High-resolution radar signal processing method for building deformation monitoring

Abstract

The invention provides a high-resolution radar signal processing method and system for building deformation monitoring, and the method comprises the steps: setting a radar parameter according to a monitoring demand, and collecting a reflection echo signal of a building surface; the data are acquired by an ADC to obtain staggered I / Q channel data, and the I / Q channel data are separated and reconstructed to obtain a complex signal; processing the complex signal by adopting an improved Chirp-Z transformation algorithm to obtain a complex frequency spectrum; calculating the amplitude of a complex frequency spectrum, extracting a frequency spectrum index corresponding to the strongest reflection point on the surface of the building through peak detection, and converting the frequency spectrum index into a preliminary distance value of a target relative to the radar; calculating an azimuth angle of the target relative to the radar, and obtaining a two-dimensional coordinate of the strongest reflection point in a relative coordinate system of the radar through coordinate transformation in combination with the initial distance value; the method is used for calculating two-dimensional coordinate position changes of monitoring points on the surface of the building, millimeter-level deformation monitoring is achieved, and the method is suitable for a radar monitoring system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of radar monitoring, and particularly relates to a high-resolution radar signal processing method for building deformation monitoring. BACKGROUND

[0002] With the acceleration of urban modernization, complex structures such as high-rise buildings and large bridges are increasing, and their long-term deformation monitoring has become an important issue to ensure public safety. Traditional monitoring methods such as total station are limited by the visibility condition, optical measurement is easily affected by weather, and traditional radar resolution is limited, making it difficult to achieve millimeter-level precision automatic monitoring.

[0003] A high-resolution millimeter wave radar and signal processing method based on FPGA with publication number CN113204013A sets the working parameters of the radar through the software loaded on the PL end of the FPGA, including the radar center frequency and waveform of the radar chip; starts the radar, and the transmitting antenna transmits radar waves outward; the receiving antenna collects the echo data obtained by reflection, and the data is preprocessed by the software loaded on the PL end; the preprocessed data is transmitted to the software loaded on the PS end of the FPGA; the software loaded on the PS end performs multi-channel multi-dimensional FFT calculation; target detection is performed using the calculation results to detect whether there is a target in the radar detection area; if there is a target in the detection area, the target point track and shape detected by the radar are output.

[0004] The existing traditional FFT processing method has obvious limitations in building deformation monitoring. The theoretical resolution is limited by the signal length, making it difficult to accurately capture millimeter-level micro deformation. The complete phase information of the complex signal in the radar echo is not fully utilized, resulting in the inability to realize high-precision two-dimensional coordinate positioning, thereby reducing the accuracy and reliability of the deformation monitoring. SUMMARY

[0005] Therefore, the present application provides a high-resolution radar signal processing method for building deformation monitoring, which realizes accurate detection of millimeter-level micro deformation through high-resolution spectrum analysis, fully utilizes the complete phase information of the complex signal in the radar echo, realizes high-precision two-dimensional coordinate positioning, and improves the accuracy and reliability of the deformation monitoring.

[0006] The technical scheme of the present application is as follows: In a first aspect, the present application provides a high-resolution radar signal processing method for building deformation monitoring, comprising the following steps: S1, setting radar parameters according to monitoring requirements and collecting reflected echo signals on the surface of the building; S2, the reflected echo signal is collected by ADC to obtain I / Q channel data arranged in staggered rows, the I / Q channel data is separated and reconstructed to obtain complex signals; S3, the improved Chirp-Z transform algorithm is used for selective phase linear frequency modulation processing of the complex signal, and a high-resolution complex spectrum is obtained; S4, calculating the amplitude of the complex spectrum, extracting the spectrum index corresponding to the strongest reflection point on the building surface through peak value detection, and converting the spectrum index into a preliminary distance value of the target relative to the radar; S5, calculating the azimuth angle of the target relative to the radar according to the phase difference of the I / Q channel data, and combining the preliminary distance value to obtain the two-dimensional coordinates of the strongest reflection point in the radar relative coordinate system through coordinate conversion; S6, mapping the two-dimensional coordinates in the radar relative coordinate system to the building absolute coordinate system based on the installation position and calibration parameters of the radar in the field to obtain the actual position of the target.

[0007] On the basis of the above technical scheme, preferably, in step S1, the radar parameters are set according to the monitoring requirements, including: The distance resolution parameter is set, when the high resolution mode is set, the distance resolution is set to 0.00276 m / N ; when the standard resolution mode is set, the distance resolution is set to 0.0046 m / N ; According to the ratio of the minimum display distance of the radar to the monitored object to the distance resolution under the corresponding resolution mode, the near-end frequency range under the corresponding resolution mode is calculated f 0; According to the ratio of the maximum display distance of the radar to the monitored object to the distance resolution under the corresponding resolution mode, the far-end frequency range under the corresponding resolution mode is calculated f 1; The number of output spectrum points M and the length of the input signal N .

[0008] On the basis of the above technical scheme, preferably, in step S2, the reflected echo signal is collected by ADC to obtain staggered I / Q channel data, and the I / Q channel data is separated and reconstructed to obtain a complex signal, including: The reflected echo signal is collected by ADC to obtain staggered I / Q channel data, the I / Q channel data is separated from the staggered I / Q channel data, the I / Q channel data is separated from the staggered I channel data and Q channel data; The separated I channel data and Q channel data are reconstructed into a complex form to obtain a complex signal, and the expression is: ; In the formula, x [ n ] is a complex signal. I [ n [This refers to channel I data.] j The imaginary unit, Q [n] is Q Channel data, n This is the index for the sampling points.

[0009] Based on the above technical solutions, preferably, step S3, which involves using an improved Chirp-Z transform algorithm to perform selective phase linear frequency modulation on the complex signal to obtain a high-resolution complex spectrum, includes the following sub-steps: S31, Construct the Chirp kernel function for frequency domain modulation, with the following expression: ; In the formula, h [ n ] is the first of the Chirp kernel functions n A complex value, N The number of signal sampling points. F s Sampling frequency, f 1- f 0 represents the signal frequency range; S32 performs a weighted convolution on the input complex signal to obtain a weighted signal, expressed as: ; In the formula, g [ n [The weighted number] is the [number]th [unit]. n One output signal value; S33, the weighted signal is multiplied point-by-point by the Chirp kernel function, and the Fourier transform of the product is performed to obtain the high-resolution complex spectrum, expressed as: ; In the formula, Y [ k [The output is the high-resolution complex spectrum of the first number.] k Each value contains the real part. I [ k ] and imaginary part Q [ k ], M The number of spectrum points in the output. k This is the index of the output spectrum.

[0010] On the basis of the above technical solutions, preferably, the step S4 comprises the following sub-steps: S41, for each frequency point of the complex spectrum, taking the sum of the square of the complex real part I[k] and the square of the complex imaginary part Q[k], and taking the square root of the sum to obtain the amplitude of the complex spectrum; S42, in the amplitude of the complex spectrum, identifying the maximum frequency point value as the strongest reflection point on the building surface through peak detection, and recording the spectrum index of the strongest peak value; S43, converting the spectrum index of the strongest peak value into the preliminary distance value of the target relative to the radar.

[0011] On the basis of the above technical solutions, preferably, the step S43 comprises the following sub-steps: According to the maximum detection distance and the minimum detection distance set by the radar system, the total detection range of the radar system is calculated; According to the total detection range of the radar system and the output spectrum point number ratio, the distance increment represented by each spectrum index is calculated; The spectrum index of the strongest peak value is multiplied by the distance increment to calculate the distance offset, and the minimum detection distance is added to calculate the preliminary distance value of the target relative to the radar.

[0012] On the basis of the above technical solutions, preferably, the step S5 comprises the following sub-steps: The difference between the current time value and the previous time value of the I channel and the difference between the current time value and the previous time value of the Q channel are calculated respectively; The difference value of the Q channel is divided by the difference value of the I channel, and the arctangent operation is performed to obtain the azimuth angle of the target relative to the radar; According to the preliminary distance value and the azimuth angle of the target relative to the radar, the x and y coordinates in the Cartesian coordinate system are converted to calculate the two-dimensional coordinates of the target in the radar relative coordinate system.

[0013] On the basis of the above technical solutions, preferably, the step S6 comprises the following sub-steps: Determine the installation position and installation angle of the radar in the building absolute coordinate system through field measurement; Translate the origin of the radar relative coordinate system to the installation position of the radar in the building absolute coordinate system, and align the spatial position of the coordinate origin according to the translation transformation matrix; According to the installation angle of the radar, the translated coordinates are rotated and transformed, and according to the rotation matrix, the coordinate axis direction of the radar relative coordinate system is aligned with the building absolute coordinate system, so as to obtain the actual position of the target in the building absolute coordinate system; The translated and rotated coordinates are the actual position of the target in the building absolute coordinate system.

[0014] In the second aspect, the application further provides a high-resolution radar signal processing system for building deformation monitoring, which is implemented by using the high-resolution radar signal processing method for building deformation monitoring, and comprises: The acquisition module is configured to set radar parameters according to monitoring requirements and acquire reflected echo signals on the surface of the building; The signal processing module is configured to obtain I / Q channel data arranged in an interleaved manner through ADC acquisition of the reflected echo signals, separate and reconstruct the I / Q channel data, and obtain complex signals; The spectrum analysis module is configured to perform selective phase linear frequency modulation processing on the complex signals by using an improved Chirp-Z transform algorithm, and obtain high-resolution complex spectrum; The distance extraction module is configured to calculate the amplitude of the complex spectrum, extract the spectrum index corresponding to the strongest reflection point on the surface of the building through peak value detection, and convert the spectrum index into a preliminary distance value of the target relative to the radar; The positioning module is configured to calculate the azimuth angle of the target relative to the radar according to the phase difference of the I / Q channel data, and obtain the two-dimensional coordinates of the strongest reflection point in the radar relative coordinate system through coordinate conversion in combination with the preliminary distance value; The mapping module is configured to map the two-dimensional coordinates in the radar relative coordinate system to the building absolute coordinate system based on the installation position and calibration parameters of the radar in the field, and obtain the actual position of the target.

[0015] In the third aspect, the application further provides a computer readable storage medium, which stores a high-resolution radar signal processing method program for building deformation monitoring, and the high-resolution radar signal processing method program for building deformation monitoring is implemented when executed.

[0016] The high-resolution radar signal processing method for building deformation monitoring has the following beneficial effects relative to the prior art: (1) By using the improved Chirp-Z transform algorithm for high-resolution frequency spectrum, combined with the complex phase information of I / Q signal processing signal, the accurate detection of millimeter-level micro deformation is realized; through peak detection and phase difference angle calculation, and with the help of field calibration and coordinate mapping, the measurement results are aligned with the building coordinate system, realizing high-precision two-dimensional coordinate positioning, and improving the accuracy and reliability of deformation monitoring; (2) By setting high-resolution and standard-resolution two switchable modes, and based on the dynamic calculation of frequency range according to the monitoring distance, the optimization balance of monitoring accuracy and system resource consumption is realized; the configuration of fixed output point number and optimized input length improves the algorithm efficiency while ensuring the millimeter-level high-precision monitoring ability; (3) By separating and reconstructing the interleaved I / Q channel data into complex form, the amplitude and phase information of radar echo are completely preserved, laying a foundation for subsequent high-resolution signal processing, and improving the frequency resolution and ranging accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0018] Figure 1 The flow chart of the high-resolution radar signal processing method for building deformation monitoring of the present application; Figure 2 The structural block diagram of the high-resolution radar signal processing system for building deformation monitoring of the present application. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0020] As shown in Figure 1 The first aspect, the present application provides a high-resolution radar signal processing method for building deformation monitoring, comprising the following steps: S1, according to the monitoring requirement, set the radar parameter, and collect the reflected echo signal of the building surface.

[0021] Step S1 includes: Set the distance resolution parameter, when it is high resolution mode, the distance resolution is set to 0.00276 m / N ; when it is standard resolution mode, the distance resolution is set to 0.0046 m / N ; It should be noted that according to the accuracy requirements and system resource conditions of building deformation monitoring, the corresponding working mode is selected, including high resolution mode and standard resolution mode, the high resolution mode is suitable for the scene with strict monitoring demand of millimeter level micro deformation, and the standard resolution mode is suitable for the case of conventional deformation monitoring and limited system resources.

[0022] Based on the selected resolution mode and monitoring distance requirement, the frequency range parameter of signal processing is calculated; According to the ratio of the minimum display distance of the radar to the monitoring object and the distance resolution under the corresponding resolution mode, the near-end frequency range under the corresponding resolution mode is calculated f 0, the expression is: f 0=distanceNear / drsec; In the formula, distanceNear is the minimum display distance of the radar to the monitoring area, and drsec is the distance resolution under the current mode; According to the ratio of the maximum display distance of the radar to the monitoring object and the distance resolution under the corresponding resolution mode, the far-end frequency range under the corresponding resolution mode is calculated f 1, the expression is: f 1=distanceFar / drsec; In the formula, distanceFar is the maximum display distance of the radar to the monitoring object; Set the output frequency spectrum point number M And the input signal length N .

[0023] It should be noted that the output frequency spectrum point number M is set to 512 points, which ensures sufficient frequency resolution while considering the calculation efficiency; the input signal length N is set to 2875 sampling points, which ensures signal integrity and provides sufficient processing data amount; According to the above parameter configuration, the radar system is started to collect the reflection echo signal of the building surface, the radar transmits continuous wave signal and receives reflection echo, data collection is carried out according to the set sampling rate and signal length, and the collected original signal is transmitted to the subsequent processing module.

[0024] In step S1, by setting two switchable modes, high resolution and standard resolution, and dynamically calculating the frequency range based on the monitoring distance, an optimized balance between monitoring accuracy and system resource consumption is achieved. The configuration of fixed output points and optimized input length ensures millimeter-level high-precision monitoring capabilities while improving algorithm efficiency. This enables the system to meet the needs of monitoring minute deformations in structures such as high-rise buildings and bridges, and to run efficiently on embedded platforms, effectively supporting multi-scenario and long-term building deformation monitoring applications.

[0025] S2, the reflected echo signal is acquired by the ADC to obtain interleaved I / Q channel data, and the I / Q channel data is separated and reconstructed to obtain a complex signal.

[0026] Step S2 includes: The reflected echo signals are acquired by the ADC and obtained in an interleaved pattern. I / Q Channel data, from interleaved arrangement I / Q Separation from channel data I Channel data and Q Channel data; It should be noted that extracting the I channel data means extracting data from all even-indexed positions in the interleaved data stream. I [ n ]=rawData[2 n Extract Q channel data, that is, extract data at all odd index positions from the interleaved data stream, Q[n] = rawData[2 n +1].

[0027] After separation I Channel data and Q The channel data is reconstructed into complex form to obtain a complex signal, expressed as: ; In the formula, x [ n ] is a complex signal. I [ n [This refers to channel I data.] j The imaginary unit, Q [n] is Q Channel data, n For the sampling point index, ( n =0,1,2,…, N- 1).

[0028] It should be noted that the amplitude and phase information of the radar echo is completely retained by separating and reconstructing the interleaved I / Q channel data into complex form in step S2, which lays a foundation for subsequent high-resolution signal processing; the complex representation not only eliminates the spectral image problem in traditional real signal processing, improves the frequency resolution and ranging accuracy, but also enables the phase information to be completely retained to support accurate angle calculation, ensuring millimeter-level monitoring accuracy.

[0029] S3, using an improved Chirp-Z transform algorithm to perform selective phase linear frequency modulation processing on the complex signal to obtain a high-resolution complex spectrum; Step S3 includes the following sub-steps: S31, constructing a Chirp kernel function for frequency domain modulation, expressed as: ; In the formula, h [ n ] is the first n complex value of the Chirp kernel function, N is the number of signal sampling points, F s is the sampling frequency, f 1- f 0 is the signal frequency range; S32, weighting convolution is performed on the input complex signal to obtain a weighted signal, expressed as: ; In the formula, g [ n ] is the first n output signal value after weighting; S33, multiplying the weighted signal point by point with the Chirp kernel function, and performing Fourier transform on the product result to obtain a high-resolution complex spectrum, expressed as: ; In the formula, Y [ k ] is the first k value of the output high-resolution complex spectrum, including real part I [ k ] and imaginary part Q [ k ], M is the number of output spectrum points, k is the index of the output spectrum.

[0030] It should be noted that in step S3, the selective phase chirp processing is realized by constructing a chirp kernel function with quadratic phase characteristics and performing weighted convolution on the input signal, combined with fast Fourier transform, which can improve the frequency resolution in a specific distance interval; not only the millimeter-level distance accuracy is realized through the nonlinear frequency mapping mechanism, but also the phase information of the complex spectrum is completely preserved to support subsequent accurate angle calculation, providing accuracy and practicality for building deformation monitoring.

[0031] S4, calculating the amplitude of the complex spectrum, extracting the frequency spectrum index corresponding to the strongest reflection point on the building surface through peak value detection, and converting the frequency spectrum index into a preliminary distance value of the target relative to the radar; Step S4 includes the following sub-steps: S41, for each frequency point of the complex spectrum, taking the sum of the square of the complex real part I[k] and the square of the complex imaginary part Q[k], and performing square root operation on the sum value to obtain the amplitude of the complex spectrum, the expression is: ; In the formula, | Y [ k ]| is the amplitude of the frequency domain signal, I [ k ] is the real part of the frequency domain signal, Q [ k ] is the imaginary part of the frequency domain signal; the operation converts the complex spectrum into a real number sequence containing only amplitude information, wherein each | Y [ k ]| value represents the reflection intensity of the building surface on the corresponding distance unit.

[0032] S42, in the amplitude of the complex spectrum, the maximum frequency point value is identified as the strongest reflection point on the building surface through peak value detection, and the frequency spectrum index of the strongest peak value is recorded; It should be noted that all points satisfying |Y[k]|>|Y[k-1]| and |Y[k]|>|Y[k+1]| are identified, a filtering threshold based on noise floor is set, and false peaks caused by environmental noise are filtered out, and among all the local maximum values meeting the conditions, the point with the largest amplitude is selected as the strongest reflection point on the building surface, and the corresponding frequency spectrum index is recorded.

[0033] S43, converting the frequency spectrum index of the strongest peak value into a preliminary distance value of the target relative to the radar.

[0034] Step S4 completes the key conversion from the frequency domain to the distance domain, the spectrum containing phase information is converted into a distribution reflecting the target reflection intensity by calculating the complex amplitude; the peak value detection algorithm identifies the most significant building surface reflection point from the distribution; and the last index-distance conversion converts the abstract spectral position into a distance value with clear physical meaning through a linear mapping relationship, which not only fully utilizes the fine distance information provided by the high-resolution spectrum to ensure the realization of millimeter-level ranging accuracy, but also effectively suppresses noise interference through the peak value screening mechanism to ensure the reliability of target identification and provides an accurate and reliable distance reference for building deformation monitoring.

[0035] Step S43 comprises the following sub-steps: According to the maximum detection distance and the minimum detection distance set by the radar system, the total detection range of the radar system is calculated; According to the ratio of the total detection range of the radar system to the output spectral point number, the distance increment represented by each spectral index is calculated; The spectral index of the strongest peak value is multiplied by the distance increment to calculate the distance offset, and the minimum detection distance is added to calculate the preliminary distance value of the target relative to the radar, and the expression is: ; In the formula, r is the preliminary distance value of the target relative to the radar, k max is the spectral index of the strongest peak value, d min is the minimum detection distance set by the radar system, d max is the maximum detection distance set by the radar system.

[0036] The present application converts the spectral index of the strongest reflection point into the accurate distance of the target by establishing a linear mapping relationship between the spectral index and the physical distance, realizing reliable conversion of the digital signal processing result to the physical space parameter; the method not only fully utilizes the fine positioning ability of high-resolution spectrum analysis to ensure the realization of millimeter-level ranging accuracy, but also avoids complex calculation through simple linear operation, reduces the system processing burden, and at the same time, the mapping mechanism has good adaptability and scalability, can flexibly adjust the detection range according to different monitoring needs, and provides reliable and efficient distance measurement for building deformation monitoring.

[0037] S5, according to the phase difference of the I / Q channel data, the azimuth of the target relative to the radar is calculated, and combined with the preliminary distance value, the two-dimensional coordinates of the strongest reflection point in the radar relative coordinate system are obtained through coordinate conversion.

[0038] Step S5 comprises the following sub-steps: Calculate the difference between the current time value and the previous time value of the I channel and the difference between the current time value and the previous time value of the Q channel respectively; Divide the difference of the Q channel by the difference of the I channel and perform an inverse tangent operation to obtain the azimuth angle of the target relative to the radar, expressed as: ; In the formula, Q 1 is the current time value of the Q channel, Q 0 is the previous time value of the Q channel; I 1 is I the current time value of the I channel, I 0 is I the previous time value of the I channel, and the difference calculation effectively extracts the time rate of change of the signal phase.

[0039] According to the preliminary distance value and the azimuth angle of the target relative to the radar, convert to x and y coordinates in the Cartesian coordinate system, calculate the two-dimensional coordinates of the target in the radar relative coordinate system, expressed as: x = r ·cos( θ ); y = r ·sin( θ ); In the formula, ( x , y ) are the two-dimensional coordinates of the target in the radar relative coordinate system.

[0040] In this step S5, the phase change characteristics of the I / Q signal are used for angle estimation. The I / Q signal constitutes a vector on the complex plane, and the phase angle of the vector carries the azimuth information of the target. By calculating the phase change rate at adjacent times, the angular position of the target can be effectively extracted. The conversion from polar coordinates to Cartesian coordinates establishes a mathematical mapping from distance-angle description to plane rectangular coordinates, providing a basic framework for subsequent absolute coordinate positioning.

[0041] S6, based on the installation position and calibration parameters of the radar in the field, map the two-dimensional coordinates in the radar relative coordinate system to the building absolute coordinate system to obtain the actual position of the target.

[0042] Step S6 includes the following sub-steps: Determine the installation position and installation angle of the radar in the building absolute coordinate system through field measurement; Translate the origin of the radar relative coordinate system to the installation position of the radar in the building absolute coordinate system, and align the spatial position of the coordinate origin according to the translation transformation matrix; According to the installation angle of the radar, the translated coordinates are rotated, and the coordinate axes of the radar relative coordinate system are aligned with the building absolute coordinate system according to the rotation matrix, to obtain the actual position of the target in the building absolute coordinate system; The translated and rotated coordinates are the actual position of the target in the building absolute coordinate system.

[0043] The core of this step is to realize accurate conversion between different coordinate systems through translation transformation and rotation transformation, which not only eliminates the system error caused by the installation position and angle of the radar, but also ensures the spatial consistency of the data of different monitoring points, and improves the monitoring efficiency and reliability.

[0044] This embodiment adopts an improved Chirp-Z transform algorithm for high-resolution spectrum division, combines a complete I / Q signal complex processing flow, realizes millimeter-level distance monitoring capability, detects the peak value and calculates the phase difference angle, and through on-site calibration and coordinate mapping, the measurement result is aligned with the building coordinate system, ensuring sub-degree angle resolution and millimeter-level distance accuracy.

[0045] As shown in Figure 2 The second aspect, the present application also provides a high-resolution radar signal processing system for building deformation monitoring, which is realized by using a high-resolution radar signal processing method for building deformation monitoring, comprising: The acquisition module is used for setting the radar parameters according to the monitoring requirements, and collecting the reflected echo signals on the surface of the building; The signal processing module is used for separating and reconstructing the I / Q channel data to obtain complex signals; The spectrum analysis module is used for selectively performing phase linear frequency modulation processing on the complex signals by using an improved Chirp-Z transform algorithm to obtain high-resolution complex spectrum; The distance extraction module is used for calculating the amplitude of the complex spectrum, extracting the spectrum index corresponding to the strongest reflection point on the surface of the building through peak value detection, and converting the spectrum index into a preliminary distance value of the target relative to the radar; The positioning module is used for calculating the azimuth angle of the target relative to the radar according to the phase difference of the I / Q channel data, and combining the preliminary distance value to obtain the two-dimensional coordinates of the strongest reflection point in the radar relative coordinate system through coordinate conversion; The mapping module is used for mapping the two-dimensional coordinates in the radar relative coordinate system to the building absolute coordinate system based on the installation position and calibration parameters of the radar on site to obtain the actual position of the target.

[0046] In a third aspect, the present application provides a computer readable storage medium, wherein the storage medium stores a program of a high-resolution radar signal processing method for building deformation monitoring, and the program of the high-resolution radar signal processing method for building deformation monitoring, when executed, implements the high-resolution radar signal processing method for building deformation monitoring.

[0047] It should be noted that the system corresponds to the high-resolution radar signal processing method for building deformation monitoring, and all implementation manners in the method embodiments are applicable to the embodiments of the system, and the same technical effects can be achieved.

[0048] Those skilled in the art can understand that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0049] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system and modules can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0050] In the embodiments provided by the present application, it should be understood that the disclosed system and method can be implemented by other ways. For example, the above-described device embodiments are only schematic, and the division of the units is only a logical function division, and there can be another division manner in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between the units can be indirect couplings or communication connections through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0051] The units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiments.

[0052] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically, or two or more units can be integrated into one unit.

[0053] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of software products. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a ROM, a RAM, a magnetic disk or an optical disk, and various program code storage media.

[0054] In addition, it should be noted that in the system and method of the present application, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered as equivalent solutions of the present application. Moreover, the steps of performing the above series of processes can naturally be executed in time sequence according to the order of description, but do not necessarily have to be executed in time sequence. Some steps can be executed in parallel or independently of each other. It can be understood by those skilled in the art that all or any steps or components of the method and device of the present application can be implemented in hardware, firmware, software or a combination thereof in any computing device (including a processor, a storage medium, etc.) or a network of computing devices, which can be implemented by those skilled in the art using their basic programming skills after reading the description of the present application.

[0055] Therefore, the object of the present application can also be achieved by running a program or a set of programs on any computing system. The computing system can be a commonly known general system. Therefore, the object of the present application can also be achieved only by providing a program product containing program code for implementing the method or device. That is, such a program product also constitutes the present application, and a storage medium storing such a program product also constitutes the present application. Obviously, the storage medium can be any commonly known storage medium or any storage medium developed in the future. It should be noted that in the device and method of the present application, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered as equivalent solutions of the present application. Moreover, the steps of performing the above series of processes can naturally be executed in time sequence according to the order of description, but do not necessarily have to be executed in time sequence. Some steps can be executed in parallel or independently of each other.

[0056] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A high-resolution radar signal processing method for monitoring building deformation, characterized in that, Includes the following steps: S1, set radar parameters according to monitoring requirements and collect reflected echo signals from the building surface; S2, the reflected echo signal is acquired by the ADC to obtain interleaved I / Q channel data, and the I / Q channel data is separated and reconstructed to obtain a complex signal; S3 employs an improved Chirp-Z transform algorithm to perform selective phase linear frequency modulation on complex signals, thereby obtaining a high-resolution complex spectrum. S4, calculate the amplitude of the complex spectrum, extract the spectrum index corresponding to the strongest reflection point on the building surface through peak detection, and convert the spectrum index into the preliminary distance value of the target relative to the radar; S5. Calculate the target's azimuth relative to the radar based on the phase difference of the I / Q channel data, and combine it with the preliminary range value to obtain the two-dimensional coordinates of the strongest reflection point in the radar's relative coordinate system through coordinate transformation. S6, based on the radar's installation location and calibration parameters on site, maps the two-dimensional coordinates in the radar's relative coordinate system to the building's absolute coordinate system to obtain the target's actual position.

2. The high-resolution radar signal processing method for building deformation monitoring as described in claim 1, characterized in that, Step S1, which involves setting radar parameters according to monitoring requirements, includes: Set the distance resolution parameter. In high-resolution mode, the distance resolution is set to 0.00276. m / N When in standard resolution mode, the distance resolution is set to 0.0046. m / N ; Calculate the near-end frequency range under the corresponding resolution mode based on the ratio of the minimum display distance of the radar to the detected object. f 0; Calculate the far-end frequency range under the corresponding resolution mode based on the ratio of the radar's maximum display distance to the monitored object to the distance resolution under the corresponding resolution mode. f 1; Set the number of output spectrum points M and input signal length N .

3. The high-resolution radar signal processing method for building deformation monitoring as described in claim 1, characterized in that, In step S2, the reflected echo signal is acquired by an ADC to obtain interleaved I / Q channel data. The I / Q channel data is then separated and reconstructed to obtain a complex signal, including: The reflected echo signals are acquired by the ADC and obtained in an interleaved pattern. I / Q Channel data, from interleaved arrangement I / Q Separation from channel data I Channel data and Q Channel data; After separation I Channel data and Q The channel data is reconstructed into complex form to obtain a complex signal, expressed as: ； In the formula, x [ n ] is a complex signal. I [ n [This refers to channel I data.] j The imaginary unit, Q [n] is Q Channel data, n This is the index for the sampling points.

4. The high-resolution radar signal processing method for building deformation monitoring as described in claim 1, characterized in that, Step S3, which involves using an improved Chirp-Z transform algorithm to perform selective phase linear frequency modulation on the complex signal to obtain a high-resolution complex spectrum, includes the following sub-steps: S31, Construct the Chirp kernel function for frequency domain modulation, with the following expression: ； In the formula, h [ n ] is the first of the Chirp kernel functions n A complex value, N The number of signal sampling points. F s Sampling frequency, f 1- f 0 represents the signal frequency range; S32 performs a weighted convolution on the input complex signal to obtain a weighted signal, expressed as: ； In the formula, g [ n [The weighted number] is the [number]th [unit]. n One output signal value; S33, the weighted signal is multiplied point-by-point by the Chirp kernel function, and the Fourier transform of the product is performed to obtain the high-resolution complex spectrum, expressed as: ； In the formula, Y [ k [The output is the high-resolution complex spectrum of the first number.] k Each value contains the real part. I [ k ] and imaginary part Q [ k ], M The number of spectrum points in the output. k This is the index of the output spectrum.

5. The high-resolution radar signal processing method for building deformation monitoring as described in claim 1, characterized in that, Step S4, which involves calculating the amplitude of the complex spectrum, extracting the spectral index corresponding to the strongest reflection point on the building surface through peak detection, and converting this spectral index into a preliminary distance value of the target relative to the radar, includes the following sub-steps: S41. For each frequency point of the complex spectrum, take the sum of the square of the real part I[k] and the square of the imaginary part Q[k], and perform a square root operation on the sum to obtain the amplitude of the complex spectrum. S42, in the amplitude of the complex spectrum, the maximum frequency point value is identified by peak detection as the strongest reflection point on the building surface, and the spectrum index of the strongest peak is recorded; S43 converts the spectral index of the strongest peak into a preliminary distance value of the target relative to the radar.

6. The high-resolution radar signal processing method for building deformation monitoring as described in claim 5, characterized in that, Step S43, which involves converting the spectral index of the strongest peak into a preliminary distance value of the target relative to the radar, includes the following sub-steps: Calculate the total detection range of the radar system based on the maximum and minimum detection ranges set by the radar system. Based on the ratio of the total detection range of the radar system to the number of output spectrum points, the distance increment represented by each spectrum index is calculated. The range offset is calculated by multiplying the spectral index of the strongest peak by the range increment, and then added to the minimum detection range to calculate the initial range value of the target relative to the radar.

7. The high-resolution radar signal processing method for building deformation monitoring as described in claim 1, characterized in that, Step S5, which involves calculating the target's azimuth relative to the radar based on the phase difference of the I / Q channel data and combining it with the preliminary range value to obtain the two-dimensional coordinates of the strongest reflection point in the radar's relative coordinate system through coordinate transformation, includes the following sub-steps: Calculate the difference between the current value and the previous value of the I channel and the difference between the current value and the previous value of the Q channel, respectively. Divide the difference in the Q channel by the difference in the I channel and perform an arctangent operation to obtain the target's azimuth angle relative to the radar. Based on the initial range and azimuth of the target relative to the radar, convert to Cartesian coordinates. x and y Coordinates: Calculates the two-dimensional coordinates of the target in the radar relative coordinate system.

8. The high-resolution radar signal processing method for building deformation monitoring as described in claim 1, characterized in that, Step S6, which involves mapping the two-dimensional coordinates of the radar in the relative coordinate system to the building's absolute coordinate system based on the radar's installation location and calibration parameters on-site, to obtain the target's actual position, includes the following sub-steps: The installation position and angle of the radar in the building's absolute coordinate system were determined through on-site measurements. The radar's relative coordinate system origin is translated to the radar's installation position in the building's absolute coordinate system, and the spatial position of the coordinate origin is aligned according to the translation transformation matrix. Based on the radar's installation angle, the translated coordinates are rotated and transformed. Using the rotation matrix, the coordinate axes of the radar's relative coordinate system are aligned with the building's absolute coordinate system, thus obtaining the target's actual position in the building's absolute coordinate system. The coordinates after translation and rotation are the actual position of the target in the building's absolute coordinate system.

9. A high-resolution radar signal processing system for building deformation monitoring, implemented using the high-resolution radar signal processing method for building deformation monitoring as described in any one of claims 1-8, comprising: The acquisition module is used to set radar parameters according to monitoring requirements and to acquire reflected echo signals from the building surface; The signal processing module is used to acquire interleaved I / Q channel data from the reflected echo signal via ADC, and then separate and reconstruct the I / Q channel data to obtain a complex signal. The spectrum analysis module is used to perform selective phase linear frequency modulation on complex signals using an improved Chirp-Z transform algorithm to obtain a high-resolution complex spectrum. The range extraction module is used to calculate the amplitude of the complex spectrum, extract the spectrum index corresponding to the strongest reflection point on the building surface through peak detection, and convert the spectrum index into a preliminary distance value of the target relative to the radar. The positioning module is used to calculate the target's azimuth angle relative to the radar based on the phase difference of the I / Q channel data, and combine it with the preliminary distance value to obtain the two-dimensional coordinates of the strongest reflection point in the radar's relative coordinate system through coordinate transformation; The mapping module is used to map the two-dimensional coordinates of the radar in the relative coordinate system to the building's absolute coordinate system based on the radar's installation location and calibration parameters on site, so as to obtain the actual position of the target.

10. A computer-readable storage medium, characterized in that, The storage medium stores a high-resolution radar signal processing method program for building deformation monitoring. When the high-resolution radar signal processing method program for building deformation monitoring is executed, it implements a high-resolution radar signal processing method for building deformation monitoring as claimed in any one of claims 1-8.

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