CN110645886B

CN110645886B - Ground-based interference virtual aperture deformation monitoring radar system and working method

Info

Publication number: CN110645886B
Application number: CN201910942276.4A
Authority: CN
Inventors: 王韬; 张思麒; 何秀凤; 万其昌; 顾玲榛; 欧阳凯婷; 李聪
Original assignee: Chongqing University
Current assignee: Chongqing University
Priority date: 2019-09-30
Filing date: 2019-09-30
Publication date: 2021-05-04
Anticipated expiration: 2039-09-30
Also published as: CN110645886A

Abstract

The invention discloses a ground-based interference virtual aperture deformation monitoring radar system and a working method thereof. The radar subsystem radiates a broadband frequency modulation continuous wave signal of a millimeter wave frequency band to the inner wall of the tunnel by adopting uniform sparse linear arrays distributed on four sides of a rectangle and receives an echo signal to obtain initial radar echo data; after the first virtual aperture processing, namely MIMO processing, the aperture expansion is realized; performing a distance-to-fourier transform; then executing the second virtual aperture processing, namely prediction extrapolation processing, and further realizing aperture expansion; and obtaining a high-resolution three-dimensional radar complex image after two-dimensional digital beam forming, obtaining an interference pattern containing a differential phase from the main image and the auxiliary image, and obtaining the deformation condition of the inner wall of the tunnel after the interference pattern is subjected to unwrapping correction and transmitting the deformation condition to the data display subsystem.

Description

Ground-based interference virtual aperture deformation monitoring radar system and working method

Technical Field

The invention relates to the technical field of disaster prevention and reduction, in particular to a ground-based interference virtual aperture deformation monitoring radar system and a working method.

Background

At present, with the continuous development of economy and science and technology, the road traffic construction of China also enters a high-speed development stage. The construction of urban rail transit is also rapidly developed in the front of the world in the mileage of newly-built expressways and expressways. The tunnel is an engineering building buried in the ground, and occupies a great proportion in the total construction mileage of a highway, a high-speed railway and an urban subway. In the tunnel construction and operation process, tunnel collapse can be caused by rapid convergence of surrounding rocks or rapid abnormal deformation of rock and soil, safety accidents are caused, and great threat is formed to life and property safety of people. In order to research the triggering mechanism of tunnel deformation and realize rapid and accurate prediction, effective tunnel monitoring instruments and equipment are urgently needed. In order to effectively avoid damage caused by tunnel collapse, deformation of a tunnel wall needs to be monitored in real time, and various traditional monitoring methods are used in the field of tunnel monitoring, such as a convergence gauge, a level gauge, a distance meter, a total station and the like. Although the displacement of the tunnel monitoring point can be measured by the methods, a large amount of manpower, material resources and time are consumed, and automatic measurement cannot be realized.

In recent years, a series of new technologies and methods are proposed by a plurality of experts, scholars and engineers for monitoring tunnel deformation, and the main methods are as follows: (1) the optical fiber strain measurement method comprises the following steps: the optical fiber is adhered to the inner wall of the tunnel by using an adhesive, and displacement deformation quantity is calculated by using the relation between certain variable quantity and strain of light based on the reflection and interference principles of the light. The method can realize the integrated design of displacement measurement and communication, but has the problem of cross sensitivity of temperature and strain in actual use; in addition, the optical fiber is very fragile and easily damaged during construction. (2) MEMS sensor methods: according to the method, flexible cable type sensing equipment containing a micro-electromechanical system is installed on the wall of a tunnel, and deformation monitoring is carried out on the stratum around the tunnel. But as a contact type measuring means, the problems of complex installation and inconvenient movement exist. (3) Close-range photogrammetry methods: the method restores the two-dimensional digital image to the three-dimensional coordinate through the computer technology and the digital image processing technology, and compares the three-dimensional coordinate change at different moments to obtain the deformation condition of the structure. The method is low in cost, can quickly obtain deformation information and real-time pictures, but is low in measurement accuracy and easy to be influenced by environmental factors. (4) The three-dimensional laser scanning measurement method comprises the following steps: the method records information such as three-dimensional coordinates of a large number of dense points on the surface of a measured object by using a laser ranging principle. Its advantages are multi-point measurement, and obtaining point cloud data over million points to draw object outline. However, the three-dimensional laser scanner is expensive, and the cost of large-scale use in the tunnel is high; in addition, the laser is susceptible to ambient factors, and dust and light in the tunnel can reduce the measurement accuracy of the system and even fail completely.

On the basis of the monitoring and measuring method, a radar monitoring method is also provided, the radar monitoring method has the advantages of strong environmental factor interference resistance, all-weather working, high measuring precision, full-automatic non-contact and the like, and the radar used in the field of deformation monitoring mainly has two types: (1) the GROUND-based real aperture radar is represented by SSR (slope Stability radar) radar of GROUND PROBE corporation of Australia. (2) Ground-based synthetic aperture Radar is represented By IBIS (image By Interferometric survey) and Hydra-U (HYper Definition Radar-understring) radars of IDS corporation, Italy. The radar systems have the advantages of all weather, automation, high precision and non-contact, and are mainly applied to long-distance slope deformation monitoring. The radar systems are high in overall manufacturing cost, large and heavy in size, inconvenient to install and use, not portable and not suitable for narrow tunnel scenes.

Therefore, how to realize monitoring suitable for narrow tunnel scenes, and a radar monitoring system which is simple to install and small in size is a problem that needs to be solved urgently by those skilled in the art.

Disclosure of Invention

In view of the above, the invention provides a ground interference virtual aperture deformation monitoring radar system and a working method thereof. And a passive corner transmitter is arranged on the inner wall of the tunnel. The working method is that the radar subsystem adopts uniform sparse linear arrays distributed on four sides of a rectangle to radiate broadband frequency modulation continuous wave signals of a millimeter wave frequency band to the inner wall of a tunnel and receive echo signals to obtain initial radar echo data; after the first virtual aperture processing, namely MIMO processing, the aperture expansion is realized; performing a distance-to-fourier transform; or executing the second virtual aperture processing, namely prediction extrapolation processing, to further realize aperture expansion; and obtaining a three-dimensional radar complex image after phase compensation correction and digital beam forming processing, obtaining an interference pattern containing a differential phase from the main image and the auxiliary image, and obtaining the deformation condition of the inner wall of the tunnel after the interference pattern is subjected to unwrapping correction and is transmitted to a data display subsystem.

In order to achieve the purpose, the invention adopts the following technical scheme:

a ground-based interference virtual aperture deformation monitoring radar system comprises a tripod, a two-dimensional rotary table, a radar subsystem and a data display subsystem; the two-dimensional rotary table is arranged on the tripod, the radar subsystem is fixedly arranged on the two-dimensional rotary table, so that the radar subsystem can mechanically rotate along with the two-dimensional rotary table, and the radar subsystem is in wireless communication connection with the data display subsystem; the radar subsystem transmits radar signals to the inner wall of the tunnel, receives echo signals reflected by monitoring points of the inner wall of the tunnel, generates a three-dimensional radar complex image of the inner wall, and acquires deformation information of the inner wall.

Preferably, the radar subsystem comprises a signal generating unit, a control circuit, a plurality of power amplifiers, a transmitting array, a receiving array, a plurality of low noise amplifiers, a plurality of mixers, a plurality of intermediate frequency filters, a plurality of analog-to-digital converters, a signal processing circuit and a wireless transmission module; the transmitting array is connected with the power amplifier, the power amplifier is connected with the control circuit and the signal generating unit, and the control circuit is connected with the signal generating unit and the signal processing circuit; the receiving array is connected with the low-noise amplifier, the low-noise amplifier is connected with the mixer, the mixer is connected with the intermediate frequency filter, the intermediate frequency filter is connected with the analog-to-digital converter, and the analog-to-digital converter is connected with the signal processing circuit; the signal processing circuit is connected with the wireless transmission module; the signal generating unit is connected with the frequency mixer.

Preferably, the transmitting array includes a plurality of transmitting antenna elements, the number of the power amplifiers is several, and each transmitting antenna element is connected to one of the power amplifiers; the receiving array comprises a plurality of receiving antenna array elements, and each receiving antenna array element is connected with a signal mixing transmission circuit formed by one low-noise amplifier, the mixer, the intermediate frequency filter and the digital-to-analog converter.

Preferably, the transmitting array and the receiving array adopt a sparse linear array transceiving split rectangular array arrangement method, one transmitting array is respectively arranged on the left edge and the right edge of the sparse linear array, and one receiving array is respectively arranged on the upper edge and the lower edge of the sparse linear array; each transmitting antenna array element is formed by connecting a plurality of microstrip patches through parallel feeders, and the patches are transversely arranged at equal intervals; each receiving antenna array element is formed by connecting a plurality of microstrip patches through the parallel feeder line, and the patches are longitudinally arranged at equal intervals; and each transmitting antenna array element and each receiving antenna array element carry out amplitude weighting processing on the array formed by the microstrip patches by adopting an ultra-low side lobe technology.

Preferably, the ground-based interferometric virtual aperture radar system further comprises a passive corner reflector, wherein the passive corner reflector is installed on the inner wall of the tunnel and reflects the radar signal transmitted by the radar system.

Preferably, the method for determining the permutation parameters of the transmitting array and the transmitting antenna elements, the receiving array and the receiving antenna elements of the radar subsystem is as follows:

step 11: calculating the maximum value of the aperture of the sparse linear array under the far field condition according to the scene in the tunnel;

step 12: determining the beam pattern of the transmitting antenna array element and the receiving antenna array element according to the sparse linear array field angle; determining the number and amplitude weighting coefficient of the microstrip patches of each transmitting antenna array element and each receiving antenna array element in the sparse linear array, and obtaining an antenna array element directional diagram with ultralow sidelobe;

step 13: and gradually increasing the array element spacing of the sparse linear array from a half wavelength within the field angle until a grating lobe is positioned in a first minor lobe of the antenna array element directional diagram, thereby determining the array element spacing and the array element number of the sparse linear array.

A ground-based interference virtual aperture deformation monitoring radar system is characterized in that a signal generating unit of a radar subsystem generates a broadband frequency modulation continuous wave signal in a millimeter wave frequency band, and the broadband frequency modulation continuous wave signal reaches a transmitting antenna array element in a transmitting array through a power amplifier of a control circuit control switch; the control circuit controls the power amplifier to be turned on and off, and only one transmitting antenna array element in the transmitting array at each moment sends the broadband frequency modulation continuous wave signal; the receiving antenna array elements in the receiving array receive echo signals reflected by the inner wall of the tunnel or the passive corner reflector, transmit the echo signals to the low-noise amplifier, and transmit the echo signals to the signal processing circuit after passing through the frequency mixer, the intermediate frequency filter and the analog-to-digital converter, and the signal processing circuit processes the echo signals to obtain deformation information of the inner wall of the tunnel and transmits the deformation information to the data display subsystem through the wireless transmission module; all the receiving antenna elements in the receiving array receive the echo signals simultaneously; the control circuit controls the power amplifier, so that the radar subsystem works in a time division multiplexing mode, and the orthogonality of MIMO signals is guaranteed.

A working method of a ground-based interference virtual aperture deformation monitoring radar is characterized in that the step of processing the echo signal in the signal processing circuit is as follows:

step 21: storing the echo signals in a data cube form, and performing MIMO processing to obtain a first virtual aperture processing result so as to realize first aperture expansion; acquiring azimuth data, pitch data and time domain sampling data;

step 22: performing Fourier transform on the first virtual aperture processing result, converting the result into a frequency domain, and obtaining distance information corresponding to the sequence numbers of the frequency domain sampling points, so as to realize distance direction focusing and obtain distance direction data;

step 23: selecting a frequency domain sampling point sequence number corresponding to the minimum distance and the maximum distance from the inner wall to the radar subsystem, and combining the azimuth data, the elevation data and the data obtained in the step 22 to perform linear prediction extrapolation processing in the azimuth direction and the elevation direction, further realizing aperture expansion, and obtaining a second virtual aperture processing result, namely obtaining more virtual array element data, and expanding the array aperture for the second time;

step 24: using the two-dimensional digital beam forming processing to the first virtual aperture processing result obtained in the step 22 to realize the focusing in the azimuth direction and the elevation direction, so as to obtain the three-dimensional radar complex image with high resolution; or using the two-dimensional digital beam forming processing to the second virtual aperture processing result obtained in the step 23 to realize the focusing in the azimuth direction and the elevation direction, so as to obtain the three-dimensional radar complex image with higher resolution;

step 25: obtaining a radar phase interference image from the three-dimensional radar complex image; representing the three-dimensional radar complex image by adopting a spherical coordinate system, wherein each coordinate comprises a distance, an azimuth angle and a pitch angle, and combining the three-dimensional radar complex image acquired at different moments with a radar complex image at a reference moment to obtain a radar phase interference image;

step 26: phase unwrapping and atmospheric correction are carried out on the interference phase to obtain the actual interference phase

Step 27: according to the corresponding relation between the actual interference phase and the displacement delta r (r, theta, phi):

and obtaining deformation information of the monitoring points on the inner wall of the tunnel.

Preferably, in step 23, linear prediction is performed by using an autoregressive model, and a prediction filter and a prediction error filter are used to adjust the weight of the prediction filter according to the errors of the prediction filter and the prediction error filter; the processing procedure of the linear prediction extrapolation is as follows:

step 231: the virtual area array B is obtained in the step 21, and the number of the array elements is M₁×N₁Said step 22 obtaining a data matrix Y transformed to the frequency domain_BSaid Y is_BOf dimension M₁×N₁Said Y is_BThe (m, n) th element of (a) isy_B(m, n); the linear prediction adopts a two-dimensional linear prediction method, a two-dimensional matrix is Y, and the dimension is M₁×N₁The (m, n) th element of the Y is Y (m, n);

set (K)₁，K₂) Order linearity the prediction filter and the prediction error filter, the prediction error filter coefficient being a (k)₁，k₂)，0≤k₁≤K₁，0≤k₂≤K₂，a(0，0)＝1；

Step 232: converting the prediction error filter coefficients into vector form: a ═ a (0), a (1), …, a (K)₂)]Is a row vector in which the K-th element a (K) ═ a (0, K), a (1, K), …, a (K)₁，k)]Also a row vector;

step 233: m of the prediction error filter₁×N₁The two-dimensional observation data is y (m, n), the linear prediction error is e (m, n):

the linear prediction error output by the prediction error filter is represented in vector form:

e(m，n)＝az(m，n) (3)

wherein z (m, n) [ [ y (m, n) ], …, y (m-K) ]₁，n)，…，y(m，n-K₂)，…，y(m-K₁，n-K₂)]^TIs a column vector;

step 234: according to said M₁×N₁The least square solution of linear prediction is solved for the observation data by adopting a two-dimensional covariance method, and an overall mean square error function is constructed as follows:

wherein R is_zzIs ((K)₁+1)(K₂+1))×((K₁+1)(K₂+1)) size covariance matrix;

step 235: calculating the coefficient a (k) of the prediction error filter by using the formula (4)₁，k₂) And carrying out prediction extrapolation by adopting the prediction filter to obtain prediction data y (m, n), wherein the formula is as follows:

wherein M is more than or equal to 1 and less than or equal to M₁/2+M₂/2，1≤n≤N₁/2+N ₂2; forming an output matrix Y from the two-dimensional matrix Y and the prediction data_PSaid dimension being (M)₂/2)×(N₂/2) of the output matrix of y_p(m，n)＝y(m+M₁/2，n+N₁/2)，1≤m≤M₂/2，1≤n≤N₂/2；

Step 236: let y (m, n) be y_B(m, n); performing prediction extrapolation from the step 233 to the step 235 to obtain a prediction matrix Y_C1Comprises the following steps: y is_c1(m，n)＝y_p(m，n)；

Step 237: let y (m, n) be y_B(M₁+1-m, n), said predictive extrapolation is performed through said steps 233 to 235 to obtain said prediction matrix Y_C2Comprises the following steps: y is_c2(m，n)＝y_p(M₂+1-m，n)；

Step 238: let y (m, n) be y_B(M₁+1-m，N₁+1-n) of the prediction extrapolation, resulting in the prediction matrix Y, from said step 233 to said step 235_C3Comprises the following steps: y is_c3(m，n)＝y_p(M₂+1-m，N₂+1-n)；

Step 239: let y (m, n) be y_B(m，N₁+1-n) of the prediction extrapolation, resulting in the prediction matrix Y, from said step 233 to said step 235_C4Comprises the following steps: y is_c4(m，n)＝y_p(m，N₂+1-n)；

Step 2310: the virtual area array after the extrapolation is predicted is marked as C, the number of array elements is M₂×N₂The corresponding data matrix is Y_C，Y_CSaid dimension of is M₂×N₂。

Preferably, the specific implementation process of step 25 is as follows:

step 251: and adopting a spherical coordinate system for the three-dimensional radar complex image, wherein each coordinate value is represented by three values of distance, azimuth angle and pitch angle, and the coordinate value I (r, theta, phi) is as follows:

in the above formula

Expressing the distance from the origin of coordinates to the ith monitoring point, wherein L is the total monitoring fixed number; w is a_(m，n)(θ, φ) is a weight coefficient; c is the propagation velocity of the electromagnetic wave; f. of₀The initial frequency of the broadband frequency modulation continuous wave signal is obtained; t is the pulse width of the broadband frequency modulation continuous wave signal, B is the signal bandwidth, and alpha is B/T is the modulation frequency;

step 252: combining the three-dimensional radar complex images acquired at different moments with reference moment radar complex images initially acquired by the radar system, wherein the reference moment radar complex images are the first radar complex images acquired after the radar system is installed and are images when the radar system is not deformed, so as to obtain radar phase interference images, and the interference phase value of each pixel point in the radar phase interference images is

Where denotes the complex conjugate and ang (-) denotes the phase angle calculation.

Preferably, the receiving array receives the echo signal and transmits the echo signal to the low noise amplifier, the echo signal is amplified and transmitted to the mixer, and the echo signal is mixed with the broadband frequency modulation continuous wave signal generated by the signal generating unit in the mixer to obtain an intermediate frequency signal, wherein the intermediate frequency signal is related to the monitoring point distance of the passive corner reflector.

Preferably, the data display subsystem is a ruggedized tablet terminal.

According to the technical scheme, compared with the prior art, the ground interference virtual aperture deformation monitoring radar system comprises a passive corner reflector arranged on the inner wall of a tunnel and a radar system arranged in the tunnel, wherein the radar system comprises a tripod, a two-dimensional rotary table arranged on the tripod and a radar subsystem fixedly arranged on the two-dimensional rotary table, the radar subsystem can mechanically rotate along with the two-dimensional rotary table, so that the transmitted radar waves cover the monitoring range in the tunnel, a transmitting array used for transmitting broadband frequency modulation continuous wave signals and a receiving array used for receiving echo signals reflected by the passive corner reflector in the radar subsystem form a sparse linear array, a transmitting antenna array element and a receiving antenna array element are formed by microstrip patches through parallel feeders, and amplitude weighting processing is carried out by adopting an ultra-low minor lobe technology; and carrying out first virtual aperture processing, namely MIMO processing, distance-to-Fourier transformation, second virtual aperture processing, namely prediction extrapolation processing, digital beam forming and phase interference measurement processing on the received echo signals in a signal processing circuit of the radar system to obtain a three-dimensional radar complex image and a phase interference pattern of the inner wall of the tunnel, and obtaining displacement condition information of monitoring points provided with passive corner reflectors in the tunnel according to the phase interference pattern so as to judge whether the tunnel is deformed.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.

FIG. 1 is a schematic diagram of the overall structure of a ground-based interferometric virtual aperture radar system according to the present invention;

FIG. 2 is a block diagram of a radar subsystem according to the present invention;

FIG. 3 is a schematic diagram of a radar antenna array according to the present invention;

fig. 4 is a schematic diagram of a transmitting antenna array element structure provided by the present invention;

fig. 5 is a schematic diagram of a receiving antenna array element structure provided by the present invention;

fig. 6 is a diagram showing the coordinates of a physical antenna array element and a virtual area array element provided by the present invention;

FIG. 7 is a schematic diagram of a linear predictive extrapolation of virtual array elements according to the present invention;

FIG. 8 is a schematic illustration of the resolution of three-dimensional imaging provided by the present invention;

FIG. 9 is a schematic representation of a radar data cube process provided by the present invention;

FIG. 10 is a flow chart of the ground-based interferometric virtual aperture radar system according to the present invention.

1-tunnel, 11-passive corner reflector, 21-tripod, 22-two-dimensional turntable, 23-radar subsystem, 231-signal generation unit, 322-power amplifier, 233-transmitting array, 2331-transmitting antenna array element, 234-receiving array, 2341-receiving antenna array element, 235-low noise amplifier, 236-mixer, 237-intermediate frequency filter, 238-analog-to-digital converter, 239-control circuit, 2310-signal processing circuit, 2311-wireless transmission module and 24-data display subsystem.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The embodiment of the invention discloses a ground-based interference virtual aperture deformation monitoring radar system and a working method thereof, wherein the radar system comprises a tripod 21, a two-dimensional turntable 22, a radar subsystem 23 and a data display subsystem 24; the two-dimensional rotary table 22 is arranged on the tripod 21, the radar subsystem 23 is fixedly arranged on the two-dimensional rotary table 22, the radar subsystem 23 is mechanically rotated along with the two-dimensional rotary table 22, and the radar subsystem 23 is in wireless communication connection with the data display subsystem 24; the radar subsystem 23 transmits radar signals to the inner wall of the tunnel 1, receives echo signals reflected by monitoring points on the inner wall of the tunnel 1, generates a three-dimensional radar complex image of the inner wall, and acquires deformation information of the inner wall.

In order to further optimize the above technical solution, the radar subsystem 23 includes a signal generating unit 231, a control circuit 239, a plurality of power amplifiers 232, a transmitting array 233, a receiving array 234, a plurality of low noise amplifiers 235, a plurality of mixers 236, a plurality of intermediate frequency filters 237, a plurality of analog-to-digital converters 238, a signal processing circuit 2310, and a wireless transmission module 2311; the transmitting array 233 is connected with a power amplifier 232, the power amplifier 232 is connected with a control circuit 239 and a signal generating unit 231, and the control circuit 239 is connected with the signal generating unit 231 and a signal processing circuit 2310; the receiving array 234 is connected with a low noise amplifier 235, the low noise amplifier 235 is connected with a mixer 236, the mixer 236 is connected with an intermediate frequency filter 237, the intermediate frequency filter 237 is connected with an analog-to-digital converter 238, and the analog-to-digital converter 238 is connected with a signal processing circuit 2310; the signal processing circuit 2310 is connected with the wireless transmission module 2311; the signal generating unit 231 is connected to the mixer 236.

In order to further optimize the above technical solution, the transmit array 233 includes a plurality of transmit antenna elements 2331, a plurality of power amplifiers 232, and each transmit antenna element 2331 is connected to one power amplifier 232; the receiving array 234 includes a plurality of receiving antenna elements 2341, and each receiving antenna element 2341 is connected to a signal mixing transmission circuit formed by a low noise amplifier 235, a mixer 236, an intermediate frequency filter 237, and a digital-to-analog converter 238.

In order to further optimize the above technical solution, the transmitting array 233 and the receiving array 234 adopt a sparse linear array transceiving split rectangular array arrangement method, wherein one transmitting array 233 is respectively arranged on the left and right edges of the sparse linear array, and one receiving array 234 is respectively arranged on the upper and lower edges of the sparse linear array; each transmitting antenna array 2331 is formed by connecting a plurality of microstrip patches through parallel feeders, wherein the patches are transversely arranged at equal intervals; each receiving antenna array element 2341 is formed by connecting a plurality of microstrip patches through parallel feeders, and the patches are longitudinally arranged at equal intervals; each transmit antenna array 2331 and each receive antenna array 2341 employ ultra-low side lobe techniques to perform amplitude weighting on the array of microstrip patches.

In order to further optimize the technical scheme, the ground-based interference virtual aperture radar system further comprises a passive corner reflector 11, wherein the passive corner reflector 11 is installed on the inner wall of the tunnel 1 and reflects radar signals transmitted by the radar subsystem 23. The passive corner reflector 11 is used for enhancing the reflection echo, and the corner reflector can be arranged in a key area of the tunnel, so that the monitoring effect is improved.

In order to further optimize the above technical solution, the data display subsystem 24 is a ruggedized tablet terminal.

In order to further optimize the above technical solution, the method for determining the arrangement parameters of the transmitting array 233, the transmitting antenna array 2331, the receiving array 234 and the receiving antenna array 2341 of the radar subsystem 23 is as follows:

s11: calculating the maximum value of the sparse linear array under the far-field condition according to the scene in the tunnel 1;

s12: determining a beam pattern of a transmitting antenna array 2331 and a receiving antenna array 2341 according to the field angle of the sparse linear array; determining the number of microstrip patches and amplitude weighting coefficients of each transmitting antenna array element 2331 and each receiving antenna array element 2341 in the coefficient linear array, and obtaining an antenna array element directional diagram with ultralow sidelobes; the wave beam width of the antenna array element can determine the field angle range of the sparse linear array;

s13: and in the field angle, gradually increasing the array element spacing of the sparse linear array from half wavelength until the grating lobe is positioned in the first minor lobe of the antenna array element directional diagram, thereby determining the array element spacing and the array element number of the sparse linear array.

A ground-based interference virtual aperture deformation monitoring radar system and a working method thereof are disclosed, wherein a signal generating unit 231 of a radar subsystem 23 generates broadband frequency modulation continuous wave signals of a millimeter wave frequency band, and the signals reach a transmitting antenna array element 2331 in a transmitting array 233 through a power amplifier 232 of which the switch is controlled by a control circuit 239; the control circuit 239 controls the on and off of the power amplifier 232, so that only one transmitting antenna array 2331 in the transmitting array 233 at each moment transmits a broadband frequency modulated continuous wave signal; the receiving antenna array element 2341 in the receiving array 234 receives the echo signal reflected by the inner wall of the tunnel 1 or the passive corner reflector 11, transmits the echo signal to the low-noise amplifier 235, and transmits the echo signal to the signal processing circuit 2310 after passing through the mixer 236, the intermediate frequency filter 237 and the analog-to-digital converter 238, and the signal processing circuit 2310 processes the echo signal to obtain tunnel inner wall deformation information and transmits the information to the data display subsystem 24 through the wireless transmission module 2311; all receive antenna elements 2341 in the receive array 234 receive echo signals simultaneously; the control circuit 239 controls the power amplifier 232 to make the radar subsystem 23 work in a time division multiplexing mode, so as to ensure the orthogonality of the MIMO signals.

In order to further optimize the above technical solution, the steps of processing the echo signal in the signal processing circuit 2310 are as follows:

s21: storing echo signals in a data cube form, performing MIMO (multiple input multiple output) processing to obtain a first virtual aperture processing result, obtaining virtual array element data, realizing first aperture expansion, and obtaining azimuth data, elevation data and time domain sampling data;

s22: carrying out Fourier transform on time domain sampling data, converting the time domain sampling data into a frequency domain, and obtaining distance information corresponding to the sequence numbers of the frequency domain sampling points to realize distance focusing and obtain distance data;

s23: selecting a frequency domain sampling point sequence number corresponding to the minimum distance and the maximum distance from the inner wall to the radar subsystem 23, and performing linear prediction extrapolation processing on the azimuth data, the elevation data and the distance data in the S22 in the azimuth direction and the elevation direction by combining the azimuth data and the elevation data to obtain a second virtual aperture processing result, so as to obtain more virtual array element data and realize second aperture expansion;

performing linear prediction by using an autoregressive-based model, and adjusting the weight of a prediction filter by using the prediction filter and a prediction error filter according to errors of the prediction filter and the prediction error filter; the process of linear prediction extrapolation is as follows:

s231: s21 obtaining virtual area array B with M array elements₁×N₁S22 obtaining a data matrix Y transformed to the frequency domain_B，Y_BOf dimension M₁×N₁，Y_BThe (m, n) th element of (a) is y_B(m, n); the linear prediction adopts a two-dimensional linear prediction method, the two-dimensional matrix is Y, and the dimension is M₁×N₁The (m, n) th element of Y is Y (m, n);

set (K)₁，K₂) An order linear prediction filter and a prediction error filter with a coefficient of a (k)₁，k₂)，0≤k₁≤K₁，0≤k₂≤K₂，a(0，0)＝1；

S232: converting the prediction error filter coefficients into vector form: a ═ a (0), a (1), …, a (K)₂)]Is a row vector in which the K-th element a (K) ═ a (0, K), a (1, K), …, a (K)₁，k)]Also a row vector;

s233: m of prediction error filter₁×N₁The two-dimensional observation data is y (m, n), the linear prediction error is e (m, n):

e(m，n)＝az(m，n) (2)

wherein，z(m，n)＝[y(m，n)，…，y(m-K₁，n)，…，y(m，n-K₂)，…，y(m-K₁，n-K₂)]^TIs a column vector;

s234: according to M₁×N₁The least square solution of linear prediction is solved by adopting a two-dimensional covariance method to the observation data, and a total mean square error function is constructed as

s235: the coefficient a (k) of the prediction error filter is calculated by the formula (4)₁，k₂) And performing prediction extrapolation by adopting a prediction filter to obtain prediction data y (m, n), wherein the formula is as follows:

wherein M is more than or equal to 1 and less than or equal to M₁/2+M₂/2，1≤n≤N₁/2+N ₂2; forming an output matrix Y from the two-dimensional matrix Y and the prediction data_PDimension of (M)₂/2)×(N₂/2) the elements of the output matrix are y_p(m，n)＝y(m+M₁/2，n+N₁/2)，1≤m≤M₂/2，1≤n≤N₂/2；

S236: let y (m, n) be y_B(m, n); performing prediction extrapolation through S233 to S235 to obtain a prediction matrix Y_C1Comprises the following steps: y is_c1(m，n)＝y_p(m，n)；

S237: let y (m, n) be y_B(M₁+1-m, n), predictive extrapolation through S233 to S235 to obtain a prediction matrix Y_C2Comprises the following steps: y is_c2(m，n)＝y_p(M₂+1-m，n)；

S238: let y (m, n) be y_B(M₁+1-m，N₁+1-n) byS233 to S235 are subjected to prediction extrapolation to obtain a prediction matrix Y_C3Comprises the following steps: y is_c3(m，n)＝y_p(M₂+1-m，N₂+1-n)；

S239: let y (m, n) be y_B(m，N₁+1-n) to obtain a prediction matrix Y by predictive extrapolation from S233 to S235_C4Comprises the following steps: y is_c4(m，n)＝y_p(m，N₂+1-n)；

S2310: the virtual area array after the extrapolation is predicted is marked as C, the number of the array elements is M₂×N₂The corresponding data matrix is Y_C，Y_COf dimension M₂×N₂，

S24: using two-dimensional digital beam forming processing to the virtual array element data in S22 or S23 to realize azimuth and elevation focusing and obtain a high-resolution three-dimensional radar complex image;

s25: obtaining a radar phase interference image from the three-dimensional radar complex image, and obtaining an interference phase of the radar phase interference image; representing the three-dimensional radar complex images by adopting a spherical coordinate system, wherein each coordinate value comprises a distance, an azimuth angle and a pitch angle, and combining the three-dimensional radar complex images acquired at different moments with the radar complex images at reference moments to obtain radar phase interference images; the method comprises the following specific steps:

s251: adopting a spherical coordinate system for the three-dimensional radar complex image, wherein the coordinate value I (r, theta, phi) is as follows:

in the above formula

Representing the distance from the origin of coordinates to the ith monitoring point，w_(m，n)(θ, φ) is a weight coefficient; c is the propagation velocity of the electromagnetic wave, f₀The frequency modulation method comprises the following steps that (1) the initial frequency of a broadband frequency modulation continuous wave signal is shown, T is the pulse width of the broadband frequency modulation continuous wave signal, B is the signal bandwidth, and alpha is B/T is the modulation frequency;

s252: combining the three-dimensional radar complex images acquired at different moments with the radar complex image at the reference moment initially acquired by the radar system to obtain a radar phase interference image, wherein the value of each pixel point in the radar phase interference image, namely the interference phase, is

Wherein, indicates complex conjugate, and ang (cndot) indicates phase angle calculation;

s26: phase unwrapping and atmospheric correction are carried out on the interference phase to obtain the actual interference phase

S27: according to the corresponding relation between the actual interference phase and the displacement delta r (r, theta, phi):

and obtaining deformation information of monitoring points on the inner wall of the tunnel.

Examples

Fig. 1 is an overall configuration diagram of the system of the present invention. The system is composed of a tunnel 1 and a ground interference virtual aperture radar system 2; a plurality of passive corner reflectors 11 can be installed on the wall of the tunnel 1 in the monitoring area to serve as main monitoring points; the ground interference virtual aperture radar system 2 is composed of a tripod 21, a two-dimensional turntable 22, a radar subsystem 23 and a data display subsystem 24; the data display subsystem 24 includes a ruggedized tablet terminal. The radar subsystem 23 is placed on a two-dimensional turntable 22 fixed on a tripod 21, and the beam range of the radar subsystem 21 covers all the monitored areas in the tunnel 1 through mechanical rotation. The radar subsystem 21 transmits a broadband frequency modulation continuous wave signal of a millimeter wave frequency band to the tunnel 1 through the transmitting array 233, the inner wall of the tunnel 1 and the passive corner reflector 11 reflect the signal, and the receiving array 234 of the radar subsystem receives and processes the echo signal reflected by the inner wall of the tunnel 1 and the passive corner reflector 11 to obtain a radar complex image and a phase interference pattern. The deformation amount of the inner wall of the tunnel 1 is calculated through the phase information, data are transmitted to the data display subsystem 24 through the wireless transmission module 2311, technicians can check deformation data of monitoring points through a reinforced tablet computer terminal, and stability of a tunnel structure is analyzed.

Fig. 2 is a block diagram of a radar subsystem architecture of the present invention. The radar subsystem 23 is composed of a signal generation unit 231, a power amplifier 232, a transmitting array 233, a receiving array 234, a low noise amplifier 235, a mixer 236, an intermediate frequency filter 237, an analog-to-digital converter 238, a control circuit 239, a signal processing circuit 2311 and a wireless transmission module 2311; the transmit array 233 is comprised of a plurality of transmit antenna elements 2331, each consisting of a plurality of microstrip patches; the receive array 234 is formed from a plurality of receive antenna elements 2341, each of which is formed from a plurality of microstrip patches. The signal generating unit 231 is configured to generate a wideband frequency modulated continuous wave signal in a millimeter wave frequency band, and the wideband frequency modulated continuous wave signal generated by the signal generating unit 231 reaches the transmitting antenna array 2331 in the transmitting array 233 through the power amplifier 232 controlled by the control circuit 239.

The receiving antenna array element 2341 in the receiving array 234 receives the echo signal reflected by the inner wall of the tunnel 1, and the echo signal passes through the low noise amplifier 235, the mixer 236, the intermediate frequency filter 237 and the analog-to-digital converter 238 in sequence and then is sent to the signal processing circuit 2310. The signal processing circuit 2310 processes the obtained initial radar echo data, including first virtual aperture processing, namely MIMO processing, distance-to-fourier transform, second virtual aperture processing, namely prediction extrapolation processing, digital beam forming, phase interferometry and the like, to obtain a three-dimensional radar complex image and a phase interferogram of the inner wall of the tunnel. Wireless transmission module 2311 transmits the data to data display subsystem 24. The control circuit 239 controls the turning on and off of the power amplifier 232 during radar operation. Only one transmitting antenna array 2331 in the transmitting array 233 at each moment transmits a broadband frequency modulated continuous wave signal in a millimeter wave frequency band, and all receiving antenna array 2341 in the receiving array 234 receive echo signals at the same time, so that the radar subsystem 23 operates in a time division multiplexing mode.

The signal transmitted by the radar subsystem 23 is a broadband frequency-modulated continuous wave signal, which can be expressed by a mathematical formula:

wherein T ∈ (0, T); f. of₀Is the initial frequency; the alpha is B/T and is the frequency modulation, and is the ratio of the signal bandwidth B and the pulse width T; theta₀Is the initial phase.

The radar subsystem uses a transmitting antenna to irradiate a monitoring point, uses a receiving antenna to receive a reflected echo signal of the monitoring point, and assumes that the total receiving and transmitting time delay is tau, the signal received by the receiving antenna is as follows:

where τ is τ_T+τ_R＝(r_T+r_R) C; c is the electromagnetic wave propagation speed; r is_TIs the distance from the transmitting antenna to the target; r is_RThe distance between the target and the receiving antenna.

Mixing the echo signal with the transmitting signal in a mixer to obtain an intermediate frequency signal:

due to f₀> B, and T > τ, so the above formula can be rewritten as:

s₃(t)＝cos(2πατt+2πf₀τ) (12)

the above formula is rewritten as a complex representation:

s₄(t)＝exp(j2πατt)·exp(j2πf₀τ) (13)

fourier transform can be performed to obtain:

the frequency corresponding to the spectrum peak is: f. of_m＝ατ＝α(r_T+r_R) And/c, so that the frequency of the spectrum peak can determine the distance between the monitoring point and the transmitting antenna and the receiving antenna of the radar subsystem. The phase of the intermediate frequency signal is: theta 2 pi f₀Tau, calculating the displacement of the monitoring point according to the variation of the phase.

Fig. 3 is a schematic diagram of a radar antenna array structure according to the present invention. The invention adopts a sparse linear array transceiving split rectangular array arrangement method, namely 2 transmitting arrays 233 are respectively arranged on the left and right edges of a rectangle, and 2 receiving arrays 234 are respectively arranged on the upper and lower edges of the rectangle; or 2 receiving arrays 234 are respectively arranged on the left and right edges of the rectangle, 2 transmitting arrays 233 are respectively arranged on the upper and lower edges of the rectangle, and the transmitting arrays 233 and the receiving arrays 234 are all sparse uniform linear arrays.

FIG. 6 is a diagram showing the coordinate representation of the physical antenna array element and the virtual area array element, assuming the origin of coordinates as the reference point

Position coordinates of the m-th transmitting antenna element are expressed by

Indicating the position coordinates of the nth receiving antenna element by

The position coordinates of the equivalent virtual receiving array element (m, n) are expressed as follows:

the MIMO array of M sending and N receiving can be equivalent to the virtual array of 1 sending MN receiving, the equivalent virtual transmitting array element of the virtual array is positioned at the origin of coordinates, and the coordinates of the equivalent virtual receiving array element are the sum of the coordinates of a pair of transmitting antenna array elements and a pair of receiving antenna array elements.

The transmitting antenna array elements are connected by a plurality of microstrip patches through parallel feeders, the patches are transversely arranged at equal intervals, and the structure of each transmitting antenna array element is the same; the receiving antenna array elements are connected by a plurality of microstrip patches through parallel feeders, the patches are longitudinally arranged at equal intervals, and the structure of each receiving antenna array element is the same; the spacing between the adjacent microstrip patches is lambda/2, and lambda is the wavelength.

In the invention, the transmitting antenna array element and the receiving antenna array element adopt microstrip patch arrays, and the transmitting array and the receiving array adopt sparse linear arrays, so that the coupling and crosstalk among the antenna array elements can be effectively reduced, and the working performance of a radar system is improved.

The synthetic array pattern is the product of the antenna element (microstrip patch array) pattern and the sparse linear array pattern. Array element interval D of transmitting array in sparse linear array_xLambda/2 and array element spacing D of the receiving array_yAnd > lambda/2, the directional pattern of the sparse linear array can generate grating lobes. The antenna array element directional diagram is the directional diagram of the antenna array element of each unit. The synthetic array directional diagram is a directional diagram of an equivalent virtual area array, the larger the aperture of the synthetic array directional diagram is, the narrower the wave beam is, and in order to reduce the influence of grating lobes on the synthetic array directional diagram, the invention adopts the following solving method: the antenna array element adopts an ultra-low side lobe technology to carry out amplitude weighting processing on the microstrip patch array, for example, Chebyshev weight is adopted; the array element spacing of the sparse linear array and the patch number of the antenna array elements are changed, so that the grating lobes of the sparse linear array are positioned outside the field angle range and fall in the side lobes of the antenna array elements, and the interference to a radar system is reduced.

The array layout needs to follow the following rules:

(1) the number of the microstrip patches of the antenna array element is an integral power of 2, and the space between every two adjacent patches is lambda/2. The number of the patches determines the field angle of the radar antenna, and the larger the number is, the smaller the width of the main lobe of the antenna directional diagram is, and the smaller the field angle of the antenna is.

(2) Array element spacing D of sparse linear array_x＞λ/2，D_yThe larger the distance is, the more the number of grating lobes is. In order to ensure that the amplitude of the corresponding position of the grating lobe in the synthetic array directional diagram is as small as possible, the grating lobe needs to fall in the secondary lobe of the antenna array element directional diagram within the whole range of the field angle of the antenna.

(3) Due to the narrow tunnel space, the aperture of the physical antenna needs to meet the far field condition. The aperture of the physical antenna is determined by the array element spacing and the array element number of the sparse linear array, if the array element spacing is increased, the array element number is reduced, the grating lobe of the array is increased, and the array element spacing is more easily within the main lobe of an antenna array element directional diagram, so that larger interference is caused; if the array element spacing is reduced, the number of the array elements is increased, on one hand, more transmitting and receiving channels are needed, and on the other hand, the transceiving crosstalk is also increased.

In summary, the process of determining the array parameters is as follows: firstly, according to a tunnel scene, calculating the maximum value of the aperture of a physical antenna (namely a sparse linear array) under a far-field condition; then determining the field angle range of the required antenna array (namely, a sparse linear array), namely the beam width of an antenna array element, and determining the number of microstrip patches and the amplitude weighting coefficient of the antenna array element to obtain an antenna array element directional diagram; in the field angle of the antenna array, the array element spacing of the sparse linear array is gradually increased from lambda/2 until the grating lobe is positioned in the first minor lobe of the antenna array element directional diagram, so that the array element spacing, the array element number and the angular resolution of the sparse linear array are determined.

FIG. 7 is a schematic diagram of the linear prediction extrapolation of the virtual array element according to the present invention. A is an original physical antenna array (2 transmitting sparse linear arrays and 2 receiving sparse linear arrays), B is an equivalent virtual area array obtained after the original physical antenna array is subjected to first virtual aperture processing, namely MIMO processing, and C is an equivalent virtual area array obtained by the previously obtained equivalent virtual area array through second virtual aperture processing, namely prediction extrapolation, so that the number of virtual array elements and the antenna aperture are further expanded.

The invention provides a two-dimensional linear prediction extrapolation method for expanding a two-dimensional area array. The method is based on the linear prediction technology of the autoregressive model, and the weight of the prediction filter is calculated according to errors of the prediction filter and the prediction error filter, so that the virtual array element snapshot data can be predicted and estimated. Each array element in the spatially equidistant distribution may correspond to a respective delay node in the linear prediction filter, the time delay of each node corresponding to the spacing between two adjacent array elements in the spatial domain.

After the first virtual aperture processing, a virtual area array B is obtained, and the number of array elements is M₁×N₁The data matrix transformed to the frequency domain is denoted as Y_B，Y_BOf dimension M₁×N₁(ii) a Remember Y_BThe (m, n) th element of (a) is y_B(m, n). And expanding the virtual area array B to 4 directions (upper right, upper left, lower left and lower right) to obtain a second virtual aperture processing result. The process of the second virtual aperture processing is as follows:

step 1, determining a two-dimensional linear prediction method: suppose that the two-dimensional data matrix is Y and the dimension is M₁×N₁And the (m, n) -th element is y (m, n). Definition (K)₁，K₂) Order linear prediction filter and prediction error filter with filter coefficient a (k)₁，k₂)，0≤k₁≤K₁，0≤k₂≤K₂，a(0，0)＝1。

Write the prediction error filter coefficients in vector form: a ═ a (0), a (1), …, a (K)₂)]Is a row vector in which a (K) ═ a (0, K), a (1, K), …, a (K)₁，k)]Is a row vector.

Define the linear prediction error e (m, n):

written in vector form, the above equation becomes:

e(m，n)＝az(m，n) (17)

wherein: z (m, n) ═[y(m，n)，…，y(m-K₁，n)，…，y(m，n-K₂)，…，y(m-K₁，n-K₂)]^TIs a column vector.

The overall mean square error function is constructed as:

R_zzis ((K)₁+1)(K₂+1))×((K₁+1)(K₂+1)) size.

The coefficient a (k) of the prediction error filter can be calculated using equation (18)₁，k₂). Using a linear prediction filter, a predictive extrapolation is performed, with the formula:

wherein M is more than or equal to 1 and less than or equal to M₁/2+M₂/2，1≤n≤N₁/2+N₂/2. From the raw data and the prediction data, a new output matrix Y is constructed_PDimension of (M)₂/2)×(N₂/2). The elements of the matrix being y_p(m，n)＝y(m+M₁/2，n+N₁/2) where 1. ltoreq. m.ltoreq.M₂/2，1≤n≤N₂/2。

Step 2: let y (m, n) be y_B(m, n); predictive extrapolation using the method described in the first step, predicted matrix Y_C1Comprises the following steps: y is_c1(m，n)＝y_p(m，n)；

And step 3: y (m, n) ═ y_B(M₁+1-m, n); predictive extrapolation using the method described in the first step, predicted matrix Y_C2Comprises the following steps: y is_c2(m，n)＝y_p(M₂+1-m，n)；

And 4, step 4: y (m, n) ═ y_B(M₁+1-m，N₁+ 1-n); predictive extrapolation using the method described in the first step, predicted matrix y_C3Comprises the following steps: y is_c3(m，n)＝y_p(M₂+1-m，N₂+1-n)；

And 5: y (m, n) ═ y_B(m，N₁+ 1-n); predictive extrapolation using the method described in the first step, predicted matrix y_C4Comprises the following steps: y is_C4(m，n)＝y_p(m，N₂+1-n)；

Step 6: the linear prediction extrapolated virtual area array is marked as C, the number of array elements is M₂×N₂Corresponding to the data matrix as Y_C，Y_COf dimension M₂×N₂This can be obtained by the following formula:

FIG. 8 is a schematic diagram of the three-dimensional imaging resolution of the present invention. Assuming that the propagation velocity of electromagnetic wave is c, the initial frequency of the frequency modulated continuous wave signal is f₀Bandwidth B, wavelength λ c/f₀The distance resolution is δ R ═ c/2B. The radar range-direction resolution depends on the signal bandwidth, the wider the bandwidth is, the higher the resolution is, the invention adopts the broadband frequency modulation continuous wave signal, and the radar range-direction resolution can reach centimeter level. Suppose the true aperture of the antenna array is D_rx×D_ryThe minimum distance of the target in the far field is R_min＝max{2(D_rx)²/λ，2(D_ry)²Lambda, the antenna aperture after two times of virtual aperture expansion processing is D_vx×D_vyAzimuthal aperture expansion factor k_x＝D_vx/D_rxThe pitch-to-pitch aperture expansion multiple is k_y＝D_vy/D_ry(ii) a The corresponding azimuthal angular resolution is δ θ 0.886 λ/D_vx＝51°·λ/D_vxThe angular resolution in the pitch direction is δ φ 0.886 λ/D_vy＝51°·λ/D_vy。R₁Being a pitch resolution cell, R₂Being an azimuth-resolving unit, R₃Is a distance resolution element. It can be concluded that the radar angular resolution is related to the antenna aperture parameter, and the most direct way to increase the angular resolution is to increase the radar antenna size, but due to the radar volumeLarge physical aperture antennas cannot be installed due to constraints of physical factors such as weight. In the invention, the antenna aperture can be expanded to 3-4 times of the original physical size by adopting two times of virtual aperture processing, and the angular resolution of the azimuth direction and the elevation direction can reach 1-2 degrees.

FIG. 9 is a schematic representation of the radar data cube processing of the present invention. The radar data are stored in a data cube form, three dimensions of the data cube respectively correspond to azimuth data, pitch data and time domain sampling data, and the number of the data is the number of azimuth virtual receiving array elements, the number of pitch virtual receiving array elements and the number of time domain sampling points. Through MIMO processing, the radar increases the number of virtual receiving array elements in the azimuth direction and the pitching direction, and the first expansion of the aperture of the antenna array is realized.

The invention adopts broadband frequency modulation continuous waves, and the frequency of the intermediate frequency signals after radar transceiving and mixing is related to the distance. Therefore, for each time-domain sample data sequence, there is a correspondence between the result of the one-dimensional fourier transform and the distance, and radar data in the distance direction can be obtained.

Because the distance that the radar reachs the monitoring target region is in certain extent, can only use the data that correspond the distance within range to calculate, the minimum distance to the radar in the tunnel promptly and the maximum distance between, the focus to the data is realized to the frequency domain sampling point sequence number that corresponds, owing to only calculating to the limited sampling point number, so the operand in the follow-up signal processing process that has significantly reduced promotes system's real-time.

And performing linear prediction extrapolation on the azimuth data and the elevation data after the first antenna aperture expansion, and acquiring more virtual array element data through calculation. The virtual antenna array is expanded in four directions, the number of virtual receiving array elements in the azimuth direction and the elevation direction is increased, and the second expansion of the aperture of the antenna array is realized.

Through the virtual aperture processing technology, the aperture expansion is realized, the angular resolution of the radar is improved, the number of radar channels and the number of physical array elements are reduced, and the cost of the system is reduced.

FIG. 10 is a flow chart of the system operation of the present invention. First, it is necessary to install a passive corner reflector 11 in the tunnel 1, and arrange the ground-based interferometric virtual aperture radar system 2.

After the system is arranged, the radar subsystem 23 is started, and the signal generating unit 231 generates broadband frequency modulation continuous waves in a millimeter wave frequency band under the control of the control circuit 239; the control circuit 239 activates a power amplifier 232 at the same time, and makes the radar transmitting array 233 transmit signals in a time division multiplexing manner while boosting the signal transmitting power. The radar beam covers the monitoring area, and the receiving array 234 receives the echo signals at the same time, and the echo signals pass through the low noise amplifier 235, the mixer 236, the intermediate frequency filter 237 and the analog-to-digital converter 238 and then enter the signal processing circuit 2310.

The invention processes the radar original data, namely the original echo signal, as follows:

1) and storing radar original data in a data cube form and carrying out MIMO (multiple input multiple output) processing, wherein three dimensions of the data cube respectively correspond to azimuth data, pitch data and time domain sampling data, so as to obtain a first-time expanded array aperture.

2) And carrying out Fourier transform on each time domain sampling data sequence to obtain distance direction data. Data in a proper data range is selected for calculation according to the distance from the radar to the monitoring area, so that the data volume can be effectively reduced, and the signal processing speed is increased.

Or performing linear prediction extrapolation on the azimuth data and the elevation data again, and obtaining more virtual array element data through calculation to expand the virtual antenna array (namely the virtual area array) in four directions to obtain the second-time expanded antenna aperture.

3) After one or two times of virtual aperture processing is finished, radar imaging focusing is realized by using two-dimensional digital beam forming processing, and a three-dimensional radar complex image of a monitoring area by a radar is obtained;

the three-dimensional radar complex image adopts a spherical coordinate system, each coordinate is represented by three values of distance, azimuth angle and pitch angle, and the coordinate value I (r, theta, phi) is as follows:

in the above formula

Expressing the distance from the origin of coordinates to the ith monitoring point, wherein L is the total monitoring fixed number; w is a_(m，n)(θ, φ) is a weight coefficient; c is the propagation velocity of the electromagnetic wave; f. of₀The initial frequency of the broadband frequency modulation continuous wave signal is obtained; t is the pulse width of the broadband frequency modulation continuous wave signal, B is the signal bandwidth, and alpha is B/T is the modulation frequency.

4) Combining the radar complex images acquired at different moments with the radar complex image at the reference moment to obtain a radar phase interference image, wherein the interference phase value of each pixel point in the image

Comprises the following steps:

5) Recognizing the coordinate value of the monitoring point in the radar complex image, and acquiring the data of the monitoring point in the phase interference image, wherein the actual interference phase is obtained in the actual processing

Is composed of

In the range of [ - π, π]For the main value of the interval, it is necessary to perform phase unwrapping and atmospheric phase correction processing on the interference phase data to obtain the actual interference phase.

6) Finally, calculating the displacement of the monitoring point in the radar sight line direction:

thereby obtaining the deformation information of the monitoring points on the inner wall of the tunnel.

The traditional MIMO radar echo signals are:

in the above formula

For the time delay from the mth transmit antenna element to the lth monitoring point,

the time delay from the ith monitoring point to the nth receiving array element. To obtain a high-precision image of the target, the phase term of the signal needs to be compensated

In phase

There are distance and directional coupling problems associated with the transmit antenna elements, the receive antenna elements, and the target location. The traditional radar adopts a Back Projection (BP) imaging algorithm, an imaging area is divided into a series of pixel points, a time delay phase item from each pixel point to different combinations of transmitting array elements and receiving array elements is solved, after compensation, coherent superposition can be carried out to obtain focused imaging of the pixel points, and all the pixel points are traversed circularly to complete imaging. This serial processing approach results in inefficient operation.

In the invention, the physical size of the antenna array is very small by adopting virtual aperture processing, so that a monitoring point is in a far field range, and electromagnetic waves reaching the antenna are regarded as plane waves, wherein the virtual aperture processing can be carried out once or twice, and the formula (24) is changed into:

in the above formula k_lIs a wave number and satisfies k_l＝2π/λ[sin(θ_l)cos(φ_l)，sin(θ_l)sin(φ_l)]Item 1 in the above formula reflects the distance between the monitoring point and the origin of coordinates of the antenna array; item 2 reflects the echo phase of the monitoring point, which is used for displacement measurement; item 3 is related to the incoming wave direction of the monitoring point, the array element coordinates of the transmitting antenna and the array element coordinates of the receiving antenna, and is the same as the virtual area array guide vector obtained through virtual aperture processing. Because the coupling problem of distance and direction is solved, the delay adding process in the traditional BP algorithm is converted into the digital beam scanning process in the two-dimensional digital beam forming processing, and the operation amount of the algorithm is greatly simplified.

The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A ground-based interference virtual aperture deformation monitoring radar system is characterized by comprising a tripod (21), a two-dimensional rotary table (22), a radar subsystem (23) and a data display subsystem (24); the two-dimensional rotary table (22) is arranged on the tripod (21), the radar subsystem (23) is fixedly arranged on the two-dimensional rotary table (22) to realize that the radar subsystem (23) mechanically rotates along with the two-dimensional rotary table (22), and the radar subsystem (23) is in wireless communication connection with the data display subsystem (24); the radar subsystem transmits radar signals to the inner wall of the tunnel (1), receives echo signals reflected by monitoring points on the inner wall of the tunnel (1), generates a three-dimensional radar complex image of the inner wall and acquires deformation information of the inner wall;

the radar subsystem (23) comprises a signal generating unit (231), a control circuit (239), a plurality of power amplifiers (232), a transmitting array (233), a receiving array (234), a plurality of low noise amplifiers (235), a plurality of mixers (236), a plurality of intermediate frequency filters (237), a plurality of analog-to-digital converters (238), a signal processing circuit (2310) and a wireless transmission module (2311); the transmitting array (233) is connected with the power amplifier (232), the power amplifier (232) is connected with the control circuit (239) and the signal generating unit (231), and the control circuit (239) is connected with the signal generating unit (231) and the signal processing circuit (2310); the receiving array (234) is connected to the low noise amplifier (235), the low noise amplifier (235) is connected to the mixer (236), the mixer (236) is connected to the intermediate frequency filter (237), the intermediate frequency filter (237) is connected to the analog-to-digital converter (238), and the analog-to-digital converter (238) is connected to the signal processing circuit (2310); the signal processing circuit (2310) is connected with the wireless transmission module (2311); the signal generation unit (231) is connected with the mixer (236).

2. The ground-based interference virtual aperture deformation monitoring radar system as claimed in claim 1, characterized in that said transmitting array (233) comprises a plurality of transmitting antenna elements (2331), said power amplifiers (232) are provided, each of said transmitting antenna elements (2331) is connected to one of said power amplifiers (232); the receiving array (234) comprises a plurality of receiving antenna elements (2341), and each receiving antenna element (2341) is connected with a signal mixing transmission circuit formed by the low noise amplifier (235), the mixer (236), the intermediate frequency filter (237) and the analog-to-digital converter (238).

3. The ground-based interference virtual aperture deformation monitoring radar system according to claim 2, wherein the transmitting array (233) and the receiving array (234) adopt a sparse linear array transceiving rectangular arrangement method, one transmitting array (233) is respectively arranged on the left and right edges of the sparse linear array, and one receiving array (234) is respectively arranged on the upper and lower edges of the sparse linear array; each transmitting antenna array element (2331) is formed by connecting a plurality of microstrip patches through parallel feeders, and the patches are transversely arranged at equal intervals; each receiving antenna array element (2341) is formed by connecting a plurality of microstrip patches through the parallel feeder line, and the patches are longitudinally arranged at equal intervals; and each transmitting antenna array element (2331) and each receiving antenna array element (2341) adopt an ultra-low side lobe technology to carry out amplitude weighting processing on the array formed by the microstrip patches.

4. The ground-based interferometric virtual aperture deformation monitoring radar system according to claim 1, characterized in that it further comprises a passive corner reflector (11), said passive corner reflector (11) being mounted on the inner wall of the tunnel (1) and reflecting the radar signal emitted by the radar subsystem (23).

5. The ground-based interference virtual aperture deformation monitoring radar system according to claim 3, characterized in that the arrangement parameters of the transmitting array (233) and the transmitting antenna array elements (2331), the receiving array (234) and the receiving antenna array elements (2341) of the radar subsystem (23) are determined as follows:

step 11: calculating the maximum value of the aperture of the sparse linear array under the far field condition according to the scene in the tunnel (1);

step 12: determining the beam pattern of the transmitting antenna array element (2331) and the receiving antenna array element (2341) according to the sparse linear array field angle; determining the number and amplitude weighting coefficient of the microstrip patches of each transmitting antenna array element (2331) and each receiving antenna array element (2341) in the sparse linear array, and obtaining an antenna array element directional diagram with ultralow sidelobes;

step 13: and in the field angle, gradually increasing the array element spacing of the sparse linear array from a half wavelength until a grating lobe is positioned in a first minor lobe of the antenna array element directional diagram, thereby determining the array element spacing and the array element number of the sparse linear array.

6. An operating method of the ground-based interferometric virtual aperture deformation monitoring radar according to claims 1-5, characterized by: a signal generating unit (231) of the radar subsystem (23) generates a broadband frequency modulation continuous wave signal, and the broadband frequency modulation continuous wave signal reaches a transmitting antenna array element (2331) in a transmitting array (233) through a power amplifier (232) of which the switch is controlled by a control circuit (239); the control circuit (239) controls the power amplifier (232) to be turned on and off, so that only one transmitting antenna array element (2331) in the transmitting array (233) transmits the broadband frequency-modulated continuous wave signal at each moment; receiving echo signals reflected by the inner wall of a tunnel (1) or a passive corner reflector (11) by a receiving antenna array element (2341) in a receiving array (234), transmitting the echo signals to a low noise amplifier (235), transmitting the echo signals to a signal processing circuit (2310) after passing through a mixer (236), an intermediate frequency filter (237) and an analog-to-digital converter (238), processing the echo signals by the signal processing circuit (2310) to obtain inner wall deformation information, and transmitting the inner wall deformation information to a data display subsystem (24) through a wireless transmission module (2311); -all of the receive antenna elements (2341) in the receive array (234) receive the echo signals simultaneously; the radar subsystem (23) operates in a time-division multiplexed manner.

7. The method for operating a ground-based interference virtual aperture deformation monitoring radar according to claim 6, wherein the step of processing the echo signal in the signal processing circuit (2310) is as follows:

step 21: storing the echo signals in a data cube form, performing MIMO processing to obtain azimuth data, elevation data and time domain sampling data, obtaining a first virtual aperture processing result, obtaining virtual array element data, and realizing first aperture expansion;

step 22: carrying out Fourier transform on the time domain sampling data, converting the time domain sampling data into a frequency domain, and obtaining distance information corresponding to the sequence numbers of the frequency domain sampling points, so as to realize distance direction focusing and obtain distance direction data;

step 23: selecting the corresponding frequency domain sampling point serial numbers between the minimum distance and the maximum distance from the inner wall to the radar subsystem (23), and performing linear prediction extrapolation in the azimuth direction and the elevation direction by combining the azimuth direction data, the elevation direction data and the distance direction data in the step 22 to obtain a second virtual aperture processing result, so as to obtain more virtual array element data and realize second aperture expansion;

step 24: using two-dimensional digital beam forming processing to the virtual array element data in the step 22 or the step 23 to realize the focusing of the azimuth direction and the elevation direction, and obtaining a three-dimensional radar complex image with high resolution;

step 25: obtaining a radar phase interference image from the three-dimensional radar complex image, and obtaining an interference phase of the radar phase interference image;

step 26: phase unwrapping and atmospheric correction are carried out on the interference phase to obtain an actual interference phase

Step 27: according to the corresponding relation between the actual interference phase and the displacement delta r (r, theta, phi)

And obtaining deformation information of the monitoring points on the inner wall of the tunnel (1).

8. The working method of the ground-based interference virtual aperture deformation monitoring radar according to claim 7, characterized in that: in step 23, linear prediction is performed by using an autoregressive-based model, and a prediction filter and a prediction error filter are used to adjust the weight of the prediction filter according to the errors of the prediction filter and the prediction error filter; the processing procedure of the linear prediction extrapolation is as follows:

step 231: the virtual area array B is obtained in the step 21, and the number of the array elements is M₁×N₁Said step 22 obtaining a data matrix Y transformed to the frequency domain_BSaid Y is_BOf dimension M₁×N₁Said Y is_BThe (m, n) th element of (a) is y_B(m, n); the linear prediction adopts a two-dimensional linear prediction method, a two-dimensional matrix is Y, and the dimension is M₁×N₁The (m, n) th element of the Y is Y (m, n);

set (K)₁,K₂) Order linearity the prediction filter and the prediction error filter, the prediction error filter coefficient being a (k)₁,k₂)，0≤k₁≤K₁，0≤k₂≤K₂，a(0,0)＝1；

Step 232: converting the prediction error filter coefficients into vector form: a ═ a (0), a (1), …, a (K)₂)]Is a row vector in which the k-th element

Also a row vector;

e(m,n)＝az(m,n) (3)

wherein the content of the first and second substances,z(m,n)＝[y(m,n),…,y(m-K₁,n),…,y(m,n-K₂),…,y(m-K₁,n-K₂)]^Tis a column vector;

step 234: according to said M₁×N₁Observing data, solving a least square solution of linear prediction by adopting a two-dimensional covariance method, and constructing an overall mean square error function as follows:

step 235: calculating the coefficient a (k) of the prediction error filter by using the formula (4)₁,k₂) And carrying out prediction extrapolation by adopting the prediction filter to obtain prediction data y (m, n), wherein the formula is as follows:

wherein M is more than or equal to 1 and less than or equal to M₁/2+M₂/2，1≤n≤N₁/2+N₂2; forming an output matrix Y from the two-dimensional matrix Y and the prediction data_pSaid dimension being (M)₂/2)×(N₂/2) of the output matrix of y_p(m,n)＝y(m+M₁/2,n+N₁/2)，1≤m≤M₂/2，1≤n≤N₂/2；

Step 236: let y (m, n) be y_B(m, n); performing prediction extrapolation from the step 233 to the step 235 to obtain a prediction matrix Y_C1Comprises the following steps: y is_c1(m,n)＝y_p(m,n)；

Step 237: let y (m, n) be y_B(M₁+1-m, n), said predictive extrapolation is performed through said steps 233 to 235 to obtain a prediction matrix Y_C2Comprises the following steps: y is_c2(m,n)＝y_p(M₂+1-m,n)；

Step 238: let y (m, n) be y_B(M₁+1-m,N₁+1-n) of the prediction extrapolation, resulting in a prediction matrix Y, from said step 233 to said step 235_C3Comprises the following steps: y is_c3(m,n)＝y_p(M₂+1-m,N₂+1-n)；

Step 239: let y (m, n) be y_B(m,N₁+1-n) of the prediction extrapolation, resulting in a prediction matrix Y, from said step 233 to said step 235_C4Comprises the following steps: y is_c4(m,n)＝y_p(m,N₂+1-n)；

Step 2310: the virtual area array after the extrapolation is predicted is marked as C, the number of the array elements is M₂×N₂The corresponding data matrix is Y_C，Y_CSaid dimension of is M₂×N₂。

9. The working method of the ground-based interference virtual aperture deformation monitoring radar according to claim 7, wherein the concrete implementation process of the step 25 is as follows:

step 251: the three-dimensional radar complex image is represented by a spherical coordinate system, each coordinate value is represented by three values of distance, azimuth angle and pitch angle, and the coordinate value I (r, theta, phi) is as follows:

in the above formula

Expressing the distance from the origin of coordinates to the ith monitoring point, wherein L is the total monitoring fixed number; w is a_(m,n)(θ, φ) is a weight coefficient; c is the propagation velocity of the electromagnetic wave; f. of₀The initial frequency of the broadband frequency modulation continuous wave signal is obtained; t is the pulse width of the broadband frequency modulation continuous wave signal, B is the signal bandwidth, and alpha is B/T is the modulation frequency;

step 252: combining the three-dimensional radar complex images acquired at different moments with reference moment radar complex images initially acquired by a radar system to obtain the radar phase interference image, wherein the interference phase value of each pixel point in the radar phase interference image is