CN112098996B - Anti-interference extraction and separation vital sign information method based on millimeter wave biological radar - Google Patents
Anti-interference extraction and separation vital sign information method based on millimeter wave biological radar Download PDFInfo
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- 230000001121 heart beat frequency Effects 0.000 claims description 3
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/023—Interference mitigation, e.g. reducing or avoiding non-intentional interference with other HF-transmitters, base station transmitters for mobile communication or other radar systems, e.g. using electro-magnetic interference [EMI] reduction techniques
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- G—PHYSICS
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- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
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Abstract
The invention discloses an anti-interference extraction and separation vital sign information method based on millimeter wave biological radar; the method comprises the following steps: s1: performing time domain interference detection on the signals, and traversing to detect whether all the frequency modulation signals are interfered; s2: detecting the interference position of the interfered signal; s3: interference suppression and signal restoration, which suppresses an interference section in an interfered frequency modulated signal and reconstructs the section; s4: detecting target vital sign information, namely detecting the position of the target and the vital sign information of the target; s5: and extracting and separating vital sign information, and extracting and separating heartbeat and respiratory signals of the target. The invention can accurately find the interference position and accurately repair the interfered signal, reduce the phase noise caused by interference, ensure that the radar system can be used in a multi-interference environment, improve the signal-to-noise ratio of the vital signal and more accurately separate the respiratory heartbeat signal.
Description
Technical Field
The invention relates to the field of radar signal processing, in particular to an anti-interference extraction and separation vital sign information method based on millimeter wave biological radar.
Background
Along with the development of society and technology, technologies for detecting vital activities of human bodies are continuously developed. The vital sign parameters are the main basis for monitoring whether the vital activity of the human body is normal, and the heart beat, the respiration, the blood pressure and the body temperature are four basic physiological parameters representing the vital sign of the human body, wherein the respiration and the heart beat are the parameters which most directly reflect the vital sign. The detection of human body activities is mainly to detect respiration and heartbeat of a human body, the common detection technology comprises a contact type detection technology and a non-contact type detection technology, the contact type detection technology directly contacts the human body, a plurality of inconveniences can be brought under many conditions, the non-contact type detection technology is mainly realized by means of a radar system, remote detection can be realized, and the direct contact with the human body is not needed, so great convenience is brought, and the millimeter wave radar is increasingly used for detecting vital signs of the human body due to the advantages of good environmental adaptability, strong anti-interference capability, high measurement accuracy and the like.
As millimeter wave radars are increasingly used, interference between radar systems is most likely to occur. When a plurality of millimeter wave radars sharing the same frequency band and of similar specification work simultaneously exist, millimeter wave signals sent out by another radar can cause interference to a radar system which is detecting vital signs of a human body, the interference signals and target echo signals enter a detection radar receiver together and are output after mixing and filtering, the bottom noise of the signals is increased, the signal to noise ratio is reduced, the vital signs of the target cannot be detected or the false target information cannot be detected by the radar system. Therefore, suppression of interference between life detection radars is a critical issue to be addressed.
At present, there are many methods for suppressing inter-radar interference, for example, a threshold detection interference point is set in a time domain, when the point value is greater than a set threshold, the point value is determined to be an interference point, and then the interference signal is zeroed, which has many drawbacks, on the one hand, the problem of setting the threshold is solved, the omission is caused due to the too large threshold, and the useful signal is also suppressed due to the too small threshold; on the other hand, direct zeroing of the interfering signal may result in discontinuous phase of the signal, and phase noise caused by interference is not suppressed. Therefore, it is urgent to improve the detection and suppression technique of the interference.
Chinese patent CN109924962a published in 6 and 25 of 2019 provides a radar-based non-contact vital sign measurement system and method, the method specifically comprises: transmitting radar signals to a living body and receiving radar echo signals reflected by the living body to form original echo data; collecting original echo data; processing the acquired original echo data to form vital sign information of a living body; and presenting vital sign information of the living body. Converting a part of acquired original echo data into the respiration rate and heart rate of a living body after Fourier change processing, constant false alarm detection processing and Kalman filtering processing; and converting the acquired other part of original echo data into body movement of the living body after clutter cancellation processing and signal intensity change rate detection processing. But the problem of interference between the life detection radars is neglected, so that the accuracy of extraction and separation of the vital sign information is required to be further improved.
Disclosure of Invention
The invention provides an anti-interference extraction and separation method for vital sign information based on millimeter wave biological radar, which aims to overcome the defect that the extraction and separation accuracy of the vital sign information is not high enough in the prior art.
The method comprises the following steps:
s1: time domain interference detection: traversing to detect whether all the frequency modulation signals transmitted by the biological radar are interfered; if yes, executing S2, and if not, executing S4;
s2: time domain interference position detection: detecting the position of interference in the interfered frequency modulation signal;
s3: interference suppression and signal repair: suppressing an interference section in the interfered frequency modulation signal and reconstructing the section;
s4: target vital sign information detection: detecting the position of the target and vital sign information of the target;
s5: extraction and separation of vital sign information: and extracting and separating heartbeat and respiratory signals of the target.
Preferably, S1 comprises the steps of:
s1.1: finding the maximum value y of the kth FM signal max ＝max|y k (t) |, initializing k=1, 2,..k, K for a total of K frequency modulated signals; y is k (t) is the kth frequency modulated signal;
s1.2: average value of kth frequency modulation signal
N is the number of samples per fm signal;
s1.3: calculating the ratio of the maximum value to the average value
Judgment d k Whether or not it is greater than a preset threshold R th1 ，R th1 The value range is [4,6 ]]Between them; if it is greater than, let d k =1, will be recorded in array d; otherwise, let d k =0, and d k Recording in the array d;
s1.4: judging whether K is larger than K, if so, executing S1.5, otherwise, returning k=k+1 to execute S1.1, wherein K is the total number of the frequency modulation signals transmitted by the radar;
s1.6: output array d= [ d ] 1 ,d 2 ,...,d K ]Recording whether the ratio of the maximum value to the average value of all the frequency modulation signals is greater than a threshold value R th1 Results of (2);
s1.7: judging whether the frequency modulation signal is interfered; if yes, executing S2, and if not, executing S4.
Preferably, S2 comprises the steps of:
s2.1: judging d in the array d k If equal to 1, executing S2.2 if equal to 1, otherwise executing S2.61, wherein k is initialized to 1;
s2.2: calculate the signal y k (t) Forward sliding Window
And a backward sliding window->
Wherein the method comprises the steps of
Wherein L is the size of the sliding window, and N is the sampling point number of each frequency modulation signal;
s2.3: calculating y k Envelope e= [ e ] of (t) 1 ,e 2 ,...,e N ]Wherein
The envelope value of the nth sampling point is e (n);
s2.4: calculating a threshold R th2 ；
S2.5: determining whether e (n) is greater than a threshold R th2 If yes, let u n =1, if not, let u n ＝0；
Wherein u is n An envelope value representing the nth sampling point is greater than the threshold R th2 Is the case in (2);
s2.6: judging whether N is greater than N, if so, executing S2.7, otherwise, returning n=n+1 to execute S2.5;
s2.7: calculation u n The result is stored in array U, i.e., U= [ U ] 2 -u 1 ,u 3 -u 2 ,...,u N -u N-1 ]；
S2.8: calculating the number m of non-zero numbers in the array U k ＝nonzero(U)；
S2.9: calculation of
Wherein->
N i Is a variable point in the frequency modulated signal;
representing the kth FM signal from N i-1 +1 to N i Average value of sampling points; />
Representing i from 1 to m k +1 +.>
Sum of functions;
s2.10: calculation of
Wherein beta is E [ beta ] k ,β k-1 ]，/>
m k (beta) represents the number of transition points of the kth frequency modulated signal; m is m k Representing the number of nonzero frequency modulation signals in a kth frequency modulation signal array U;
s2.11: adjusting the value of beta so that m k ＝m k (beta) to obtain a series of variational points
S2.12: storing the variable point obtained in S2.11 in an array cp k In, i.e
S2.13: judging whether K is larger than K, if so, outputting an array cp k Otherwise, returning to S2.1.
Preferably, the threshold value R th2 The calculation formula of (2) is as follows:
R th2 ＝(1+α)min(e)
wherein, alpha is a control parameter, and the value range of alpha is between (0, 1).
Preferably, S3 comprises the steps of:
s3.1: will y k (t) is divided into three parts: before interference, during interference and after interference are respectively:
wherein, the liquid crystal display device comprises a liquid crystal display device,
sample data points are respectively N F 、N I 、N B ；
S3.2: respectively using
Reference signal pair->
Repair is carried out to obtain
S3.3: calculation of
Wherein->
S3.4: calculation of
S3.5: calculating window function w [ t ]]＝v[F(t-N k,1 +1)]Wherein, the liquid crystal display device comprises a liquid crystal display device,
s3.6: repairing interference section signals
Wherein->
S3.7: judging whether K is larger than K, if yes, executing S3.8, otherwise, returning to execute S3.1;
s3.8: all post-repair signals are recorded as
Preferably, the repair formula of the interference signal in S3.6 is:
wherein t=n k,1 ,
Preferably, S4 comprises the steps of:
s4.1: will be
Sampling points of each frequency modulation signal are used as a row, and each row is subjected to P-point frequency spectrum transformation to obtain a distance matrix D [ K, P ]]；
S4.2: finding the point with the maximum amplitude value of each row in the distance matrix as a target position TD (k);
s4.3: calculating the phase of the target position
S4.4: unwrapping the phase phi (k);
s4.5: calculating a phase difference signal ΔΦ=Φ (K) - Φ (K-1), k=2.
S4.6: and performing spectrum transformation on the phase difference signal delta phi, and detecting peaks of the spectrum transformation result to obtain the respiration and heartbeat frequency of the target.
Preferably, the peak detection in S4.6 is performed on the result of the spectral transformation, specifically, between 0.2hz and 0.8hz and between 0.8hz and 2.0 hz.
Preferably, S5 comprises the steps of:
s5.1: will suppress the interfered signal
Adding Gaussian white noise to obtain a signal +.>
r=1, R is initialized to 1, r=1, 2,;
s5.2: all extreme points of the signal x (t) are calculated and the upper envelope x of the signal is fitted up (t) and lower envelope x down (t)；
S5.3: calculating an average function f (t) = (x) of the upper and lower envelopes up (t)+x down (t))/2, a difference function h z (t) =x (t) -f (t), z being initialized to 1;
s5.4: calculating standard deviation SD, judging whether SD is larger than a preset threshold R th3 ，R th3 The value range is [0.2,0.3 ]]If yes, executing S5.5, otherwise returning to executing S5.2;
s5.5: j h obtained after S5.4 z (q) is denoted as
j＝1,...,J；
S5.6: judging whether R is larger than R, if yes, executing S5.7, otherwise, returning to execute S5.1;
s5.7: calculation of
S5.8: calculate h j Energy E (j) of (h) j An energy EB (j) having a medium frequency in the range of 0.2hz to 0.8hz, and an energy EH (j) having a frequency in the range of 0.8hz to 2.0 hz;
s5.9: calculation of
Is to judge whether H1 is greater than R th4 If yes, let h j '＝h j Executing S5.11, otherwise executing S5.10; wherein R is th4 The value range is 0.6,0.7]Between them;
s5.10: calculation of
And determining whether H2 is greater than R th4 If yes, let h j ”＝h j S511 is performed, otherwise S511 is performed;
s5.11: judging whether J is greater than J, if so, executing S5.12, otherwise, returning to executing S5.7;
s5.12: all h j '，h j Accumulating to obtain respiratory signal
Heart beat signal->
Preferably, the standard deviation is calculated by the following formula:
compared with the prior art, the technical scheme of the invention has the beneficial effects that:
the invention can accurately find the interference position and accurately repair the interfered signal by utilizing the improved interference position detection and interference repair algorithm, thereby reducing the phase noise caused by interference;
the method can ensure the use of the radar system in a multi-interference environment through time domain interference position detection, interference suppression and signal restoration, and can effectively suppress the mutual interference among the radars even in an environment where a plurality of radar systems are simultaneously detected, thereby avoiding the false detection of vital sign information by the radar systems;
the method for extracting and separating the vital sign information can inhibit noise in the frequency band of the vital sign, improve the signal-to-noise ratio of the vital sign, and can more accurately extract and separate the vital sign information.
Drawings
Fig. 1 is a flowchart of a method for extracting and separating vital sign information based on millimeter wave bioradar in this embodiment;
fig. 2 is a flowchart of the time domain interference detection according to the present embodiment;
fig. 3 is a flowchart of target vital sign information detection according to the present embodiment;
fig. 4 is a flowchart of the extraction and separation of vital sign information according to the present embodiment.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the present patent;
for the purpose of better illustrating the embodiments, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the actual product dimensions;
it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical scheme of the invention is further described below with reference to the accompanying drawings and examples.
Example 1:
the embodiment provides an anti-interference extraction and separation vital sign information method based on millimeter wave biological radar, as shown in fig. 1, comprising the following specific steps:
step S1: detecting time domain interference, namely traversing and detecting whether all frequency modulation signals transmitted by the biological radar are interfered;
step S2: detecting the interference position in the time domain, and detecting the interference position in the interfered frequency modulation signal;
step S3: interference suppression and signal restoration, which suppresses an interference section in an interfered frequency modulated signal and reconstructs the section;
step S4: detecting target vital sign information, namely detecting the position of the target and the vital sign information of the target;
step S5: and extracting and separating vital sign information, and extracting and separating heartbeat and respiratory signals of the target.
Referring to fig. 2, the method for detecting S1 time domain interference includes the following specific steps:
step S11: finding the maximum value y of the kth FM signal max ＝max|y k (t) |, initialize k=1, 2,..k, K for a total of K frequency modulated signals. For example, when k=5, the maximum value y of the 5 th frequency modulated signal max ＝max|y 5 (t)|；y k (t) is the kth frequency modulated signal;
step S12: average value of kth frequency modulation signal
N is the number of samples per fm signal. For example, when k= 5,N =128, the average value of the 5 th fm signal +.>
Step S13: calculating the ratio of the maximum value to the average value
Determining whether the value is greater than a threshold value R th1 If yes, step S141 is executed, otherwise step S142 is executed. For example, when k= 5,N =128, r th1 When =4, if the ratio of the maximum value to the average value of the 5 th FM signal +.>
Step S141 is performed if->
Step S142 is performed;
step S141: let d k =1, the ratio of the maximum value to the average value of the kth frequency modulated signal is greater than the threshold R th1 In the record array d of (1), the frequency modulation signal is interfered;
step S142: let d k =0, the ratio of the maximum value to the average value of the kth frequency modulated signal is less than the thresholdValue R th1 In the record array d of (2), marked as 0, indicating that the frequency modulated signal is not disturbed;
step S15: and judging whether K is larger than K, if so, executing S16, otherwise, returning k=k+1 to execute S11, wherein K is the total number of the frequency modulation signals transmitted by the radar. For example, k=100, k=5, 5<100, let k=5+1 at this time, return to step S11;
step S16: array d= [ d ] 1 ,d 2 ,...,d K ]Recording whether the ratio of the maximum value to the average value of all the frequency modulation signals is greater than a threshold value R th1 As a result of (a). For example, when k=5, if d in the array d 5 =1, indicating that the ratio of the maximum value to the average value of the 5 th frequency modulation signal is greater than the threshold R th1 I.e. the frequency modulated signal is disturbed.
The S2 time domain interference position detection method comprises the following specific steps:
step S21: judging d in the array d k If equal to 1, S22 is performed, otherwise S216 is performed, where k is initialized to 1. For example, when k=5, if d 5 If =1, go to step S22, if d 5 =0, then step S216 is performed;
step S22: calculate the signal y k (t) Forward sliding Window
And a backward sliding window->
Wherein the method comprises the steps of
L is the size of the sliding window and N is the number of samples per fm signal. For example, when k= 5,L =20, n=128, n=1,
when n=2, the number of the n-type groups,
and so on to obtain the forward sliding window
And a backward sliding window->
Step S23: calculating y k Envelope e= [ e ] of (t) 1 ,e 2 ,...,e N ]Wherein
The envelope value of the nth sample point is e (n). For example, forward sliding window in the above step +.>
And a backward sliding window->
Then y 5 (t) envelope e= [ e 1 ,e 2 ,...,e 128 ]Wherein
And so on to obtain an envelope e, wherein the envelope value of the 1 st sampling point is e (1), and the n is e (n);
step S24: calculating a threshold R th2 = (1+α) min (e), α is a control parameter. For example, in the above step, when the minimum value of the envelope of the 5 th frequency-modulated signal is 5α=0.6, R th2 ＝(1+0.6)×5＝8；
Step S25: determining whether e (n) is greater than a threshold R th2 If so, S261 is performed, otherwise S262 is performed. For example, in the above step, R th2 8, if e (35) =40, 40>8, thisExecuting S261;
step S261: let u n =1, the envelope value of the nth sampling point is greater than the threshold R th2 The case of (2) is denoted as 1. For example, in the above step, u 35 ＝1；
Step S262: let u n =0, the envelope value of the nth sampling point is smaller than the threshold value R th2 The case of (2) is noted as 0;
step S27: and judging whether N is greater than N, if so, executing S28, otherwise, returning n=n+1 to execute S25. For example, n=35, n=128, 35<128, at which time n=35+1=36 is returned to S25;
step S28: calculation u n The result is stored in array U, i.e., U= [ U ] 2 -u 1 ,u 3 -u 2 ,...,u N -u N-1 ]. For example when k=5, only u 35 When the values of =1 and 0 are all other values, u= [0, ], 1, -1,0, ], 0]；
Step S29: calculating the number m of non-zero numbers in the array U k =non zero (U), e.g., in the above steps k=5, u= [0, ], 1, -1,0, ], 0]M is then 5 ＝2；
Step S210: calculation of
Wherein->
N i Is the change point, N 0 ＝0，
For example, in the above steps, N is set 1 ＝33，N 2 N is =36 0 ＝0，N 3 ＝128J 2 ＝c(y 5,1:33 )+c(y 5,34:36 )+c(y 5,37:128 ),/>
Representing the kth FM signal from N i-1 +1 to N i Average value of sampling points; />
Representing i from 1 to m k +1 +.>
Sum of functions.
Step S211: calculation of
Wherein beta is E [ beta ] k ,β k-1 ],/>
m k (beta) represents the number of transition points of the kth frequency modulated signal; m is m k Representing the number of nonzero frequency modulation signals in a kth frequency modulation signal array U; for example, in the above step, m 5 =2, let m 4 ＝1,m 6 ＝7/>
Then m 5 (β)＝argmin(J 2 +2×β)β∈[0.9,1.2]；
Step S212: adjusting the value of beta so that m k ＝m k (beta) to obtain a series of variational points
For example, in the above steps
The value of beta is adjusted so that 2=m 5 (beta), and beta.epsilon. 0.9,1.2]Variable point N 5,1 ,N 5,2 ；
Step S213: the variable point obtained in S212 is stored in an array cp k In, i.e
For example cp in the above step 5 ＝[N 5,1 ,N 5,2 ]；
Step S214: and judging whether K is greater than K, if so, ending the step S2, otherwise, returning to continue to execute the step S21. For example, in the above steps, if k=5 and k=100, 5<100, at this time, the process returns to S21;
the S3 interference suppression and signal restoration method comprises the following specific steps:
step S31: will y k (t) is divided into three parts: before interference, during interference and after interference are respectively:
wherein, the liquid crystal display device comprises a liquid crystal display device,
sample data points are respectively N F 、N I 、N B . For example when m 5 ＝2,N＝128，N 5,1 ＝33，N 5,2 When=36, then>
At this time N F ＝33、N I ＝4、N B ＝91；
Step S32: respectively using
Reference signal pair->
Repair is carried out to obtain
For example +.>
Then->
t＝33,34,35,36
Step S33: calculation of
Wherein->
For example N in the above step F ＝33、N I ＝4、N B ＝91t＝33,34,35,36，NR 1 ≈2.28,NR 2 ≈-14.28，
Step S34: calculation of
For example in the above steps
Then->
Step S35: calculating window function w [ t ]]＝v[F(t-N k,1 +1)]Wherein, the liquid crystal display device comprises a liquid crystal display device,
step S36: repairing interference section signals
Wherein->
Step S37: judging whether K is greater than K, if so, executing S38, otherwise, returning to executing S31;
step S38: all post-repair signals are recorded as
The method for detecting S4 target vital sign information referring to FIG. 3 comprises the following specific steps:
step S41: will be
Sampling points of each frequency modulation signal are used as a row, and each row is subjected to P-point frequency spectrum transformation to obtain a distance matrix D [ K, P ]]. For example, when n=128, k=100, and p=256, each sampling point is taken as a row, and a 256-point FFT is performed on each row, a distance matrix D [100, 256 ] is obtained]；
Step S42: finding the point with the maximum amplitude value of each row in the distance matrix as a target position TD (k);
step S43: calculating the phase of the target position
Step S44: unwrapping the phase phi (k). To obtain a continuous phase, the phase phi (k) needs to be unwrapped, for example when the value of phi (2) -phi (1) is greater than pi, phi (1) +2pi, and so on, to obtain a continuous phase;
step S45: calculating a phase difference signal ΔΦ=Φ (K) - Φ (K-1), k=2.
Step S46: and performing frequency spectrum transformation on the phase difference signal delta phi, and detecting peaks between 0.2hz and 0.8hz and between 0.8hz and 2.0hz to obtain the respiration and heartbeat frequency of the target.
S5, extracting and separating vital sign information, referring to FIG. 4, comprises the following specific steps:
step S51: will suppress the interfered signal
Adding Gaussian white noise to obtain a signal
R is initialized to 1, r=1, 2.
Step S52: all extreme points of the signal x (t) are calculated and the upper envelope x of the signal is fitted up (t) and lower envelope x down (t)；
Step S53: calculate the function f (t) = (x) up (t)+x down (t))/2，h z (t) =x (t) -f (t), z being initialized to 1;
step S54: calculation of
Judging whether the value is larger than a set threshold value R th3 If so, execution is S55, otherwise execution is returned to S52.R is R th3 Take [0.2,0.3 ]]Values of the range;
step S55: j h obtained after S54 z (q) is denoted as h r j ,j＝1,...,J；
Step S56: judging whether R is larger than R, if so, executing S57, otherwise, returning to executing S51;
step S57: calculation of
Will get h each time r j Taking an average value;
step S58: calculate h j Energy E (j) of (h) j An energy EB (j) having a medium frequency in the range of 0.2hz to 0.8hz, and a frequency inEnergy EH (j) in the range of 0.8hz to 2.0 hz;
step S59: calculation of
Is determined whether the value is greater than R th4 If yes, let h j '＝h j S511 is performed, otherwise S510 is performed;
step S510: calculation of
Is determined whether the value is greater than R th4 If yes, let h j ”＝h j S511 is performed, otherwise S511 is performed;
step S511: judging whether J is greater than J, if so, executing S512, otherwise, returning to executing S57;
step S512: all h j '，h j Accumulating to obtain respiratory signal
Heart beat signal->
According to the embodiment, an improved interference position detection and interference restoration algorithm is utilized, so that the interference position is accurately found, an interfered signal is accurately restored, and phase noise caused by interference is reduced; the radar system can be ensured to be used in a multi-interference environment, and even if a plurality of radar systems are detected simultaneously, the mutual interference among the radars can be effectively inhibited, so that the false detection of vital sign information by the radar systems is avoided; the method for extracting and separating the vital sign information can effectively inhibit noise in the vital sign frequency band, improve the signal-to-noise ratio of the vital sign, and accurately separate respiratory heartbeat signals.
The terms describing the positional relationship in the drawings are merely illustrative, and are not to be construed as limiting the present patent;
it is to be understood that the above examples of the present invention are provided by way of illustration only and not by way of limitation of the embodiments of the present invention. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the invention are desired to be protected by the following claims.
Claims (8)
1. The method for extracting and separating vital sign information based on the millimeter wave biological radar is characterized by comprising the following steps of:
s1: time domain interference detection: traversing to detect whether all the frequency modulation signals transmitted by the biological radar are interfered; if yes, executing S2, and if not, executing S4; the method comprises the following steps:
s1.1: finding the maximum value y of the kth FM signal max ＝max|y k (t) |, initializing k=1, 2,..k, K for a total of K frequency modulated signals; y is k (t) is the kth frequency modulated signal;
s1.2: average value of kth frequency modulation signal
N is the number of samples per fm signal;
s1.3: calculating the ratio of the maximum value to the average value
Judgment d k Whether or not it is greater than a preset threshold R th1 If it is greater than, let d k =1, will be recorded in array d; otherwise, let d k =0, and d k Recording in the array d;
s1.4: judging whether K is larger than K, if so, executing S1.5, otherwise, returning k=k+1 to execute S1.1, wherein K is the total number of the frequency modulation signals transmitted by the radar;
s1.5: output array d= [ d ] 1 ,d 2 ,...,d K ]Recording the ratio of the maximum value to the average value of all the frequency modulation signalsWhether the value is greater than the threshold value R th1 As a result of (a),
s1.6: judging whether the frequency modulation signal is interfered; if yes, executing S2, and if not, executing S4;
s2: time domain interference position detection: detecting the position of interference in the interfered frequency modulation signal; the method comprises the following steps:
s2.1: judging d in the array d k If equal to 1, executing S2.2 if equal to 1, otherwise executing S2.13, wherein k is initialized to 1;
s2.2: calculate the signal y k (t) Forward sliding Window
And backward sliding window
Wherein the method comprises the steps of
Wherein L is the size of the sliding window, and N is the sampling point number of each frequency modulation signal;
s2.3: calculating y k Envelope e= [ e ] of (t) 1 ,e 2 ,...,e N ]Wherein
The envelope value of the nth sampling point is e (n);
s2.4: determining a threshold R th2 ；
S2.5: determining whether e (n) is greater than a threshold R th2 If yes, let u n =1, if not, let u n ＝0；
Wherein u is n An envelope value representing the nth sampling point is greater than the threshold R th2 Is the case in (2);
s2.6: judging whether N is greater than N, if so, executing S2.7, otherwise, returning n=n+1 to execute S2.5;
s2.7: calculation u n The result is stored in array U, i.e., U= [ U ] 2 -u 1 ,u 3 -u 2 ,...,u N -u N-1 ]；
S2.8: calculating the number m of non-zero numbers in the array U k ＝nonzero(U)；
S2.9: calculation of
Wherein->
N i Is a variable point in the frequency modulated signal;
representing the kth FM signal from N i-1 +1 to N i Average value of sampling points;
representing i from 1 to m k +1 +.>
Sum of functions;
s2.10: calculation of
Wherein beta is E [ beta ] k ,β k-1 ]，/>
m k (beta) represents the number of transition points of the kth frequency modulated signal; m is m k Representing the number of nonzero frequency modulation signals in a kth frequency modulation signal array U;
s2.11: adjusting the value of beta so that m k ＝m k (beta) to obtain a series of variational points
S2.12: storing the variable point obtained in S2.11 in an array cp k In, i.e
S2.13: judging whether K is larger than K, if so, outputting an array cp k Otherwise, returning to S2.1;
s3: interference suppression and signal repair: suppressing an interference section in the interfered frequency modulation signal and reconstructing the section;
s4: target vital sign information detection: detecting the position of the target and vital sign information of the target;
s5: extraction and separation of vital sign information: and extracting and separating heartbeat and respiratory signals of the target.
2. The method for extracting and separating vital sign information based on millimeter wave bioradar according to claim 1, wherein the threshold value R th2 The calculation formula of (2) is as follows:
R th2 ＝(1+α)min(e)
where α is a control parameter.
3. The method for extracting and separating vital sign information based on millimeter wave bioradar according to claim 1 or 2, wherein S3 comprises the steps of:
s3.1: will y k (t) is divided into three parts: before interference, during interference and after interference are respectively:
wherein, the liquid crystal display device comprises a liquid crystal display device,
sample data points respectivelyIs N F 、N I 、N B ；
S3.2: respectively using
Reference signal pair->
Repair is carried out to obtain
S3.3: calculation of
Wherein->
S3.4: calculation of
S3.5: calculating window function w [ t ]]＝v[F(t-N k,1 +1)]Wherein, the liquid crystal display device comprises a liquid crystal display device,
s3.6: repairing interference section signals
Wherein->
S3.7: judging whether K is larger than K, if yes, executing S3.8, otherwise, returning to execute S3.1;
s3.8: all post-repair signal registrationIs that
4. The method for extracting and separating vital sign information based on millimeter wave bioradar according to claim 3, wherein the repair formula of the interference signal in S3.6 is:
wherein the method comprises the steps of
5. The method for extracting and separating vital sign information based on millimeter wave bioradar of claim 4, wherein S4 comprises the steps of:
s4.1: will be
Sampling points of each frequency modulation signal are used as a row, and each row is subjected to P-point frequency spectrum transformation to obtain a distance matrix D [ K, P ]]；
S4.2: finding the point with the maximum amplitude value of each row in the distance matrix as a target position TD (k);
s4.3: calculating the phase of the target position
S4.4: unwrapping the phase phi (k);
s4.5: calculating a phase difference signal ΔΦ=Φ (K) - Φ (K-1), k=2.
S4.6: and performing spectrum transformation on the phase difference signal delta phi, and detecting peaks of the spectrum transformation result to obtain the respiration and heartbeat frequency of the target.
6. The method for extracting and separating vital sign information based on millimeter wave biological radar according to claim 5, wherein the peak detection of the result of the spectral transformation in S4.6 is specifically between 0.2hz and 0.8hz and between 0.8hz and 2.0 hz.
7. The method for extracting and separating vital sign information based on millimeter wave bioradar according to claim 5 or 6, wherein S5 comprises the steps of:
s5.1: will suppress the interfered signal
Adding Gaussian white noise to obtain a signal
s5.2: all extreme points of the signal x (t) are calculated and the upper envelope x of the signal is fitted up (t) and lower envelope x down (t)；
S5.3: calculating an average function f (t) = (x) of the upper and lower envelopes up (t)+x down (t))/2, a difference function h z (t) =x (t) -f (t), z being initialized to 1;
s5.4: calculating standard deviation SD, judging whether SD is larger than a preset threshold R th3 If yes, executing S5.5, otherwise, returning to executing S5.2;
s5.5: j h obtained after S5.4 z (q) is denoted as
S5.6: judging whether R is larger than R, if yes, executing S5.7, otherwise, returning to execute S5.1;
s5.7: calculation of
S5.8: calculate h j Energy E (j) of (h) j An energy EB (j) having a medium frequency in the range of 0.2hz to 0.8hz, and an energy EH (j) having a frequency in the range of 0.8hz to 2.0 hz;
s5.9: calculation of
Judging whether H1 is larger than a preset threshold R th4 If yes, let h j '＝h j Executing S5.11, otherwise executing S5.10;
s5.10: calculation of
And determining whether H2 is greater than R th4 If yes, let h j ”＝h j Executing S5.11, otherwise executing S5.11;
s5.11: judging whether J is greater than J, if so, executing S5.12, otherwise, returning to executing S5.7;
s5.12: all h j '，h j Accumulating to obtain respiratory signal
Heart beat signal->
8. The method for extracting and separating vital sign information based on millimeter wave bioradar of claim 7, wherein the standard deviation is calculated according to the formula:
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