Radar-based multi-target ranging method and deformation monitoring method

Abstract

The present invention provides a radar-based multi-target ranging method and deformation monitoring method, which sequentially obtains the echo signals of the frequency modulated continuous wave signals sequentially emitted to the monitoring area and calculates the beat signals, and obtains a one-dimensional spectrum by Fourier transform; splices the sequentially obtained one-dimensional spectrum along the slow time to obtain a slow time-spectrum image, determines the number of targets in the slow time-spectrum image, and separates the slow time-spectrum image corresponding to each target from the slow time-spectrum image; estimates the frequency value and phase value of the frequency unit corresponding to each target based on the slow time-spectrum image corresponding to each target; combines the target distance roughly estimated and the target distance finely estimated for each target, estimates the accurate distance value of each target, and then realizes dynamic deformation monitoring through continuous real-time measurement. The present invention has the advantages of high precision and low complexity, can achieve sub-millimeter distance measurement accuracy, and realizes real-time monitoring of sub-millimeter micro-deformations of multiple targets.

Description

Technical Field

[0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a radar-based multi-target ranging method and a deformation monitoring method. Background Art

[0002] High-precision ranging technology is widely used in building deformation monitoring, lake level measurement, vehicle autonomous driving, and target positioning. Deformation monitoring can be achieved through real-time dynamic measurement. Radar has been proven to have potential technical advantages in these applications.

[0003] Frequency modulated continuous wave (FMCW) radar has been gradually applied to the fields of high-precision ranging and deformation monitoring due to its simple structure, high ranging resolution, and strong anti-noise capability. A key technology for high-precision ranging of FMCW radar is to accurately obtain the frequency of the beat signal after mixing the echo signal with the transmitted signal, thereby obtaining high-precision ranging information.

[0004] Existing high-precision ranging methods can be divided into two categories: non-parametric methods and parametric methods. At present, non-parametric methods used for ranging generally include interpolation methods, spectrum refinement algorithms based on fast Fourier transform (FFT), etc. Among them, the interpolation method mainly uses the amplitude ratio of several spectral lines near the spectrum peak to correct the frequency, and the interpolation calculation is large. The spectrum refinement algorithm based on fast Fourier transform (FFT) first uses the FFT algorithm with fewer points for rough estimation, and then uses the refinement algorithm to amplify the local spectrum for fine estimation. In order to achieve higher theoretical accuracy, it is necessary to sacrifice exponential calculation and sampling time, which is very unfavorable for engineering applications. Parametric methods generally include model-based methods, such as multiple signal classification (MUSIC) and signal parameter estimation based on rotation invariant technology (ESPRIT). Parametric methods require some prior information of the signal, and their estimation accuracy is higher than that of non-parametric methods. The disadvantage is that if the model does not match or the signal-to-noise ratio (SNR) is low, the performance will be limited.

[0005] With the rapid development of my country's infrastructure and industrial engineering, the demand for the use of radar in high-precision ranging and deformation monitoring applications is growing. How to quickly and accurately measure distance at a lower cost and system complexity to achieve deformation monitoring is an urgent need. Summary of the invention

[0006] In order to solve at least one of the above technical problems in the prior art, the present invention proposes a radar-based multi-target ranging method and deformation monitoring method. The present invention has the advantages of high precision and low complexity, can achieve sub-millimeter distance measurement accuracy, and realize real-time monitoring of sub-millimeter micro deformation.

[0007] In order to achieve the above technical objectives, the technical solution proposed by the present invention is:

[0008] On the one hand, the present invention provides a radar-based multi-target ranging method, comprising:

[0009] The echo signals of the frequency modulated continuous wave signals sequentially transmitted to the monitoring area are obtained in sequence and the beat signals are calculated, and the one-dimensional spectrum is obtained by Fourier transform;

[0010] The one-dimensional spectra obtained sequentially are spliced ​​along the slow time to obtain a slow time-spectrum image, and the slow time-spectrum image corresponding to each target is separated from the slow time-spectrum image;

[0011] Based on the slow time-spectrum image corresponding to each target, the frequency value of the frequency unit corresponding to each target is estimated, and based on the frequency value of the frequency unit corresponding to each target, the distance thereof is roughly estimated;

[0012] The phase value of the frequency unit corresponding to each target is estimated based on the slow time-spectrum image corresponding to each target, and the distance of each target is precisely estimated based on the phase value of the frequency unit corresponding to each target;

[0013] The target distance obtained by roughly estimating each target and the target distance obtained by fine estimating each target are combined to estimate the precise distance value of each target.

[0014] On the other hand, the present invention provides a radar-based multi-target deformation monitoring method, which utilizes the above-mentioned radar-based multi-target ranging method to estimate the precise distance value of each target at different times, and realizes real-time dynamic deformation monitoring by monitoring the precise distance value of each target at different times.

[0015] On the other hand, the present invention provides a radar-based multi-target ranging device, comprising:

[0016] The first module is used to sequentially obtain the echo signals of the frequency modulated continuous wave signals sequentially transmitted to the monitoring area and calculate the beat signals, and obtain the one-dimensional spectrum by Fourier transform;

[0017] The second module is used to splice the sequentially obtained one-dimensional spectra along slow time to obtain a slow time-spectrum image, calculate the variance of each frequency unit in the slow time-spectrum image along slow time, determine the number of targets according to the variance, and separate the slow time-spectrum image corresponding to each target from the slow time-spectrum image;

[0018] The third module is used to estimate the frequency value of the frequency unit corresponding to each target based on the slow time-spectrum image corresponding to each target, and roughly estimate the distance of each target based on the frequency value of the frequency unit corresponding to each target;

[0019] The fourth module is used to estimate the phase value of the frequency unit corresponding to each target based on the slow time-spectrum image corresponding to each target, and accurately estimate the distance of each target based on the phase value of the frequency unit corresponding to each target;

[0020] The fifth module is used to combine the roughly estimated target distance of each target and the finely estimated target distance of each target to estimate the precise distance value of each target.

[0021] In another aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0022] The echo signals of the frequency modulated continuous wave signals sequentially transmitted to the monitoring area are obtained in sequence and the beat signals are calculated, and the one-dimensional spectrum is obtained by Fourier transform;

[0023] The one-dimensional spectra obtained sequentially are spliced ​​along slow time to obtain a slow time-spectrum image, the variance of each frequency unit in the slow time-spectrum image is calculated along slow time, the number of targets is determined according to the variance, and the slow time-spectrum image corresponding to each target is separated from the slow time-spectrum image;

[0024] Based on the slow time-spectrum image corresponding to each target, the frequency value of the frequency unit corresponding to each target is estimated, and based on the frequency value of the frequency unit corresponding to each target, the distance thereof is roughly estimated;

[0025] The phase value of the frequency unit corresponding to each target is estimated based on the slow time-spectrum image corresponding to each target, and the distance of each target is precisely estimated based on the phase value of the frequency unit corresponding to each target;

[0026] The target distance obtained by roughly estimating each target and the target distance obtained by fine estimating each target are combined to estimate the precise distance value of each target.

[0027] In another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the following steps are implemented:

[0028] The echo signals of the frequency modulated continuous wave signals sequentially transmitted to the monitoring area are obtained in sequence and the beat signals are calculated, and the one-dimensional spectrum is obtained by Fourier transform;

[0029] The one-dimensional spectra obtained sequentially are spliced ​​along slow time to obtain a slow time-spectrum image, the variance of each frequency unit in the slow time-spectrum image is calculated along slow time, the number of targets is determined according to the variance, and the slow time-spectrum image corresponding to each target is separated from the slow time-spectrum image;

[0030] Based on the slow time-spectrum image corresponding to each target, the frequency value of the frequency unit corresponding to each target is estimated, and based on the frequency value of the frequency unit corresponding to each target, the distance thereof is roughly estimated;

[0031] The phase value of the frequency unit corresponding to each target is estimated based on the slow time-spectrum image corresponding to each target, and the distance of each target is precisely estimated based on the phase value of the frequency unit corresponding to each target;

[0032] The target distance obtained by roughly estimating each target and the target distance obtained by fine estimating each target are combined to estimate the precise distance value of each target.

[0033] The present invention adopts a method combining rough and fine estimation to determine the precise distance of each target, and then realizes high-precision deformation monitoring through real-time dynamic measurement. Compared with the prior art, the advantages of the present invention are:

[0034] The present invention can realize multi-target monitoring and utilize the high resolution capability of the FMCW radar to realize simultaneous measurement of multiple targets.

[0035] The present invention has high measurement accuracy, combines rough estimation with precise estimation, and realizes high-precision distance measurement on the basis of deambiguation.

[0036] The present invention has high calculation efficiency and low calculation complexity and is easy for real-time processing by embedded systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0038] Figure 1 is a flow chart of an embodiment of the present invention;

[0039] Figure 2 is the real data continuous monitoring result of the first micro-motion target in one embodiment of the present invention;

[0040] Figure 3 is the real data continuous monitoring result of the second micro-motion target in one embodiment of the present invention;

[0041] Figure 4 It is a structural schematic diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention more clearly understood, the following will be used with drawings and detailed descriptions to clearly illustrate the spirit of the contents disclosed by the present invention. After understanding the embodiments of the contents of the present invention, any person skilled in the art can change and modify the techniques taught by the contents of the present invention without departing from the spirit and scope of the contents of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0043] Reference Figure 1 In one embodiment, a radar-based multi-target ranging method is provided, comprising:

[0044] (S1) sequentially acquiring echo signals of the frequency modulated continuous wave signals sequentially transmitted to the monitoring area and calculating the beat signals, and obtaining a one-dimensional spectrum by Fourier transform;

[0045] (S2) splicing the sequentially obtained one-dimensional spectra along the slow time to obtain a slow time-spectrum image, and separating the slow time-spectrum image corresponding to each target from the slow time-spectrum image;

[0046] (S3) estimating the frequency value of the frequency unit corresponding to each target based on the slow time-spectrum image corresponding to each target, and roughly estimating the distance of each target based on the frequency value of the frequency unit corresponding to each target;

[0047] (S4) estimating a phase value of a frequency unit corresponding to each target based on the slow time-spectrum image corresponding to each target, and precisely estimating a distance thereof based on the phase value of the frequency unit corresponding to each target;

[0048] (S5) The target distance roughly estimated and the target distance precisely estimated for each target are combined to estimate the precise distance value for each target.

[0049] Assume that the frequency modulated continuous wave signal sequentially transmitted to the monitoring area has a starting frequency of f0, a bandwidth of B, and a frequency modulation duration of T. In step (S1) of the present invention, the echo signals of the frequency modulated continuous wave signal sequentially transmitted to the monitoring area are sequentially obtained and the beat signal is calculated, and a one-dimensional spectrum is obtained by Fourier transform.

[0050] In step (S2) of one embodiment, the method for separating the slow time-spectrum images corresponding to each target from the slow time-spectrum image is: calculating the variance of each frequency unit in the slow time-spectrum image along the slow time, and determining the number of targets according to the variance; for the kth target, taking the frequency unit corresponding to the kth target in the slow time-spectrum image as the center, taking M distance units on both sides thereof, and separating the slow time-spectrum image corresponding to the kth target.

[0051] In step (S3) of one embodiment, the frequency value of the frequency unit corresponding to each target is estimated by the following formula:

[0052]

[0053] Where: Φ(n) is the phase of the nth sample value of the inverse Fourier transform of the slow time-spectrum image corresponding to the kth target, △T is the signal slow time sampling interval, and N is the number of IFFT points.

[0054] In step (S3) of an embodiment, the distance of each target is roughly estimated based on the frequency value of the frequency unit corresponding to each target, and the method is as follows:

[0055]

[0056] Where: C is the propagation speed of electromagnetic waves, is the frequency value of the frequency unit corresponding to the kth target, B is the bandwidth of the FM continuous wave signal, and T is the FM duration.

[0057] In step (S4) of an embodiment, the distance of each target is precisely estimated based on the phase value of the frequency unit corresponding to each target, and the method is as follows:

[0058]

[0059] Where: C is the propagation speed of electromagnetic waves; is the phase value of the frequency unit corresponding to the kth target, Φ(n) is the phase of the nth sample value of the inverse Fourier transform of the slow time-spectrum image corresponding to the kth target, N is the number of IFFT points; f0 is the starting frequency of the frequency modulated continuous wave signal.

[0060] In step (S5) of one embodiment, the precise distance value of each target is obtained by the following formula:

[0061]

[0062] in represents the floor function, The target distance discrete value obtained by roughly estimating the corresponding target (i.e., the value obtained in step (S4) ).

[0063] In order to verify the effectiveness of the high-precision long-distance deformation monitoring method based on radar proposed in the present invention, the present invention conducted an experiment. In this embodiment, for the real construction site slope deformation monitoring scenario, two trihedral corner reflectors are fixed at the slope deformation position, and non-contact measurement is performed in a light rain environment. The FMCW radar is used to sequentially transmit and receive frequency modulated continuous wave signals to the monitoring area, with a starting frequency f0 = 77 GHz, a bandwidth B = 3.86 GHz, and a frequency modulation duration T = 163.84 μs. This embodiment includes the following steps:

[0064] (S1) sequentially receiving echo signals of frequency modulated continuous wave signals sequentially transmitted to the monitoring area and calculating the beat signal, and obtaining a one-dimensional spectrum by using a 2048-point Fourier transform;

[0065] (S2) splicing the sequentially obtained one-dimensional spectra along slow time to obtain a slow time-spectrum image, calculating the variance of each frequency unit in the slow time-spectrum image along slow time, and determining the number of targets K according to the variance. In this embodiment, two regions with the largest variance are selected, that is, the number of targets is 2. Taking the frequency unit corresponding to the two targets as the center, M=100 distance units are taken on both sides to separate the slow time-spectrum images corresponding to the two targets;

[0066] (S3) estimating the frequency value of the frequency unit corresponding to each target based on the slow time-spectrum image corresponding to each target, and roughly estimating the distance of each target based on the frequency value of the frequency unit corresponding to each target;

[0067]

[0068] Where C is the propagation speed of electromagnetic waves, is the frequency value of the frequency unit corresponding to the kth target, Φ(n) is the phase of the nth sample value of the inverse Fourier transform (IFFT) of the slow time-spectrum image corresponding to the kth target along the spectrum dimension, and N=2048 is the number of IFFT points.

[0069] (S4) estimating a phase value of a frequency unit corresponding to each target based on the slow time-spectrum image corresponding to each target, and precisely estimating a distance thereof based on the phase value of the frequency unit corresponding to each target;

[0070]

[0071] in

[0072] (S5) The target distance roughly estimated and the target distance precisely estimated for each target are combined to estimate the precise distance value for each target.

[0073]

[0074] in Represents the floor function.

[0075] The precise distance value corresponding to the second target is obtained through steps (S3) to (S5).

[0076] Furthermore, steps (S1) to (S5) are repeated for the echo signals received sequentially for 300 seconds to estimate the precise distance value of each target at different times, and real-time dynamic deformation monitoring is achieved by monitoring the precise distance value of each target at different times. Figure 2 is the 300-second continuous monitoring result of the real data of the first micro-motion target in this embodiment; Figure 3 This is the 300-second continuous monitoring result of the real data of the second micro-motion target in this embodiment. The results show that the FMCW radar can accurately track the distance change using the method provided by the present invention. At different times, external construction and rain cause surface vibration and slope deformation, resulting in dynamic changes in the distance from the monitoring point to the radar. By accurately measuring the distance change using the radar echo signal, it is possible to monitor sub-millimeter-level micro-deformations, thereby achieving long-distance dynamic monitoring of the slope.

[0077] In one embodiment, a radar-based multi-target ranging device is provided, comprising:

[0078] The first module is used to sequentially obtain the echo signals of the frequency modulated continuous wave signals sequentially transmitted to the monitoring area and calculate the beat signals, and obtain the one-dimensional spectrum by Fourier transform;

[0079] The second module is used to splice the sequentially obtained one-dimensional spectra along the slow time to obtain a slow time-spectrum image, and separate the slow time-spectrum image corresponding to each target from the slow time-spectrum image;

[0080] The third module is used to estimate the frequency value of the frequency unit corresponding to each target based on the slow time-spectrum image corresponding to each target, and roughly estimate the distance of each target based on the frequency value of the frequency unit corresponding to each target;

[0081] The fourth module is used to estimate the phase value of the frequency unit corresponding to each target based on the slow time-spectrum image corresponding to each target, and accurately estimate the distance of each target based on the phase value of the frequency unit corresponding to each target;

[0082] The fifth module is used to combine the roughly estimated target distance of each target and the finely estimated target distance of each target to estimate the precise distance value of each target.

[0083] The methods for implementing the functions of the above modules can be implemented using the same methods as in the above embodiments, which will not be described in detail here.

[0084] In this embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 4As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store sample data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps of the radar-based multi-target ranging method in the above embodiment are implemented.

[0085] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0086] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the radar-based multi-target ranging method in the above embodiment when executing the computer program.

[0087] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the radar-based multi-target ranging method in the above embodiment are implemented.

[0088] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0089] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A radar-based multi-target ranging method, characterized in that: include: The echo signals of the frequency modulated continuous wave signals sequentially transmitted to the monitoring area are obtained in sequence and the beat signals are calculated, and the one-dimensional spectrum is obtained by Fourier transform; The one-dimensional spectra obtained in sequence are spliced ​​along the slow time to obtain a slow time-spectrum image, and the slow time-spectrum image corresponding to each target is separated from the slow time-spectrum image. The method is: for each frequency unit in the slow time-spectrum image, the variance is calculated along the slow time, and the number of targets is determined according to the variance. For the kth target, the frequency unit corresponding to the kth target in the slow time-spectrum image is taken as the center, and M distance units are taken on both sides of the frequency unit, and the slow time-spectrum image corresponding to the kth target is separated; Based on the slow time-spectrum image corresponding to each target, the frequency value of the frequency unit corresponding to each target is estimated, and based on the frequency value of the frequency unit corresponding to each target, the distance thereof is roughly estimated; The phase value of the frequency unit corresponding to each target is estimated based on the slow time-spectrum image corresponding to each target, and the distance of each target is precisely estimated based on the phase value of the frequency unit corresponding to each target; The target distance obtained by roughly estimating each target and the target distance obtained by fine estimating each target are combined to estimate the precise distance value of each target.

2. The radar-based multi-target ranging method according to claim 1, characterized in that: The frequency value of the frequency unit corresponding to each target is estimated by the following formula: in: is the inverse Fourier transform of the slow time-spectrum image corresponding to the kth target n The phase of the sampled value, △ T is the signal slow time sampling interval, N is the number of IFFT points.

3. The radar-based multi-target ranging method according to claim 2, characterized in that: The distance of each target is roughly estimated based on the frequency value of the frequency unit corresponding to each target. The method is as follows: in: C is the electromagnetic wave propagation speed, is the frequency value of the frequency unit corresponding to the kth target, B is the bandwidth of the FM continuous wave signal, T is the FM duration.

4. The radar-based multi-target ranging method according to claim 1, 2 or 3, characterized in that: The distance of each target is precisely estimated based on the phase value of the frequency unit corresponding to the target. The method is as follows: in: C is the propagation speed of electromagnetic waves; is the phase value of the frequency unit corresponding to the kth target, , is the inverse Fourier transform of the slow time-spectrum image corresponding to the kth target n The phase of the sampled values, N is the number of points of IFFT; is the starting frequency of the FM continuous wave signal.

5. The radar-based multi-target ranging method according to claim 4, characterized in that: The precise distance value of each target is obtained by the following formula: in , Represents the floor function.

6. A radar-based multi-target deformation monitoring method, characterized in that: The radar-based multi-target ranging method described in claim 1 is used to estimate the precise distance value of each target at different times, and real-time dynamic deformation monitoring is achieved by monitoring the precise distance value of each target at different times.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the radar-based multi-target ranging method according to claim 1 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the processor executes the computer program, the steps of the radar-based multi-target ranging method as claimed in claim 1 are implemented.

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