CN111045006A - Corner hidden target imaging method based on multi-imaging dictionary fusion - Google Patents

Corner hidden target imaging method based on multi-imaging dictionary fusion Download PDF

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CN111045006A
CN111045006A CN201911334844.9A CN201911334844A CN111045006A CN 111045006 A CN111045006 A CN 111045006A CN 201911334844 A CN201911334844 A CN 201911334844A CN 111045006 A CN111045006 A CN 111045006A
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wall
imaging
target
corner
radar
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CN111045006B (en
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郭世盛
李松林
崔国龙
罗皓蓝
师贞鹏
李虎泉
孔令讲
杨晓波
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University of Electronic Science and Technology of China
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/887—Radar or analogous systems specially adapted for specific applications for detection of concealed objects, e.g. contraband or weapons
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/418—Theoretical aspects

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Abstract

The invention discloses a corner hidden target imaging method based on multi-imaging dictionary fusion, which solves the problem of corner hidden target imaging positioning in an urban non-line-of-sight environment. The invention utilizes the characteristics of the MIMO radar to transmit electromagnetic wave signals to carry out corner hidden target imaging detection through diffraction and reflection propagation. Firstly, diffraction and primary reflection propagation characteristics under an L-shaped corner scene are analyzed; then, a diffraction and primary reflection virtual radar array is constructed based on electromagnetic propagation characteristics, time delays of different propagation paths of electromagnetic waves are calculated according to the virtual radar array, a corresponding imaging dictionary is established, and original imaging results which comprise real targets and false targets and correspond to the different propagation paths are obtained by utilizing a back projection imaging algorithm; and finally, multiplying and fusing all the original imaging results to obtain a radar image only containing a real target. The method has simple implementation process, can obtain high-quality and accurate radar target images, and can effectively solve the problem of imaging and positioning of multiple targets at corners.

Description

Corner hidden target imaging method based on multi-imaging dictionary fusion
Technical Field
The invention belongs to the technical field of ultra-wideband MIMO radar target imaging, and particularly relates to a corner hidden target imaging method based on multi-imaging dictionary fusion.
Background
Different from the traditional radar which utilizes the 'direct vision detection' of electromagnetic waves, in urban roadway operations, anti-terrorist operations and disaster rescue, the threatened target is usually hidden in the complex building environment, and because the electromagnetic waves are shielded by buildings, the electromagnetic waves cannot be transmitted to the threatened or rescue target along a straight line, and can only be detected in a 'non-direct vision' mode. Because a large number of electromagnetic wave reflection and diffraction propagation paths exist in the complex building environment, compared with electromagnetic transmission propagation, the multipath propagation electromagnetic energy attenuation is small, the available propagation paths are multiple, and various building shielding environments exist, so that the hidden target detection is facilitated. Therefore, multipath detection is the best way to realize the detection of the shielding target of the building in the complex urban environment.
Corner object detection is the most typical scenario in multipath detection. At present, a plurality of research institutions at home and abroad develop the theory and technical research related work of detecting the hidden target behind the corner by utilizing the electromagnetic wave multipath propagation. Under the condition of known building layout, the scholars of the American air force laboratory respectively propose two hidden target synthetic aperture radar imaging methods based on original time domain echoes and original beam forming images in the literature (Setler P, Negishi T, Devrroy N, actual. multipath extraction in non-los composite imaging radar [ J ]. IEEEjournal of Selected topocs in Signal Processing,2013,8(1):137-152.) aiming at the problems of failure of the traditional synthetic aperture radar imaging method under the non-direct-view environment and the like. The method only considers two typical electromagnetic wave multipath propagation scenes and omits the electromagnetic diffraction propagation, and meanwhile, the synthetic aperture radar has great limitation in urban operation environments due to the defects of large array aperture, difficulty in carrying, poor mobility flexibility and the like. In the literature (Rabaste O, Bosse J, Poulin D, et al, detection-localization Algorithms in the Around-the-corner radar project [ J ]. IEEE Transactions on Aerospace and Electronic Systems,2019.), the authors propose two methods for target detection and localization using electromagnetic wave multipath echoes, and compare the detection performance with the traditional matched filtering algorithm, but the target localization accuracy is not high due to the spatial ambiguity of the scene geometry. In a complex urban environment, radar echo signals often contain a large number of disordered multipath signals between a round-trip radar and a target, and it is relatively difficult to directly detect the target or sort out echo peak signals corresponding to different multipaths from the disordered echo signals, and meanwhile, the requirements of strong equipment portability, strong anti-interference capability, high positioning accuracy of a hidden target and the like in the urban operation environment are met, and the imaging detection of the hidden target behind a corner by using the ultra-wideband MIMO radar imaging technology has important application value.
Disclosure of Invention
In order to solve the problem of detecting the corner hidden target in the complex urban environment, the invention provides a corner hidden target imaging method based on multi-imaging dictionary fusion, which can accurately obtain a clear radar image of the hidden target behind the corner. The method is simple in calculation and high in practicability. Under the condition of knowing building layout and radar position information, firstly analyzing the propagation characteristics of electromagnetic wave diffraction and primary reflection in a non-line-of-sight region behind a corner, then constructing a virtual radar array related to diffraction and various primary reflections according to the electromagnetic propagation characteristics, then calculating the propagation delay of the diffracted and primary reflected electromagnetic waves according to the virtual radar array and establishing a corresponding imaging dictionary, obtaining an original radar image containing a real target and a false target by utilizing a back projection imaging algorithm, and finally multiplying and fusing all the original radar images to obtain a clear radar image only containing the real target.
The technical scheme of the invention is as follows:
a corner target imaging method based on multi-imaging dictionary fusion comprises the following steps:
step 1: detecting scene environment parameter setting;
a scene that a building channel is formed by Wall-1, Wall-2 and Wall-3 and is an L-shaped corner, wherein the Wall-2 and the Wall-3 form a right angle; wall-1 is a square Wall body in a right angle formed by Wall-2 and Wall-3; wherein the corner position of Wall-1 is marked as C ═ xc,yc]T(ii) a The ordinate of the Wall-2 surface is denoted yw2The abscissa of Wall-3 surface is denoted as xw2(ii) a Assuming that the building layout is known and the electromagnetic wave is specularly reflected at the wall surface; the target is located in the non-direct-view area of the channel of Wall-1 and Wall-3 and is marked as P ═ xp,yp]T(ii) a An ultra-wideband MIMO radar linear array with M transmitting antennas and N receiving antennas is positioned in a passage of Wall-1 and Wall-2 and the array is vertically arranged, and the central position of the radar is [ x ]r,yr]TThe m-th transmitting antenna and n-th receiving antenna of the radar are respectively represented as Tm＝[xr,ytm]TAnd Rn＝[xr,yrn]T(ii) a Due to the shielding of Wall-1, the radar antenna array is invisible to a target P, electromagnetic wave signals emitted by the antenna can only reach the target position through the diffraction of a Wall corner C and the mirror reflection of the surfaces of Wall-1 and Wall-2, and the reflection points are W respectively2、W3(ii) a High-order reflection paths with large electromagnetic wave attenuation are omitted, only diffraction paths and primary reflection paths occurring in Wall-1 and Wall-2 are considered, and the three propagation paths are named as follows:
Path-1：Tm→C→P→C→Rn；
Path-2：Tm→W2→P→W2→Rn；
Path-3：Tm→W3→P→W3→Rn。
wherein, TmDenotes a transmitting antenna, RnDenotes a receiving antenna;
step 2: defining diffraction and primary reflection distribution areas;
when the target position satisfies the following relationship, the diffraction Path Path-1 exists:
Figure BDA0002330672840000031
the primary reflection Path-2 exists when the target position satisfies the following relationship:
Figure BDA0002330672840000032
the primary reflection Path-3 exists when the target position satisfies the following relationship:
Figure BDA0002330672840000033
and step 3: preprocessing an echo signal;
performing MTI processing on the received echo signals s (t, k) of k periods; the step adopts a two-pulse cancellation technology to obtain a target echo signal sr,mpn(t, k), the two-pulse canceller structure is:
sr,mpn(t,k)＝s(t,k)-s(t,k-1) (4)
and 4, step 4: virtual array position acquisition
4.1, the electromagnetic wave signals are diffracted at the corner C, and the virtual array position corresponding to Path-1 is calculated as follows:
Figure BDA0002330672840000034
wherein lt、lrThe distances from the corner C to the transmitting antenna and the receiving antenna are respectively;
the virtual array positions corresponding to Path-2 and Path-3 obtained according to the symmetry relationship of the electromagnetic wave mirror reflection are respectively as follows:
Figure BDA0002330672840000041
Figure BDA0002330672840000042
4.2, respectively calculating the propagation delays of the three paths according to the virtual array position obtained in the step 4.1 as follows:
Figure BDA0002330672840000043
wherein c is the propagation speed of the electromagnetic wave in the air;
and 5: rear projection imaging
And (4) establishing a corresponding imaging dictionary based on the propagation delay of different electromagnetic wave paths obtained in the step (4). Firstly, an imaging area is divided into X multiplied by Y pixel points, namely, any pixel point P has:
Zp＝(xpi,ypi),i＝1,2,…,X,j＝1,2,…,Y. (9)
according to propagation delay tau of different paths'i,mpnI is 1,2,3, the pixel values of the whole image are calculated:
Figure BDA0002330672840000044
step 6: image fusion
And 5, obtaining original imaging results corresponding to three different imaging dictionaries, wherein the radar images not only contain real targets, but also contain a plurality of false targets. The real target positions in the imaging results corresponding to different paths are the same, and other false targets are different, so that the false targets are removed by adopting image multiplication fusion according to the characteristic.
6.1, in order to ensure that the contribution values of the imaging results of different paths to the same pixel point are consistent, firstly normalizing the original imaging result obtained in the step 5:
Figure BDA0002330672840000045
where abs (. cndot.) represents an absolute value, and max (. cndot.) represents a maximum value.
6.2, performing multiplicative fusion on all the original images normalized in the step 6.1:
Figure BDA0002330672840000046
wherein ⊙ represents the Hadamard product, to which end I is fusedP(Zp) The image contains only real objects.
The invention has the beneficial effects that:
the invention provides a corner hidden target imaging method based on multi-imaging dictionary fusion. According to the building layout and radar position information, the distribution ranges of three typical electromagnetic propagation paths in a non-direct-view area behind a corner, namely electromagnetic diffraction and primary reflection of different reflection points, are obtained firstly, a virtual radar array related to diffraction and primary reflection is constructed according to scene structure information, then the electromagnetic wave propagation time delay of the three propagation paths is calculated according to the virtual radar array, a corresponding imaging dictionary is established, an original radar image containing a real target and a false target is obtained by utilizing a back projection imaging algorithm, and finally, all the original radar images are subjected to multiplication fusion to obtain a radar image only containing the real target. The method has the advantages of simple implementation process, strong practicability, small calculation amount in the whole process from signal preprocessing to radar image acquisition, and high imaging and positioning accuracy of the hidden target behind the corner. The invention can also be applied to the fields of urban street fighting, anti-terrorism stability maintenance, disaster rescue and the like.
Drawings
Fig. 1 is an L-shaped electromagnetic wave propagation model in the embodiment.
FIG. 2 is a schematic diagram of a single-target electromagnetic simulation in an embodiment.
Fig. 3 is a schematic diagram of dual-target electromagnetic simulation in the specific embodiment.
FIG. 4 is an imaging model in an embodiment.
FIG. 5 shows the results of the original imaging in the preferred embodiment.
FIG. 6 shows the result of imaging a single target in an embodiment.
Fig. 7 shows the result of the dual target imaging in the embodiment.
Detailed Description
The following description of the present invention is given in conjunction with an electromagnetic simulation experiment:
step 1: detecting scene environment parameter setting;
the electromagnetic simulation adopts gprMax3.0 software, and simulation scene schematic diagrams are shown in fig. 2 and fig. 3, wherein fig. 2 is a single-target electromagnetic simulation schematic diagram, and fig. 3 is a dual-target electromagnetic simulation schematic diagram. In the experiment, the Wall corner O of Wall-2 is taken as the origin of coordinates, the position coordinates of the Wall corner of Wall-1 are (3m,2m), the ordinate of the outer surface of Wall-2 is taken as 1m, the abscissa of the outer surface of Wall-3 is taken as 9m, the dielectric constant of the Wall is 6, and the magnetic permeability is 0.05S/m; the simulation considers two conditions of a single target and multiple targets, firstly, the coordinate of the single target is (4m,5m), the positions of the multiple targets are (4m,5.7m) and (5.3m,7m), the dielectric constant of the target is 55, and the magnetic permeability is 1.05S/m; the simulation radar system adopts a two-transmitting four-receiving ultra-wideband radar, the aperture of an array is 0.6m, the array is vertically arranged, and the central coordinate is (1.5m,1.7 m); the radar transmitting signal is a step frequency continuous wave signal, the initial frequency is 1GHz, the cut-off frequency is 2GHz, and the signal bandwidth is 1 GHz.
Step 2: defining diffraction and primary reflection distribution areas;
and (3) obtaining distribution ranges corresponding to the three paths according to the simulation parameter setting in the step (1), and imaging the targets in the ranges.
And step 3: preprocessing an echo signal;
echo data of 100 periods are obtained in an electromagnetic simulation experiment, echo signals of all periods are subjected to two-pulse cancellation processing, and echo signals s after cancellation are obtainedr,mpn(t,k)。
And 4, step 4: virtual array position acquisition
4.1, according to the simulation parameter setting in the step 1, the virtual array positions corresponding to the Path-1, the Path-2 and the Path-3 can be obtained: the virtual array center coordinates corresponding to Path-1 are (1.82m,1.55m), the virtual array center coordinates corresponding to Path-2 are (1.5m,0.3m), and the virtual array center coordinates corresponding to Path-3 are (16.5m,1.7m), as shown in FIG. 4.
And 4.2, respectively calculating the propagation delay of three paths of eight channels according to the virtual array position obtained in the step 4.1.
And 5: rear projection imaging
And (4) establishing a corresponding imaging dictionary based on the propagation delay of different electromagnetic wave paths obtained in the step (4). The simulation imaging area is set to be 10m × 12m, the imaging area is divided into 417 × 434 pixel points, and an original imaging result is obtained by using a back projection imaging algorithm, and imaging results of Path-2 and Path-3 in the 15 th period are given as shown in fig. 5.
Step 6: image fusion
6.1, in order to ensure that the contribution values of the imaging results of different paths to the same pixel point are consistent, normalizing the original imaging result obtained in the step 5, and then performing image multiplication fusion to obtain a radar image only containing a real target. Fig. 6 and 7 show the original imaging result and the fusion result of different paths of the single target and the double target respectively.
Simulation experiments prove that the corner hidden target imaging method based on the fusion of the multiple imaging dictionaries is simple in implementation process and small in calculated amount, and the correctness and the practicability of the corner hidden target imaging method are verified.
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.

Claims (1)

1. A hidden corner target imaging method based on multi-imaging dictionary fusion comprises the following steps:
step 1: detecting scene environment parameter setting;
a scene that a building channel is formed by Wall-1, Wall-2 and Wall-3 and is an L-shaped corner, wherein the Wall-2 and the Wall-3 form a right angle; wall-1 is a square Wall body in a right angle formed by Wall-2 and Wall-3; wherein the corner position of Wall-1 is marked as C ═ xc,yc]T(ii) a The ordinate of the Wall-2 surface is denoted yw2The abscissa of Wall-3 surface is denoted as xw2(ii) a Assuming that the building layout is known and the electromagnetic wave is specularly reflected at the wall surface; the target is located in the non-direct-view area of the channel of Wall-1 and Wall-3 and is marked as P ═ xp,yp]T(ii) a An ultra-wideband MIMO radar linear array with M transmitting antennas and N receiving antennas is positioned in a passage of Wall-1 and Wall-2 and the array is vertically arranged, and the central position of the radar is [ x ]r,yr]TThe m-th transmitting antenna and n-th receiving antenna of the radar are respectively represented as Tm＝[xr,ytm]TAnd Rn＝[xr,yrn]T(ii) a Due to the shielding of Wall-1, the radar antenna array is invisible to a target P, electromagnetic wave signals emitted by the antenna can only reach the target position through the diffraction of a Wall corner C and the mirror reflection of the surfaces of Wall-1 and Wall-2, and the reflection points are W respectively2、W3(ii) a High-order reflection paths with large electromagnetic wave attenuation are omitted, only diffraction paths and primary reflection paths occurring in Wall-1 and Wall-2 are considered, and the three propagation paths are named as follows:
Path-1：Tm→C→P→C→Rn；
Path-2：Tm→W2→P→W2→Rn；
Path-3：Tm→W3→P→W3→Rn；
wherein, TmDenotes a transmitting antenna, RnDenotes a receiving antenna;
step 2: defining diffraction and primary reflection distribution areas;
when the target position satisfies the following relationship, the diffraction Path Path-1 exists:
Figure FDA0002330672830000011
the primary reflection Path-2 exists when the target position satisfies the following relationship:
Figure FDA0002330672830000021
the primary reflection Path-3 exists when the target position satisfies the following relationship:
Figure FDA0002330672830000022
and step 3: preprocessing an echo signal;
performing MTI processing on the received echo signals s (t, k) of k periods; the step adopts a two-pulse cancellation technology to obtain a target echo signal sr,mpn(t, k), the two-pulse canceller structure is:
sr,mpn(t,k)＝s(t,k)-s(t,k-1) (4)
and 4, step 4: virtual array position acquisition
4.1, the electromagnetic wave signals are diffracted at the corner C, and the virtual array position corresponding to Path-1 is calculated as follows:
Figure FDA0002330672830000023
wherein lt、lrThe distances from the corner C to the transmitting antenna and the receiving antenna are respectively;
the virtual array positions corresponding to Path-2 and Path-3 obtained according to the symmetry relationship of the electromagnetic wave mirror reflection are respectively as follows:
Figure FDA0002330672830000024
Figure FDA0002330672830000025
4.2, respectively calculating the propagation delays of the three paths according to the virtual array position obtained in the step 4.1 as follows:
Figure FDA0002330672830000031
wherein c is the propagation speed of the electromagnetic wave in the air;
and 5: rear projection imaging
Establishing a corresponding imaging dictionary based on the propagation delay of different electromagnetic wave paths obtained in the step 4, firstly dividing an imaging area into X multiplied by Y pixel points, namely, for any pixel point P:
Zp＝(xpi,ypi),i＝1,2,…,X,j＝1,2,…,Y. (9)
according to propagation delay tau of different paths'i,mpnI is 1,2,3, the pixel values of the whole image are calculated:
Figure FDA0002330672830000032
step 6: image fusion
Original imaging results corresponding to three different imaging dictionaries are obtained through the step 5, the radar images not only contain real targets, but also contain a plurality of false targets, the positions of the real targets in the imaging results corresponding to different paths are the same, and other false targets are different, so that the false targets are removed by adopting image multiplication fusion according to the characteristic;
6.1, in order to ensure that the contribution values of the imaging results of different paths to the same pixel point are consistent, firstly normalizing the original imaging result obtained in the step 5:
Figure FDA0002330672830000033
wherein abs (. cndot.) represents an absolute value, and max (. cndot.) represents a maximum value;
6.2, performing multiplicative fusion on all the original images normalized in the step 6.1:
Figure FDA0002330672830000034
wherein ⊙ represents the Hadamard product, to which end I is fusedP(Zp) The image contains only real objects.
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