Doppler radar vital signs feature extraction method based on second-order instantaneous moment

Abstract

The invention discloses a method for extracting vital signs features of Doppler radar based on second-order instantaneous moment, comprising: 1. obtaining a baseband signal of orthogonal sampling received by Doppler radar, wherein the baseband signal is a signal obtained by mixing the echo of the radar transmission signal and the transmission signal of the target; 2. performing mean filtering on the baseband signal to obtain a baseband signal with a DC component removed; 3. taking the complex data after mean filtering as an observed quantity, adopting the second-order instantaneous moment method to obtain a demodulated vital sign signal waveform; 4. passing the demodulated vital sign signal waveform through a bandpass filter of [0.1, 0.6] and [0.8, 2.5] Hz respectively to obtain a respiratory and heartbeat time domain signal; 5. performing Fourier transform processing on the extracted respiratory and heartbeat time domain waveforms to obtain the spectrum of the respiratory waveform and the heartbeat waveform respectively, and estimating the respiratory and heartbeat frequency parameters based on the threshold detection technology. The invention improves the estimation accuracy of respiratory rate and heart rate parameters.

Description

Technical Field

[0001] The invention belongs to the technical field of signal processing, and in particular relates to a Doppler radar vital sign feature extraction method based on second-order instantaneous moment. Background Art

[0002] As people's living standards improve, the demand for quick and comfortable acquisition of vital signs such as breathing and heart rate is getting higher and higher. Low-cost Doppler radar can use the scattering characteristics of electromagnetic waves to obtain the vital signs of a single target, and has been gradually applied to non-contact vital signs detection scenarios. However, in actual situations, due to the influence of factors such as antenna transceiver coupling, the accuracy requirements of the A / D converter, and environmental noise interference, it is difficult to use existing methods to extract obvious vital signs features from the baseband signal of the radar echo.

[0003] Existing extraction methods are mainly divided into two categories: one is complex signal demodulation, which first performs Fourier transform on the baseband signal, and then completes the vital sign feature extraction based on threshold detection. Its advantage is that the processing steps are simple and it has certain anti-noise performance. However, the disadvantage is that the amplitude of the vital sign characteristic line spectrum is modulated by the first-order Bessel function, which cannot accurately reflect the relative size of the vital sign line spectrum amplitude. In addition, due to the intermodulation effect of breathing and heart rate, there are a large number of cross-term line spectra in the vital sign characteristic line spectrum detection interval, making it difficult to accurately determine the position of the target line spectrum.

[0004] The other type is inverse tangent demodulation, which first extracts the phase of the baseband signal, then performs Fourier transform on the phase signal, and finally completes the vital sign feature extraction based on threshold detection. The advantage is that there is no intermodulation effect of breathing and heart rate in the extracted phase information, so there is no cross-term line spectrum, and the amplitude of the target line spectrum frequency can more accurately reflect the relative size. However, the disadvantage is that the phase signal is easily affected by noise, and a series of operations such as unwrapping and removing trend terms are required for the extracted phase signal. The processing steps are complicated and the quality of the demodulated vital sign signal is poor. Summary of the invention

[0005] The present invention aims to provide a Doppler radar vital sign feature extraction method based on second-order instantaneous moment to solve the technical problem that it is difficult to accurately extract vital sign features through existing processing methods when the environmental noise is large.

[0006] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0007] A method for extracting vital sign features of Doppler radar based on second-order instantaneous moment, wherein the vital sign features include respiratory rate features and heart rate features, comprises the following steps:

[0008] Step 1, obtaining the orthogonal sampled baseband signal received by the Doppler radar, the baseband signal being the in-phase component I(t) of the baseband signal and the orthogonal component Q(t) of the baseband signal obtained by mixing the target's echo of the radar transmission signal with the transmission signal;

[0009] Step 2, performing mean filtering on the baseband signal to obtain a baseband signal with a DC component removed, including an in-phase component I′(t) after the DC is removed from the baseband signal and a quadrature component Q′(t) after the DC is removed from the baseband signal;

[0010] Step 3: Taking the complex data after mean filtering as the observation quantity, the second-order instantaneous moment method is used to obtain the demodulated vital sign signal waveform S(t);

[0011] Step 4: Pass the demodulated vital sign signal waveform through bandpass filters of [0.1, 0.6] Hz and [0.8, 2.5] Hz respectively to obtain breathing and heartbeat time domain signals;

[0012] Step 5: Perform Fourier transform processing on the extracted respiratory and heartbeat time domain waveforms to obtain the frequency spectra of the respiratory waveform and the heartbeat waveform respectively, and estimate the respiratory and heartbeat frequency parameters based on the threshold detection technology.

[0013] Preferably, step 1 specifically includes the following steps:

[0014] Step 1.1, the Doppler radar transmitting antenna transmits a single-frequency continuous wave signal:

[0015] x T (t) = A T cos(2πf c t)

[0016] Among them, A T is the signal amplitude, f c is the carrier frequency, t is the time;

[0017] When the electromagnetic wave irradiates the human target and returns to the receiving antenna, the echo signal reaching the receiving antenna is written as:

[0018] x R (t) = σcos(2πf c (t-τ)

[0019] Where σ is the scattering coefficient of the target, τ = 2d(t) / c is the echo delay of the target, d(t) is the distance from the radar to the target, and c is the propagation speed of the electromagnetic wave;

[0020] The Doppler radar hardware system uses the transmitted signal to mix the echo signal and obtains the mixed signal through low-pass filtering, which is written as:

[0021]

[0022] Step 1.2: The mixed signal is sampled by quadrature sampling. Considering the DC bias introduced by the level inconsistency of the IQ sampling channels in the actual hardware system, the in-phase component I(t) and the quadrature component Q(t) of the baseband signal obtained by the IQ quadrature sampling channels are respectively:

[0023]

[0024]

[0025] DC I is the in-phase component of the baseband signal, DC Q is the DC component of the orthogonal component in the baseband signal, A I is the in-phase component of the baseband signal, A Q is the amplitude of the orthogonal component in the baseband signal, λ=c / f c Indicates the carrier wavelength;

[0026] Set the sampling frequency f of the Doppler radar system s , the observation time length is T, then the discrete sampling signal of the IQ channel is

[0027]

[0028]

[0029] Where n=1,…,N,N=f s T represents the number of signal sampling points;

[0030] Step 1.3, Doppler radar extracts the breathing and heart rate characteristics by sensing the weak periodic distance changes of the chest wall of the human target. The distance d(n) is expressed as:

[0031] d(n)=d0(n)+m h sin(2πf h n)+m r sin(2πf r n)

[0032] Where d0 is the nominal distance from the radar to the target, m h Represents the amplitude of the periodic displacement of the chest wall caused by the human target heart rate, m r represents the amplitude of the periodic displacement of the chest wall caused by human target breathing, f h Represents the frequency of the human target heart rate, f r Indicates the breathing frequency of a human target.

[0033] Preferably, step 2 comprises the following steps:

[0034] Step 2.1: Estimate the mean of the in-phase component and the orthogonal component of the baseband signal respectively and

[0035] The estimated baseband signal mean processing block size is N,

[0036] The estimated baseband signal mean value processing method is:

[0037]

[0038]

[0039] Step 2.2: Use mean filtering to remove the DC components of the in-phase component and the orthogonal component of the baseband signal respectively:

[0040] The mean filtering method is:

[0041]

[0042]

[0043] Considering that the amplitude distortion caused by IQ channel inconsistency is usually small, it is assumed that after the mean filter processing, the signal amplitudes of the IQ channels are basically the same, and the above formula is rewritten as:

[0044]

[0045]

[0046] Where A is the signal amplitude after mean filtering.

[0047] Preferably, step 3 comprises the following steps:

[0048] Step 3.1, using the mean filtered signal as the observation, construct the complex signal C(n):

[0049]

[0050] Where j is an imaginary number; since d0 is the nominal distance from the radar to the target, which is basically unchanged during the observation time, it is regarded as a quantity independent of time, and the above formula is rewritten as:

[0051]

[0052] in

[0053] Step 3.2: Use the second-order instantaneous moment method to obtain the demodulated vital sign signal S(n):

[0054] The second-order instantaneous moment method is:

[0055]

[0056] Where Δ represents the digital signal sampling interval, C * (n-Δ) represents the conjugate of C(n-Δ), C(n-Δ) represents the signal after the complex signal C(n) is delayed by Δ, and Imag[.] represents the imaginary part of the complex signal;

[0057] When the delay Δ is taken When , the above formula satisfies sin(x)=x+O(x), where O(x) represents the high-order infinitesimal of x. The above formula can be approximately written as:

[0058]

[0059] Preferably, step 4 comprises the following steps:

[0060] Step 4.1, design a linear phase FIR bandpass filter with passband ranges of [0.1, 0.6] Hz and [0.8, 2.5] Hz respectively. The transfer function of the bandpass filter is:

[0061] H(z)=b0+b1z -1 +…+b N z -N

[0062] Among them, {b i}i=0,1,…,N represents the N-order FIR filter coefficient, Z represents the Z transform operator;

[0063] Step 4.2: Pass the demodulated vital sign signal waveform through a [0.1, 0.6] Hz bandpass filter to obtain a respiratory time domain signal, and pass the demodulated vital sign signal waveform through a [0.8, 2.5] Hz bandpass filter to obtain a heartbeat time domain signal.

[0064] The Doppler radar vital sign feature extraction method based on second-order instantaneous moment of the present invention has the following advantages:

[0065] The present invention uses the second-order instantaneous moment of the baseband signal after mean filtering to complete the demodulation of the vital sign signal, and then uses bandpass filtering and threshold detection technology to estimate the vital sign characteristics. The application is simple and direct, with low economic cost and obvious effect, small amount of calculation, and high degree of restoration of vital sign characteristics. The method only needs to calculate the second-order instantaneous moment of the baseband signal, without special consideration of the influence of environmental noise and the intermodulation effect of the heart rate and respiratory spectrum, so it can complete the accurate extraction of vital sign characteristics in actual scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1A flow chart of a Doppler radar vital sign feature extraction method based on second-order instantaneous moment implemented by the present invention;

[0067] Figure 2 A waveform diagram of the in-phase component of the baseband signal received by the radar in the embodiment;

[0068] Figure 3 A waveform diagram of orthogonal components of a baseband signal received by the radar in the embodiment;

[0069] Figure 4 [0.1, 0.6] Hz bandpass filter frequency response in the embodiment;

[0070] Figure 5 [0.8, 2.5] Hz bandpass filter frequency response in the embodiment;

[0071] Figure 6 A heart rate spectrum demodulated based on the second-order instantaneous moment technique and bandpass filtered in the embodiment;

[0072] Figure 7 In the embodiment, the respiratory spectrum is demodulated based on the second-order instantaneous moment technique and band-pass filtered. DETAILED DESCRIPTION

[0073] In order to better understand the purpose, structure and function of the present invention, the following is a further detailed description of a Doppler radar vital sign feature extraction method based on second-order instantaneous moment of the present invention in conjunction with the accompanying drawings.

[0074] Embodiment 1:

[0075] This method can solve the technical problem that it is difficult to obtain the vital sign characteristics without cross-line spectrum interference through a simple and effective parameter estimation method when the interference of environmental noise is too large. In order to verify the effectiveness of this method, this embodiment takes the following scenario as an example to obtain vital sign characteristics. The reference breathing frequency of a single human target is 0.3Hz, and the heart rate is 1.4Hz. The digital sampling interval is 0.01 seconds, and the input signal-to-noise ratio is 5dB.

[0076] This example discloses a method for extracting vital sign features from Doppler radar based on second-order instantaneous moments. The vital sign features include respiratory rate features and heart rate features. The specific implementation block diagram is as follows: Figure 1 As shown, the following steps are included:

[0077] Step 1: Obtain the orthogonal sampled baseband signal received by the Doppler radar. The baseband signal is the in-phase component I(t) of the baseband signal obtained by mixing the target's echo of the radar's transmitted signal with the transmitted signal, as shown in Figure 2 As shown, and the orthogonal component Q(t) of the baseband signal, as Figure 3 As shown;

[0078] Step 2, performing mean filtering on the baseband signal to obtain an in-phase component I′(t) of the baseband signal with the DC component removed and a quadrature component Q′(t) of the baseband signal with the DC component removed;

[0079] Step 2.1, the Doppler radar transmitting antenna transmits a single-frequency continuous wave signal:

[0080] x T (t) = A T cos(2πf c t)

[0081] Among them, A T is the signal amplitude, f c is the carrier frequency and t is the time.

[0082] When the electromagnetic wave irradiates the human target and returns to the receiving antenna, the echo signal reaching the receiving antenna can be written as:

[0083] x R (t) = σcos(2πf c (t-τ)

[0084] Where σ is the scattering coefficient of the target, τ = 2d(t) / c is the echo delay of the target, d(t) is the distance from the radar to the target, and c is the propagation speed of the electromagnetic wave.

[0085] The Doppler radar hardware system uses the transmitted signal to mix the echo signal and obtains the mixed signal through low-pass filtering, which can be written as:

[0086]

[0087] The mixed signal is sampled through quadrature sampling. Considering the DC bias introduced by the level inconsistency of the IQ sampling channel in the actual hardware system, the in-phase component I(t) and the quadrature component Q(t) of the baseband signal obtained by the IQ quadrature sampling channel are respectively:

[0088]

[0089]

[0090] DC I is the in-phase component of the baseband signal, DC Q is the DC component of the orthogonal component in the baseband signal, A I is the in-phase component of the baseband signal, A Q is the amplitude of the orthogonal component in the baseband signal, λ=c / f c Indicates the carrier wavelength.

[0091] Assume that the sampling frequency f of the Doppler radar system iss , the observation time length is T, then the discrete sampling signal of the IQ channel is obtained as,

[0092]

[0093]

[0094] Where n=1,…,N,N=f s T represents the number of signal sampling points.

[0095] Doppler radar extracts the breathing and heart rate characteristics by sensing the weak periodic distance changes of the chest wall of the human target. The distance d(n) can be expressed as:

[0096] d(n)=d0(n)+m h sin(2πf h n)+m r sin(2πf r n)

[0097] Where d0 is the nominal distance from the radar to the target, m h Represents the amplitude of the periodic displacement of the chest wall caused by the human target heart rate, m r represents the amplitude of the periodic displacement of the chest wall caused by human target breathing, f h Represents the frequency of the human target heart rate, f r Indicates the breathing frequency of a human target.

[0098] Step 3: Taking the complex data after mean filtering as the observation quantity, the second-order instantaneous moment method is used to obtain the demodulated vital sign signal waveform S(t);

[0099] Step 3.1, using the mean filtered signal as the observation, construct the complex signal C(n):

[0100]

[0101] Where j is an imaginary number. Since d0 is the nominal distance from the radar to the target, which is basically unchanged during the observation time, it can be regarded as a quantity independent of time. The above formula can be rewritten as:

[0102]

[0103] in

[0104] Step 3.2: Use the second-order instantaneous moment method to obtain the demodulated vital sign signal S(n):

[0105] The second-order instantaneous moment method is:

[0106]

[0107] Where Δ represents the digital signal sampling interval, C * (n-Δ) represents the conjugate of C(n-Δ), C(n-Δ) represents the signal after the complex signal C(n) is delayed by Δ, and Imag[.] represents taking the imaginary part of the complex signal.

[0108] When the delay Δ is taken When , the above formula satisfies sin(x)=x+O(x), where O(x) represents the high-order infinitesimal of x. The above formula can be approximately written as:

[0109]

[0110] Step 4: Pass the demodulated vital sign signal waveform through bandpass filters of [0.1, 0.6] Hz and [0.8, 2.5] Hz respectively to obtain the breathing and heartbeat time domain signals.

[0111] Step 4.1, use the window function method to design a 512-order linear phase FIR bandpass filter with passband ranges of [0.1, 0.6] Hz and [0.8, 2.5] Hz, respectively. Figure 4 and Figure 5 As shown in the figure, it can be seen that the passband has a relatively flat amplitude-frequency characteristic and a linear phase, and the stopband attenuation meets the actual needs;

[0112] Step 4.2: The demodulated vital sign signal waveform is passed through the above-mentioned [0.1, 0.6] Hz and [0.8, 2.5] Hz bandpass filters to obtain the respiratory and heartbeat time domain signals respectively.

[0113] Step 5: Perform Fourier transform processing on the extracted respiratory and heartbeat time domain waveforms to obtain the frequency spectra of the respiratory waveform and the heartbeat waveform respectively, and estimate the respiratory and heartbeat frequency parameters based on the threshold detection technology.

[0114] Step 5.1: Perform Fourier transform on the extracted time domain waveforms of breathing and heartbeat to obtain the frequency spectra of the heart rate waveform and breathing waveform, respectively. Figure 6 and Figure 7 As shown, it can be seen that there is an obvious peak at the target frequency;

[0115] Step 5.2: Estimate breathing and heart rate parameters based on threshold detection technology, according to Figure 6 and Figure 7 The spectrum shown in the figure selects the peak line spectrum as the estimated value of breathing and heart rate to complete the estimation of vital signs characteristics.

[0116] It is to be understood that the present invention is described by some embodiments, and it is known to those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the scope of protection of the present invention.

Claims

1. A Doppler radar vital sign feature extraction method based on second-order instantaneous moment, characterized in that: The vital sign features include respiratory rate features and heart rate features, and include the following steps: Step 1, obtaining the orthogonal sampled baseband signal received by the Doppler radar, the baseband signal being the in-phase component I(t) of the baseband signal and the orthogonal component Q(t) of the baseband signal obtained by mixing the target's echo of the radar transmission signal with the transmission signal; Step 2, performing mean filtering on the baseband signal to obtain a baseband signal with a DC component removed, including an in-phase component I′(t) after the DC is removed from the baseband signal and a quadrature component Q′(t) after the DC is removed from the baseband signal; Step 3: Taking the complex data after mean filtering as the observation quantity, the second-order instantaneous moment method is used to obtain the demodulated vital sign signal waveform S(t); Step 4: Pass the demodulated vital sign signal waveform through bandpass filters of [0.1, 0.6] Hz and [0.8, 2.5] Hz respectively to obtain breathing and heartbeat time domain signals; Step 5, performing Fourier transform processing on the extracted respiratory and heartbeat time domain waveforms to obtain the frequency spectra of the respiratory waveform and the heartbeat waveform respectively, and estimating the respiratory and heartbeat frequency parameters based on the threshold detection technology; The step 1 specifically comprises the following steps: Step 1.1, the Doppler radar transmitting antenna transmits a single-frequency continuous wave signal: x T (t)=A T cos(2πf c t) Among them, A T is the signal amplitude, f c is the carrier frequency, t is the time; When the electromagnetic wave irradiates the human target and returns to the receiving antenna, the echo signal reaching the receiving antenna is written as: x R (t)=σcos(2πf c (t-τ)) Where σ is the scattering coefficient of the target, τ = 2d(t) / c is the echo delay of the target, d(t) is the distance from the radar to the target, and c is the propagation speed of the electromagnetic wave; The Doppler radar hardware system uses the transmitted signal to mix the echo signal and obtains the mixed signal through low-pass filtering, which is written as: Step 1.2: The mixed signal is sampled by quadrature sampling. Considering the DC bias introduced by the level inconsistency of the IQ sampling channels in the actual hardware system, the in-phase component I(t) and the quadrature component Q(t) of the baseband signal obtained by the IQ quadrature sampling channels are respectively: DC I is the in-phase component of the baseband signal, DC Q is the DC component of the orthogonal component in the baseband signal, A I is the in-phase component of the baseband signal, A Q is the amplitude of the orthogonal component in the baseband signal, λ=c / f c Indicates the carrier wavelength; Set the sampling frequency f of the Doppler radar system s , the observation time length is T, then the discrete sampling signal of the IQ channel is Where n=1,…,N,N=f s T represents the number of signal sampling points; Step 1.3, Doppler radar extracts the breathing and heart rate characteristics by sensing the weak periodic distance changes of the chest wall of the human target. The distance d(n) is expressed as: d(n)=d0(n)+m h sin(2πf h n)+m r sin(2πf r n) Where d0 is the nominal distance from the radar to the target, m h Represents the amplitude of the periodic displacement of the chest wall caused by the human target heart rate, m r represents the amplitude of the periodic displacement of the chest wall caused by human target breathing, f h Represents the frequency of the human target heart rate, f r Indicates the breathing frequency of human target; The step 2 comprises the following steps: Step 2.1: Estimate the mean of the in-phase component and the orthogonal component of the baseband signal respectively and The estimated baseband signal mean processing block size is N, The estimated baseband signal mean value processing method is: Step 2.2: Use mean filtering to remove the DC components of the in-phase component and the orthogonal component of the baseband signal respectively: The mean filtering method is: Considering that the amplitude distortion caused by IQ channel inconsistency is usually small, it is assumed that after the mean filter processing, the signal amplitudes of the IQ channels are basically the same, and the above formula is rewritten as: Where A is the signal amplitude after mean filtering; The step 3 comprises the following steps: Step 3.1, using the mean filtered signal as the observation, construct the complex signal C(n): Where j is an imaginary number; since d0 is the nominal distance from the radar to the target, which is basically unchanged during the observation time, it is regarded as a quantity independent of time, and the above formula is rewritten as: in Step 3.2: Use the second-order instantaneous moment method to obtain the demodulated vital sign signal S(n): The second-order instantaneous moment method is: Where Δ represents the digital signal sampling interval, C * (n-Δ) represents the conjugate of C(n-Δ), C(n-Δ) represents the signal after the complex signal C(n) is delayed by Δ, and Imag[.] represents the imaginary part of the complex signal; When the delay Δ is taken When , the above equation satisfies sin(x)=x+Ο(x), where Ο(x) represents the high-order infinitesimal of x. The above equation can be approximately written as:

2. The Doppler radar vital sign feature extraction method based on second-order instantaneous moment according to claim 1 is characterized in that: The step 4 comprises the following steps: Step 4.1, design a linear phase FIR bandpass filter with passband ranges of [0.1, 0.6] Hz and [0.8, 2.5] Hz. The transfer function of the bandpass filter is: H(z)=b0+b1z -1 +…+b N from -N Among them, {b i }i=0,1,…,N represents the N-order FIR filter coefficient, Z represents the Z transform operator; Step 4.2: Pass the demodulated vital sign signal waveform through a [0.1, 0.6] Hz bandpass filter to obtain a respiratory time domain signal, and pass the demodulated vital sign signal waveform through a [0.8, 2.5] Hz bandpass filter to obtain a heartbeat time domain signal.

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