FAST IMAGING METHOD SUITABLE FOR PASSIVE IMAGING AND ACTIVE IMAGING

Abstract

The present invention relates to the technical fields of optical imaging, microwave imaging, radar detection, sonar, ultrasonic imaging, and target detection, imaging identification and wireless communication based on media such as sound, light and electricity, and in particular, to a fast imaging method suitable for passive imaging and active imaging and application of the fast imaging method in the above fields. According to the method provided by the present invention, image field distribution corresponding to a target is achieved based on a lens imaging principle, in combination with an electromagnetic field theory, according to a target signal received by an antenna array, through the amplitude and phase weighting of a unit signal and by using an efficient parallel algorithm. The method provided by the present invention has the advantages of capability of being compatible with passive imaging and holographic imaging, good imaging effect, small operation amount, low hardware cost, high imaging speed and suitability for long-distance imaging, and can be widely applied in the fields of optical imaging, microwave imaging, radar detection, sonar, ultrasonic imaging, and target detection, imaging identification and wireless communication based on media such as sound, light and electricity.

Claims

1. A fast imaging method suitable for passive imaging and active imaging, wherein according to the method, image field distribution corresponding to a target is achieved based on a lens imaging principle, in combination with an electromagnetic field theory, according to a target signal received by an antenna array, through the amplitude and phase weighting of a unit signal and by using an efficient parallel algorithm, and the specific algorithm is as follows: ${\stackrel{.Math.}{E}}_q\left(\delta ,\sigma \right)={.Math.}_{m=1}^M{.Math.}_{n=1}^N\left({\stackrel{.Math.}{E}}_{mn}{A}_{mn}{e}^{j{\varphi }_{F_{mn}}}{e}^{j{\varphi }_{S_{\mathrm{mn}}}}\right)e^{\frac{j\eta \left(k\delta x_m+k\sigma y_n\right)}{V}};$ to wherein j is an imaginary unit, e is an Euler's constant, {right arrow over (E)}.sub.q(δ,σ) is image field distribution, {right arrow over (E)}.sub.mn is a target signal received by an array unit, A.sub.mn is an array unit amplitude weighting coefficient, ϕ.sub.F.sub.mn is a focusing phase weighting coefficient, ϕ.sub.S.sub.mn is a scanning phase weighting coefficient, M is the number of array units in an x direction, N is the number of array units in a y direction, (x.sub.m, y.sub.n) is the is coordinates of the array unit, (δ, σ) is the coordinates of an image point, V is an image distance, that is, a distance from an imaging plane to an array plane, η is an object selectivity parameter, different values are selected according to the characteristic of an imaging system, in and n are the serial number of the array units in the x direction and the y direction respectively, $k{=}_{\lambda }^{\underset{¯}{2\pi }}$ is a wave number, λ is a wave length and the symbol Σ denotes summation operation.

2. The method according to claim 1, wherein the method is suitable for different imaging systems by selecting different parameter r.sub.i values, specifically: when η=1 is selected, the method is suitable for passive imaging, semi-active imaging, conventional active imaging, phased array beam scanning imaging and phase array digital beam synthetic imaging systems; and when η=2 is selected, the method is suitable for active holographic imaging, synthetic aperture imaging and inverse synthetic aperture imaging systems.

3. The method according to claim 2, comprising the following steps: Step 1: performing amplitude weighting on an array unit signal to reduce a minor lobe level; Step 2: performing scanning phase weighting on the array unit signals to adjust a center view direction of an imaging system; Step 3: performing focusing phase weighting on the array unit signals to realize imaging focusing; Step 4: performing fast imaging processing on the array unit signals by an efficient parallel algorithm; and Step 5: calculating the coordinates of an image field and performing coordinate inversion on the image field to obtain the position of a real target.

4. The method according to claim 3, wherein in the step 1, the amplitude weighting method comprises uniform distribution, cosine weighting, Hamming window, Taylor distribution, Chebyshev distribution and mixed weighting methods.

5. The method according to claim 3, wherein in the step 2, the scanning phase weighting is adjusted into the center view direction of the imaging system, and the phase calculation formula of the scanning phase weighting is:
ϕ.sub.S(m, n)=ηmΔ.sub.ϕ.sub.x+ηnΔ.sub.ϕ.sub.y; wherein Δ.sub.ϕ.sub.x and Δ.sub.ϕ.sub.y are the phase differences between the adjacent array units in the x direction and the y direction respectively, and the calculation formulas are respectively as follows:
Δ.sub.ϕ.sub.x=kΔ.sub.x sin θ.sub.ζ,
Δ.sub.ϕ.sub.y=kΔ.sub.y sin θ.sub.ξ; wherein Δ.sub.x and Δ.sub.y are the distances between the array units in the x direction and the y direction respectively, the symbol sin denotes a sine function, θ.sub.ζ and θ.sub.ξ are the coordinates of scanning angles in the x direction and the y direction when the center view angle direction points to the source coordinates (ζ, ξ), and the calculation formulas are respectively as follows: ${\theta }_{\zeta }=-{\tan }^{-1}\left(\frac{\zeta }{U}\right),$ ${\theta }_{\xi }=-{\tan }^{-1}\left(\frac{\xi }{U}\right);$ wherein U is an object distance, that is, a distance from a plane where the target is located to an array plane, and the symbol tan.sup.−1 denotes an arctangent function.

6. The method according to claim 3, wherein the step 3 comprises: performing focusing phase weighting on the array unit signals by a focusing phase weighting method to realize imaging focusing, wherein the focusing phase calculation formula of automatic focusing phase weighting is: ${\varphi }_F=\frac{\eta k\left(x_m^2+y_n^2\right)}{2R};$ wherein R is a target slant distance, that is, a distance from the target to the array center; the focusing phase calculation formula of variable-focus or fixed-focus phase weighting is: ${\varphi }_F=\frac{\eta k\left(V-F\right)\left(x_m^2+y_n^2\right)}{2VF};$ wherein F is a focal distance, V is an image distance, that is, a distance from an imaging plane to a plane where a receiving plane is located, and F<U and F<V.

7. The method according to claim 3, wherein the step 4 comprises: performing fast imaging processing on the amplitude-phase-weighted array unit signals by the efficient parallel algorithm; and the efficient parallel algorithm comprises two-dimensional or three-dimensional FFT, IFFT, non-uniform FFT, sparse FFT, and the calculation formula is:
.sub.q(ω.sub.δ,ω.sub.σ)=(.Math.A.Math.e.sup.jϕF.Math.e.sup.jϕS); wherein the symbol denotes an efficient parallel algorithm function, is a target signal received by the array unit, A is an array unit amplitude weighting coefficient, ϕ.sub.F is a focusing phase weighting coefficient, and ϕ.sub.S is a scanning phase weighting coefficient; the value ranges of ω.sub.δ and ω.sub.σ corresponding to the image field calculation result are: ω.sub.δ∈[0,2π] and ω.sub.σ∈[0,2π], the value ranges of ω.sub.δ and ω.sub.σ after the fftshift operation are transformed into: ω.sub.δ∈[−π,π] and ω.sub.σ∈[−π, π], and at this time, to the image is an image according with the actual distribution:
.sub.q(ω.sub.δ,ω.sub.σ)=fftshift[.sub.q(ω.sub.δ,ω.sub.σ)].

8. The method according to claim 3, wherein the step 5 comprises: performing coordinate calculation on the image field obtained by the efficient parallel algorithm and performing coordinate inversion on the image field to obtain the is distribution situation of a real target, wherein for the IFFT type efficient parallel algorithm, the formula of calculating the coordinates of the scanning angle of the image field is: ${\theta }_{\delta }={\sin }^{-1}\left(\frac{{\omega }_{\delta }}{\eta k{\Delta }_x}\right),$ ${\theta }_{\sigma }={\sin }^{-1}\left(\frac{{\omega }_{\sigma }}{\eta k{\Delta }_y}\right);$ wherein the symbol sin.sup.−1 denotes an arcsine function; for the FFT type efficient parallel algorithm, the formula of calculating the coordinates of the scanning angle of the image field is: ${\theta }_{\delta }=-{\sin }^{-1}\left(\frac{{\omega }_{\delta }}{\eta k{\Delta }_x}\right),$ ${\theta }_{\sigma }=-{\sin }^{-1}\left(\frac{{\omega }_{\sigma }}{\eta k{\Delta }_y}\right);$ the rectangular coordinate calculation formula of the image is:
δ=V tan θ.sub.δ;
σ=V tan θ.sub.σ; wherein the symbol tan denotes a tangent function; the coordinate inversion calculation formula of the real target is: $\zeta =-\frac{U\delta }{V},$ $\xi =-\frac{U\sigma }{V}.$

9. The method according to claim 3, wherein the distances ${\Delta }_x\le \frac{\lambda }{2\eta }\mathrm{and}{\Delta }_y\le \frac{\lambda }{2\eta }$ among units of a transceiving antenna are set, so that the imaging aliasing phenomenon is avoided.

10. Application of the method according to claim 1 in the fields of optical imaging, microwave imaging, radar detection, sonar, ultrasonic imaging, and target detection, imaging identification and wireless communication based on sound, light and electricity.

11. A fast imaging method suitable for passive imaging and active imaging, wherein the fast imaging method is applied to long-distance imaging and comprises: selecting u=∞, then ϕ.sub.F=0, wherein the simplified formula suitable for long-distance imaging is:
.sub.q(ω.sub.δ,ω.sub.σ)=(Ae.sup.jϕS); and calculating the image by the efficient parallel algorithm as defined in claim 7, and obtaining the target distribution situation in a wide view range through one operation.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0088] For clearer description of the technical solutions of the embodiments of the present invention, the accompanying drawings required to describe the embodiments are briefly described hereinafter. Obviously, the accompanying drawings to be described below are merely some embodiments of the present invention, and a person of ordinary skill in the art may obtain other drawings according to these drawings without paying any creative effort.

[0089] FIG. 1 is a schematic diagram of an imaging system coordinate system of an imaging method according to the present invention.

[0090] FIG. 2 is an algorithm block diagram of an imaging method according to the present invention.

[0091] FIG. 3 is an imaging result diagram of a passive imaging case 1 performed by an imaging method according to the present invention.

[0092] FIG. 4 is an imaging result diagram of an active holographic imaging case 2 performed by an imaging method according to the present invention.

[0093] FIG. 5 is an imaging result diagram of a passive imaging case 3 performed by an imaging method according to the present invention.

[0094] FIG. 6 is an imaging result diagram of an active holographic imaging case 4 performed by an imaging method according to the present invention.

DETAILED DESCRIPTION OF EMBODIMENTS

[0095] To make the objectives, technical solutions and advantages of the present invention clearer, the following clearly and completely describes the technical solutions of the present invention with reference to the specific embodiments and the corresponding accompanying drawings. Obviously, the described embodiments are only some rather than all of the embodiments of the present invention. The present invention can be implemented or applied through other different specific implementation manners. Various modifications or changes can be made to various details in the specification based on different viewpoints and applications without departing from the spirit of the present invention.

[0096] Meanwhile, it should be understood that the protection scope of the present invention is not limited to the following specific embodiments; and it should also be understood that the terms used in the embodiments of the present invention are used for describing specific embodiments, rather than limiting the protection scope of the present invention.

[0097] Embodiment 1: a fast imaging method suitable for passive imaging and active imaging (referring to FIG. 1 to FIG. 2). According to the method, image field distribution corresponding to a target is achieved based on a lens imaging principle, in combination with an electromagnetic field theory, according to a target signal received by an antenna array, through the amplitude and phase weighting of a unit signal and by using an efficient parallel algorithm, and the specific algorithm is as follows:

[00028]${\stackrel{.Math.}{E}}_q\left(\delta ,\sigma \right)={.Math.}_{m=1}^M{.Math.}_{n=1}^N\left({\stackrel{.Math.}{E}}_{mn}{A}_{mn}{e}^{j{\varphi }_{F_{mn}}}{e}^{j{\varphi }_{S_{mn}}}\right)e\frac{j\eta \left(k\delta x_m+k\sigma y_n\right)}{V};$

[0098] where j is an imaginary unit, e is an Euler's constant, .sub.q(δ,σ) is image field distribution, .sub.mn is a target signal received by an array unit, A.sub.mn is an array unit amplitude weighting coefficient, ϕ.sub.F.sub.mn is a focusing phase weighting coefficient, ϕ.sub.S.sub.mn is a scanning phase weighting coefficient, M is the number of array units in x direction, Nis the number of array units in a y direction, (x.sub.m, y.sub.n) is the coordinates of the array unit, (δ, σ) is the coordinates of an image point, V is an image distance, that is, a distance from an imaging plane to an array plane, η is an object selectivity parameter, different values are selected according to the characteristic of an imaging system: when η=1, it is suitable for passive imaging, semi-active imaging, conventional active imaging, phase array beam scanning imaging and phase array digital beam synthetic imaging systems; when η=2, it is suitable for active holographic imaging, synthetic aperture imaging and inverse synthetic aperture imaging systems; m and n are the serial number of the array units in the x direction and the y direction respectively,

[00029]$k=\frac{2\pi }{\lambda }$

is a wave number, λ is a wave length, and the symbol Σ denotes summation operation.

[0099] Specifically, the fast imaging method provided by the present invention includes the following steps:

[0100] Step 1: performing amplitude weighting on array unit signal to reduce a minor lobe level,

[0101] where the amplitude weighting method includes uniform distribution, cosine weighting, Hamming window, Taylor distribution, Chebyshev distribution and mixed weighting methods.

[0102] Step 2: performing scanning phase weighting on the array unit signals to adjust a center view direction of an imaging system,

[0103] where the phase calculation formula of the scanning phase weighting is:

ϕ.sub.S(m,n)=ηmΔ.sub.ϕ.sub.x+ηnΔ.sub.ϕ.sub.y;

[0104] where Δ.sub.ϕ.sub.x and Δ.sub.ϕ.sub.y are the phase differences between the adjacent array units in the x direction and the y direction respectively, and the calculation formulas are respectively as follows:

Δ.sub.ϕ.sub.x=kΔ.sub.x sin ν.sub.ζ,

Δ.sub.ϕ.sub.y=kΔ.sub.y sin θ.sub.ξ,

[0105] where Δ.sub.x and Δ.sub.y are the distances between the array units in the x direction and the y direction respectively, the symbol sin denotes a sine function, θ.sub.ζ and θ.sub.ξ are the coordinates of scanning angles in the x direction and the y direction when the center view angle direction points to the source coordinates (ζ,ξ), and the calculation formulas are respectively as follows:

[00030]$$\begin{gathered} {\theta }_{\zeta }=-{\tan }^{-1}\left(\frac{\zeta }{U}\right), \\ {\theta }_{\xi }=-{\tan }^{-1}\left(\frac{\xi }{U}\right); \end{gathered}$$

[0106] where U is an object distance, that is, a distance from a plane where the target is located to an array plane, and the symbol tan.sup.−1 denotes an arctangent function.

[0107] Step 3: performing focusing phase weighting on the array unit to realize imaging focusing,

[0108] specifically including: performing focusing phase weighting on the array unit signal by a focusing phase weighting method to realize imaging focusing, where

[0109] the focusing phase calculation formula of automatic focusing phase weighting is:

[00031]${\varphi }_F=\frac{\eta k\left(x_m^2+y_n^2\right)}{2R};$

[0110] where R is a target slant distance, that is, a distance from the target to the array center;

[0111] the focusing phase calculation formula of variable-focus or fixed-focus phase weighting is:

[00032]${\varphi }_F=\frac{\eta k\left(V-F\right)\left(x_m^2+y_n^2\right)}{2VF};$

[0112] where F is a focal distance, V is an image distance, that is, a distance from an imaging plane to a plane where a receiving plane is located, and F<U and F<V.

[0113] Step 4: performing fast imaging processing on the array unit signals by an efficient parallel algorithm,

[0114] specifically including: fast imaging processing is performed on the amplitude-phase-weighted array unit signals by the efficient parallel algorithm, where the efficient parallel algorithm includes two-dimensional or three-dimensional FFT, IFFT, non-uniform FFT, sparse FFT, and the calculation formula is:

.sub.q(ω.sub.δ,ω.sub.σ)=(.Math.A.Math.e.sup.jϕF.Math.e.sup.jϕS).

[0115] where the symbol denotes an efficient parallel algorithm function, is a target signal received by the array unit, A is an array unit amplitude weighting coefficient, ϕ.sub.F is a focusing phase weighting coefficient, and ϕ.sub.S is a scanning phase weighting coefficient;

[0116] the value ranges of ω.sub.S and ω.sub.σ corresponding to the image field calculation result are: ω.sub.S∈[0,2π] and ω.sub.σ∈[0,2π], the value ranges of ω.sub.δ and ω.sub.σ after the fftshift operation are transformed into: ω.sub.δ∈[−π, π] and ω.sub.σ∈[−π, π], and at this time, the image is an image according with the actual distribution:

.sub.q(ω.sub.δ,ω.sub.σ)=fftshift[.sub.q(ω.sub.δ,ω.sub.σ)].

[0117] Step 5: calculating the coordinates of an image field and performing coordinate inversion on the image field to obtain the position of a real target,

[0118] specifically including: coordinate calculation is performed on the image field obtained by the efficient parallel algorithm and coordinate inversion is performed on the image field to obtain the distribution situation of a real target, where

[0119] for the IFFT type efficient parallel algorithm, the formula of calculating the coordinates of the scanning angle of the image field is:

[00033]${\theta }_{\delta }={\sin }^{-1}\left(\frac{{\omega }_{\delta }}{\eta k{\Delta }_x}\right),$${\theta }_{\sigma }={\sin }^{-1}\left(\frac{{\omega }_{\sigma }}{\eta k{\Delta }_y}\right);$

[0120] where the symbol sin.sup.−1 denotes an arcsine function;

[0121] for the FFT type efficient parallel algorithm, the formula of calculating the coordinates of the scanning angle of the image field is:

[00034]${\theta }_{\delta }=-{\sin }^{-1}\left(\frac{{\omega }_{\delta }}{\eta k{\Delta }_x}\right),$${\theta }_{\sigma }=-{\sin }^{-1}\left(\frac{{\omega }_{\sigma }}{\eta k{\Delta }_y}\right);$

[0122] the rectangular coordinate calculation formula of the image is

δ=V tan θ.sub.δ;

σ=V tan θ.sub.σ;

[0123] where the symbol tandenotes a tangent function;

[0124] the coordinate inversion calculation formula of the real target is:

[00035]$\zeta =-\frac{U\delta }{V},$$\xi =-\frac{U\sigma }{V}.$

[0125] In addition, in the method provided by the present invention, distances

[00036]${\Delta }_x\le \frac{\lambda }{2\eta }\mathrm{and}{\Delta }_y\le \frac{\lambda }{2\eta }$

among units of a transceiving antenna are set, so that the imaging aliasing phenomenon is avoided.

[0126] Embodiment 2: the method provided by the present invention (the method in the embodiment 1) is applied to effect verification test of passive imaging

[0127] Test conditions: the work frequency is 30 GHz, the distance between the antenna units is λ/2, the array scale is 32*32, one target is located in an array normal direction, the other target deviates from the normal direction by 30°, the distance from the target to the plane where the antenna array is located is 1 m, and the imaging result is shown in FIG. 3.

[0128] Embodiment 3: the method provided by the present invention (the method in the embodiment 1) is applied to effect verification test of active holographic imaging

[0129] Test conditions: the work frequency is 30 GHz, the distance between the antenna units is λ/4, the array scale is 66*66, one target is located in an array normal direction, the other target deviates from the normal direction by 30°, the distance from the target to the plane where the antenna array is located is 1 m, and the imaging result is shown in FIG. 4.

[0130] Embodiment 4: the method provided by the present invention (the method in the embodiment 1) is applied to effect verification test of passive imaging

[0131] Test conditions: the work frequency is 30 GHz, the distance between the antenna units is λ/2, the array scale is 32*32, the target deviates from the normal direction by 60°, the distance from the target to the plane where the antenna array is located is 1 m, the object distance parameter U is replaced with the slant distance R during phase matching, the minor lobe level is reduced by about 3.6 dB, and the imaging result is shown in FIG. 5.

[0132] Embodiment 5: the method provided by the present invention (the method in the embodiment 1) is applied to effect verification test of active holographic imaging

[0133] Test conditions: the work frequency is 30 GHz, the distance between the antenna units is λ/4, the array scale is 66*66, the target deviates from the normal direction by 60°, the distance from the target to the plane where the antenna array is located is 1 m, the object distance parameter U is replaced with the slant distance R during phase matching, the minor lobe level is reduced by about 7 dB, and the imaging result is shown in FIG. 6.

[0134] Embodiment 6: a fast imaging method suitable for passive imaging and active imaging. The method is applied to long-distance imaging and includes: U=∞ is selected, then ϕ.sub.F=0, and the simplified formula suitable for long-distance imaging is:

.sub.q(ω.sub.δ, ω.sub.σ)=F(Ae.sup.jϕS); and

[0135] the symbol F denotes an efficient parallel algorithm function, the image field is calculated by the efficient parallel algorithm, and the target distribution situation in the wide view range is obtained through one operation.

[0136] Each embodiment in the present invention is described in a progressive manner, each embodiment focuses on the difference from other embodiments, and the same and similar parts between the embodiments may refer to each other.

[0137] The above is only embodiments of the present invention, and is not intended to limit the present invention. Various changes and modifications may be made to the present invention by those skilled in the art. Any modifications, substitutions and the like made within the spirit and principle of the present invention should be included within the protection scope of the claims of the present invention.