Ground-based Rayleigh laser radar temperature measurement uncertainty GUM evaluation method

Abstract

The invention discloses a GUM evaluation method for temperature measurement uncertainty of a ground-based Rayleigh laser radar, and the method comprises the steps: determining the source of measurement uncertainty after determining a temperature measurement model of the ground-based Rayleigh laser radar and main parameters of detection equipment; the measurement uncertainty sources comprise detection point photon noise, upper boundary point photon noise, background noise, detection point dead zone time, upper boundary point dead zone time and inversion reference temperature, respectively calculating the measurement uncertainty and sensitivity coefficient introduced by the uncertainty sources, and obtaining the measurement uncertainty component of each uncertainty source; and finally synthesizing the temperature standard measurement uncertainty. The complete temperature measurement uncertainty evaluation method provided by the invention can accurately and efficiently evaluate the temperature measurement uncertainty of the ground-based Rayleigh laser radar during high-altitude detection.

Description

Technical Field

[0001] The invention belongs to the field of metrology testing and environmental detection, and specifically relates to a GUM evaluation method for temperature measurement uncertainty of a ground-based Rayleigh laser radar. Background Art

[0002] With the increasing demand for high-altitude atmospheric environment cognition and assessment of the dispersion of detection data in the defense field, uncertainty assessment of detection data has become a crucial link. Measurement uncertainty can characterize the dispersion and credibility of measurement results, and indirectly reflect the quality of detection activities. Ground-based Rayleigh LiDAR can detect environmental parameters such as atmospheric temperature, temperature, wind field, etc. at an altitude of 30km to 80km from the ground. It is an important detection method for near-space environment cognition. Therefore, the assessment of its measurement uncertainty is particularly important for the quality control of data and detection activities. The GUM measurement uncertainty assessment method is relatively simple to calculate, and it is easy to use software calculations for batch data, but there are certain subjective factors, and the sensitivity coefficient is very difficult to solve.

[0003] Before the invention of this patent, there was no effective evaluation method for the uncertainty evaluation of ground-based lidar temperature measurement, and the knowledge of the dispersion of measurement results was insufficient. The main technical difficulties included the following three items:

[0004] The ground-based Rayleigh LiDAR detection system has complex composition and numerous equipment parameters, which poses great difficulties for digital twins. It is difficult to assess measurement uncertainty with only a few basic parameters.

[0005] Since the sensitivity coefficient contains many partial derivatives of composite functions, it needs to be obtained through approximate calculation and derivation, which makes the evaluation calculation more difficult. Summary of the invention

[0006] The purpose of the present invention is to provide a complete temperature measurement uncertainty assessment method, which can accurately and efficiently assess the temperature measurement uncertainty of ground-based Rayleigh lidar during high-altitude detection.

[0007] To achieve the purpose of the present invention, the ground-based Rayleigh lidar temperature measurement uncertainty GUM evaluation method provided by the present invention adopts the following technical scheme:

[0008] After clarifying the ground-based Rayleigh lidar temperature measurement model and the main parameters of the detection equipment, the sources of measurement uncertainty are clarified. The sources of measurement uncertainty include: detection point photon noise, upper boundary point photon noise, background noise, detection point dead time, upper boundary point dead time and inversion reference temperature. The measurement uncertainty and sensitivity coefficient introduced by the above uncertainty sources are calculated respectively, and the measurement uncertainty components of each uncertainty source are obtained, and finally the temperature standard measurement uncertainty is synthesized.

[0009] The present invention takes the GUM measurement uncertainty assessment method as the core, and forms a complete measurement uncertainty assessment mathematical model, sensitivity coefficient calculation formula, calculation process, etc. for the ground-based Rayleigh laser radar temperature detection process and detection system characteristics. The present invention has the following characteristics: (1) It provides a GUM measurement uncertainty assessment method for ground-based Rayleigh laser radar; (2) It provides a calculation formula for measurement uncertainty components and sensitivity coefficients; (3) It provides a calculation formula for synthetic standard uncertainty; (4) The calculation process of the present invention is clear and simple, and is suitable for the ground-based laser radar equipment parameters that are not fully understood; (5) The present invention has low calculation difficulty, is easy to implement software calculation, and is suitable for situations where the amount of detection data is large. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The included drawings are used to provide a further understanding of the embodiments of the present invention, which constitute a part of the specification, are used to illustrate the embodiments of the present invention, and together with the text description, explain the principles of the present invention. Obviously, the drawings in the following description are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 A schematic flow chart of a method for evaluating the uncertainty in temperature measurement (GUM) of a ground-based Rayleigh lidar provided according to a specific embodiment of the present invention is shown. DETAILED DESCRIPTION

[0012] It should be noted that, in the absence of conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present invention and its application or use. Based on the embodiments in 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.

[0013] Figure 1 The following is a schematic diagram of a method for evaluating the uncertainty in temperature measurement of a ground-based Rayleigh lidar provided in accordance with a specific embodiment of the present invention, which mainly includes the following steps:

[0014] Step 1. Define the measurement model

[0015] Rayleigh lidar temperature measurement generally uses the following inversion model. According to the ideal gas state equation, the temperature of the detection point is calculated by the atmospheric density at the detection point, the atmospheric temperature at the upper boundary point height, and the atmospheric density value.

[0016]

[0017] Among them, T(z u ) and n A (z u ) are the atmospheric temperature and atmospheric density at the upper boundary height, R is the gas universal constant, g(z') is the gravitational acceleration, M is the molecular mass, z u The upper boundary height.

[0018] Step 2. Define the detection equipment parameters

[0019] The detection equipment parameters include: Rayleigh laser radar detector dead time τ; Rayleigh laser radar height resolution δz; Rayleigh laser radar cumulative pulse number L; light speed value c; inverted atmospheric temperature T(z); upper boundary point atmospheric temperature T(z u ).

[0020] Step 3. Identify sources of measurement uncertainty

[0021] The sources of measurement uncertainty include: detection point photon noise; upper boundary point photon noise; background noise; detection point dead time; upper boundary point dead time; inversion reference temperature.

[0022] Step 4. Calculate the uncertainty and sensitivity coefficient introduced by the photon noise at the detection point

[0023] 4.1) Calculate the number of photons after saturation correction at the detection point

[0024] The photon number N after saturation correction is calculated as follows: c (z)

[0025]

[0026] Among them, N R (z) is the number of photons of the original Rayleigh scattering echo signal received by the lidar at the detection point (z height), τ is the dead time, c is the speed of light, δz is the height resolution, and L is the number of accumulated pulses.

[0027] 4.2) Calculate the number of photons after background noise correction at the detection point

[0028] The number of photons N after background noise correction is calculated as follows: B (z)

[0029] N B (z) = N C (z)-B

[0030] Among them, N c(z) is the number of echo photons at the detection point (height z) after saturation correction, and B is the number of background light photons.

[0031] 4.3) Calculate the uncertainty introduced by the photon noise at the detection point

[0032] The measurement uncertainty introduced by the photon noise at the detection point is calculated according to the following formula:

[0033]

[0034] 4.4) Calculate the sensitivity coefficient of the measurement uncertainty component

[0035] The sensitivity coefficient c1 is calculated as follows

[0036]

[0037] Where T is the inverted atmospheric temperature value.

[0038] 4.5) Calculate the measurement uncertainty component u1

[0039] The measurement uncertainty components are calculated as follows:

[0040] u1=c1u(N R (z))

[0041] Step 5. Calculate the uncertainty and sensitivity coefficient introduced by the photon noise at the upper boundary point

[0042] 5.1) Calculate the number of photons after saturation correction at the upper boundary point

[0043] The photon number N after saturation correction is calculated as follows: c (z u )

[0044]

[0045] Among them, N R (z u ) is the height z of the upper boundary point received by the laser radar u The number of photons in the original echo signal of Rayleigh scattering, τ is the dead time, c is the speed of light, δz is the height resolution, and L is the number of accumulated pulses.

[0046] 5.2) Calculate the number of photons after background noise correction at the upper boundary point;

[0047] The number of photons N after background noise correction is calculated as follows: B (z u ).

[0048] N B (z u )=NC (z u )-B

[0049] Among them, N c (z u ) is the height z of the upper boundary point u B is the number of echo photons after saturation correction, and B is the number of background light photons.

[0050] 5.3) Calculate the uncertainty introduced by the photon noise at the upper boundary point;

[0051] The measurement uncertainty introduced by the photon noise at the upper boundary point is calculated according to the following formula.

[0052]

[0053] 5.4) Calculate the sensitivity coefficient of this measurement uncertainty component.

[0054] The sensitivity coefficient c2 is calculated as follows

[0055]

[0056] 5.5) Calculate the measurement uncertainty component u2

[0057] The measurement uncertainty components are calculated as follows:

[0058] u2=c2u(N R (z u ))

[0059] Step 6. Calculate the uncertainty and sensitivity factor introduced by background noise

[0060] 6.1) Calculate the uncertainty introduced by background noise

[0061] The measurement uncertainty introduced by background noise is calculated according to the following formula:

[0062] 6.2) Calculate the sensitivity coefficient of this measurement uncertainty component.

[0063] The sensitivity coefficient c3 is calculated as follows

[0064]

[0065] 6.3) Calculate the measurement uncertainty component u3

[0066] The measurement uncertainty components are calculated as follows:

[0067] u3=c3u(B)

[0068] Step 7. Calculate the uncertainty and sensitivity coefficient of the detection point introduced by the dead time of the detection point. 7.1) Calculate the uncertainty introduced by the dead time of the detection point. Calculate the measurement uncertainty introduced by the dead time of the detection point according to the following formula.

[0069] u(τ)=0.01ns

[0070] 7.2) Calculate the sensitivity coefficient of this measurement uncertainty component.

[0071] The sensitivity coefficient c4 is calculated as follows

[0072]

[0073] 7.3) Calculate the measurement uncertainty component u4

[0074] The measurement uncertainty components are calculated as follows:

[0075] u4=c4u(τ)

[0076] Step 8. Calculate the uncertainty and sensitivity coefficient of the upper boundary point introduced by the upper boundary point dead time

[0077] 8.1) Calculate the uncertainty introduced by the dead time of the upper boundary point;

[0078] The measurement uncertainty introduced by the dead time of the detection point is calculated according to the following formula.

[0079] u(τ)=0.01ns

[0080] 8.2) Calculate the sensitivity coefficient of the measurement uncertainty component

[0081] The sensitivity coefficient c5 is calculated as follows

[0082]

[0083] 8.3) Calculate the measurement uncertainty component u5

[0084] The measurement uncertainty components are calculated as follows:

[0085] u5=c5u(τ)

[0086] Step 9. Calculate the uncertainty and sensitivity factor introduced by the reference temperature

[0087] 9.1) Calculate the uncertainty introduced by the reference temperature

[0088] If the reference temperature is standard atmosphere, the provisional measurement uncertainty u(n A (z u ))=0, if the in-situ detection method is used, then u(n A(z u )) is the measurement uncertainty value evaluated by in-situ detection.

[0089] 9.2) Calculate the sensitivity coefficient of the measurement uncertainty component

[0090] The sensitivity coefficient c6 is calculated as follows

[0091]

[0092] 9.3) Calculate the measurement uncertainty component u6

[0093] The measurement uncertainty components are calculated as follows:

[0094] u6=c6u(n A (z u ))

[0095] Step 10. Combined standard uncertainty

[0096] The combined standard uncertainty is calculated as follows:

[0097]

[0098] Step 11. Calculate the expanded uncertainty

[0099] The expanded uncertainty is calculated as follows:

[0100] U=k·u c (T)

[0101] Infinite atmospheric temperature detections follow a normal distribution. Select the confidence probability p according to the table below and check the inclusion factor k.

[0102] Table 1 Confidence probability and coverage factor correspondence table

[0103] Confidence probability p 0.999 0.9973 0.99 0.954 0.95 0.90 0.683 0.6745 Inclusion factor k 3.3 3 2.58 2 1.96 1.645 1 0.5

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the uncertainty of temperature measurement of ground-based Rayleigh lidar, characterized in that: After clarifying the ground-based Rayleigh lidar temperature measurement model and the main parameters of the detection equipment, the sources of measurement uncertainty are clarified. The sources of measurement uncertainty include: detection point photon noise, upper boundary point photon noise, background noise, detection point dead time, upper boundary point dead time and inversion reference temperature. The measurement uncertainty and sensitivity coefficient introduced by the above uncertainty sources are calculated respectively, and the measurement uncertainty components of each uncertainty source are obtained. Finally, the temperature standard measurement uncertainty is synthesized. Among them, the ground-based Rayleigh lidar temperature measurement model is: Among them, T(z u ) and n A (z u ) are the atmospheric temperature and atmospheric density at the upper boundary height, R is the gas universal constant, g(z') is the gravitational acceleration, M is the molecular mass, z u is the height of the upper boundary point.

2. The method for evaluating the temperature measurement uncertainty GUM of ground-based Rayleigh laser radar according to claim 1 is characterized in that: The calculation method for the measurement uncertainty component introduced by the detection point photon noise is as follows: 1) Calculate the number of photons N after saturation correction at the detection point c (z) Among them, N R (z) is the number of photons of the original echo signal of Rayleigh scattering received by the lidar at the detection point height z, τ is the dead time, c is the speed of light, δz is the height resolution, and L is the number of accumulated pulses; 2) Calculate the number of photons N after background noise correction at the detection point B (z) N B (z)=N C (z)-B Among them, N c (z) is the number of echo photons at the detection point height z after saturation correction, and B is the number of background light photons; 3) Calculate the uncertainty introduced by the photon noise at the detection point 4) Calculate the sensitivity coefficient c1 of the measurement uncertainty Where T is the inverted atmospheric temperature value; 5) Calculate the measurement uncertainty component u1 u1=c1u(N R (with)).

3. The method for evaluating the temperature measurement uncertainty GUM of ground-based Rayleigh laser radar according to claim 1 or 2, characterized in that: The calculation method for the measurement uncertainty component introduced by the photon noise at the upper boundary point is as follows: 1) Calculate the number of photons N after saturation correction at the upper boundary point c (z u ) Among them, N R (z u ) is the height z of the upper boundary point received by the laser radar u The number of photons of the original echo signal of Rayleigh scattering, τ is the dead time, c is the speed of light, δz is the height resolution, and L is the number of accumulated pulses; 2) Calculate the number of photons N after background noise correction at the upper boundary point B (z u ) N B (z u )=N C (z u )-B Among them, N c (z u ) is the height z of the upper boundary point u The number of echo photons after saturation correction, B is the number of background light photons; 3) Calculate the uncertainty introduced by the photon noise at the upper boundary point 4) Calculate the sensitivity coefficient c2 of uncertainty 5) Calculate the measurement uncertainty component u2 <h2 style=";text-align:left;direction:ltr">u2=c2u(N<h2 style=";text-align:left;direction:ltr"> R <h2 style=";text-align:left;direction:ltr"> (z<h2 style=";text-align:left;direction:ltr"> u <h2 style=";text-align:left;direction:ltr"> ))。 4. The method for evaluating the uncertainty of temperature measurement GUM of ground-based Rayleigh laser radar according to claim 2 is characterized in that: The calculation method for the measurement uncertainty component introduced by background noise is as follows: 1) Calculate the uncertainty introduced by background noise 2) Calculate the sensitivity coefficient of uncertainty c3 3) Calculate the measurement uncertainty component u3 u3=c3u(B).

5. The method for evaluating the uncertainty of temperature measurement GUM of ground-based Rayleigh laser radar according to claim 2 is characterized in that: The calculation method for the measurement uncertainty component introduced by the dead time of the detection point is as follows: 1) Calculate the uncertainty introduced by the dead time of the detection point u(τ)=0.01ns 2) Calculate the sensitivity coefficient of uncertainty c4 3) Calculate the measurement uncertainty component u4 u4=c4u(τ).

6. The method for evaluating the uncertainty of temperature measurement GUM of ground-based Rayleigh laser radar according to claim 3 is characterized in that: The calculation method for the measurement uncertainty component introduced by the dead time of the upper boundary point is as follows: 1) Calculate the measurement uncertainty introduced by the dead time of the detection point according to the following formula: u(τ)=0.01ns 2) Calculate the sensitivity coefficient c5 of uncertainty 3) Calculate the measurement uncertainty component u5 u5=c5u(τ).

7. The method for evaluating the uncertainty of temperature measurement GUM of ground-based Rayleigh laser radar according to claim 3 is characterized in that: The calculation method for the measurement uncertainty component introduced by the reference temperature is as follows: 1) Calculate the uncertainty introduced by the reference temperature If the reference temperature is standard atmosphere, the provisional measurement uncertainty u(n A (z u ))=0, if the in-situ detection method is used, then u(n A (z u )) is the measurement uncertainty value evaluated by in-situ detection; 2) Calculate the sensitivity coefficient of the measurement uncertainty component The sensitivity coefficient c6 is calculated as follows 3) Calculate the measurement uncertainty component u6 u6=c6u(n A (with u ))。 8. The method for evaluating the uncertainty of temperature measurement GUM of ground-based Rayleigh laser radar according to claim 1 is characterized in that: The combined standard uncertainty is calculated as follows: Among them, u1 is the measurement uncertainty component introduced by the photon noise at the detection point, u2 is the measurement uncertainty component introduced by the photon noise at the upper boundary point, u3 is the measurement uncertainty component introduced by the background noise, u4 is the measurement uncertainty component introduced by the dead time of the detection point, u5 is the measurement uncertainty component introduced by the dead time of the upper boundary point, and u6 is the measurement uncertainty component introduced by the inversion reference temperature.

9. The method for evaluating the temperature measurement uncertainty GUM of ground-based Rayleigh laser radar according to claim 8 is characterized in that: The expanded uncertainty calculation method is as follows: U=k·u c (T) K is the inclusion factor. Infinite atmospheric temperature detections follow a normal distribution. Select the confidence probability p according to the table below to obtain the inclusion factor k. Table 1 Confidence probability and coverage factor correspondence table 。

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