FMCW radar target distance high-precision measurement method fusing difference frequency signal and integral signal

Abstract

The invention relates to the technical field of FMCW radar ranging, and particularly discloses an FMCW radar target distance high-precision measurement method fusing a difference frequency signal and an integral signal, and the method comprises the steps: obtaining a discrete difference frequency signal; performing frequency shift processing on FFT conversion; a Toeplitz square matrix is constructed, eigenvalue decomposition denoising is carried out, and discrete difference frequency signals after denoising and frequency shifting are obtained; solving a primary integral signal of the denoised and frequency-shifted difference frequency signal; and constructing a generalized characteristic equation, solving a generalized characteristic value, and then obtaining the accurate distance of the measured target. According to the method, a barrier effect and frequency spectrum leakage existing in FFT transformation are solved, and meanwhile, a theoretical solution of the frequency of the difference frequency signal can be obtained, so that accurate solution of the target distance can be realized; moreover, the target displacement can be measured by directly utilizing the frequency of the difference frequency signal, so that the problem of phase winding existing in a phase interference method is effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of FMCW radar ranging, and in particular to a high-precision FMCW radar target distance measurement method that fuses a difference frequency signal and an integral signal. Background Art

[0002] FMCW radar has the unique advantages of non-contact and all-weather, and has been widely used in remote sensing mapping and transportation infrastructure monitoring in terms of ranging and displacement measurement. Its measurement principle is to receive and transmit microwaves with a certain modulation bandwidth and mix them to obtain a difference frequency signal, and then perform FFT transformation on the difference frequency signal to obtain the target distance spectrum, thereby achieving target ranging; further extract the phase of the measured target spectrum, and measure the target displacement based on the phase interferometry method. Among them, the distance resolution of FMCW radar is limited by the modulation bandwidth, and the traditional FFT method has fence effect and spectrum leakage problems. Therefore, how to improve the ranging accuracy of FMCW radar mainly lies in optimizing the ranging algorithm and the accurate solution of frequency.

[0003] The methods used in the existing methods are: Fast Fourier Transform (FFT): The FFT algorithm can convert time domain data into the frequency domain, so as to quickly and accurately analyze the frequency difference in the received echo signal, and then calculate the distance. FFT has the characteristics of fast calculation speed and high precision, and is suitable for real-time signal processing. Coherent accumulation: By accumulating and averaging the echo signals received multiple times, the signal-to-noise ratio of the signal can be significantly improved, thereby reducing the impact of noise on distance measurement and improving the ranging accuracy. Doppler filtering: Filter out the frequency difference of the echo signal caused by the speed of non-target objects, extract the echo signal of the target object, and reduce the interference of other stray signals. Phase difference differential method: The distance is calculated by analyzing the phase difference change between the received echo signal and the transmitted signal. This method has the advantages of high precision and real-time performance. However, although the use of advanced signal processing algorithms (such as FFT, coherent integration, etc.) can improve the ranging accuracy, it will also increase the computational complexity and put forward higher requirements on hardware performance. In some complex environments (such as severe multipath effects, strong electromagnetic interference, etc.), the above methods may not be able to completely eliminate errors, affecting the ranging accuracy, and the ranging of distant target objects may not be accurate enough.

[0004] In addition, in recent years, some scholars have used the prior condition of the sparsity of the target distance spectrum when measuring targets with microwave radar to conduct research on target distance super-resolution based on compressed sensing. However, it should be noted that the existing methods are all frequency optimization estimation methods, and the accurate solution of frequency has not been achieved. Moreover, in the implementation of compressed sensing, the stability of the reconstruction algorithm is easily affected by the sparsity of the signal and the observation matrix. In order to accurately restore the sparse signal, it is required that the atoms of the observation matrix have a low correlation. However, in practical applications, this ideal condition is often difficult to fully meet, which may lead to unstable reconstruction results. Moreover, microwave radar detectors are highly sensitive to the environment, such as terrain, buildings, etc., which will affect their detection performance. In complex environments, the sparsity of the target distance spectrum may be disturbed, thereby affecting the accuracy of super-resolution research based on compressed sensing. In particular, under the condition of severe noise pollution, the implementation and effectiveness of existing methods are greatly reduced. Summary of the invention

[0005] In order to solve the problems existing in the prior art, the present invention provides a high-precision measurement method for FMCW radar target distance that integrates difference frequency signals and integral signals. The method can obtain a theoretical solution for the difference frequency signal frequency while solving the fence effect and spectrum leakage existing in FFT transformation, thereby realizing accurate solution of target distance; in addition, the present invention can directly use the frequency of the difference frequency signal to realize the measurement of target displacement, thereby effectively solving the phase entanglement problem existing in the phase interference method. In particular, the present invention can realize the absolute value measurement of the distance between the target and the microwave radar, and can also solve the problem that the displacement data of the monitoring target is difficult to connect after the current microwave radar displacement monitoring system is powered off, that is, the data island effect, and solves the problems mentioned in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a high-precision FMCW radar target distance measurement method that fuses a difference frequency signal and an integral signal, comprising the following steps:

[0007] S1, obtaining discrete difference frequency signal;

[0008] S2, FFT transformation for frequency shift processing;

[0009] S3, construct a Toeplitz matrix, perform eigenvalue decomposition and denoising, and obtain a discrete difference frequency signal after denoising and frequency shifting;

[0010] S4, solving the primary integral signal of the difference frequency signal after denoising and frequency shifting;

[0011] S5. Construct a generalized characteristic equation, solve the generalized eigenvalue, and then obtain the accurate distance of the measured target.

[0012] Preferably, in step S1, the FMCW radar signal transmitter generates and transmits a signal with a starting frequency of f0 and a modulation period of T s , the linear frequency modulated continuous wave with modulation bandwidth B is reflected by the target at distance R and received by the radar signal receiver. After mixing and low-pass filtering, the difference frequency signal is obtained, which is

[0013] Among them, A IF is the amplitude of the difference frequency signal corresponding to the target under test; the subscript IF represents the difference frequency signal; K = B / T s is the modulation slope, τ = 2R / c is the time delay corresponding to the target under test, c is the speed of light, and n(t) is the noise;

[0014] With sampling frequency F s For the above difference frequency signal S IF (t) Discrete sampling is performed, and the number of sampling points is N = T s F s , the difference frequency signal after discrete sampling is obtained as:

[0015] Preferably, in step S2, the discretely sampled difference frequency signal S IF (i) Perform FFT transformation to obtain the range spectrum of the target being measured, and identify the peak point of the range spectrum as f max , with the frequency band f on the left side of the peak point max -Δf is the reference frequency, construct the frequency shift function Perform frequency shift processing, specifically: At the same time, the reference distance is

[0016] Preferably, in step S3, based on the frequency-shifted signal Construct the corresponding Toeplitz matrix Perform eigenvalue decomposition on a Toeplitz matrix For the eigenvalue matrix Correct it, keep its maximum eigenvalue, set the remaining eigenvalues ​​to zero, and get a new eigenvalue matrix Further according to the eigenvector matrix and the eigenvalue matrix Construct the Toeplitz matrix after denoising and frequency shifting Further obtain the discrete difference frequency signal after denoising and frequency shifting

[0017] Preferably, in step S4, the discrete difference frequency signal after denoising and frequency shifting is Perform an integration to get the integral signal

[0018] Preferably, in step S5, according to the above-mentioned integral signal Construct the corresponding Toeplitz matrix The generalized characteristic equation is established as ν is a generalized eigenvector, and I is a matrix whose elements are all 1;

[0019] Solve the generalized characteristic equation to obtain the eigenvalue matrix λ, and select its maximum eigenvalue λ max , and perform relationship conversion to obtain the precise distance of the measured target

[0020] The beneficial effects of the present invention are as follows: the method of the present invention is different from the traditional frequency estimation methods such as FFT, CZT, MUSIC, Zoom-FFT and MUSIC. While solving the fence effect and spectrum leakage existing in FFT transformation, the method can obtain the theoretical solution of the frequency of the difference frequency signal, and compared with the differential signal of the difference frequency signal, the integral signal used by the method of the present invention is not sensitive to noise, so that the target distance can be accurately solved; the present invention can realize the absolute value measurement of the distance between the measured target and the FMCW radar. Moreover, the method can also be extended to the field of bridge health monitoring, which can solve the phase entanglement problem existing in the traditional phase interferometry method to measure the target displacement, and simultaneously solve the data island effect problem caused by system power failure in actual engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a flowchart of the steps of the FMCW radar target distance high-precision measurement method by fusing the difference frequency signal and the integral signal in an embodiment of the present invention;

[0022] Figure 2 Schematic diagram of FFT result of the measured target distance in an embodiment of the present invention;

[0023] Figure 3 Schematic diagram of the result of the Zoom-FFT method of the measured target distance in an embodiment of the present invention;

[0024] Figure 4 Schematic diagram of the CZT method result of the measured target distance in an embodiment of the present invention;

[0025] Figure 5 The result diagram of the fused difference frequency signal and its integrated signal of the measured target distance in an embodiment of the present invention is shown;

[0026] Figure 6 Graph showing the relationship between the absolute error of the distance of the measured target and different noise contents in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] See also Figure 1-Figure 6 The present invention provides a technical solution: a high-precision FMCW radar target distance measurement method that combines a difference frequency signal and an integral signal, such as Figure 1 As shown, the following steps are included:

[0029] S1. Obtain discrete difference frequency signal:

[0030] In step S1, the FMCW radar signal transmitter generates and transmits a signal with a starting frequency of f0 and a modulation period of T. s , the linear frequency modulated continuous wave with modulation bandwidth B is reflected by the target at distance R and received by the radar signal receiver. After mixing and low-pass filtering, the difference frequency signal is obtained, which is

[0031] Among them, A IF is the amplitude of the difference frequency signal corresponding to the target under test; the subscript IF represents the difference frequency signal; K = B / T s is the modulation slope, τ = 2R / c is the time delay corresponding to the target under test, c is the speed of light, and n(t) is the noise;

[0032] With sampling frequency F s For the above difference frequency signal S IF (t) Discrete sampling is performed, and the number of sampling points is N = T s F s , the difference frequency signal after discrete sampling is obtained as:

[0033] S2, FFT transformation for frequency shift processing:

[0034] In step S2, the discretely sampled difference frequency signal S IF (i) Perform FFT transformation to obtain the range spectrum of the target being measured, and identify the peak point of the range spectrum as f max , with the frequency band f on the left side of the peak point max -Δf is the reference frequency, construct the frequency shift function Perform frequency shift processing, specifically: At the same time, the reference distance is

[0035] S3, construct a Toeplitz matrix, perform eigenvalue decomposition and denoising, and obtain the discrete difference frequency signal after denoising and frequency shifting:

[0036] In step S3, based on the frequency-shifted signal Construct the corresponding Toeplitz matrix Perform eigenvalue decomposition on a Toeplitz matrix For the eigenvalue matrix Correct it, keep its maximum eigenvalue, set the remaining eigenvalues ​​to zero, and get a new eigenvalue matrix Further according to the eigenvector matrix and the eigenvalue matrix Construct the Toeplitz matrix after denoising and frequency shifting Further obtain the discrete difference frequency signal after denoising and frequency shifting

[0037] S4. Calculate the first integral signal of the difference frequency signal after denoising and frequency shifting:

[0038] In step S4, the discrete difference frequency signal after denoising and frequency shifting is Perform an integration to get the integral signal

[0039] S5. Construct the generalized characteristic equation, solve the generalized eigenvalue, and then obtain the accurate distance of the measured target:

[0040] In step S5, according to the above integrated signal Construct the corresponding Toeplitz matrix The generalized characteristic equation is established as is a generalized eigenvector, and I is a matrix whose elements are all 1;

[0041] Solve the generalized characteristic equation to obtain the eigenvalue matrix λ, and select its maximum eigenvalue λ max , and perform relationship conversion to obtain the precise distance of the measured target

[0042] Example verification

[0043] The FMCW radar target distance high-precision measurement method integrating the difference frequency signal and the integral signal in the embodiment of the present invention is used for example verification, as follows:

[0044] Let the FMCW radar transmit a starting frequency of f0 = 9.4 GHz; the modulation bandwidth is B = 200 MHz; the modulation period is T s = 0.5ms frequency modulated continuous wave signal. The target is located at R = 10.12345m. The transmitted signal is received after being reflected by the target. Suppose the sampling frequency f s =4MHz, the corresponding number of sampling points is N=2000, and a discrete difference frequency signal can be obtained.

[0045] Directly perform N-point FFT transformation on the obtained discrete difference frequency signal to obtain the range spectrum of the measured target. The result is as follows: Figure 2 As shown in Figure 2, the distance error of the measured target is large. The Zoom-FFT method is further used to refine the spectrum, and the refined target distance spectrum is obtained as follows: Figure 3 As shown in Figure 2, there is still an error in the distance of the measured target after refinement; secondly, according to the peak point f of the distance spectrum of the measured target max , the frequency band range is selected as [f max -Δf f max +Δf], the signal in the selected frequency band is refined by a factor of 10, and the distance spectrum of the measured target based on the CZT method is obtained. The results are as follows Figure 4 As shown, there is still an error in the distance of the identified target;

[0046] Finally, with f max -Δf is used as the reference frequency for frequency shift processing, and denoising is performed based on eigenvalue decomposition. The denoised signal is integrated once to obtain an integral signal. The generalized characteristic equation is constructed and the generalized eigenvalue is solved. The exact solution of the beat frequency is 2.69958664e+04, corresponding to a distance of 10.1234499m for the target being measured. The results are as follows Figure 5 shown.

[0047] Assume that the signal-to-noise ratio has a mean of 0 and a variance of σ 2 Gaussian white noise is added to analyze the effect of signal-to-noise ratio (SNR) on frequency solution. Under each signal-to-noise ratio, 100 Monte Carlo tests are performed independently. Different degrees of Gaussian white noise (1%-30%) are added to obtain the absolute error of target distance recognition under different signal-to-noise ratios. The results are shown in Figure 6 When 25% Gaussian white noise is added, the error of target distance recognition is greater than mm level due to the influence of noise; as the noise content decreases, the distance recognition error gradually decreases, and the FMCW radar target distance accurate solution method that fuses the difference frequency signal and its integral signal has excellent performance.

[0048] In the embodiments provided in the embodiments of the present invention, it should be noted that, in this article, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0049] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0050] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0051] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0052] The "first\second" mentioned in the embodiments is only to distinguish similar objects, and does not represent a specific order for the objects. It is understandable that the "first\second" can be interchanged with the specific order or sequence where permitted. It should be understood that the objects distinguished by "first\second" can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than those illustrated or described herein.

[0053] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A high-precision FMCW radar target distance measurement method that combines a difference frequency signal and an integral signal, characterized in that: The steps include: S1, obtaining discrete difference frequency signal; S2, FFT transformation for frequency shift processing; S3, construct a Toeplitz matrix, perform eigenvalue decomposition and denoising, and obtain a discrete difference frequency signal after denoising and frequency shifting; S4, solving the primary integral signal of the difference frequency signal after denoising and frequency shifting; S5. Construct a generalized characteristic equation, solve the generalized eigenvalue, and then obtain the accurate distance of the measured target.

2. The method for high-precision measurement of FMCW radar target distance by fusing difference frequency signal and integral signal according to claim 1 is characterized in that: In step S1, the FMCW radar signal transmitter generates and transmits a signal with a starting frequency of f0 and a modulation period of T. s , the linear frequency modulated continuous wave with modulation bandwidth B is reflected by the target at distance R and received by the radar signal receiver. After mixing and low-pass filtering, the difference frequency signal is obtained, which is t∈(0,T s ); Among them, A IF is the amplitude of the difference frequency signal corresponding to the target under test; the subscript IF represents the difference frequency signal; K = B / T s is the modulation slope, τ = 2R / c is the time delay corresponding to the target under test, c is the speed of light, and n(t) is the noise; With sampling frequency F s For the above difference frequency signal S IF (t) Discrete sampling is performed, and the number of sampling points is N = T s F s , the difference frequency signal after discrete sampling is obtained as: i∈(1,N).

3. The method for high-precision measurement of FMCW radar target distance by fusing difference frequency signal and integral signal according to claim 1, characterized in that: In step S2, the discretely sampled difference frequency signal S IF (i) Perform FFT transformation to obtain the range spectrum of the target being measured, and identify the peak point of the range spectrum as f max , with the frequency band f on the left side of the peak point max -Δf is the reference frequency, construct the frequency shift function Perform frequency shift processing, specifically: At the same time, the reference distance is 4. The method for high-precision measurement of FMCW radar target distance by fusing difference frequency signal and integral signal according to claim 1, characterized in that: In step S3, based on the frequency-shifted signal Construct the corresponding Toeplitz matrix Perform eigenvalue decomposition on a Toeplitz matrix For the eigenvalue matrix Correct it, keep its maximum eigenvalue, set the remaining eigenvalues ​​to zero, and get a new eigenvalue matrix Further according to the eigenvector matrix and the eigenvalue matrix Construct the Toeplitz matrix after denoising and frequency shifting Further obtain the discrete difference frequency signal after denoising and frequency shifting 5. The FMCW radar target distance high-precision measurement method of fusing the difference frequency signal and the integral signal according to claim 1 is characterized in that: In step S4, the discrete difference frequency signal after denoising and frequency shifting is Perform an integration to obtain the integral signal 6. The FMCW radar target distance high-precision measurement method by fusing the difference frequency signal and the integral signal according to claim 1 is characterized in that: In step S5, according to the above integrated signal Construct the corresponding Toeplitz matrix The generalized characteristic equation is established as ν is a generalized eigenvector, and I is a matrix whose elements are all 1; Solve the generalized characteristic equation to obtain the eigenvalue matrix λ, and select its maximum eigenvalue λ max , and perform relationship conversion to obtain the precise distance of the measured target

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