CN112485792B - Three-dimensional enhanced imaging method for human body target - Google Patents
Three-dimensional enhanced imaging method for human body target Download PDFInfo
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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
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Abstract
The invention discloses a three-dimensional enhancement imaging method of a human body target, which comprises the steps of firstly enhancing the amplitude of a micro-motion physiological signal pixel by pixel; then, performing visualized enhancement of the inching physiological signals pixel by pixel; finally, obtaining forward reinforced image slices according to the amplitude enhancement and the visual enhancement of the oligodynamic physiological signals, and arranging all the forward reinforced image slices to form a three-dimensional image I 3D . According to the invention, a three-dimensional imaging method is adopted, so that mutually-aliased body parts in two-dimensional imaging are mutually distinguished in a three-dimensional space, and clutter and human body parts are better separated, so that the aliasing phenomenon in the two-dimensional imaging is obviously improved, the imaging quality is improved, and the technical problem that the aliasing part cannot be distinguished in the two-dimensional imaging in the prior art is solved.
Description
Technical Field
The invention belongs to the field of radar monitoring, relates to radar human body three-dimensional imaging, and in particular relates to a three-dimensional enhanced imaging method of a human body target.
Background
For a long time, the radar takes military targets such as airplanes, tanks and the like as observation objects, and the biological radar takes living bodies as observation objects, so that a new chapter of the radar in the application fields such as medicine, anti-terrorism, search and rescue and the like is opened. Electromagnetic waves emitted by the biological radar can detect body surface micro-motion caused by vital signs such as respiration, heartbeat and the like of a human body target, and detect and identify the vital body target based on the body surface micro-motion. The biological radar has the advantages of all weather, non-contact, positioning and the like, and has irreplaceable advantages in the fields of emergency rescue, anti-terrorism maintenance and the like.
The single-channel biological radar can only solve the detection of a single stationary human body target facing the sight direction of the radar or the rough identification of a plurality of moving human body targets, and the detection and positioning performance of the single stationary human body target is reduced when the targets deviate from the sight direction or a plurality of stationary human body targets exist in a scene. When the Multiple-Input Multiple-Output (MIMO) radar technology is applied to the field of life detection, the problem of detection performance degradation caused by single-channel detection can be overcome by utilizing the multi-view information of the MIMO radar technology, so that the detection performance of the biological radar is improved by a new step.
In the two-dimensional imaging, a target in a real three-dimensional space is projected to a two-dimensional imaging plane area, partial detail characteristics of the target area are lost in the projection process, shadow effect and space blurring occur, and for some complex scenes, aliasing of target information is caused, structures of all parts of the target information cannot be distinguished, and a clear image cannot be seen. If a three-dimensional image of the target scene can be acquired, adverse effects caused by the projection process can be eliminated, which brings certain benefits to the accurate positioning of the target, the subsequent processing of target identification, target state analysis and the like.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide a three-dimensional enhanced imaging method of a human body target, which solves the technical problem that the two-dimensional imaging of the human body target in the prior art cannot distinguish aliasing parts.
In order to solve the technical problems, the invention adopts the following technical scheme:
a three-dimensional enhanced imaging method of a human body target is carried out according to the following steps:
step one, a plurality of transmitting antennas of the MIMO biological radar sequentially radiate electromagnetic wave transmitting signals to space in a time-sharing mode, the transmitting signals are broadband frequency modulation continuous wave signals, the electromagnetic wave transmitting signals encounter object reflection, and a plurality of receiving antennas receive the reflected electromagnetic wave signals to form a multi-channel radar original echo signal s i ；
Wherein: i represents the serial number of the equivalent virtual receiving channel;
step two, for the radar original echo signal s of each channel i Respectively preprocessing to obtain a distance-slow time two-dimensional data matrixThe signals of the channels are arranged in sequence to form a three-dimensional data matrix of distance-slow time-multiple channels +.>
Step three, according to the three-dimensional data matrixAt a certain depth of field y 0 Obtaining a human body forward image by adopting a backward projection two-dimensional imaging algorithm, and forming a slow time sequence I of the MIMO forward image y0 (p,q,l)；
p is the transverse sampling sequence number of the forward image;
q is the height sampling sequence number of the forward image;
y 0 is a certain depth of field;
l is a slow time sampling sequence number;
the method is characterized in that:
step four, enhancing the amplitude of the inching physiological signal pixel by pixel;
the process for enhancing the amplitude of the inching physiological signal pixel by pixel comprises the following steps:
step 4.1, slow time series of MIMO forward images using equation (4-1)Processing to obtain amplitude enhanced image of physiological inching signal>
Wherein:
l is the number of slow time samples in the forward-backward image projection image sequence;
lambda is a relaxation factor controlling the enhancement degree of the inching signal;
step 4.2, slow time series for MIMO Forward imagesMTD processing is carried out on pixel points by pixel points to obtain Doppler spectrum +.>In Doppler spectrum->Finding out the maximum Doppler amplitude value corresponding to each pixel point>Obtaining maximum Doppler amplitude value image +.>
Step 4.3, mask multiplying the enhanced physiological micro-motion signal image obtained in step 4.1 and the maximum Doppler amplitude value image obtained in step 4.2Obtaining a pixel value of each pixel point;
step five, performing visualized enhancement of the inching physiological signals pixel by pixel;
the process for carrying out visualized enhancement on the micro-motion physiological signals pixel by pixel comprises the following steps:
step 5.1, according to the Doppler spectrum of each pixel point obtained in step 4.2Estimating a sampling value of a speed value corresponding to the maximum Doppler amplitude value on the horizontal axis by using a formula (5-1);
wherein:
k is a horizontal axis sampling variable;
an estimated value sampled on the horizontal axis;
obtaining depth of field y 0 Velocity estimation value corresponding to each pixel point on image slice
Step 5.2, mapping the colors according to the sampling value of the speed value of each pixel point on the horizontal axis, mapping the speed value of each pixel point into different colors, displaying the colors of the pixel points according to the mapped colors in the subsequent image display step, displaying the adjacent colors of the pixel points with similar speed values, and dividing different parts of a human body so as to obtain a visual enhanced image with better visual effect;
step six, obtaining forward enhancement image slices according to the amplitude enhancement of the physiological micro-motion signals in the step four and the visual enhancement of the physiological micro-motion signals in the step five, and arranging all the forward enhancement image slices to form an amplitude data matrix A of the three-dimensional image 3D And a color value matrix C 3D Data matrix A 3D Amplitude value screening is carried out, and then C is adopted 3D Displaying the color to finally obtain a three-dimensional image I 3D ；
Said forming a three-dimensional image I 3D The process of (1) comprises the following steps:
step 6.1, according to the depth of field y obtained in the fourth and fifth steps 0 Corresponding forward image slice, y 0 Taking different values to obtain different forward image slices, and uniformly arranging all the forward image slices along the depth of field from small to large to form an amplitude matrix A of the three-dimensional image 3D And a color value matrix C 3D ；
Wherein:
A 3D and C 3D Is a U, P, Q three-dimensional matrix;
u is the number of depth slices of the image;
p is the number of transverse sampling points of the three-dimensional image;
q is the number of sampling points in the height direction of the three-dimensional image;
A 3D ＝[a u,p,q ]，a u,p,q representing the depth of field of the ith image, the p-th transverse sampling and the amplitude value of the pixel point at the q-th height-to-sampling position;
C 3D ＝[c u,p,q ]，c u,p,q representing the depth of field of the ith image, the p-th lateral sampling, and the color value of the pixel point at the q-th height-to-sampling position;
step 6.2, pair A 3D Setting amplitude screening according to the pixel value;
for amplitude matrix A 3D The amplitude value of the pixel point is normalized, the logarithm of the normalized value is taken, the obtained amplitude value is compared with a set threshold value T, and when the amplitude value is smaller than the threshold value T, the amplitude value of the pixel point is set to be zero; when the amplitude value is larger than the threshold value T, the amplitude value of the pixel point is kept unchanged, and an uncolored three-dimensional image is obtained; step 6.3, coloring the three-dimensional image which is not colored in the step 6.2;
step 6.3, coloring the three-dimensional image which is not colored in the step 6.2;
using a colour matrix C 3D And (3) coloring the corresponding pixel points in the uncolored three-dimensional image in the step (6.2) by using the colors of the pixel points, and then marking the scattered points corresponding to all the pixel points in the colored three-dimensional image into a three-dimensional coordinate system to obtain a final three-dimensional image.
The invention also has the following technical characteristics:
specifically, in the second step, the pretreatment process includes the following steps:
step 2.1, for broadband frequency modulated continuous wave echo s i Performing declining treatment to obtain an original echo signal s of the real radar i ；
Step 2.2, for real radar original echo signalss i Low-pass filtering is carried out to obtain a radar echo signal s after filtering i For the filtered radar echo signal s i Performing FFT processing to obtain a radar one-dimensional range profile;
step 2.3, for the filtered radar echo signal s i Performing system correction to obtain a radar echo signal s after system correction i ；
The system correction is based on the closed loop measurement data of the system, the relative time delay difference between channels is estimated, the difference is recorded, and the filtered radar echo signal s is obtained i Eliminating the difference;
step 2.4, carrying out average cancellation (MTI) processing on the radar echo signals corrected by the system, and eliminating the background;
the average cancellation MTI processing method is shown as a formula (2-1),
wherein:
t is a fast time;
τ is the slow time;
τ 0 is the slow time starting moment;
τ 1 is the slow time end moment.
Specifically, in the third step, a slow time sequence of the MIMO image is obtainedIs characterized by comprising the following specific steps:
step 3.1, for a certain depth of field y 0 Dividing a forward imaging area into uniform grids along the azimuth direction and the height direction, wherein each grid comprises 1 pixel point (x, z);
step 3.2, traversing pixel points (x, z) on the uniform grid point by point, and obtaining amplitude values of the pixel points (x, z) by adopting a back image projection imaging formula (3-1):
wherein:
m is the serial number of the transmitting antenna;
n is the serial number of the receiving antenna;
m is the number of transmitting antennas;
n is the number of the receiving antennas;
t is fast time, t=2r/c;
r is the distance;
c is the speed of light;
delta (·) is dirichlet function;
x Tm 、y Tm and z Tm The azimuth, the distance and the height coordinates of the mth transmitting antenna;
x Rn 、y Rn and z Rn The azimuth, distance and altitude coordinates of the nth receiving antenna.
Compared with the prior art, the invention has the beneficial technical effects that:
according to the invention, a three-dimensional imaging method is adopted, so that mutually aliased body parts in two-dimensional imaging are mutually distinguished in a three-dimensional space, and clutter and body parts are better separated, so that the aliasing phenomenon in the two-dimensional imaging is obviously improved, the imaging quality is improved, and the technical problem that aliasing parts cannot be distinguished in the two-dimensional imaging in the prior art is solved.
And (II) the invention adds the micro Doppler feature of human motion, accumulates and enhances the micro signal energy, and improves the signal-to-noise ratio of three-dimensional imaging.
The invention adopts the estimated speed value of each component to encode the color, thus obtaining the color enhanced visual image, enhancing the image display of the human body component and facilitating the understanding and interpretation of the image.
Drawings
Fig. 1 is a block diagram of an information processing flow.
Fig. 2 is a schematic diagram of an antenna array configuration.
Fig. 3 is a simulated human actual measurement experimental scenario.
Fig. 4 is a schematic diagram of an echo range profile after preprocessing by a dummy.
Fig. 5 is a schematic diagram of the results of three-dimensional imaging of a simulated person.
Fig. 6 is a schematic diagram of a human target actual measurement scene.
Fig. 7 is a schematic diagram of a one-dimensional range profile of a human target.
Fig. 8 is a schematic diagram of a three-dimensional imaging result of a human body.
Fig. 9 is a velocity sample value corresponding to each pixel point of the forward image at an image depth of 4.5 m.
Fig. 10 is a schematic diagram of a result of enhanced visualization three-dimensional imaging of a human target.
The following examples illustrate the invention in further detail.
Detailed Description
The MIMO bioradar in the present invention is called Multiple-Input Multiple-Output, i.e., a MIMO bioradar.
The FMCW signal in the present invention is generally referred to as Frequency Modulated Continuous Wave, i.e., a wideband fm continuous wave signal.
It should be noted that, in the present invention, the Back Projection two-dimensional imaging algorithm, that is, the BP two-dimensional imaging algorithm, BP is called Back Projection. The backprojection two-dimensional imaging algorithm is an algorithm known in the art.
The MTD in the present invention is generally referred to as Moving Target Detection, i.e., moving object detection.
The FFT in the present invention is generally referred to as Fast Fourier transform and refers to the fast fourier transform.
In the present invention, MTI is generally referred to as Moving Target Indication and indicates a moving object instruction.
It should be noted that, in the three-dimensional matrix of the present invention, each pixel point corresponds to a scatter point,A 3D the amplitude of the middle pixel point controls the size of the scattered point, C 3D The color of the middle pixel point controls the coloring of each scatter point.
It should be noted that the process of obtaining the three-dimensional image in the present invention is mainly implemented in MATLAB, and the specific operation is that in MATLAB, the three-dimensional image is drawn by using a sciter 3 function, and the color matrix of the sciter 3 function is input into C 3D The number of the color bars displayed can be set by utilizing lines and color commands; and finally, displaying the corresponding relation between the speed value and the display color by the colorbar. Wherein, the amplitude value only displays the pixel point with the amplitude value in the range of-40 dB to 0 dB. Amplitude matrix A of pixel points 3D The size of the scattered points is controlled, and the larger the amplitude value is, the larger the displayed volume of the pixel points is.
Slow time: the MIMO radar completes one data transmission and acquisition in one period, then completes the next data transmission and acquisition in one period again, and the steps are repeated. In this process, the repeated periodic sequence is a slow time.
Fast timeWhere R represents the distance, i.e. distance-slow time-distance as described in the three-dimensional data matrix of the multi-channel.
y 0 : refers to image depth, referred to in the optical arts as depth of field.
Transverse direction: refers to a direction perpendicular to a plane formed by the radial direction and the height direction of the radar, and is generally parallel to the extending direction of the aperture of the radar antenna.
Height direction: refers to the direction perpendicular to the ground.
The radar receives the target reflection echo, which already contains three-dimensional information of the target scene area, however, when the radar receives the target scene echo information insufficiently, the three-dimensional reconstruction of the target scene is difficult to realize. The inversion can be achieved by acquiring scene information of the target from at least three dimensions. Thus, in addition to the time-distance dimension of the transmitted signal, three-dimensional imaging also requires a two-dimensional spatial spread of radar reception locations to acquire three-dimensional information of the target scene.
The radar system consists of a signal source, a transmitter, a switch array, an antenna array, a receiving channel, a real-time signal acquisition processing module, a display control module, a battery and the like. The signal source generates FMCW signals, and generates transmitting signals and couples a local oscillator signal after power amplification of the transmitter; the transmitting signals are transmitted from 8 transmitting antennas by the transmitting switch array in a time division manner, echo signals received by 8 receiving antennas are received by the receiving switch array in a time division manner, the echo signals are respectively sent to 4 receiving channels, and meanwhile, local oscillation signals are also fed to the receiving channels through the power divider; the receiving channel comprises a down-conversion circuit and an intermediate frequency signal conditioning circuit, and is used for filtering FMCW modulation waveforms, antenna coupling leakage and partial wall clutter by low-pass filtering, and then filtering high-frequency noise by a high-pass filter to improve the signal to noise ratio; 4 paths of intermediate frequency signals are fed into the real-time signal acquisition and processing module, and the embedded GPU completes the information processing flow.
The equivalent receiving channels are 64 in total, and the actual receiving channels are 4, and during the working period of each transmitting antenna, the receiving switch array is switched for 2 times, namely 16 times in total, so as to complete one-frame imaging.
Aiming at the technical problem of aliasing of target information in two-dimensional imaging, the invention adds the micro Doppler feature of human motion to accumulate and strengthen the energy of micro signals, and simultaneously uses the method of encoding the colors by using the estimated speed value of each part to obtain a color enhanced visual image, which can strengthen the image display of human parts, thereby obviously improving the aliasing phenomenon in two-dimensional imaging, distinguishing the mutually aliased human parts in the two-dimensional imaging from each other in three-dimensional space, and simultaneously better dividing clutter from human parts and improving imaging quality.
The invention provides a three-dimensional enhanced imaging method of a human body target, which comprises the following steps:
step one, a plurality of transmitting antennas of the MIMO biological radar sequentially radiate electromagnetic wave transmitting signals to space in a time-sharing mode, the transmitting signals are broadband frequency modulation continuous wave signals, the electromagnetic wave transmitting signals encounter object reflection, and a plurality of receiving antennas receive the reflected electromagnetic wave signals to form multi-channel radar original echo signalss i ；
Wherein:
i represents the serial number of the equivalent virtual receiving channel;
step two, for the radar original echo signal s of each channel i Respectively preprocessing to obtain a distance-slow time two-dimensional data matrixThe signals of the channels are arranged in sequence to form a three-dimensional data matrix of distance-slow time-multiple channels +.>
Step three, according to the three-dimensional data matrixAt a certain depth of field y 0 Obtaining a human body forward image by adopting a backward projection two-dimensional imaging algorithm, and forming a slow time sequence of MIMO forward images>
p is the transverse sampling sequence number of the forward image;
q is the height sampling sequence number of the forward image;
y 0 is a certain depth of field;
l is a slow time sampling sequence number;
step four, enhancing the amplitude of the inching physiological signal pixel by pixel;
the process of enhancing the amplitude of the inching physiological signal pixel by pixel comprises the following steps:
step 4.1, slow time series of MIMO forward images using equation (4-1)Processing to obtain amplitude enhanced image of physiological inching signal>
The motion and respiration of the body surface and the heartbeat micro-motion are the most obvious characteristics between the living body and static environment clutter; the variance of the micro-motion signals in the image slow time sequence is taken and accumulated, so that the physiological micro-motion signals of the human body can be effectively enhanced;
wherein:
l is the number of slow time samples in the forward-backward image projection image sequence;
lambda is a relaxation factor controlling the enhancement degree of the inching signal;
for each pixel point sequence, the variance solving process will retain and enhance the variable component, the static component is generally regarded as the mean value, and the operation of average reduction will be effectively inhibited;
in this embodiment, the slow time sampling number is the maximum value that can be taken in practical situations.
Step 4.2, slow time series for MIMO Forward imagesMTD processing is carried out on pixel points by pixel points to obtain Doppler spectrum +.>In Doppler spectrum->Finding out the maximum Doppler amplitude value corresponding to each pixel point>Obtaining maximum Doppler amplitude value image +.>
At a depth position of interest, each pixel corresponds to a slow time series; the human body part presents an approximate cosine signal along with slow time, fourier transformation is carried out on the sequence signal, so that a single-frequency micro Doppler spectrum signal is contained in a micro Doppler spectrum of the part, and a clutter micro Doppler spectrum does not have an obvious peak value; the component can be enhanced by taking the maximum value of the micro Doppler spectrum corresponding to each pixel point, and clutter is suppressed;
step 4.3, mask multiplying the enhanced physiological micro-motion signal image obtained in step 4.1 and the maximum Doppler amplitude value image obtained in step 4.2Obtaining a pixel value of each pixel point;
step five, performing visualized enhancement of the inching physiological signals pixel by pixel;
the process of performing visualized enhancement of the inching physiological signal pixel by pixel comprises the following steps:
step 5.1, according to the Doppler spectrum of each pixel point obtained in step 4.2Estimating a sampling value of a speed value corresponding to the maximum Doppler amplitude value on the horizontal axis by using a formula (5-1);
wherein:
k is a horizontal axis sampling variable;
an estimated value sampled on the horizontal axis;
obtaining depth of field y 0 Velocity estimation value corresponding to each pixel point on image slice
Step 5.2, mapping the colors according to the sampling value of the speed value of each pixel point on the horizontal axis, mapping the speed value of each pixel point into different colors, displaying the colors of the pixel points according to the mapped colors in the subsequent image display step, displaying the adjacent colors of the pixel points with similar speed values, and dividing different parts of a human body so as to obtain a visual enhanced image with better visual effect;
step six, obtaining forward enhancement image slices according to the amplitude enhancement of the physiological micro-motion signals in the step four and the visual enhancement of the physiological micro-motion signals in the step five, and arranging all the forward enhancement image slices to form an amplitude data matrix A of the three-dimensional image 3D And a color value matrix C 3D Data matrix A 3D Amplitude value screening is carried out, and then C is adopted 3D Displaying the color to finally obtain a three-dimensional image I 3D ；
Said forming a three-dimensional image I 3D The process of (1) comprises the following steps:
step 6.1, according to the depth of field y obtained in the fourth and fifth steps 0 Corresponding forward image slice, y 0 Taking different values to obtain different forward image slices, and uniformly arranging all the forward image slices along the depth of field from small to large to form an amplitude matrix A of the three-dimensional image 3D And a color value matrix C 3D ；
A 3D And C 3D Is a U, P, Q three-dimensional matrix;
u is the number of depth slices of the image;
p is the number of transverse sampling points of the three-dimensional image;
q is the number of sampling points in the height direction of the three-dimensional image;
A 3D ＝[a u,p,q ]，a u,p,q representing the depth of field of the ith image, the p-th transverse sampling and the amplitude value of the pixel point at the q-th height-to-sampling position;
C 3D ＝[c u,p,q ]，c u,p,q representing the depth of field of the ith image, the p-th lateral sampling, and the color value of the pixel point at the q-th height-to-sampling position;
step 6.2, pair A 3D Setting amplitude screening according to the pixel value;
for amplitude matrix A 3D The amplitude value of the pixel point is normalized, the logarithm of the normalized value is taken, the obtained amplitude value is compared with a set threshold value T, and when the amplitude value is smaller than the threshold value T, the amplitude value of the pixel point is set to be zero; when the amplitude value is larger than the threshold value T, the amplitude value of the pixel point is kept unchanged, and an uncolored three-dimensional image is obtained;
step 6.3, coloring the three-dimensional image which is not colored in the step 6.2;
using a colour matrix C 3D And (3) coloring the corresponding pixel points in the uncolored three-dimensional image in the step (6.2) by using the colors of the pixel points, and then marking the scattered points corresponding to all the pixel points in the colored three-dimensional image into a three-dimensional coordinate system to obtain a final three-dimensional image.
In the second step, the pretreatment process comprises the following steps:
step 2.1, for broadband frequency modulated continuous wave echo s i Performing declining treatment to obtain a real echo signal;
step 2.2, for the radar raw echo signal s i Performing low-pass filtering to obtain a filtered radar echo signal, and performing FFT processing on the filtered radar echo signal to obtain a radar one-dimensional range profile;
step 2.3, performing system correction on the filtered radar echo signals to obtain radar echo signals after system correction;
the system correction is based on system closed loop measurement data, the relative time delay difference between channels is estimated, the difference is recorded, and the difference is eliminated for the filtered radar echo signals;
step 2.4, carrying out average cancellation (MTI) processing on the radar echo signals corrected by the system, and eliminating the background;
the average cancellation MTI processing method is shown as a formula (2-1),
wherein:
t is a fast time;
τ is the slow time;
τ 0 is the slow time starting moment;
τ 1 is the slow time end moment.
In the third step, a slow time sequence of the MIMO forward image is obtainedIs characterized by comprising the following specific steps:
step 3.1, for a certain depth of field y 0 Dividing a forward imaging area into uniform grids along the azimuth direction and the height direction, wherein each grid comprises 1 pixel point (x, z);
step 3.2, traversing pixel points (x, z) on the uniform grid point by point, and obtaining amplitude values of the pixel points (x, z) by adopting a back image projection imaging formula (3-1):
wherein:
m is the serial number of the transmitting antenna;
n is the serial number of the receiving antenna;
m is the number of transmitting antennas;
n is the number of the receiving antennas;
t is fast time, t=2r/c;
r is the distance;
c is the speed of light;
delta (·) is dirichlet function;
x Tm 、y Tm and z Tm The azimuth, the distance and the height coordinates of the mth transmitting antenna;
x Rn 、y Rn and z Rn Is the nth jointAnd receiving the azimuth, the distance and the height coordinates of the antenna.
In this embodiment, the number of transmitting antennas and receiving antennas is generally 8, and the number of transmitting antennas and receiving antennas can be specifically adjusted according to practical situations.
The following gives specific practical examples of the present invention according to the above technical scheme, and it should be noted that the present invention is not limited to the specific practical examples, and all equivalent changes made on the basis of the technical scheme of the present application fall within the protection scope of the present invention.
Actual measurement example 1:
according to the technical scheme, the actual measurement example provides a three-dimensional enhanced imaging method of a human body target, the method is carried out by adopting the processes from the first step to the sixth step, and the method simulates the human body target in a normal breathing state by adopting a simulator. As shown in fig. 2, the MIMO radar array is composed of 8 transmitting units and 8 receiving units arranged in a mouth shape. The transmitted signal is a pulsed waveform of FMCW with a center frequency of 3 GHz. The center of the antenna array is set as the origin of the coordinate system. The dummy was located 5m from the longitudinal direction, 5m from the transverse direction and 0m from the height direction, and the breathing rate of the dummy was set to 1Hz. As shown in FIG. 3, a solid wall with the thickness of 0.3m is arranged between the antenna array and the detection target, and the antenna array is tightly attached to the wall.
The preprocessed echo range profile is shown in fig. 4. In the image, point-shaped reflection echoes simulating uniform changes of intensity of a person are visible at the position of 5m, and the point-shaped reflection echoes are simulated uniform respiration signals. It can be seen that the simulated oligodynamic vital sign signal is enhanced to some extent after pretreatment.
The three-dimensional imaging result is shown in fig. 5, the position of the imaging result is consistent with the measured value of the simulated person placing position, the error is about 0.25 meter, and the resolution in three directions is about 0.3 meter.
Actual measurement example 2:
according to the technical scheme, the actual measurement example provides a three-dimensional enhanced imaging method of a human body target, the method is carried out by adopting the processes from the first step to the sixth step, the scene is shown in fig. 6, the human body target is opposite to the radar antenna array in a free space, stands at a position 4 meters away from the radar in the radar sight line direction, and slightly shakes back and forth.
The preprocessed echo range profile is shown in fig. 7, and the human body target echo has a certain extension in the range direction. The result of monochromatic imaging of a human body target is shown in fig. 8, which is a display result drawn based on only an amplitude matrix, in which the outline of the human body can be roughly seen.
Obtaining a speed sampling value corresponding to each pixel point of the forward image at the position of 4.5m of image depth (namely scene depth) according to the sampling value of the speed value corresponding to the maximum Doppler amplitude value on the horizontal axis of Doppler spectrum estimation, as shown in figure 9; then color matrix input C of the scanner 3 function in MATLAB 3D The number of the color bars displayed can be set by utilizing lines and color commands; finally, the correspondence between the speed value and the display color is shown by colorbar, and the result is shown in fig. 10.
In the imaging result, the result of human body imaging is divided into a plurality of color areas, the visual effect of a human body target is better, and the application of subsequent further target identification, action classification and the like is facilitated.
Claims (3)
1. A three-dimensional enhanced imaging method of a human body target is carried out according to the following steps:
step one, a plurality of transmitting antennas of the MIMO biological radar sequentially radiate electromagnetic wave transmitting signals to space in a time-sharing mode, the transmitting signals are broadband frequency modulation continuous wave signals, the electromagnetic wave transmitting signals encounter object reflection, and a plurality of receiving antennas receive the reflected electromagnetic wave signals to form a multi-channel radar original echo signal s i ；
Wherein:
i represents the serial number of the equivalent virtual receiving channel;
step two, for the radar original echo signal s of each channel i Respectively preprocessing to obtain a distance-slow time two-dimensional data matrixThe signals of all channels are arranged in sequence to form a distance-slow timeThree-dimensional data matrix of m-multichannel->
Step three, according to the three-dimensional data matrixAt a certain depth of field y 0 Obtaining a human body forward image by adopting a backward projection two-dimensional imaging algorithm, and forming a slow time sequence of MIMO forward images>
p is the transverse sampling sequence number of the forward image;
q is the height sampling sequence number of the forward image;
y 0 is a certain depth of field;
l is a slow time sampling sequence number;
the method is characterized in that:
step four, enhancing the amplitude of the inching physiological signal pixel by pixel;
the process for enhancing the amplitude of the inching physiological signal pixel by pixel comprises the following steps:
step 4.1, slow time series of MIMO forward images using equation (4-1)Processing to obtain amplitude enhanced image of physiological inching signal>
Wherein:
l is the number of slow time samples in the forward-backward image projection image sequence;
lambda is a relaxation factor controlling the enhancement degree of the inching signal;
step 4.2, slow time series for MIMO Forward imagesMTD processing is carried out on pixel points by pixel points to obtain Doppler spectrum +.>In Doppler spectrum->Finding out the maximum Doppler amplitude value corresponding to each pixel point>Obtaining maximum Doppler amplitude value image +.>
Step 4.3, mask multiplying the enhanced physiological micro-motion signal image obtained in step 4.1 and the maximum Doppler amplitude value image obtained in step 4.2Obtaining a pixel value of each pixel point;
step five, performing visualized enhancement of the inching physiological signals pixel by pixel;
the process for carrying out visualized enhancement on the micro-motion physiological signals pixel by pixel comprises the following steps:
step 5.1, according to the Doppler spectrum of each pixel point obtained in step 4.2Estimating a sampling value of a speed value corresponding to the maximum Doppler amplitude value on the horizontal axis by using a formula (5-1);
wherein:
k is a horizontal axis sampling variable;
an estimated value sampled on the horizontal axis;
obtaining depth of field y 0 Velocity estimation value corresponding to each pixel point on image slice
Step 5.2, mapping the colors according to the sampling value of the speed value of each pixel point on the horizontal axis, mapping the speed value of each pixel point into different colors, displaying the colors of the pixel points according to the mapped colors in the subsequent image display step, displaying the adjacent colors of the pixel points with similar speed values, and dividing different parts of a human body so as to obtain a visual enhanced image with better visual effect;
step six, obtaining forward enhancement image slices according to the amplitude enhancement of the physiological micro-motion signals in the step four and the visual enhancement of the physiological micro-motion signals in the step five, and arranging all the forward enhancement image slices to form an amplitude data matrix A of the three-dimensional image 3D And a color value matrix C 3D Data matrix A 3D Amplitude value screening is carried out, and then C is adopted 3D Displaying the color to finally obtain a three-dimensional image I 3D ；
Said forming a three-dimensional image I 3D The process of (1) comprises the following steps:
step 6.1, according to the depth of field y obtained in the fourth and fifth steps 0 Corresponding forward image slice, y 0 Taking different values to obtain different forward image slices, and uniformly arranging all the forward image slices along the depth of field from small to large to form an amplitude matrix A of the three-dimensional image 3D And color valueMatrix C 3D ；
Wherein:
A 3D and C 3D Is a U, P, Q three-dimensional matrix;
u is the number of depth slices of the image;
p is the number of transverse sampling points of the three-dimensional image;
q is the number of sampling points in the height direction of the three-dimensional image;
A 3D ＝[a u,p,q ]，a u,p,q representing the depth of field of the ith image, the p-th transverse sampling and the amplitude value of the pixel point at the q-th height-to-sampling position;
C 3D ＝[c u,p,q ]，c u,p,q representing the depth of field of the ith image, the p-th lateral sampling, and the color value of the pixel point at the q-th height-to-sampling position;
step 6.2, pair A 3D Setting amplitude screening according to the pixel value;
for amplitude matrix A 3D The amplitude value of the pixel point is normalized, the logarithm of the normalized value is taken, the obtained amplitude value is compared with a set threshold value T, and when the amplitude value is smaller than the threshold value T, the amplitude value of the pixel point is set to be zero; when the amplitude value is larger than the threshold value T, the amplitude value of the pixel point is kept unchanged, and an uncolored three-dimensional image is obtained;
step 6.3, coloring the three-dimensional image which is not colored in the step 6.2;
using a colour matrix C 3D And (3) coloring the corresponding pixel points in the uncolored three-dimensional image in the step (6.2) by using the colors of the pixel points, and then marking the scattered points corresponding to all the pixel points in the colored three-dimensional image into a three-dimensional coordinate system to obtain a final three-dimensional image.
2. The method for three-dimensional enhanced imaging of a human target according to claim 1, wherein in the second step, the preprocessing process comprises the steps of:
step 2.1, for broadband frequency modulated continuous wave echo s i Performing declining treatment to obtain an original echo signal s of the real radar i ；
Step 2.2, for real radar original echo signal s i Low-pass filtering is carried out to obtain a radar echo signal s after filtering i For the filtered radar echo signal s i Performing FFT processing to obtain a radar one-dimensional range profile;
step 2.3, for the filtered radar echo signal s i Performing system correction to obtain a radar echo signal s after system correction i ；
The system correction is based on the closed loop measurement data of the system, the relative time delay difference between channels is estimated, the difference is recorded, and the filtered radar echo signal s is obtained i Eliminating the difference;
step 2.4, carrying out average cancellation (MTI) processing on the radar echo signals corrected by the system, and eliminating the background;
the average cancellation MTI processing method is shown as a formula (2-1),
wherein:
t is a fast time;
τ is the slow time;
τ 0 is the slow time starting moment;
τ 1 is the slow time end moment.
3. The method of three-dimensional enhancement imaging of a human body object according to claim 1, wherein in the third step, a slow time series of MIMO images is obtainedIs characterized by comprising the following specific steps:
step 3.1, for a certain depth of field y 0 Dividing a forward imaging area into uniform grids along the azimuth direction and the height direction, wherein each grid comprises 1 pixel point (x, z);
step 3.2, traversing pixel points (x, z) on the uniform grid point by point, and obtaining amplitude values of the pixel points (x, z) by adopting a back image projection imaging formula (3-1):
wherein:
m is the serial number of the transmitting antenna;
n is the serial number of the receiving antenna;
m is the number of transmitting antennas;
n is the number of the receiving antennas;
t is fast time, t=2r/c;
r is the distance;
c is the speed of light;
delta (·) is dirichlet function;
x Tm 、y Tm and z Tm The azimuth, the distance and the height coordinates of the mth transmitting antenna;
x Rn 、y Rn and z Rn The azimuth, distance and altitude coordinates of the nth receiving antenna.
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