega2Is the receive frequency.
Further, the intermediate frequency data reflects the velocity components of all velocities, and the sampling frequency of the captured intermediate frequency data is 315 hz.
Further, the velocity components of all velocities reflected by the intermediate frequency signal of the intermediate frequency data are velocities reflected by the moving object, the velocities reflected by the moving object are calculated according to a doppler effect, and the doppler effect formula is as follows:
Figure BDA0003358041110000021
wherein f isDDoppler or difference frequencies;
f0the transmitting frequency of the radar;
v is the speed range of the moving object;
c0the speed of light;
alpha is the angle between the actual direction of motion and the line connecting the sensor to the target object.
Further, when the intermediate frequency data is subjected to direct current removal, all the acquired intermediate frequency data are added and divided by the average value and then subtracted due to the fact that the direct current signal is a fixed value, and the value y of the processed intermediate frequency signal is obtainedk1The calculation formula of (2) is as follows:
Figure BDA0003358041110000031
wherein x iskFor the acquired intermediate frequency data, N is the number of the intermediate frequency data acquired this time.
Furthermore, after the intermediate frequency data is subjected to direct current removal, a Hanning window adding method is to multiply the acquired data by a function, namely, adding a window; the intermediate frequency signal is subjected to DC-removing processing and then subjected to windowing againkThe calculation formula of (2) is as follows:
Figure BDA0003358041110000032
wherein: x is the number ofkFor the acquired intermediate frequency data, N is the number of the intermediate frequency data acquired this time.
Further, an FFT function formula f for obtaining the velocity component of the current intermediate frequency data through Fast Fourier Transform (FFT) is:
f＝(a0,a1,…,an-1)
the odd terms and the even terms are respectively proposed and constructed as follows
Figure BDA0003358041110000033
The coefficient of (a) represents, wherein a is the intermediate frequency signal after windowing and direct current removal;
f0＝(a0,a2,…,an-2)
f1＝(a1,a3,…,an-1)
has f (x) ═ f0(x2)+xf1(x2)；
For the
Figure BDA0003358041110000041
Is provided with
Figure BDA0003358041110000042
Figure BDA0003358041110000043
Order to
Figure BDA0003358041110000044
Is provided with
Figure BDA0003358041110000045
Figure BDA0003358041110000046
The above-mentioned series of operations is called butterfly operations,
Figure BDA0003358041110000047
referred to as the twiddle factor;
recursive determination of y[0],y[1]All on a scale of
Figure BDA0003358041110000048
Merging to obtain y;
Figure BDA0003358041110000049
the frequency information of the current waveform is obtained after the calculation, and in the FFT, the interval df between adjacent spectral lines is as follows:
Figure BDA00033580411100000410
wherein fs is a sampling frequency, N is the number of the intermediate frequency data collected this time, Ts is a sampling time interval, the spectral line interval determines the frequency resolution of FFT, and when the spectral line interval is large, useful information will be lost due to the fence effect.
As a further scheme of the present invention, the speed components corresponding to different target objects have different values after clustering, for example, when determining whether the target object is a person or a fan, since the speed components of the fan have values at several fixed positions, and the human body has multiple and continuous speed components, after clustering the speed components, it is determined whether the speed components meet the above logic, and whether the target object is a person or a fan is obtained.
Further, the method for clustering the velocity components comprises the following steps:
setting a frequency point threshold value of clustering operation;
searching a frequency point which is larger than the threshold value, marking the frequency point after the frequency point is found, calling the value of the frequency point as a head, and then continuing the cycle;
and searching a frequency point smaller than the threshold value, marking the frequency point after the frequency point is found, and ending the circulation by calling the value of the frequency point as a tail.
Further, the method for judging the target object corresponding to the velocity component includes:
subtracting the value corresponding to the head from the value corresponding to the tail to obtain a difference value;
and judging the category of the target object according to the magnitude of the difference value.
The invention also comprises an object state sensing detection system, which adopts the sensing detection method to judge the category and the action amplitude of the target object and detect the large action, the micro-motion and the static state of the target object; the object state sensing detection system comprises a speed component calculation module, a target object judgment module and a state analysis module.
The speed component calculation module is used for obtaining the speed component of the current intermediate frequency data through fast Fourier transform on the acquired intermediate frequency data;
the target object judgment module is used for analyzing and judging the obtained speed components, and judging target objects corresponding to the speed components by clustering the speed components and analyzing the value positions;
the state analysis module is used for detecting the energy maximum value of each speed component of the target object, comparing the energy maximum value with a preset energy value interval, judging the distance and the action amplitude of the target object corresponding to the energy maximum value, and analyzing and outputting an induction detection result according to the distance and the action amplitude of the target object.
The invention also includes a computer apparatus comprising: the object state sensing device comprises at least one processor and a memory which is in communication connection with the at least one processor, wherein the memory stores instructions which can be executed by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor executes the object state sensing detection method.
The present invention also includes a computer readable storage medium having stored thereon computer instructions for causing the computer to execute the object state sensing detection method.
The technical scheme provided by the invention has the following beneficial effects:
the invention detects the intermediate frequency data emitted and reflected by the electromagnetic wave through the sensing device, analyzes and judges the speed component of the intermediate frequency data, judges the type of the target object by utilizing different values of the speed components of different types of target objects, judges the action amplitude of the target object by calculating the maximum energy value of the speed component, can detect whether the target object is in a large action, micro action or static state, can obtain the approximate distance of the target object, judges whether a person exists according to the output result, and is suitable for sensing and detecting the target object in application scenes such as offices, meeting rooms or sickbeds.
These and other aspects of the invention are apparent from and will be elucidated with reference to the embodiments described hereinafter. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
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In order to more clearly illustrate the embodiments of the present invention or technical solutions in the related art, the drawings, which are needed to be used in the description of the exemplary embodiments or related art, will be briefly described below, and are used for providing further understanding of the present invention and are a part of the specification, and together with the embodiments of the present invention, serve to explain the present invention without limiting the present invention. In the drawings:
fig. 1 is a flow chart of an object state sensing detection method according to the present invention.
Fig. 2 is a flow chart of obtaining a velocity component of the intermediate frequency data in the object state sensing detection method according to an embodiment of the present invention.
Fig. 3 is a schematic structural diagram of an angle α in the object state sensing detection method according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of an intermediate frequency signal collected in the object state sensing detection method according to an embodiment of the present invention.
Fig. 5 is a diagram illustrating a value after fast fourier transform in an object state sensing detection method according to an embodiment of the invention.
FIG. 6 is a system diagram of an object state sensing detection system in accordance with an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In some of the flows described in the present specification and claims and in the above figures, a number of operations are included that occur in a particular order, but it should be clearly understood that these operations may be performed out of order or in parallel as they occur herein, with the order of the operations being indicated as 101, 102, etc. merely to distinguish between the various operations, and the order of the operations by themselves does not represent any order of performance. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first", "second", etc. in this document are used for distinguishing different messages, devices, modules, etc., and do not represent a sequential order, nor limit the types of "first" and "second" to be different.
The technical solutions in the exemplary embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the exemplary embodiments of the present invention, and it is apparent that the described exemplary embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart of an object state sensing detection method according to the present invention. The invention provides an object state induction detection method, which comprises the following steps:
and S1, acquiring intermediate frequency data, and obtaining the speed component of the current intermediate frequency data through fast Fourier transform.
It should be noted that, the method for obtaining the velocity component of the intermediate frequency data includes:
s101, capturing intermediate frequency data;
s102, removing direct current from the captured intermediate frequency data, and adding a Hanning window;
and S103, obtaining the speed component of the current intermediate frequency data through fast Fourier transform.
In this embodiment, the intermediate frequency data reflects velocity components of all velocities, and the Intermediate Frequency (IF) data is data that is transmitted out of the electromagnetic wave and reflected back, and reflects velocity components of all velocities. In this embodiment, the sampling frequency of the captured intermediate frequency data is 315hz, and the data collected at other frequencies is incomplete.
The intermediate frequency data is a waveform obtained by transmitting an electromagnetic wave with a fixed frequency by a sensor, reflecting the electromagnetic wave by an object, receiving the signal by the sensor and mixing the signal, and the mixing formula of the intermediate frequency data is as follows:
Ifmixing of＝sin[(ω1-ω2)]
Wherein, ω is1For transmitting frequency, omega2Is the receive frequency.
The velocity components of all velocities reflected by the intermediate frequency signals of the intermediate frequency data are velocities reflected by the moving object, the velocities reflected by the moving object are calculated according to a Doppler effect, and the Doppler effect formula is as follows:
Figure BDA0003358041110000081
wherein f isDDoppler or difference frequencies;
f0the transmitting frequency of the radar;
v is the speed range of the moving object;
c0the speed of light;
the angle between the actual direction of motion and the line connecting the sensor to the target object, a is shown schematically in fig. 3.
In this embodiment, when the intermediate frequency data is dc-removed, since the dc signal is a fixed value, all the acquired intermediate frequency data are added and divided by the average value, and then subtracted, that is, the processed value y of the intermediate frequency signal is obtainedk1The calculation formula of (2) is as follows:
Figure BDA0003358041110000091
wherein x iskFor the acquired intermediate frequency data, N is the number of the intermediate frequency data acquired this time.
After the direct current of the intermediate frequency data is removed, a Hanning window is added by multiplying the acquired data by a function, namely adding a window; the intermediate frequency signal is subjected to DC removal processing and thenThe value y of the second passkThe calculation formula of (2) is as follows:
Figure BDA0003358041110000092
wherein: x is the number ofkFor the acquired intermediate frequency data, N is the number of the intermediate frequency data acquired this time.
It should be noted that, if the FFT is performed directly on the data without windowing, the problem of spectral leakage occurs, and the windowing can reduce the leakage of the spectrum after FFT.
In this embodiment, an FFT function formula f for obtaining the velocity component of the current intermediate frequency data through Fast Fourier Transform (FFT) is:
f＝(a0,a1,…,an-1)
the odd terms and the even terms are respectively proposed and constructed as follows
Figure BDA0003358041110000093
The coefficient of (a) represents, wherein a is the intermediate frequency signal after windowing and direct current removal;
f0＝(a0,a2,…,an-2)
f1＝(a1,a3,…,an-1)
has f (x) ═ f0(x2)+xf1(x2)；
For the
Figure BDA0003358041110000094
Is provided with
Figure BDA0003358041110000095
Figure BDA0003358041110000096
Order to
Figure BDA0003358041110000101
Is provided with
Figure BDA0003358041110000102
Figure BDA0003358041110000103
The above-mentioned series of operations is called butterfly operations,
Figure BDA0003358041110000104
referred to as the twiddle factor;
recursive determination of y[0],y[1]All on a scale of
Figure BDA0003358041110000105
Are combined to obtain y
Figure BDA0003358041110000106
The frequency information of the current waveform is obtained after the calculation, and in the FFT, the interval df between adjacent spectral lines is as follows:
Figure BDA0003358041110000107
wherein fs is a sampling frequency, N is the number of the intermediate frequency data collected this time, Ts is a sampling time interval, the spectral line interval determines the frequency resolution of FFT, and when the spectral line interval is large, useful information will be lost due to the fence effect.
In this embodiment, the sampling rate of 315Hz is used as an example in fs, and the number of sampling points is 128 points, so the frequency resolution is:
Figure BDA0003358041110000108
calculating the speed 1m/s of the radar according to a radar formula as follows:
Figure BDA0003358041110000109
calculating the Doppler speed of the intermediate frequency signal when outputting a sine wave of 38.6Hz to be 1m/s, and obtaining the frequency resolution by substituting:
Figure BDA00033580411100001010
i.e. the resolution of one velocity component is: 0.06375m/s, the sensor does not support angle measurement, so it has no direction judgment.
Examples are as follows:
fig. 4 and 5 are waveforms of signals received by a radar, wherein fig. 4 is a collected intermediate frequency signal, which is subjected to windowing and dc removal, fig. 5 is a value after FFT (fast fourier transform), and the picture shown in fig. 5 after FFT is viewed, wherein the abscissa is the frequency resolution of FFT and the ordinate is the energy value.
And S2, analyzing and judging the obtained velocity components, and clustering the velocity components and analyzing the value positions to judge the target object corresponding to the velocity components.
In this embodiment, the value positions of the clustered speed components corresponding to different target objects are different, for example, when it is determined whether the target object is a person or a fan, since the speed components of the fan only have values at several fixed positions, and the human body has multiple and continuous speed components, after the speed components are clustered, it is determined which logic the speed components conform to, and whether the target object is a person or a fan is obtained.
Taking the judgment of whether the object is a person or a fan as an example, the speed components are clustered, and because the speed components of the fan only have values of a plurality of fixed positions, and the human body has various positions and continuous speed components, the logic that the speed components accord with the above is judged, and whether the object of the target object is a person or a fan is obtained. It should be noted that the sampling frequency does not occur at a fraction of a hertz.
In this embodiment, the method for clustering the velocity components includes:
setting a frequency point threshold value of clustering operation;
searching a frequency point which is larger than the threshold value, marking the frequency point after the frequency point is found, calling the value of the frequency point as a head, and then continuing the cycle;
and searching a frequency point smaller than the threshold value, marking the frequency point after the frequency point is found, and ending the circulation by calling the value of the frequency point as a tail.
Specifically, the frequency point threshold is taken as 200 as an example. 1. Find a bin greater than the 200 threshold, mark this point after finding, call this value the head, and then continue this round of cycles. 2. And searching a frequency point smaller than the threshold of 200, marking the point after the point is found, and ending the cycle by using the value as a tail. The purpose of this embodiment is to find consecutive frequency points greater than 200. Since the human body is a non-rigid body, the speed of different parts is different when the human body moves, but the speed is formed by a plurality of continuous speeds.
In this embodiment, the method for determining the target object corresponding to the velocity component includes:
subtracting the value corresponding to the head from the value corresponding to the tail to obtain a difference value;
and judging the category of the target object according to the magnitude of the difference value.
For example, since different motion amplitudes of a person can be used to determine what state the person is in at the moment, the following is defined as the frequency point situation of the person at 1 m:
(1) breathing: the frequency points are defined as that a person sits and four limbs do not move, and the frequency points at the moment are only 1-3 frequency points which are larger than a 200 threshold value;
(2) micro-motion: the method is defined as slight shaking of a person, only slight movements such as keyboard typing and the like are carried out on four limbs, and at the moment, 3-10 frequency points are larger than a 200 threshold value;
(3) large movement: the frequency point is defined as that more than 10 frequency points are larger than 200 when people walk and the like in large movement.
S3, detecting the energy maximum value of each speed component of the target object, comparing the energy maximum value with a preset energy value interval, and judging the distance and the action amplitude of the target object corresponding to the energy maximum value.
In this embodiment, the energy value of each velocity component of the target object is detected, the energy value is compared with a preset energy value interval, the energy value interval to which the energy value belongs is determined, and the approximate distance and the motion amplitude (large motion, micro motion or static motion) of the target object are obtained.
When the judgment is carried out, whether the target object is a person or a fan is judged, the energy maximum value of the speed component is obtained, the action amplitude of the target object is judged according to the energy maximum value, and whether the target object belongs to a large action or a micro action or a static action is judged.
In this embodiment, because the attenuation of the electromagnetic wave is larger as the distance is changed, the attenuation of the detected energy value is larger as the distance is farther, the distance of the current person needs to be determined by the maximum value of the energy, and different frequency point conditions are applied according to the distance between the person and the radar.
Because the fan belongs to rigid motion, only a few frequency points exist, but the speed is too high, and the position can be regarded as the fan.
And S4, outputting a sensing detection result according to the distance and the action amplitude of the target object.
In the embodiment, whether a person exists is judged according to the output sensing detection result, and the invention does not need to distinguish a single person from a plurality of persons during sensing detection.
The invention detects the intermediate frequency data emitted and reflected by the electromagnetic wave through the sensing device, analyzes and judges the speed component of the intermediate frequency data, judges the type of the target object by utilizing different values of the speed components of different types of target objects, judges the action amplitude of the target object by calculating the maximum energy value of the speed component, can detect whether the target object is in a large action, micro action or static state, can obtain the approximate distance of the target object, judges whether a person exists according to the output result, and is suitable for sensing and detecting the target object in application scenes such as offices, meeting rooms or sickbeds.
It should be understood that although the steps are described above in a certain order, the steps are not necessarily performed in the order described. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, some steps of the present embodiment may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or in turns with other steps or at least a part of the steps or stages in other steps.
In one embodiment, as shown in fig. 6, an object state sensing detection system is provided, which includes a velocity component calculation module 100, a target object determination module 200, and a state analysis module 300. Wherein:
the velocity component calculation module 100 is configured to obtain a velocity component of the current intermediate frequency data through fast fourier transform on the acquired intermediate frequency data.
The target object determination module 200 is configured to analyze and determine the obtained velocity components, and determine target objects corresponding to the velocity components by clustering the velocity components and analyzing the value positions.
The state analysis module 300 is configured to detect an energy maximum value of each velocity component of the target object, compare the energy maximum value with a preset energy value interval, determine a distance and an action amplitude of the target object corresponding to the energy maximum value, and analyze and output an induction detection result according to the distance and the action amplitude of the target object.
In this embodiment, the sensing detection system is implemented by using the steps of the object state sensing detection method as described above, and therefore, the operation process of the sensing detection system in this embodiment is not described in detail.
In an embodiment, there is further provided a computer device in an embodiment of the present invention, including at least one processor, and a memory communicatively connected to the at least one processor, the memory storing instructions executable by the at least one processor, the instructions being executable by the at least one processor to cause the at least one processor to execute the object state sensing detection method, the processor executing the instructions to implement the steps in the method embodiments:
acquiring intermediate frequency data, and obtaining the speed component of the current intermediate frequency data through fast Fourier transform;
analyzing and judging the obtained velocity components, and clustering the velocity components and analyzing the value positions to judge a target object corresponding to the velocity components;
detecting the energy maximum value of each speed component of the target object, comparing the energy maximum value with a preset energy value interval, and judging the distance and the action amplitude of the target object corresponding to the energy maximum value;
and outputting a sensing detection result according to the distance and the action amplitude of the target object.
In one embodiment, a computer-readable storage medium is provided, having stored thereon computer instructions for causing a computer to execute the object state sensing detection method:
acquiring intermediate frequency data, and obtaining the speed component of the current intermediate frequency data through fast Fourier transform;
analyzing and judging the obtained velocity components, and clustering the velocity components and analyzing the value positions to judge a target object corresponding to the velocity components;
detecting the energy maximum value of each speed component of the target object, comparing the energy maximum value with a preset energy value interval, and judging the distance and the action amplitude of the target object corresponding to the energy maximum value;
and outputting a sensing detection result according to the distance and the action amplitude of the target object.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program represented by computer instructions and stored in a non-volatile computer-readable storage medium, and the computer program can include the processes of the embodiments of the methods described above when executed. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory.
Non-volatile memory may include read-only memory, magnetic tape, floppy disk, flash memory, optical storage, or the like. Volatile memory may include random access memory or external cache memory. By way of illustration, and not limitation, RAM can take many forms, such as static random access memory, dynamic random access memory, and the like.
In summary, the present invention detects the intermediate frequency data transmitted and reflected by the electromagnetic wave through the sensing device, analyzes and judges the velocity component of the intermediate frequency data, judges the type of the target object by utilizing the different values of the positions of the velocity components of different types of target objects, judges the action amplitude of the target object by calculating the maximum energy value of the velocity component, can detect whether the target object is in a large action, a micro action or a static state, can obtain the approximate distance of the target object, and judges whether a person is present according to the output result, which is suitable for the target object sensing detection of application scenes such as offices, conference rooms or sickbeds.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (10)

1. An object state sensing detection method, comprising:
acquiring intermediate frequency data, and obtaining the speed component of the current intermediate frequency data through fast Fourier transform;
analyzing and judging the obtained velocity components, and clustering the velocity components and analyzing the value positions to judge a target object corresponding to the velocity components;
detecting the energy maximum value of each speed component of the target object, comparing the energy maximum value with a preset energy value interval, and judging the distance and the action amplitude of the target object corresponding to the energy maximum value;
and outputting a sensing detection result according to the distance and the action amplitude of the target object.
2. The object state sensing detection method of claim 1, characterized in that: the method for obtaining the speed component of the current intermediate frequency data comprises the following steps:
capturing intermediate frequency data;
removing direct current from the captured intermediate frequency data, and adding a Hanning window;
and obtaining the velocity component of the current intermediate frequency data through fast Fourier transform.
3. An object state sensing detection method according to claim 1 or 2, characterized in that: the intermediate frequency data is a waveform obtained by transmitting an electromagnetic wave with a fixed frequency by a sensor, reflecting the electromagnetic wave by an object, receiving the signal by the sensor and mixing the signal, and the mixing formula of the intermediate frequency data is as follows:
Ifmixing of＝sin[(ω1-ω2)]
Wherein, ω is1For transmitting frequency, omega2Is the receive frequency.
4. An object state sensing detection method according to claim 3, characterized in that: the velocity components of all velocities reflected by the intermediate frequency signals of the intermediate frequency data are velocities reflected by the moving object, the velocities reflected by the moving object are calculated according to a Doppler effect, and the Doppler effect formula is as follows:
Figure FDA0003358041100000011
wherein f isDDoppler or difference frequencies;
f0the transmitting frequency of the radar;
v is the speed range of the moving object;
c0the speed of light;
alpha is the angle between the actual direction of motion and the line connecting the sensor to the target object.
5. The object state sensing detection method of claim 2, characterized in that: when the intermediate frequency data is subjected to direct current removal, all the acquired intermediate frequency data are added and divided by the average value and then subtracted due to the fact that the direct current signal is a fixed value, and the value y of the intermediate frequency signal after processing is obtainedk1The calculation formula of (2) is as follows:
Figure FDA0003358041100000021
wherein x iskFor the acquired intermediate frequency data, N is the number of the intermediate frequency data acquired this time.
6. The object state sensing detection method of claim 5, wherein: after the direct current of the intermediate frequency data is removed, a Hanning window is added by multiplying the acquired data by a function, namely adding a window; the intermediate frequency signal is subjected to DC-removing processing and then subjected to windowing againkThe calculation formula of (2) is as follows:
Figure FDA0003358041100000022
wherein: x is the number ofkFor the acquired intermediate frequency data, N is the number of the intermediate frequency data acquired this time.
7. The object state sensing detection method of claim 6, wherein: the FFT function formula f for obtaining the velocity component of the current intermediate frequency data by fast fourier transform is:
f＝(a0,a1,…,an-1)
the odd terms and the even terms are respectively proposed and constructed as follows
Figure FDA0003358041100000023
The coefficient of (a) represents, wherein a is the intermediate frequency signal after windowing and direct current removal;
in the fast fourier transform, the separation df of adjacent spectral lines is:
Figure FDA0003358041100000024
wherein fs is a sampling frequency, N is the number of the intermediate frequency data collected this time, Ts is a sampling time interval, the spectral line interval determines the frequency resolution of FFT, and when the spectral line interval is large, useful information will be lost due to the fence effect.
8. The object state sensing detection method of claim 1, characterized in that: the method for clustering the velocity components comprises the following steps:
setting a frequency point threshold value of clustering operation;
searching a frequency point which is larger than the threshold value, marking the frequency point after the frequency point is found, calling the value of the frequency point as a head, and then continuing the cycle;
and searching a frequency point smaller than the threshold value, marking the frequency point after the frequency point is found, and ending the circulation by calling the value of the frequency point as a tail.
9. The object state sensing detection method of claim 8, wherein: the method for judging the target object corresponding to the velocity component comprises the following steps:
subtracting the value corresponding to the head from the value corresponding to the tail to obtain a difference value;
and judging the category of the target object according to the magnitude of the difference value.
10. An object condition sensing detection system, comprising: the object state sensing detection system adopts the object state sensing detection method of any one of claims 1 to 9 to judge the category and the action amplitude of the target object and detect the large action, the micro-motion and the static state of the target object; the object state sensing detection system comprises:
the speed component calculation module is used for obtaining the speed component of the current intermediate frequency data through fast Fourier transform on the acquired intermediate frequency data;
the target object judgment module is used for analyzing and judging the obtained speed components, and judging target objects corresponding to the speed components by clustering the speed components and analyzing the value positions; and
and the state analysis module is used for detecting the energy maximum value of each speed component of the target object, comparing the energy maximum value with a preset energy value interval, judging the distance and the action amplitude of the target object corresponding to the energy maximum value, and analyzing and outputting an induction detection result according to the distance and the action amplitude of the target object.
CN202111358176.0A 2021-11-16 2021-11-16 Object state sensing detection method and system Pending CN114063067A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117835399A (en) * 2024-03-06 2024-04-05 深圳市飞睿智能有限公司 Method for tracking wireless signal tag by mobile terminal

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117835399A (en) * 2024-03-06 2024-04-05 深圳市飞睿智能有限公司 Method for tracking wireless signal tag by mobile terminal
CN117835399B (en) * 2024-03-06 2024-05-10 深圳市飞睿智能有限公司 Method for tracking wireless signal tag by mobile terminal

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