A phase-encoded based vital sign detection method

Abstract

The application relates to the technical field of vital sign detection, and discloses a vital sign detection method based on phase coding, which encodes a vital sign detection signal in a random coding mode, so that the emitted signal has certain randomness, adjacent carrier interference can be avoided, and after correct decoding, the phases of false targets caused by coherent interference can be randomized, so that real targets can be detected, and the influence of coherent interference is avoided; through phase coding and traversal decoding, phase noise caused by interference is reduced, vital signs are obtained from signals suffering from relatively serious non-coherent interference, and the ability of a radar system to detect vital signs is enhanced; static clutter and false targets are distinguished through variance of phase signals, so that human targets can be accurately detected, heartbeat signals are subjected to differential operation, heartbeat signal components are enhanced, and the accuracy of heartbeat frequency detection is improved.

Description

Technical Field

[0001] This invention relates to the field of vital sign detection technology, and in particular to a vital sign detection method based on phase encoding. Background Technology

[0002] Over the past decade, with the accelerating aging of the global population, the incidence of chronic diseases has been on the rise, necessitating the provision of effective and convenient healthcare services. Long-term monitoring of patients' vital signs can detect functional decline and assess potential life-threatening situations. Close monitoring and timely, effective treatment can reduce the risk of death; however, long-term monitoring presents several challenges. First, typical monitoring devices require physical contact with the patient, potentially causing discomfort, skin allergies, and easy detachment. Second, these devices are usually attached to the patient by medical personnel, increasing the risk of infection and disease transmission, especially during pandemics such as COVID-19. Therefore, non-contact vital sign monitoring technology is a feasible solution to these problems.

[0003] Compared to monitoring methods based on infrared, acoustic vibration, and cameras, bio-radar is less affected by environmental factors such as light and temperature, and has advantages such as less privacy concerns, better penetration, and higher sensitivity, making it advantageous for detecting vital signs. Furthermore, due to the rapid development of semiconductor technology and advancements in signal processing and artificial intelligence, today's radar sensors are more portable, lower cost, and more intelligent. Therefore, radar has become a key sensor in many applications, such as indoor and outdoor surveillance, fall detection, and autonomous driving. However, with the increasing density of radar systems, coherent interference from other radars can create false targets within the radar's detection range, causing a decrease in radar detection performance and increasing the probability of false alarms. Incoherent interference can cause additive noise, increasing the probability of missed alarms, and can also cause phase distortion, reducing the signal-to-noise ratio of respiratory and heartbeat signals, thus degrading the performance of bio-radar in detecting vital signs.

[0004] In existing interference mitigation techniques, most methods require first detecting the location of the interference and then reducing or removing it in different domains. The simplest technique is to remove the distorted portion in the time domain after detecting the interference, and then replace it with zeros or undisturbed portions. However, this leads to phase discontinuities and introduces high sidelobes. Other methods include using adaptive threshold iteration to reconstruct sparse signals, using adaptive selection of the peak value of the distance spectrum for inverse Fourier transform to suppress interference, using Kalman filters for interference mitigation and signal recovery, using autoregressive models for signal reconstruction in both fast and slow time dimensions, and using deep learning to recover the interference-free signal from the distorted signal. These passive interference suppression techniques are effective for relatively short interference times and relatively low interference signal amplitudes. However, when the echo signal has a large number of abrupt changes in sample points or the amplitude of these changes is high, the effectiveness of these methods is limited, and the time complexity increases.

[0005] Existing technology discloses a method for extracting and separating vital signs information based on millimeter-wave bio-radar, including the following steps: S1: Time-domain interference detection of the signal, traversing and detecting whether all frequency-modulated signals are interfered with; S2: Interference location detection of the interfered signal; S3: Interference suppression and signal restoration, suppressing the interference segment in the interfered frequency-modulated signal and reconstructing this segment; S4: Target vital signs detection, detecting the target's location and vital signs information; S5: Extraction and separation of vital signs information, extracting and separating the target's heartbeat and respiratory signals. This existing technology suffers from the problem of phase discontinuity during the anti-interference process and limited interference mitigation effect under severe interference conditions. Summary of the Invention

[0006] The purpose of this invention is to provide a vital sign detection method based on phase encoding, so as to solve the problems in the existing technology that the anti-interference process will lead to phase discontinuity and the interference mitigation effect is limited when the interference is severe.

[0007] To achieve the above objectives, the present invention provides a vital sign detection method based on phase encoding, comprising: S1. Randomly select an encoding sequence from the codebook, use the selected encoding sequence to perform phase encoding on the vital signs detection signal, and transmit the phase-encoded vital signs detection signal at the radar transmitter. The vital signs detection signal is a signal generated by the radar that can detect vital signs. S2. The radar receiver receives the echo signal of the phase-coded vital signs detection signal, and uses the encoding sequence in the codebook to traverse and decode the echo signal, and selects the correctly decoded beat frequency signal, which contains vital signs. S3. Detect the distance bin where the human target is located, merge the distance bin where the human target is located with multiple adjacent distance bins to obtain a merged distance bin, and obtain the phase signal of vital signs in the merged distance bin. The phase signal of vital signs includes the torso displacement signal. S4. The trunk displacement signal includes respiratory and heartbeat signals. The respiratory rate is estimated from the respiratory signal of the phase signal of vital signs. After suppressing respiratory harmonics and enhancing the heartbeat signal component, the heartbeat rate is estimated, and finally the respiratory rate and heartbeat rate are obtained.

[0008] Preferably, in step S In section 1, the specific process of generating vital sign detection signals and randomly selecting encoded sequences from the codebook is as follows: S 11. The generation of the first m individual vital signs detection signal S m ( t ), m =1,2,…, M ; S 12. Order m =1; S 13. Randomly select the first code from the codebook. z Encoded sequences C z ( i ), i 1,2,…, I , z 1,2,…,2 I The codebook has 2 I There are coded sequences, and one coded sequence contains ... I Each code element.

[0009] Preferably, in step S In section 1, the specific process of phase encoding the vital signs detection signal is as follows: S 14. Order i =1; S 15. Use the generated detection signal C z ( i Phase encoding is performed. m ( t ) = S m ( t)× C z ( i ); S16, Judgment i Is it equal to I If they are equal, proceed to step [step 1]. S 17. If they are not equal, let i = i +1, m = m +1, execute steps S 15; S 17. Judgment m Is it equal to M If they are equal, proceed to step [step 1]. S 18. If they are not equal, let m = m +1, execute steps S 14; S18, Transmit signal m ( t ).

[0010] Preferably, in step S In step 1, the phase-encoded signal m ( t It transmits signals to human targets via an antenna to detect vital signs.

[0011] Preferably, in step S In section 2, the process of traversing and decoding the echo signal using the encoded sequence in the codebook is as follows: S 21. Acquire the transmitted signal m ( t echo signal m ( t ), m =1,2,…, M ; S 22. Order z =1; S 23. Order m =1; S 24. Order i =1; S 25. Select the first code in the codebook. z Decode the encoded sequence h m,z ( t )= m,z ( t )× C z ( i ); S 26. Judgment i Is it equal to I If they are equal, proceed to step [step 1]. S 27. If they are not equal, let i = i +1, m = m +1, execute steps S 25; S 27. Judgment m Is it equal to M If they are equal, proceed to step [step 1]. S 28. If they are not equal, let m = m +1, execute steps S twenty four; S 28. Judgment z Is it equal to 2? I If they are equal, proceed to step [step 1]. S 29. If they are not equal, let z = z +1, execute steps S twenty three; S 29. Decoding the same sequence M The echo signals are denoted as { h m,z ( t )} M m=1 ,Will{ h m,z ( t )} M m=1 Each signal sampling point in the data is treated as a row, and each row is... N Point spectrum transformation yields 2 I Position matrix D [ M , N ]; S 210. For each D [ M , N Each column of ] M Point spectrum transformation yields 2 I Position-Doppler matrix V [ M , N ].

[0012] Preferably, in step S In section 2, the process of selecting the correct beat frequency signal for decoding is as follows: S 211. Calculate each using the peak-to-average power ratio (PAPR) formula. V [ M , N Peak-to-peak ratio PAPR z The formula for calculating the peak-to-average power ratio is as follows:

[0013] in, m hp yes V [ M , N The point with the largest amplitude. m db Is with m hp Frequency points in the same column p z Indicates the first z indivual V [ M , N Power at the mid-frequency point; S 212. Set peak-to-average ratio threshold R th1 ,judge PAPR z maximum value max ( PAPR z Is it greater than the threshold? R th1 If so, proceed with the steps. S 213. If not, proceed to step 213. S 21, regaining the next group M The echo signal of a phase-coded signal; S 213. Calculate the correct encoded sequence used for decoding in the codebook. z max The formula is as follows:

[0014] S 214. Obtain the selection number z max After correctly decoding the encoded sequence M A beat frequency signal, denoted as { h m ( t )} M m= 1.

[0015] Preferably, in step S In step 3, the specific process of detecting the distance cell where the human target is located, then merging it with multiple adjacent distance cells, and obtaining the phase signal containing vital signs in the merged distance cell is as follows: S 31. [The rest of the text appears to be a list of characters and symbols, possibly related to a document or instruction.] h m ( t )} M m= In step 1, each signal sampling point is treated as a row, and each row is... N Point spectrum transformation yields the distance matrix. R [ M , N ]; S 32. Distance matrix R [ M , N Summing by rows yields the distance vector. r ( n ), n =1,2,…, N ; S 33. Order k =1; S 34. Calculate using formulas r ( n The point with the largest amplitude n k , n k For distance bins, the formula is as follows: ; S 35. Extraction n k The phase at the point is compensated to obtain the phase. f k ( m ), m =1,2,…, M ; S 36. Obtain trunk displacement signal using formula d k ( m The formula is as follows:

[0016] in, l The wavelength of the transmitted signal; S 37. Calculate using the formula dk ( m variance var k The formula is as follows:

[0017] in, d k Representing time series d k The average value; S 38. Set the static clutter threshold R th2 and false target threshold R th3 ,judge var k Is it greater than the threshold? R th2 And less than the threshold R th3 If so, proceed with the steps. S 37, otherwise let n ≠ n K , K =1,2,… k , and then k = k +1, execute steps S 34; S 39. Calculate d k ( m )and d q ( m correlation coefficient heart q , d q ( m ) is the adjacent first q Reconstructed torso displacement signal at each frequency point q The initial value is n k - Q ; S 310. Set the correlation coefficient threshold. R th4 ,judge heart q Is it greater than the threshold? R th4 If so, proceed with the steps. S 311, otherwise proceed to step 2. S 39; S 311. Sum the obtained trunk displacement signals, as shown in the following formula: d k ( m )= d k ( m )+ d q ( m ) S 312. Judgment q Is it greater than n k + Q If so, proceed with the steps. S 313, otherwise let q = q +1, if q=n k Let q = q + 1, if q≠n k Execution steps S 39; S 313. Obtain the merged trunk displacement signal, using the following formula: d ( m )= d k ( m ).

[0018] Preferred steps S 35 of them f k ( m The specific process is as follows: S 351. Regarding the acquisition M Phase f k ( m ), judgment| f k ( m )- f k ( m -1) Whether it is less than or equal to π If so, proceed with the steps. S 353, otherwise proceed to step 1. S 352; S 352. Judgment f k ( m )- f k ( m-1) Is it greater than π If so, let f k ( m )= f k ( m )-2 π Execution steps S 353, otherwise let f k ( m )= f k ( m )+2 π Execution steps S 353; S 353, Output f k ( m ).

[0019] Preferably, in step S In section 4, the process of estimating respiratory rate is as follows: S 41. Calculate using the formula d ( m The autocorrelation function of ) r 1( u The formula is as follows:

[0020] in, u Indicates the number of delayed sample points. d Representing time series d The average value, c 1 represents a time series d The sample variance; S 42. Calculate the respiratory signal frequency f r =1 / u r t ,in, u r Represents the autocorrelation function r 1( u The number of delayed sample points corresponding to the peak value. t This indicates the time interval between two adjacent sampling points.

[0021] Preferably, in step S In section 4, after suppressing respiratory harmonics and enhancing the cardiac signal components, the process of estimating the heart rate is as follows: S 43. d ( m After passing through a bandpass filter, the respiratory signal is filtered out, and the result is obtained. d h ( m ); S 44. Calculate using formulas d h ( m First-order difference d′ h ( m The formula is as follows: S 45. Yes d′ h ( m ) Perform a spectral transformation to obtain D′ h ( f ); S 46. ​​Set the threshold for the difference order. R th5 ,judge D′ h ( f ) max / D′ h ( f ) mean Is it greater than the threshold? R th5 If so, proceed with the steps. S 47, otherwise proceed to step 47. S 410, of which, D′ h ( f ) max Indicates the highest peak amplitude of the spectrum. D′ h ( f ) mean This represents the average amplitude of the spectrum; S 47. Calculate using the formula d′ h ( m The autocorrelation function of ) r 2( u The formula is as follows:

[0022] in, d′ h ( m ) represents a time series d′h ( m The average value of ) c 2 represents a time series d′ h The sample variance; S 48. Calculate the heartbeat signal frequency. f h1 =1 / u h1 t ,in, u h1 Represents the autocorrelation function r 2( u The number of delayed sample points corresponding to the peak value; S 49. Calculate using formulas d h ( m Second difference d″ h ( m The formula is as follows: S 410. Calculate using the formula d″ h ( m The autocorrelation function of ) r 3( u The formula is as follows:

[0023] in, d″ h Representing time series d″ h The average value, c 3 indicates a time series d″ h The sample variance; S 411. Calculate the heartbeat signal frequency. f h2 =1 / u h2 t ,in, u h2 Represents the autocorrelation function r 3( u The number of delayed sample points corresponding to the peak value.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows: By encoding the vital signs detection signal using random coding, the transmitted signal has a certain degree of randomness, which can avoid interference between adjacent carriers. After correct decoding, the phase of false targets generated by coherent interference can be randomized, thereby detecting real targets and avoiding the influence of coherent interference. Through phase coding and ergonomic decoding, the phase noise caused by interference is reduced, and vital signs can be obtained from signals that are subject to more severe incoherent interference, thus enhancing the radar system's ability to detect vital signs. Furthermore, by using the variance of the phase signal to distinguish between static clutter and false targets, it is possible to accurately detect human targets. By performing differential operations on the heartbeat signal, the heartbeat signal components are enhanced, thereby improving the accuracy of heartbeat frequency detection. Attached Figure Description

[0025] Figure 1 This is a flowchart of a phase-encoded vital sign detection method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the information flow of vital sign detection signal generation and encoding according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the information flow for echo signal reception and decoding according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the information flow for human target detection according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the information flow for respiratory and heart rate detection according to an embodiment of the present invention. Detailed Implementation

[0026] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0027] In the description of this invention, it should be noted that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0028] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0029] Furthermore, in the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0030] Example 1 like Figure 1 As shown, a preferred embodiment of the present invention provides a vital sign detection method based on phase coding, comprising: S1. Randomly select an encoding sequence from the codebook, use the selected encoding sequence to perform phase encoding on the vital signs detection signal, and transmit the phase-encoded vital signs detection signal at the radar transmitter. The vital signs detection signal is a signal generated by the radar that can detect vital signs. S2. The radar receiver receives the echo signal of the phase-coded vital signs detection signal, and uses the encoding sequence in the codebook to traverse and decode the echo signal, and selects the correctly decoded beat frequency signal, which contains vital signs. S3. Detect the distance bin where the human target is located, merge the distance bin where the human target is located with multiple adjacent distance bins to obtain a merged distance bin, and obtain the phase signal of vital signs in the merged distance bin. The phase signal of vital signs includes the torso displacement signal. S4. The trunk displacement signal includes respiratory and heartbeat signals. The respiratory rate is estimated from the respiratory signal of the phase signal of vital signs. After suppressing respiratory harmonics and enhancing the heartbeat signal component, the heartbeat rate is estimated, and finally the respiratory rate and heartbeat rate are obtained.

[0031] By encoding the vital signs detection signal using random coding, the transmitted signal has a certain degree of randomness, which can avoid interference between adjacent carriers. After correct decoding, the phase of false targets generated by coherent interference can be randomized, thereby detecting real targets and avoiding the influence of coherent interference. Through phase coding and ergonomic decoding, the phase noise caused by interference is reduced, and vital signs can be obtained from signals that are subject to more severe incoherent interference, thus enhancing the radar system's ability to detect vital signs. Furthermore, by using the variance of the phase signal to distinguish between static clutter and false targets, it is possible to accurately detect human targets. By performing differential operations on the heartbeat signal, the heartbeat signal components are enhanced, thereby improving the accuracy of heartbeat frequency detection.

[0032] Example 2 like Figure 2 As shown, in the steps S In section 1, the specific process of generating vital sign detection signals and randomly selecting encoded sequences from the codebook is as follows: S 11. The generation of the first m individual vital signs detection signal S m ( t ), m =1,2,…, M ; In this embodiment, when m When =4, the fourth vital sign detection signal generated is S 4( t ); S 12. Order m =1; S 13. Randomly select the first code from the codebook. z Encoded sequences C z ( i ), i 1,2,…, I , z 1,2,…,2 I The codebook has 2 I There are coded sequences, and one coded sequence contains ... I Each code element.

[0033] In this embodiment, when i =2, I =8, z When =10, select the second symbol from the 10th encoded sequence. C 10 (2); In the steps S In section 1, the specific process of phase encoding the vital signs detection signal is as follows: S 14. Order i =1; S 15. Use the generated detection signal C z ( i Phase encoding is performed. m ( t ) = S m( t )× C z ( i ); In this embodiment, when m =4, i =2, I =8, z When =10, 4( t ) = S 4( t )× C 10 (2); S16, Judgment i Is it equal to I If they are equal, proceed to step [step 1]. S 17. If they are not equal, let i = i +1, m = m +1, execute steps S 15; In this embodiment, i =2, I =8, m =4, 2<8, then let... i =2+1, m =4+1, execute the steps S 15; S 17. Judgment m Is it equal to M If they are equal, proceed to step [step 1]. S 18. If they are not equal, let m = m +1, execute steps S 14; S18, Transmit signal m ( t ).

[0034] In this embodiment, m =4, M =512, 4<512, then let... m =4+1, execute the steps S 14; In the steps S In step 1, the phase-encoded signal m ( t It transmits signals to human targets via an antenna to detect vital signs.

[0035] Example 3 like Figure 3 As shown, in the steps S In section 2, the process of traversing and decoding the echo signal using the encoded sequence in the codebook is as follows: S 21. Acquire the transmitted signal m ( t echo signal m ( t ), m =1,2,…, M ; In this embodiment, when m When =4, acquire the transmitted signal. 4( t echo signal 4( t ); S 22. Order z =1; S 23. Order m =1; S 24. Order i =1; S 25. Select the first code in the codebook. z Decode the encoded sequence h m,z ( t )= m,z ( t )× C z ( i ); In this embodiment, when m =4, i =2, z When =10, h 4,10 ( t )= 4,10 ( t )× C 10 (2); S 26. Judgment i Is it equal to I If they are equal, proceed to step [step 1]. S 27. If they are not equal, let i = i +1, m = m +1, execute steps S 25; In this embodiment, i =2, I =8, m =4, 2<8, then let... i =2+1, m =4+1, execute the steps S 25; S 27. Judgment m Is it equal to M If they are equal, proceed to step [step 1]. S 28. If they are not equal, let m = m +1, execute steps S twenty four; In this embodiment, m =4, M =512, 4<512, so let m=4+1 and execute the steps. S twenty four; S 28. Judgment z Is it equal to 2? I If they are equal, proceed to step [step 1]. S 29. If they are not equal, let z = z +1, execute steps S twenty three; In this embodiment, z =100, I =8, 100<256, so let... z =100+1, execute steps S twenty three; S 29. Decoding the same sequence M The echo signals are denoted as { h m,z ( t )} M m=1 ,Will{ h m,z ( t )} M m=1 Each signal sampling point in the data is treated as a row, and each row is... N Point spectrum transformation yields 2 I Position matrix D [ M , N ]; In this embodiment, when I =8, M =512, N When the value is 128, each signal sampling point is arranged as a row, and each row contains 128 points. FFT This yields a matrix of 256 positions.D [512,128]; S 210. For each D [ M , N Each column of ] M Point spectrum transformation yields 2 I Position-Doppler matrix V [ M , N ].

[0036] In this embodiment, when I =8, M =512, N When =128, for 256 D Performing a 512-point spectral transformation on each column of [512,128] yields 256 position-Doppler matrices. V [512,128]; In this embodiment, each sequence is selected through iteration, and the peak-to-average power ratio (PAPR) is used as the correlation index. The sequence with the highest correlation is used for decoding. After performing distance-dimensional FFT and velocity-dimensional FFT on the beat frequency signal, the PAPR of the signal is calculated, and the signal with the highest PAPR is the correct beat frequency signal.

[0037] In the steps S In section 2, the process of selecting the correct beat frequency signal for decoding is as follows: S 211. Calculate each using the peak-to-average power ratio (PAPR) formula. V [ M , N Peak-to-peak ratio PAPR z The formula for calculating the peak-to-average power ratio is as follows:

[0038] in, m hp yes V [ M , N The point with the largest amplitude. m db Is with m hp Frequency points in the same column p z Indicates the first z indivual V [ M , N Power at the mid-frequency point; In this embodiment, when z =100, M =512, N =128,m hp Position-Doppler matrix coordinates V When (200, 50), m db For one of the coordinates in the 50th column of the position-Doppler matrix, the formula is given. I Calculate the peak ratio of the Doppler matrix at the 100th position: ; S 212. Set peak-to-average ratio threshold R th1 ,judge PAPR z maximum value max ( PAPR z Is it greater than the threshold? R th1 If so, proceed with the steps. S 213. If not, proceed to step 213. S 21, regaining the next group M The echo signal of a phase-coded signal; In this embodiment, when max ( PAPR z )=20, R th1 =5, 20>5, then proceed to step 5. S 213; S 213. Calculate the correct encoded sequence used for decoding in the codebook. z max The formula is as follows:

[0039] S 214. Obtain the selection number z max After correctly decoding the encoded sequence M A beat frequency signal, denoted as { h m ( t )} M m= 1.

[0040] Example 4 When the human body is at rest, the trunk displacement signal includes respiratory and heartbeat signals. This embodiment detects vital signs when the human body is at rest.

[0041] like Figure 4 As shown, in the steps SIn step 3, the specific process of detecting the distance cell where the human target is located, then merging it with multiple adjacent distance cells, and obtaining the phase signal containing vital signs in the merged distance cell is as follows: S 31. [The rest of the text appears to be a list of characters and symbols, possibly related to a document or instruction.] h m ( t )} M m= In step 1, each signal sampling point is treated as a row, and each row is... N Point spectrum transformation yields the distance matrix. R [ M , N ]; In this embodiment, when M =512, N When the value is 128, each signal sampling point is arranged as a row, and each row contains 128 points. FFT The distance matrix is ​​obtained. R [512,128]; S 32. Distance matrix R [ M , N Summing by rows yields the distance vector. r ( n ), n =1,2,…, N ; In this embodiment, when M =512, N =128, n When =64, the distance matrix R Summing [512,128] row by row yields the distance vector. r (64); S 33. Order k =1; S 34. Calculate using formulas r ( n The point with the largest amplitude n k , n k For distance bins, the formula is as follows: ; S 35. Extraction n k The phase at the point is compensated to obtain the phase. f k ( m ), m =1,2,…, M ; S 36. Obtain trunk displacement signal using formula d k ( m The formula is as follows:

[0042] in, l The wavelength of the transmitted signal; S 37. Calculate using the formula d k ( m variance var k The formula is as follows:

[0043] in, d k Representing time series d k The average value; S 38. Set the static clutter threshold R th2 and false target threshold R th3 ,judge var k Is it greater than the threshold? R th2 And less than the threshold R th3 If so, proceed with the steps. S 37, otherwise let n ≠ n K , K =1,2,… k , and then k = k +1, execute steps S 34; In this embodiment, k =2, Var 2 = 0.01, R th2 =6, R th3 =30, 0.01<6<30, at this time, let n ≠ n 1, n 2. Then order k =2+1, execute the steps S 34; S 39. Calculate d k( m )and d q ( m correlation coefficient heart q , d q ( m ) is the adjacent first q Reconstructed torso displacement signal at each frequency point q The initial value is n k - Q ; In this embodiment, heart q It can be represented as a time series. d k and d q The Pearson correlation coefficient; S 310. Set the correlation coefficient threshold. R th4 ,judge heart q Is it greater than the threshold? R th4 If so, proceed with the steps. S 311, otherwise proceed to step 2. S 39; In this embodiment, heart q =7, R th4 =8, 7<8, at this time, execute step S311; S 311. Sum the obtained trunk displacement signals, as shown in the following formula: d k ( m )= d k ( m )+ d q ( m ) S 312. Judgment q Is it greater than n k + Q If so, proceed with the steps. S 313, otherwise let q = q +1, if q=n k Let q = q + 1, if q≠n kExecution steps S 39; In this embodiment, q =49, n k =50, Q =4, 49 < 54, at this time, let q =49+1, execute steps S 39; S 313. Obtain the merged trunk displacement signal, using the following formula: d ( m )= d k ( m ).

[0044] step S 35 of them f k ( m The specific process is as follows: S 351. Regarding the acquisition M Phase f k ( m ), judgment| f k ( m )- f k ( m -1) Whether it is less than or equal to π If so, proceed with the steps. S 353, otherwise proceed to step 1. S 352; In this embodiment, when k =32, m =6, f 32 (6) = 2.65, f 32 When (5) = 0.47, then | f 32 (6)- f 32 (5)|=2.18< π Execution steps S 353, direct output f 32 (6) = 2.65; S 352. Judgment f k ( m )- f k (m -1) Is it greater than π If so, let f k ( m )= f k ( m )-2 π Execution steps S 353, otherwise let f k ( m )= f k ( m )+2 π Execution steps S 353; In this embodiment, when k =32, m =6, f 32 (6) = 2.65, f 32 When (5) = -1.22, then f 32 (6)- f 32 (5) = 3.87 π At this time, order f 32 (6)= f 32 (6)-2 π Execution steps S 353, Output f 32 (6) = -3.63; S 353, Output f k ( m ).

[0045] Example 5 like Figure 5 As shown, in the steps S In section 4, the process of estimating respiratory rate is as follows: S 41. Calculate using the formula d ( m The autocorrelation function of ) r 1( u The formula is as follows:

[0046] in, u Indicates the number of delayed sample points. d Representing time seriesd The average value, c 1 represents a time series d The sample variance; S 42. Calculate the respiratory signal frequency f r =1 / u r t ,in, u r Represents the autocorrelation function r 1( u The number of delayed sample points corresponding to the peak value. t This indicates the time interval between two adjacent sampling points.

[0047] In this embodiment, when u r =60, t =0.05 seconds, f r =1 / 60 × 0.05 = 0.33 Hz ; In the steps S In section 4, after suppressing respiratory harmonics and enhancing the cardiac signal components, the process of estimating the heart rate is as follows: S 43. d ( m After passing through a bandpass filter, the respiratory signal is filtered out, and the result is obtained. d h ( m ); S 44. Calculate using formulas d h ( m First-order difference d′ h ( m The formula is as follows: S 45. Yes d′ h ( m ) Perform a spectral transformation to obtain D′ h ( f ); In this embodiment, when M When =512, for d′ h ( m ) Make 512 points FFT ,get D′h ( f ); S 46. ​​Set the threshold for the difference order. R th5 ,judge D′ h ( f ) max / D′ h ( f ) mean Is it greater than the threshold? R th5 If so, proceed with the steps. S 47, otherwise proceed to step 47. S 410, of which, D′ h ( f ) max Indicates the highest peak amplitude of the spectrum. D′ h ( f ) mean This represents the average amplitude of the spectrum; In this embodiment, when M =512, R th5 =6, if the ratio of the maximum value to the mean of the spectrum is D′ h ( f ) max / D′ h ( f ) mean =512× D′ h ( f ) max / ∑512 f= 1 D′ h ( f If )>6, then proceed to step 1. S 47, if D′ h ( f ) max / D′ h ( f ) mean =512× D′ h ( f ) max / ∑512 f= 1 D′ h ( f If ) < 6, then proceed with the steps. S410; S 47. Calculate using the formula d′ h ( m The autocorrelation function of ) r 2( u The formula is as follows:

[0048] in, d′ h ( m ) represents a time series d′ h ( m The average value of ) c 2 represents a time series d′ h The sample variance; S 48. Calculate the heartbeat signal frequency. f h1 =1 / u h1 t ,in, u h1 Represents the autocorrelation function r 2( u The number of delayed sample points corresponding to the peak value; S 49. Calculate using formulas d h ( m Second difference d″ h ( m The formula is as follows: S 410. Calculate using the formula d″ h ( m The autocorrelation function of ) r 3( u The formula is as follows:

[0049] in, d″ h Representing time series d″ h The average value, c 3 indicates a time series d″ h The sample variance; S411. Calculate the heartbeat signal frequency. f h2 =1 / u h2 t ,in, u h2 Represents the autocorrelation function r 3( u The number of delayed sample points corresponding to the peak value.

[0050] The working process of this invention is as follows: S1. Randomly select an encoding sequence from the codebook, use the selected encoding sequence to perform phase encoding on the vital signs detection signal, and transmit the phase-encoded vital signs detection signal at the radar transmitter. The vital signs detection signal is a signal generated by the radar that can detect vital signs. S2. The radar receiver receives the echo signal of the phase-coded vital signs detection signal, and uses the encoding sequence in the codebook to traverse and decode the echo signal, and selects the correctly decoded beat frequency signal, which contains vital signs. S3. Detect the distance bin where the human target is located, merge the distance bin where the human target is located with multiple adjacent distance bins to obtain a merged distance bin, and obtain the phase signal of vital signs in the merged distance bin. The phase signal of vital signs includes the torso displacement signal. S4. The trunk displacement signal includes respiratory and heartbeat signals. The respiratory rate is estimated from the respiratory signal of the phase signal of vital signs. After suppressing respiratory harmonics and enhancing the heartbeat signal component, the heartbeat rate is estimated, and finally the respiratory rate and heartbeat rate are obtained.

[0051] In summary, this invention provides a phase-encoded vital sign detection method. By using random encoding to encode the vital sign detection signal, the transmitted signal exhibits a degree of randomness, avoiding interference between adjacent carriers. Furthermore, after correct decoding, the phase of false targets generated by coherent interference can be randomized, thereby detecting the real target and avoiding the influence of coherent interference. Through phase encoding and ergonomic decoding, phase noise caused by interference is reduced, and vital signs are obtained from signals subject to severe incoherent interference, enhancing the radar system's ability to detect vital signs. By using the variance of the phase signal to distinguish between static clutter and false targets, human targets can be accurately detected. Finally, differential operations are performed on the heartbeat signal, enhancing the heartbeat signal components and improving the accuracy of heartbeat frequency detection.

[0052] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present invention.

Claims

1. A vital sign detection method based on phase encoding, comprising: S1. Randomly select an encoding sequence from the codebook, use the selected encoding sequence to perform phase encoding on the vital signs detection signal, and transmit the phase-encoded vital signs detection signal at the radar transmitter. The vital signs detection signal is a signal generated by the radar that can detect vital signs. S2. The radar receiver receives the echo signal of the phase-coded vital signs detection signal, and uses the coding sequence in the codebook to traverse and decode the echo signal, and selects the correctly decoded beat frequency signal, which contains vital signs. The process of traversing and decoding the echo signal using the encoded sequence in the codebook, and selecting the correctly decoded beat frequency signal, is as follows: S 21. Acquire the transmitted signal m ( t echo signal m ( t ), m =1,2,…, M ; S 22. Order z =1; S 23. Order m =1; S 24. Order i =1; S 25. Select the first code in the codebook. z Decode the encoded sequence h m,z ( t )= m,z ( t )× C z ( i ); S 26. Judgment i Is it equal to I If they are equal, proceed to step [step 1]. S 27. If they are not equal, let i = i +1, m = m +1, execute steps S 25; S 27. Judgment m Is it equal to M If they are equal, proceed to step [step 1]. S 28. If they are not equal, let m = m +1, execute steps S twenty four; S 28. Judgment z Is it equal to 2? I If they are equal, proceed to step [step 1]. S 29. If they are not equal, let z = z +1, execute steps S twenty three; S 29. Decoding the same sequence M Each echo signal is denoted as ,Will Each signal sampling point in the data is treated as a row, and each row is... N Point spectrum transformation yields 2 I Position matrix D [ M , N ]; S 210. For each D [ M , N Each column of ] M Point spectrum transformation yields 2 I Position-Doppler matrix V [ M , N ]; S 211. Calculate each using the peak-to-average power ratio (PAPR) formula. V [ M , N Peak-to-peak ratio PAPR z The formula for calculating the peak-to-average power ratio is as follows: in, m hp yes V [ M , N The point with the largest amplitude, m db Is with m hp Frequency points in the same column p z Indicates the first z indivual V [ M , N Power at the mid-frequency point; S 212. Set peak-to-average ratio threshold R th1 ,judge PAPR z maximum value max ( PAPR z Is it greater than the threshold? R th1 If so, proceed with the steps. S 213. If not, proceed to step 213. S 21, regaining the next group M The echo signal of a phase-coded signal; S 213. Calculate the correct encoded sequence used for decoding in the codebook. z max The formula is as follows: S 214. Obtain the selection number z max After correctly decoding the encoded sequence M A beat frequency signal, denoted as ; S3. Detect the distance bin where the human target is located, merge the distance bin where the human target is located with multiple adjacent distance bins to obtain a merged distance bin, and obtain the phase signal of vital signs in the merged distance bin. The phase signal of vital signs includes the torso displacement signal. The specific process of detecting the location of a human target in a distance bin, merging it with multiple adjacent distance bins, and obtaining a phase signal containing vital signs in the merged distance bin is as follows: S 31. Each signal sampling point is treated as a row, and each row is... N Point spectrum transformation yields the distance matrix. R [ M , N ]; S 32. Distance matrix R [ M , N Summing by rows yields the distance vector. r ( n ), n =1,2,…, N ; S 33. Order k =1; S 34. Calculate using formulas r ( n The point with the largest amplitude n k , n k For distance bins, the formula is as follows: ； S 35. Extraction n k The phase at the point is compensated to obtain the phase. φ k ( m ), m =1,2,…, M ; S 36. Obtain trunk displacement signal using formula d k ( m The formula is as follows: in, λ The wavelength of the transmitted signal; S 37. Calculate using the formula d k ( m variance var k The formula is as follows: in, Representing time series d k The average value; S 38. Set the static clutter threshold R th2 and false target threshold R th3 ,judge var k Is it greater than the threshold? R th2 And less than the threshold R th3 If so, proceed with the steps. S 37, otherwise let n ≠ n K , K =1,2,… k , and then k = k +1, execute steps S 34; S 39. Calculate d k ( m )and d q ( m correlation coefficient cor q , d q ( m ) is the adjacent first q Reconstructed torso displacement signal at each frequency point q The initial value is n k - Q ; S 310. Set the correlation coefficient threshold. R th4 ,judge cor q Is it greater than the threshold? R th4 If so, proceed with the steps. S 311, otherwise proceed to step 2. S 39; S 311. Sum the obtained trunk displacement signals, as shown in the following formula: d k ( m )= d k ( m )+ d q ( m ) S 312. Judgment q Is it greater than n k + Q If so, proceed with the steps. S 313, otherwise let q = q +1, if q=n k Let q = q + 1, if q ≠n k Execution steps S 39; S 313. Obtain the merged trunk displacement signal, using the following formula: d ( m )= d k ( m ) S4. The trunk displacement signal includes respiratory and heartbeat signals. The respiratory rate is estimated from the respiratory signal of the phase signal of vital signs. After suppressing respiratory harmonics and enhancing the heartbeat signal component, the heartbeat rate is estimated, and finally the respiratory rate and heartbeat rate are obtained.

2. The vital sign detection method based on phase encoding according to claim 1, characterized in that, In the steps S In section 1, the specific process of generating vital sign detection signals and randomly selecting encoded sequences from the codebook is as follows: S 11. The generation of the first m individual vital signs detection signal S m ( t ), m =1,2,…, M ; S 12. Order m =1; S 13. Randomly select the first code from the codebook. z Encoded sequences C z ( i ), i 1,2,…, I , z 1,2,…,2 I The codebook has 2 I There are coded sequences, and one coded sequence contains ... I Each code element.

3. The vital sign detection method based on phase encoding according to claim 2, characterized in that, In the steps S In section 1, the specific process of phase encoding the vital signs detection signal is as follows: S 14. Order i =1; S 15. Use the generated detection signal C z ( i Phase encoding is performed. m ( t ) = S m ( t )× C z ( i ); S16, Judgment i Is it equal to I If they are equal, proceed to step [step 1]. S 17. If they are not equal, let i = i +1, m = m +1, execute steps S 15; S 17. Judgment m Is it equal to M If they are equal, proceed to step [step 1]. S 18. If they are not equal, let m = m +1, execute steps S 14; S18, Transmit signal m ( t ).

4. The vital sign detection method based on phase encoding according to claim 3, characterized in that, In the steps S In step 1, the phase-encoded signal m ( t It transmits signals to human targets via an antenna to detect vital signs.

5. The vital sign detection method based on phase encoding according to claim 1, characterized in that, step S 35 of them φ k ( m The specific process is as follows: S 351. Regarding the acquisition M Phase φ k ( m ), judgment| φ k ( m )- φ k ( m -1) Whether it is less than or equal to π If so, proceed with the steps. S 353, otherwise proceed to step 353. S 352; S 352. Judgment φ k ( m )- φ k ( m -1) Is it greater than π If so, let φ k ( m )= φ k ( m )-2 π Execution steps S 353, otherwise let φ k ( m )= φ k ( m )+2 π Execution steps S 353; S 353, Output φ k ( m ).

6. The vital sign detection method based on phase encoding according to claim 5, characterized in that, In the steps S In section 4, the process of estimating respiratory rate is as follows: S 41. Calculate using formulas d ( m The autocorrelation function of ) r 1( u The formula is as follows: in, u Indicates the number of delayed sample points. Representing time series d The average value, c 1 represents a time series d The sample variance; S 42. Calculate the respiratory signal frequency f r =1 / u r t ,in, u r Represents the autocorrelation function r 1( u The number of delayed sample points corresponding to the peak value. t This indicates the time interval between two adjacent sampling points.

7. The vital sign detection method based on phase encoding according to claim 6, characterized in that, In the steps S In section 4, after suppressing respiratory harmonics and enhancing the cardiac signal components, the process of estimating the heart rate is as follows: S 43. d ( m After passing through a bandpass filter, the respiratory signal is filtered out, and the result is obtained. d h ( m ); S 44. Calculate using formulas d h ( m First-order difference d′ h ( m The formula is as follows: ； S 45. Yes d′ h ( m ) Perform a spectral transformation to obtain D′ h ( f ); S 46. ​​Set the threshold for the difference order. R th5 ,judge D′ h ( f ) max / D′ h ( f ) mean Is it greater than the threshold? R th5 If so, proceed with the steps. S 47, otherwise proceed to step 47. S 410, of which, D′ h ( f ) max Indicates the highest peak amplitude of the spectrum. D′ h ( f ) mean This represents the average amplitude of the spectrum; S 47. Calculate using the formula d′ h ( m The autocorrelation function of ) r 2( u The formula is as follows: in, Representing time series d′ h ( m The average value of ) c 2 represents a time series d′ h The sample variance; S 48. Calculate the heartbeat signal frequency. f h1 =1 / u h1 t ,in, u h1 Represents the autocorrelation function r 2( u The number of delayed sample points corresponding to the peak value; S 49. Calculate using the formula d h ( m Second difference d″ h ( m The formula is as follows: ； S 410. Calculate using the formula d″ h ( m The autocorrelation function of ) r 3( u The formula is as follows: in, Representing time series d″ h The average value, c 3 indicates a time series d″ h The sample variance; S 411. Calculate the heartbeat signal frequency. f h2 =1 / u h2 t ,in, u h2 Represents the autocorrelation function r 3( u The number of delayed sample points corresponding to the peak value.

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