Liquid level radar adaptive adjustment method and system based on coherent accumulation, and medium

Abstract

The application discloses a liquid level radar adaptive adjustment method and system based on coherent accumulation and a medium, relates to the technical field of radar detection, and aims to solve the problem that if the phase or amplitude of an interference signal is similar to that of a target signal, the accumulation of the interference signal is caused, and the accuracy of a measurement result is affected.The application controls the number of coherent accumulations required at different distances by means of a required signal-to-noise ratio, thereby solving the problem of waste of the number of coherent accumulations at different distances, reducing the coherent accumulation time, reducing the accumulation of the interference signal, optimizing the radar computing power, optimizing the time for obtaining distance information in the near end, ensuring the timeliness of the near end and the accuracy of the far end, and improving the accuracy of the measurement result.

Description

Technical Field

[0001] This invention relates to the field of radar detection technology, specifically to an adaptive adjustment method, system, and medium for liquid level radar based on coherent accumulation. Background Technology

[0002] Radar ranging is a commonly used technique for measuring the distance between a target object and a radar system. It is widely used in many applications, including aviation, aerospace, navigation, military, and meteorology. Radar ranging is also a common application in oil tank level measurement. Accurate measurement of oil tank levels is crucial for the petroleum industry and tank management.

[0003] Radar ranging, a non-contact measurement technology, measures the liquid level in an oil tank by reflecting radio waves back to the tank, without physical contact. This non-contact method helps reduce equipment wear and contamination, improving measurement reliability and durability. Radar ranging offers high accuracy and stability in oil tank level measurement. By precisely measuring the round-trip time of the electromagnetic waves, the liquid level can be accurately calculated. Furthermore, radar ranging technology is less affected by temperature changes, gas environments, and liquid properties, maintaining measurement stability. Accurate measurement of oil tank levels is crucial for ensuring the safe operation of oil tanks. Radar ranging technology enables remote monitoring and control, allowing level data to be transmitted in real-time to a central control system, thus enabling real-time monitoring and alarm functions for oil tank levels. This helps in the timely detection of potential problems and leaks, allowing for appropriate measures to protect the environment and personnel safety.

[0004] Coherent accumulation is a commonly used signal processing technique in radar ranging. It improves measurement accuracy and stability, and reduces the impact of noise on the results. Coherent accumulation utilizes the radar system to continuously transmit a series of pulse signals with the same phase but random amplitudes. After receiving the target echo signal, the amplitude and phase information of the target echo signal can be extracted through phase comparison and accumulation calculation. In coherent accumulation, multiple echo signals are accumulated through summation or averaging. By comparing the phases and accumulating the amplitudes of multiple received echo signals, the influence of noise can be reduced, the strength of the target signal can be enhanced, and the accuracy of the measurement can be improved. Coherent accumulation can suppress random noise because the amplitude and phase of noise vary randomly, while the target signal has a certain phase stability. Through multiple accumulations and averaging, the randomness of noise is canceled out, while the stability of the target signal is enhanced, thereby improving the signal-to-noise ratio (SNR). By processing the accumulated target echo signal, the target's range information can be extracted.

[0005] Increasing the number of coherent accumulation cycles leads to longer measurement times. Each accumulation cycle requires receiving and processing multiple echo signals; a higher accumulation cycle results in a longer overall measurement time. This may be unsuitable for applications requiring real-time measurement or tracking rapidly changing targets. A high number of coherent accumulation cycles also means more computational and storage resources are needed to process and store multiple echo signals. This may require higher-performance processors and larger-capacity memory, increasing system complexity and cost. During coherent accumulation, if the target moves within different accumulation cycles, the accumulated signals can overlap, causing ambiguity. This can affect measurement accuracy, especially for rapidly moving targets. Strong interference or clutter in the environment can also accumulate and sum. If the interference signal is similar in phase or amplitude to the target signal, it can accumulate, further affecting the accuracy of the measurement results. Summary of the Invention

[0006] The purpose of this invention is to address the problem in the prior art that if the phase or amplitude of the interference signal is similar to that of the target signal, the interference signal will accumulate, thereby affecting the accuracy of the measurement results. The invention proposes an adaptive adjustment method, system, and medium for liquid level radar based on coherent accumulation.

[0007] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0008] An adaptive adjustment method for liquid level radar based on coherent accumulation is provided, the method comprising:

[0009] Obtain the actual signal-to-noise ratio And the true value of distance R, and using the relationship between distance, signal-to-noise ratio and coherent accumulation number D, the coherent accumulation number D is obtained. The relationship between distance, signal-to-noise ratio and coherent accumulation number D is expressed as:

[0010]

[0011] The relationship between the distance, signal-to-noise ratio, and the number of coherent accumulations D is obtained through the following steps:

[0012] Step 1: Obtain the echo signal r(t) after reflection from the liquid surface, and then process the echo signal r(t) by removing the carrier frequency and descrambling to obtain the signal r′(t). Then, differentiate the signal r′(t) to obtain the time τ when the echo of the transmitted signal arrives at the radar.

[0013] Step 2: Based on the time τ it takes for the echo of the transmitted signal to reach the radar, and combined with the speed of light c, obtain the distance between the liquid surface and the radar. The echo signal r(t) is accumulated D times to obtain the distance matrix. Where k is the total number of accumulated distance data points. R is the true distance value, n m It is additive white Gaussian noise;

[0014] Step 3: Based on the echo signal r(t), L pulses are coherently accumulated to obtain the ranging accuracy, which is expressed as:

[0015]

[0016] Where SNR is the signal-to-noise ratio at each sampling point, LP·SNR is the signal-to-noise ratio at the peak of the liquid surface after coherent accumulation and Fourier transform, and B is the signal bandwidth after sampling.

[0017] The bandwidth B of the sampled signal is expressed as:

[0018]

[0019] Among them, B T The bandwidth of the signal before sampling is given, P is the number of sampling points, and f is the signal bandwidth before sampling. s T is the sampling frequency. all α is the total sampling time, and α is the signal frequency modulation slope;

[0020] This leads to the relationship between ranging accuracy and signal-to-noise ratio, expressed as:

[0021]

[0022] in, γ is an intermediate variable;

[0023] The relationship between the final ranging accuracy and the signal-to-noise ratio is expressed as:

[0024]

[0025] Step 4: For the distance matrix For all elements in the set, calculate the average y, which is expressed as:

[0026]

[0027] Step 5: Take the standard deviation of the mean y. The standard deviation is expressed as:

[0028]

[0029] Combining the 3σ principle, the ranging accuracy is obtained, which is expressed as:

[0030]

[0031] Based on the relationship between the final overall ranging accuracy and the signal-to-noise ratio, and get:

[0032]

[0033] Based on ranging accuracy and actual signal-to-noise ratio The relationship between distance, signal-to-noise ratio, and the number of coherent accumulations D is obtained, expressed as:

[0034]

[0035] Furthermore, the steps for obtaining the echo signal r(t) after reflection from the liquid surface are as follows:

[0036] Step 1: Use FMCW radar to transmit a signal, wherein the transmitted signal is a frequency-modulated continuous wave signal;

[0037] Step 2: After reflection from the liquid surface, the received signal is obtained, namely the echo signal r(t) after reflection from the liquid surface.

[0038] Furthermore, the FMCW radar transmission signal is represented as follows:

[0039]

[0040] Among them, f o Let α be the signal carrier frequency, t be the signal modulation slope, j be the transmission time, and T be the imaginary unit.

[0041] Furthermore, the received signal is represented as:

[0042]

[0043]

[0044] Where ξ represents the propagation attenuation of the electromagnetic wave and the intensity of the signal reflected from the liquid surface.

[0045] Furthermore, the echo signal r(t) after carrier frequency removal and descrambling processing is expressed as follows:

[0046]

[0047] Furthermore, the total sampling time T all Represented as:

[0048]

[0049] The liquid level radar adaptive adjustment system based on coherent accumulation includes: an echo receiving module, a coherent accumulation module, and an adjustment module.

[0050] The echo receiving module is used to acquire the echo signal r(t) reflected from the liquid surface. After removing the carrier frequency and descrambling the echo signal r(t), the signal r′(t) is obtained. Then, the derivative of the signal r′(t) is calculated to obtain the time τ when the echo of the transmitted signal arrives at the radar. Based on the time τ when the echo of the transmitted signal arrives at the radar, and combined with the speed of light c, the distance between the liquid surface and the radar is obtained. The echo signal r(t) is accumulated D times to obtain the distance matrix. Where k is the total number of accumulated distance data points. R is the true distance value, n m It is additive white Gaussian noise;

[0051] The coherent accumulation module is used to coherently accumulate L pulses based on the echo signal r(t) to obtain the ranging accuracy, which is expressed as:

[0052]

[0053] Where SNR is the signal-to-noise ratio at each sampling point, LP·SNR is the signal-to-noise ratio at the peak of the liquid surface after coherent accumulation and Fourier transform, and B is the signal bandwidth after sampling.

[0054] The bandwidth B of the sampled signal is expressed as:

[0055]

[0056] Among them, B T The bandwidth of the signal before sampling is given, P is the number of sampling points, and f is the signal bandwidth before sampling. s T is the sampling frequency. all α is the total sampling time, and α is the signal frequency modulation slope;

[0057] This leads to the relationship between ranging accuracy and signal-to-noise ratio, expressed as:

[0058]

[0059] in, γ is an intermediate variable;

[0060] The relationship between the final ranging accuracy and the signal-to-noise ratio is expressed as:

[0061]

[0062] The adjustment module is used for adjusting the distance matrix. For all elements in the set, calculate the average y, which is expressed as:

[0063]

[0064] Take the standard deviation of the mean y. The standard deviation is expressed as:

[0065]

[0066] Combining the 3σ principle, the ranging accuracy is obtained, which is expressed as:

[0067]

[0068] Based on the relationship between the final overall ranging accuracy and the signal-to-noise ratio, and get:

[0069]

[0070] Based on ranging accuracy and actual signal-to-noise ratio The relationship between distance, signal-to-noise ratio, and the number of coherent accumulations D is obtained, expressed as:

[0071]

[0072] according to The distance is given by the true value R, and the coherent accumulation number D is obtained by using the relationship between distance, signal-to-noise ratio and coherent accumulation number D.

[0073] Furthermore, the steps for obtaining the echo signal r(t) after reflection from the liquid surface are as follows:

[0074] Step 1: Use FMCW radar to transmit a signal, wherein the transmitted signal is a frequency-modulated continuous wave signal;

[0075] Step 2: After reflection from the liquid surface, the received signal is obtained, namely the echo signal r(t) after reflection from the liquid surface.

[0076] Furthermore, the FMCW radar transmission signal is represented as follows:

[0077]

[0078] Among them, f o α is the signal carrier frequency, t is the signal modulation slope, j is the transmission time, and T represents the total duration of the transmitted signal in one cycle.

[0079] The received signal is represented as:

[0080]

[0081]

[0082] Where ξ represents the propagation attenuation of the electromagnetic wave and the intensity of the signal reflected from the liquid surface;

[0083] The echo signal r(t) after carrier frequency removal and descrambling processing is expressed as follows:

[0084]

[0085] The total sampling time T all Represented as:

[0086]

[0087] The liquid level radar adaptive adjustment medium based on coherent accumulation includes a computer-readable program for performing the method as claimed in any one of claims 1 to 6.

[0088] The beneficial effects of this invention are:

[0089] This application controls the number of coherent accumulations required at different distances by controlling the required signal-to-noise ratio, thereby solving the problem of wasted coherent accumulation times at different distances and reducing coherent accumulation time, which in turn reduces the accumulation of interference signals. While optimizing radar computing power, it can also optimize the time for obtaining distance information at the near end, ensuring the timeliness of the near end and the accuracy of the far end, thereby improving the accuracy of the measurement results.

[0090] This application utilizes the relationship between the standard deviation and accuracy of statistics to effectively adjust the number of coherent accumulation iterations, reducing the coherent accumulation time for short-range detection while ensuring accuracy and signal-to-noise ratio for long-range detection. This application can effectively improve the detection accuracy and performance of radar systems. Attached Figure Description

[0091] Figure 1 This is the overall flowchart of this application;

[0092] Figure 2 A schematic diagram showing the signal-to-noise ratio of different maximum coherent accumulation times with an accuracy of 1 mm.

[0093] Figure 3 Schematic diagram of signal-to-noise ratio for different maximum coherent accumulation times with an accuracy of 1.5mm;

[0094] Figure 4 Schematic diagram of signal-to-noise ratio for different maximum coherent accumulation times with an accuracy of 2mm;

[0095] Figure 5 A graph showing the difference between theoretical and actual values. Detailed Implementation

[0096] It should be noted that, where there is no conflict, the various embodiments disclosed in this application can be combined with each other.

[0097] Specific implementation method one: Refer to Figure 1This embodiment is described in detail. Step 1 of this embodiment is as follows: Obtain the echo signal r(t) after reflection from the liquid surface, and after removing the carrier frequency and descrambling the echo signal r(t), obtain the signal r′(t). Then, perform differentiation on the signal r′(t) to obtain the time τ when the echo of the transmitted signal arrives at the radar.

[0098] Step 2: Based on the time τ it takes for the echo of the transmitted signal to reach the radar, and combined with the speed of light c, obtain the distance between the liquid surface and the radar. The echo signal r(t) is accumulated D times to obtain the distance matrix. Where k is the total number of accumulated distance data points. R is the true distance value, n m It is additive white Gaussian noise;

[0099] Step 3: From the echo signal r(t), L pulses are coherently accumulated to obtain the ranging accuracy, which is expressed as:

[0100]

[0101] Where SNR is the signal-to-noise ratio at each sampling point, LP·SNR is the signal-to-noise ratio at the peak of the liquid surface after coherent accumulation and Fourier transform, and B is the signal bandwidth after sampling.

[0102] The bandwidth B of the sampled signal is expressed as:

[0103]

[0104] Among them, B T The bandwidth of the signal before sampling is given, P is the number of sampling points, and f is the signal bandwidth before sampling. s T is the sampling frequency. all α is the total sampling time, and α is the signal frequency modulation slope;

[0105] This leads to the relationship between ranging accuracy and signal-to-noise ratio, expressed as:

[0106]

[0107] in, γ is an intermediate variable;

[0108] The relationship between the final ranging accuracy and the signal-to-noise ratio is expressed as:

[0109]

[0110] Step 4: For the distance matrix For all elements in the set, calculate the average y, which is expressed as:

[0111]

[0112] Step 5: Take the standard deviation of the mean y. The standard deviation is expressed as:

[0113]

[0114] Combining the 3σ principle, the ranging accuracy is obtained, which is expressed as:

[0115]

[0116] Based on the relationship between the final overall ranging accuracy and the signal-to-noise ratio, and get:

[0117]

[0118] Based on ranging accuracy and actual signal-to-noise ratio The relationship between distance, signal-to-noise ratio, and the number of coherent accumulations D is obtained, expressed as:

[0119]

[0120] Step Six: According to The distance is given by the true value R, and the coherent accumulation number D is obtained by using the relationship between distance, signal-to-noise ratio and coherent accumulation number D.

[0121] The method described in this application comprises two stages:

[0122] Phase 1: Precision Detection Based on Coherent Accumulation

[0123] The transmitted signal of the FMCW radar for liquid level gauges can be expressed as:

[0124]

[0125] This signal is called a frequency-modulated continuous wave signal, where f o Let α be the signal carrier frequency, t be the signal modulation slope, j be the transmission time, and T be the imaginary unit.

[0126] Assuming the distance between the liquid surface and the radar is R, the time it takes for the echo of the transmitted signal to reach the radar after reflection from the liquid surface is:

[0127]

[0128] Here, 'c' represents the speed of light, which is typically 3 × 10⁻⁶ in practice. 8 m / s.

[0129] After being reflected by the target, the received signal is:

[0130]

[0131] Among them, f o Let α be the signal carrier frequency, t be the signal modulation slope, j be the imaginary unit, and ξ be the propagation attenuation of the electromagnetic wave and the intensity of the signal reflected from the liquid surface, which is a complex number.

[0132] When processing signals using hardware, we first need to remove the carrier frequency and de-skewing from the echo signal. This involves removing the carrier frequency (i.e., multiplying r(t) by exp(-j2πf0t)) and de-skewing from r(t). ).

[0133]

[0134] In the formula, ξ′=ξexp(-j2πf0τ). Note that τ is much smaller than T. u Therefore, exp(jαπτ) 2 The time delay of the target can be ignored. At this time, r′(t) is a single-frequency signal with a frequency of ατ. The frequency includes the time delay of the target, so the distance of the target can be obtained.

[0135] Then, it needs to be sampled by an analog-to-digital converter (AD). The sampling process is performed within each period T. Assume the sampling frequency is f. s If a total of P points are sampled, then the total sampling time is:

[0136]

[0137] The bandwidth of the sampled signal is:

[0138]

[0139] Among them, B T It is the signal bandwidth before sampling.

[0140] Step 1: From the echo signal, assuming coherent accumulation of L pulses, the total accuracy formula is as follows:

[0141]

[0142] Where δR represents the ranging accuracy, c represents the speed of light, SNR represents the signal-to-noise ratio at each sampling point, and LP·SNR represents the signal-to-noise ratio at the target peak after Fourier transform following coherent accumulation. In the formula, δR represents the ranging accuracy, meaning that 99% of the ranging error will fall within the range of ±δR. We adopt the 3σ principle here, so the relationship between accuracy and standard deviation is:

[0143] δR=3σ (8)

[0144] Substituting (7) into (8), we get:

[0145]

[0146] From (7), we can see that Therefore, (7) can be simplified to:

[0147]

[0148] in For ease of practical application, let's set This represents the signal-to-noise ratio at the target peak after performing an FFT on the coherently accumulated data. The result is:

[0149]

[0150] Phase Two: High-Precision Calculation Based on Adaptation

[0151] Each time a new distance data is received (the distance data here is obtained from the delay of the echo signal, R obtained from the above derivation of equation (2)) (denoted as R) After that, we take the first D data points, that is...

[0152] Because δR << R, therefore in Let represent the measured distance, s represent the true distance, which is a constant for a fixed distance, so the variance of s is 0, and n m This represents additive white Gaussian noise. Our calculation of the liquid surface distance involves averaging the D data points taken from S, i.e.

[0153]

[0154] We take the standard deviation of y to obtain the accuracy:

[0155]

[0156] We found that the accuracy increases with the distance, and at this point, the accuracy can be reduced by changing D. To address the issues of coherent accumulation time and computational efficiency, we can segment the distance to improve accuracy over long distances by changing D. As shown in (13), changing D here changes the accuracy.

[0157] According to (9), δR and From the relationship, we can obtain:

[0158]

[0159] We need to obtain the number of coherent accumulations required for different distances based on different signal-to-noise ratio requirements. Then, by substituting (14) into (14), we can obtain a relationship between signal-to-noise ratio, distance, and number of coherent accumulations.

[0160]

[0161] Next, we will refer to (15) The relationship between R and the matrix is ​​used to select the number of coherent accumulations.

[0162]

[0163] The specific data is shown in Table 1.

[0164] Table 1. Maximum number of coherent accumulations required for a fixed signal-to-noise ratio at different distances.

[0165]

[0166] The detection range of this radar is 0–30 m, and its specific parameters are P = 2048, f s =630kHz,

[0167] α = 1.5625 × 10 12 Hz / s. Considering the limitations of radar computing power and the requirements of computational complexity, when D = 20, the distance is approximately λm when δR = ζmm. At this time, we use the floor function to round down λ. Therefore, before λm, we can use D = 20. After λm, by controlling δR = ζmm unchanged, we can obtain the relationship between D and R. We assume that the upper limit of D is D max Once D reaches its upper limit, D remains unchanged.

[0168] When we control ξ = 1, We can obtain λ = 8m, and the relationship between D and R is:

[0169]

[0170]

[0171] We then set up a control group, with D... max The values ​​are set to [20 50 100 150 200], where the first control group is the unoptimized algorithm.

[0172] from Figure 2 It can be seen that when we control it to ξ = 1, When D is set max =20, can maintain a signal-to-noise ratio up to 9m; if D is set max =50, can maintain a signal-to-noise ratio up to 14m; if D is set max =100, can maintain a signal-to-noise ratio up to 20m; if D is set max =150, which can maintain a signal-to-noise ratio up to 25m; if D is setmax =200, which can maintain the signal-to-noise ratio up to 28m; if a longer distance is required to maintain the signal-to-noise ratio, a larger D is needed. max .

[0173] When ξ = 1.5, At this time, it can be obtained using the same method as (4-2). The relationship with R is:

[0174]

[0175] Figure 2

[0176] Depend on Figure 3 We can see that when we control it to ξ = 1.5, When D is set max =20, can maintain a signal-to-noise ratio up to 13m; if D is set max =50, which can maintain a signal-to-noise ratio up to 21m; when our D max When the signal-to-noise ratio is 100, it can maintain its maximum value after reaching 3m.

[0177] Similarly, when ξ = 2, At this time, it can be obtained using the same method. The relationship with R is:

[0178]

[0179] Depend on Figure 4 We can see that when we control it to ξ = 2, When D is set max =20, which can maintain a signal-to-noise ratio up to 17m; if D is set max =50, which can maintain a signal-to-noise ratio up to 28m; when our D max When the signal-to-noise ratio is 57, it can maintain its maximum value after reaching 4m.

[0180] When we have specific signal-to-noise ratio requirements, we obtain the minimum number of data accumulations required at a certain distance point.

[0181] In the simulations above, we only analyzed the theory. Next, in our simulations, we introduce noise at a known distance R to simulate real-world applications and obtain the difference between the actual and theoretical signal-to-noise ratios at different distances. Figure 5 We can see the difference between the theoretical value (dashed line) and the actual value (solid line).

[0182] Specific procedures:

[0183] (1) Obtain the echo signal r(t) after the target is reflected, and perform carrier frequency removal and skewing removal processing on the echo signal r(t) to obtain r′(t). Then, perform differentiation on r′(t) to obtain the time f when the echo of the transmitted signal arrives at the radar after being reflected by the liquid surface.

[0184] The process of removing the carrier frequency and descrambling from the echo signal r(t) is expressed as follows:

[0185]

[0186] (2) Based on the time τ it takes for the echo of the transmitted signal to reach the radar after being reflected by the liquid surface, the distance between the liquid surface and the radar is obtained. And based on the coherent accumulation times D corresponding to the required signal-to-noise ratio (12), the distance matrix is ​​obtained. Where k represents the total number of distance data points accumulated in a short period of time;

[0187] Each of the distance matrices It includes errors caused by the actual distance r and noise n;

[0188] (3) For the distance matrix The mean (y) of all elements is calculated, and the standard deviation of the mean is taken to obtain the relationship between distance, signal-to-noise ratio, and coherent accumulation times D, which is expressed as:

[0189]

[0190] (4) Based on the actual situation The coherent accumulation number D is obtained by utilizing the relationship between distance, signal-to-noise ratio, and coherent accumulation number D.

[0191] Compared to a single coherent accumulation method, this application is applicable to detection equipment that maintains a fixed accuracy within a certain range; it can save coherent accumulation time and radar computing power.

[0192] It should be noted that the specific embodiments are merely explanations and illustrations of the technical solution of the present invention and should not be used to limit the scope of protection. Any modifications made in accordance with the claims and specification of the present invention that are only partial should still fall within the protection scope of the present invention.

Claims

1. A liquid level radar adaptive adjustment method based on coherent accumulation, characterized in that... The method includes: Obtain the actual signal-to-noise ratio And the true value of distance R, and using the relationship between distance, signal-to-noise ratio and coherent accumulation number D, the coherent accumulation number D is obtained. The relationship between distance, signal-to-noise ratio and coherent accumulation number D is expressed as: The relationship between the distance, signal-to-noise ratio, and the number of coherent accumulations D is obtained through the following steps: Step 1: Obtain the echo signal r(t) after reflection from the liquid surface, and then process the echo signal r(t) by removing the carrier frequency and descrambling to obtain the signal r′(t). Then, differentiate the signal r′(t) to obtain the time τ when the echo of the transmitted signal arrives at the radar. Step 2: Based on the time τ it takes for the echo of the transmitted signal to reach the radar, and combined with the speed of light c, obtain the distance between the liquid surface and the radar. The echo signal r(t) is accumulated D times to obtain the distance matrix. Where k is the total number of accumulated distance data points. R is the true distance value, n m It is additive white Gaussian noise; Step 3: Based on the echo signal r(t), L pulses are coherently accumulated to obtain the ranging accuracy, which is expressed as: Where SNR is the signal-to-noise ratio at each sampling point, LP·SNR is the signal-to-noise ratio at the peak of the liquid surface after coherent accumulation and Fourier transform, and B is the signal bandwidth after sampling. The bandwidth B of the sampled signal is expressed as: Among them, B T The bandwidth of the signal before sampling is given, P is the number of sampling points, and f is the signal bandwidth before sampling. s T is the sampling frequency. all α is the total sampling time, and α is the signal frequency modulation slope; This leads to the relationship between ranging accuracy and signal-to-noise ratio, expressed as: in, γ is an intermediate variable; The relationship between the final ranging accuracy and the signal-to-noise ratio is expressed as: Step 4: For the distance matrix For all elements in the set, calculate the average y, which is expressed as: Step 5: Take the standard deviation of the mean y. The standard deviation is expressed as: Combining the 3σ principle, the ranging accuracy is obtained, which is expressed as: Based on the relationship between the final overall ranging accuracy and the signal-to-noise ratio, and get: Based on ranging accuracy and actual signal-to-noise ratio The relationship between distance, signal-to-noise ratio, and the number of coherent accumulations D is obtained, expressed as:

2. The adaptive adjustment method for liquid level radar based on coherent accumulation according to claim 1, characterized in that... The steps for obtaining the echo signal r(t) after reflection from the liquid surface are as follows: Step 1: Use FMCW radar to transmit a signal, wherein the transmitted signal is a frequency-modulated continuous wave signal; Step 2: After reflection from the liquid surface, the received signal is obtained, namely the echo signal r(t) after reflection from the liquid surface.

3. The adaptive adjustment method for liquid level radar based on coherent accumulation according to claim 2, characterized in that... The FMCW radar transmission signal is represented as follows: Among them, f o Let α be the signal carrier frequency, t be the signal modulation slope, j be the transmission time, and T be the imaginary unit.

4. The adaptive adjustment method for liquid level radar based on coherent accumulation according to claim 3, characterized in that... The received signal is represented as: Where ξ represents the propagation attenuation of the electromagnetic wave and the intensity of the signal reflected from the liquid surface.

5. The adaptive adjustment method for liquid level radar based on coherent accumulation according to claim 4, characterized in that... The echo signal r(t) after carrier frequency removal and descrambling processing is expressed as follows: Among them, ξ′=ξexp(-j2πf0τ).

6. The adaptive adjustment method for liquid level radar based on coherent accumulation according to claim 5, characterized in that... The total sampling time T all Represented as:

7. A liquid level radar adaptive adjustment system based on coherent accumulation, characterized in that, The system includes: an echo receiving module, a coherent accumulation module, and an adjustment module; The echo receiving module is used to acquire the echo signal r(t) reflected from the liquid surface. After removing the carrier frequency and descrambling the echo signal r(t), the signal r′(t) is obtained. Then, the derivative of the signal r′(t) is calculated to obtain the time τ when the echo of the transmitted signal arrives at the radar. Based on the time τ when the echo of the transmitted signal arrives at the radar, and combined with the speed of light c, the distance between the liquid surface and the radar is obtained. The echo signal r(t) is accumulated D times to obtain the distance matrix. Where k is the total number of accumulated distance data points. R is the true distance value, n m It is additive white Gaussian noise; The coherent accumulation module is used to coherently accumulate L pulses based on the echo signal r(t) to obtain the ranging accuracy, which is expressed as: Where SNR is the signal-to-noise ratio at each sampling point, LP·SNR is the signal-to-noise ratio at the peak of the liquid surface after coherent accumulation and Fourier transform, and B is the signal bandwidth after sampling. The bandwidth B of the sampled signal is expressed as: Among them, B T The bandwidth of the signal before sampling is given, P is the number of sampling points, and f is the signal bandwidth before sampling. s T is the sampling frequency. all α is the total sampling time, and α is the signal frequency modulation slope; This leads to the relationship between ranging accuracy and signal-to-noise ratio, expressed as: in, γ is an intermediate variable; The relationship between the final ranging accuracy and the signal-to-noise ratio is expressed as: The adjustment module is used for adjusting the distance matrix. For all elements in the set, calculate the average y, which is expressed as: Take the standard deviation of the mean y. The standard deviation is expressed as: Combining the 3σ principle, the ranging accuracy is obtained, which is expressed as: Based on the relationship between the final overall ranging accuracy and the signal-to-noise ratio, and get: Based on ranging accuracy and actual signal-to-noise ratio The relationship between distance, signal-to-noise ratio, and the number of coherent accumulations D is obtained, expressed as: according to The distance is given by the true value R, and the coherent accumulation number D is obtained by using the relationship between distance, signal-to-noise ratio and coherent accumulation number D.

8. The adaptive liquid level radar control system based on coherent accumulation according to claim 7, characterized in that... The steps for obtaining the echo signal r(t) after reflection from the liquid surface are as follows: Step 1: Use FMCW radar to transmit a signal, wherein the transmitted signal is a frequency-modulated continuous wave signal; Step 2: After reflection from the liquid surface, the received signal is obtained, namely the echo signal r(t) after reflection from the liquid surface.

9. The adaptive liquid level radar control system based on coherent accumulation according to claim 8, characterized in that... The FMCW radar transmission signal is represented as follows: Among them, f o α is the signal carrier frequency, t is the signal modulation slope, j is the transmission time, and T represents the total duration of the transmitted signal in one cycle. The received signal is represented as: Where ξ represents the propagation attenuation of the electromagnetic wave and the intensity of the signal reflected from the liquid surface; The echo signal r(t) after carrier frequency removal and descrambling processing is expressed as follows: Among them, ξ′=ξexp(-j2πf0τ); The total sampling time T all Represented as:

10. A liquid level radar adaptive adjustment medium based on coherent accumulation, characterized in that... The medium contains a computer-readable program for performing the method as claimed in any one of claims 1 to 6.

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