Target speed accurate calculation method based on frequency mixing signal and primary integral signal thereof

Abstract

The invention belongs to the technical field of target accurate speed measurement, and discloses a target speed accurate calculation method based on a frequency mixing signal and a primary integral signal thereof, and the method comprises the following steps: S1, obtaining a discrete frequency mixing signal; s2, acquiring a low-order discrete frequency mixing signal after frequency shift; s3, acquiring a primary integral signal of the low-order discrete mixing signal; step S4, constructing a Hankel square matrix; s5, constructing a generalized characteristic equation; and step S6, solving the generalized characteristic equation. Different from a traditional frequency estimation method, the target speed accurate calculation method based on the frequency mixing signal and the primary integral signal of the frequency mixing signal is adopted, the method is not limited by the frequency resolution while the barrier effect and spectrum leakage existing in FFT transformation are solved, the integral signal of the frequency mixing signal is adopted, and the target speed accuracy is improved. Accurate solving of the target speed is achieved, and noise resistance is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of target precise speed measurement, and in particular to a method for accurately calculating target speed based on a mixing signal and a primary integral signal thereof. Background Art

[0002] In the field of traffic speed measurement, continuous wave radar has the advantages of simple equipment, light weight, high speed measurement accuracy and no close-range blind spots, and has been widely used in the speed measurement of vehicle targets. With the development of digital signal processing technology, continuous wave radar mainly uses the digital phase comparison method based on FFT transformation to measure speed, and its speed measurement accuracy is related to spectrum estimation, that is, frequency resolution.

[0003] Radar signal processing usually uses spectrum estimation. Discrete Fourier transform (DFT), as a basic method in classical spectrum estimation theory, was originally used to calculate radar mixing to extract target distance. Subsequently, the development of fast Fourier transform (FFT) significantly enhanced the application of DFT in frequency domain analysis. However, when there is a fixed sampling interval and a finite length, spectrum leakage and fence effect seriously affect the frequency estimation accuracy of FFT, resulting in ranging errors. To solve these problems, many studies have focused on interpolation techniques, that is, reducing spectrum leakage and fence effect through window functions and interpolation. Although they are popular, the accuracy of interpolation methods is low when there are coherent signals in the spectrum. At present, frequency estimation methods are mainly divided into time domain and frequency domain methods. Time domain methods include maximum likelihood (ML) algorithm, autoregressive (AR) spectrum estimation method, multiple signal classification (MUSIC) algorithm and signal parameter estimation with rotation invariant technique (ESPRIT) algorithm. The above methods each have their own advantages and disadvantages. For example, the ML method has high computational complexity; the AR spectrum estimation method is easily affected by noise and outliers; the MUSIC algorithm has limitations when processing coherent signal sources and has high computational complexity; the ESPRIT algorithm has limitations in applications with small sample sizes, etc.

[0004] Relatively speaking, the frequency domain method is more suitable for real-time signal processing because of its small amount of calculation and high efficiency. In essence, it uses FFT transformation and frequency refinement technology for accurate frequency estimation. Frequency domain methods mainly include amplitude ratio method, neighbor spectrum refinement method, autocorrelation method and spectrum line fitting method. Although these methods are simple to calculate, they have low estimation accuracy and are easily affected by the target distance. Unlike FFT-based techniques, matrix-based singular value decomposition (SVD) and singular spectrum decomposition (SSD) aim to represent the signal as a linear combination of basic variable modes without redundant harmonic components. Although these techniques do not provide spectrum estimation, they act as powerful denoising filters that can separate autocorrelation features from random features. In addition, wavelet transform (WT) and Hilbert-Huang transform (HHT) are often used to extract signal features, but they cannot accurately calculate the frequency of multi-frequency signals.

[0005] In order to achieve accurate calculation of the frequency of the mixing signal, this paper proposes an accurate calculation method of the target speed based on the mixing signal and its first integral signal based on basic theoretical calculation, which can achieve accurate solution of the target speed. Summary of the invention

[0006] The purpose of the present invention is to provide a method for accurately calculating the target speed based on a mixing signal and its first integrated signal. Different from the traditional frequency estimation method, this method is not limited by the frequency resolution while solving the fence effect and spectrum leakage existing in the FFT transform. It uses the integrated signal of the mixing signal to achieve accurate solution of the target speed and has noise resistance.

[0007] To achieve the above object, the present invention provides a method for accurately calculating a target speed based on a mixing signal and its first integral signal, comprising the following steps:

[0008] Step S1, obtaining a discrete mixing signal;

[0009] Step S2, obtaining a low-order discrete mixing signal after frequency shifting;

[0010] Step S3, obtaining a primary integration signal of the low-order discrete mixing signal;

[0011] Step S4, constructing a Hankel matrix;

[0012] Step S5, constructing a generalized characteristic equation;

[0013] Step S6: Solve the generalized characteristic equation.

[0014] Preferably, in step S1, a discrete mixing signal is obtained, and the specific process is as follows:

[0015] Step S11: transmit a single-frequency continuous wave radar with a starting frequency of f0 and a period of T c , with an amplitude of A T , the initial phase is The microwave signal is as follows:

[0016]

[0017] Step S12: After being reflected by a target with a speed of v, the received signal is received, as shown below:

[0018]

[0019] Where, τ = 2vt / c is the delay of the measurement target, c = 3.0×10 8 m / s is the speed of light, k is the echo attenuation coefficient;

[0020] Step S13: Mix the received and transmitted signals and ignore the influence of the signal amplitude to obtain a mixed signal, as shown below:

[0021]

[0022] in, is the Doppler frequency;

[0023] Step S14: Perform digital AD discrete sampling on the mixed signal, with a sampling frequency of f s , the number of sampling points is N, and the mixed signal after discrete sampling is obtained as follows:

[0024]

[0025] Preferably, in step S2, the low-order discrete mixing signal after frequency shifting is obtained, and the specific process is as follows:

[0026] Step S21: IF (n) Performing N-point FFT transformation to obtain the spectrum information of the target;

[0027] Step S22: Select the peak point f of the target spectrum to be measured max , with its left spectrum point is the reference spectrum point, where df = 1 / T c ;

[0028] Step S23: construct a reference signal as follows:

[0029]

[0030] Step S24: frequency-shift the discrete mixing signal according to the reference signal to obtain a low-order discrete mixing signal, as shown below:

[0031]

[0032] in,

[0033] Preferably, in step S3, the low-order discrete mixing signal is integrated once to obtain an integrated signal as shown below:

[0034]

[0035] Preferably, in step S4, according to the above low-order discrete mixing signal and its first integrated signal Construct Hankel matrices H and D, with the mth row and lth column of matrix H as follows:

[0036]

[0037] Preferably, in step S5, a generalized characteristic equation is established according to the above Hankel matrices H and D, as shown below:

[0038]

[0039] The matrix E is a square matrix whose elements are all 1.

[0040] Preferably, in step S6, the generalized characteristic equation is solved to obtain an eigenvalue matrix, and its maximum eigenvalue is selected. And perform relationship conversion to obtain the precise speed of the target being measured, as shown below:

[0041]

[0042] Therefore, the present invention adopts the above-mentioned method for accurately calculating the target speed based on the mixing signal and its first integrated signal. Different from the traditional frequency estimation method, this method is not limited by the frequency resolution while solving the fence effect and spectrum leakage existing in the FFT transform. It uses the integral signal of the mixing signal to achieve accurate solution of the target speed and is noise-resistant.

[0043] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a flow chart of the target speed accurate calculation method based on the mixing signal and its first integration signal of the present invention. DETAILED DESCRIPTION

[0045] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0046] like Figure 1 As shown, the target speed accurate calculation method based on the mixing signal and its first integration signal of the present invention comprises the following steps:

[0047] Step S1, obtaining a discrete mixing signal;

[0048] Step S2, obtaining a low-order discrete mixing signal after frequency shifting;

[0049] Step S3, obtaining a primary integration signal of the low-order discrete mixing signal;

[0050] Step S4, constructing a Hankel matrix;

[0051] Step S5, constructing a generalized characteristic equation;

[0052] Step S6: Solve the generalized characteristic equation.

[0053] Example

[0054] Step S1, obtaining a discrete mixing signal.

[0055] Step S11: transmit a single-frequency continuous wave radar with a starting frequency of f0 and a period of T c , with an amplitude of A T , the initial phase is The microwave signal is as follows:

[0056]

[0057] Step S12: After being reflected by a target with a speed of v, the received signal is received, as shown below:

[0058]

[0059] Where, τ = 2vt / c is the delay of the measurement target, c = 3.0×10 8 m / s is the speed of light, and k is the echo attenuation coefficient.

[0060] Step S13: Mix the received and transmitted signals and ignore the influence of the signal amplitude to obtain a mixed signal, as shown below:

[0061]

[0062] in, is the Doppler frequency.

[0063] Step S14: Perform digital AD discrete sampling on the mixed signal, with a sampling frequency of f s , the number of sampling points is N, and the mixed signal after discrete sampling is obtained as follows:

[0064]

[0065] Step S2: Obtain a low-order discrete mixing signal after frequency shifting.

[0066] Step S21: IF (n) Perform N-point FFT transformation to obtain the spectrum information of the target under test.

[0067] Step S22: Select the peak point f of the target spectrum to be measured max , with its left spectrum point is the reference spectrum point, where df = 1 / T c .

[0068] Step S23: construct a reference signal as follows:

[0069]

[0070] Step S24: frequency-shift the discrete mixing signal according to the reference signal to obtain a low-order discrete mixing signal, as shown below:

[0071]

[0072] in,

[0073] Step S3: Obtain a first integration signal of the low-order discrete mixing signal.

[0074] The above low-order discrete mixing signal is integrated once to obtain an integrated signal as shown below:

[0075]

[0076] Step S4: construct a Hankel matrix.

[0077] According to the above low-order discrete mixing signal and its first integrated signal Construct the corresponding Hankel matrices H and D.

[0078] Among them, the mth row and lth column of the square matrix H is as follows:

[0079]

[0080] Step S5: construct a generalized characteristic equation.

[0081] According to the above Hankel matrices H and D, the generalized characteristic equation is established as follows:

[0082]

[0083] The matrix E is a square matrix whose elements are all 1.

[0084] Step S6: Solve the generalized characteristic equation.

[0085] Solve the above generalized characteristic equation to obtain the eigenvalue matrix, and select its maximum eigenvalue And perform relationship conversion to obtain the precise speed of the target being measured, as shown below:

[0086]

[0087] Therefore, the present invention adopts the above-mentioned method for accurately calculating the target speed based on the mixing signal and its first integrated signal. Different from the traditional frequency estimation method, this method is not limited by the frequency resolution while solving the fence effect and spectrum leakage existing in the FFT transform. It uses the integral signal of the mixing signal to achieve accurate solution of the target speed and is noise-resistant.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for accurately calculating the target speed based on a mixing signal and its first integral signal, characterized in that: The following steps are involved: Step S1, obtaining a discrete mixing signal; Step S2, obtaining a low-order discrete mixing signal after frequency shifting; Step S3, obtaining a primary integration signal of the low-order discrete mixing signal; Step S4, constructing a Hankel matrix; Step S5, constructing a generalized characteristic equation; Step S6: Solve the generalized characteristic equation.

2. The method for accurately calculating the target speed based on the mixing signal and its first integral signal according to claim 1, characterized in that: In step S1, a discrete mixing signal is obtained, and the specific process is as follows: Step S11: transmit a single-frequency continuous wave radar with a starting frequency of f0 and a period of T c , with an amplitude of A T , the initial phase is The microwave signal is as follows: Step S12: After being reflected by a target with a speed of v, the received signal is received, as shown below: Where, τ = 2vt / c is the time delay of the measurement target, c = 3.0×10 8 m / s is the speed of light, k is the echo attenuation coefficient; Step S13: Mix the received and transmitted signals and ignore the influence of the signal amplitude to obtain a mixed signal, as shown below: in, is the Doppler frequency; Step S14: Perform digital AD discrete sampling on the mixed signal, with a sampling frequency of f s , the number of sampling points is N, and the mixed signal after discrete sampling is obtained as follows:

3. The method for accurately calculating the target speed based on the mixing signal and its first integral signal according to claim 2, characterized in that: In step S2, the low-order discrete mixing signal after frequency shift is obtained, and the specific process is as follows: Step S21: IF (n) Performing N-point FFT transformation to obtain the spectrum information of the target; Step S22: Select the peak point f of the target spectrum to be measured max , with its left spectrum point is the reference spectrum point, where df = 1 / T c ; Step S23: construct a reference signal as follows: Step S24: frequency-shift the discrete mixing signal according to the reference signal to obtain a low-order discrete mixing signal, as shown below: in, 4. The method for accurately calculating the target speed based on the mixing signal and its first integral signal according to claim 3, characterized in that: In step S3, the low-order discrete mixing signal is integrated once to obtain an integrated signal, as shown below:

5. The method for accurately calculating the target speed based on the mixing signal and its first integral signal according to claim 4, characterized in that: In step S4, according to the low-order discrete mixing signal and its first integrated signal Construct Hankel matrices H and D, with the mth row and lth column of matrix H as follows:

6. The method for accurately calculating the target speed based on the mixing signal and its first integral signal according to claim 5, characterized in that: In step S5, a generalized characteristic equation is established based on the above Hankel matrices H and D, as shown below: The matrix E is a square matrix whose elements are all 1.

7. The method for accurately calculating the target speed based on the mixing signal and its first integral signal according to claim 6, characterized in that: In step S6, the generalized characteristic equation is solved to obtain an eigenvalue matrix, and its maximum eigenvalue is selected. And perform relationship conversion to obtain the precise speed of the target being measured, as shown below:

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