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

Abstract

The invention discloses a GUM evaluation method for temperature measurement uncertainty of a ground-based Raman laser radar, and the method comprises the steps: determining a measurement uncertainty source after a temperature measurement model and main parameters of the ground-based Raman laser radar are determined; the uncertainty sources comprise low-order channel photon noise, high-order channel photon noise, low-order channel background noise, high-order channel background noise, low-order channel dead zone time and high-order channel dead zone time, 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. According to the method, the measurement uncertainty of the ground-based Raman laser radar during high-altitude detection can be accurately and efficiently evaluated.

Description

Technical Field

[0001] The present invention belongs to the fields of metrology testing and environmental exploration, and particularly relates to a method for evaluating the uncertainty of temperature measurement of a ground-based Raman lidar according to the Guide to the Expression of Uncertainty in Measurement (GUM). Background Art

[0002] With the increasing demand in the defense field for understanding the high-altitude atmospheric environment and evaluating the dispersion of detection data, the evaluation of the uncertainty 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. A ground-based Raman lidar can detect environmental parameters such as atmospheric density, temperature, and wind field at altitudes from 0 km to 30 km above the ground, and is an important detection means for understanding the near-space environment. Therefore, the evaluation of its measurement uncertainty is particularly important for the quality control of data and detection activities. The GUM method for evaluating measurement uncertainty is relatively simple to calculate, and is convenient for software calculation for batch data, but there are certain subjective factors, and it is very difficult to solve the sensitivity coefficient.

[0003] The main technical difficulties include the following three items:

[0004] (1) Before the invention of this patent, there was no relatively effective method for evaluating the uncertainty of temperature measurement of a ground-based lidar, and the understanding of the dispersion of measurement results was insufficient.

[0005] (2) Due to the complex composition and numerous equipment parameters of the ground-based Raman lidar detection system, it causes great difficulties for digital twin, and it is difficult to evaluate the measurement uncertainty with only a few basic parameters.

[0006] (3) Since the sensitivity coefficient contains partial derivatives of many composite functions and needs to be obtained through approximate calculation and derivation, it causes great difficulties for the evaluation calculation. Summary of the Invention

[0007] The purpose of the present invention is to provide a method for evaluating the uncertainty of temperature measurement of a ground-based Raman lidar according to the GUM, which can accurately and efficiently evaluate the measurement uncertainty of the ground-based Raman lidar during high-altitude detection.

[0008] To achieve the purpose of the present invention, the technical solutions adopted by the present invention are as follows:

[0009] After clarifying the temperature measurement model and main parameters of the ground-based Raman lidar, determine the sources of measurement uncertainty, and the sources of uncertainty include: low-order channel photon noise, high-order channel photon noise, low-order channel background noise, high-order channel background noise, low-order channel dead time, and high-order channel dead time. Calculate the measurement uncertainty and sensitivity coefficient introduced by the above sources of uncertainty respectively, obtain the measurement uncertainty components of each source of uncertainty, and finally synthesize the standard measurement uncertainty of temperature.

[0010] The present invention takes the GUM measurement uncertainty evaluation method as the core, and forms a complete mathematical model for measuring uncertainty evaluation, a calculation formula for sensitivity coefficients, a calculation process, etc. according to the temperature detection process and the characteristics of the detection system of the ground-based Raman lidar. It has the following characteristics: (1) providing a GUM evaluation method for the temperature measurement uncertainty of the ground-based Raman lidar; (2) providing calculation formulas for the uncertainty components and sensitivity coefficients; (3) providing a calculation formula for the combined standard uncertainty; (4) the calculation process of the present invention is clear and simple, and is applicable to the situation where the parameters of the ground-based lidar equipment are not fully mastered; (5) the calculation difficulty of the present invention is low, which is convenient for software calculation and is applicable to the situation with a large amount of detection data. Specific Embodiments

[0011] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and in no way restrictive of the present invention and its application or use. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0012] The GUM evaluation method for the temperature measurement uncertainty of the ground-based Raman lidar provided by the embodiment of the present invention mainly includes the following steps:

[0013] Step 1. Define the measurement model and the inversion model

[0014] The following inversion model is used for the temperature measurement of the ground-based Raman lidar. By substituting the ratio of the echo photon numbers of the high-order channel and the low-order channel into the temperature inversion formula, the temperature value at the corresponding height is obtained.

[0015]

[0016] Among them, a, b, and c are system parameters given by the developer, and Q is the ratio of the echo photon numbers of the high-order channel and the low-order channel.

[0017]

[0018] Among them, N B1 and N B2 respectively correspond to the echo signal intensities of the high-order channel and the low-order channel after saturation correction and background noise correction.

[0019] Step 2. Define the parameters of the detection equipment

[0020] Specifically, it includes: the dead time τ of the Raman lidar detector; the altitude resolution δz of the Raman lidar; the number of accumulated pulses L of the Raman lidar; and the value of the speed of light c.

[0021] Step 3. Identify the sources of measurement uncertainty

[0022] The sources of uncertainty include: photon noise in the low-order channel, photon noise in the high-order channel, background noise in the low-order channel, background noise in the high-order channel, dead time in the low-order channel, and dead time in the high-order channel.

[0023] Step 4. Calculate the uncertainty and sensitivity coefficient introduced by photon noise in the low-order channel

[0024] 4.1) Calculate the number of photons after saturation correction in the low-order channel;

[0025] Calculate the number of photons N after saturation correction according to the following formula C1 .

[0026]

[0027] where N R1 (z) is the number of photons of the raw Raman backscatter signal received by the lidar in the low-order channel, τ is the dead time, c is the speed of light, δz is the altitude resolution, and L is the number of accumulated pulses.

[0028] 4.2) Calculate the number of photons after background noise correction in the low-order channel

[0029] Calculate the number of photons N after background noise correction according to the following formula B1 (z).

[0030] N B1 (z) = N C1 (z) - B1

[0031] where N c1 (z) is the number of echo photons in the low-order channel after saturation correction, and B1 is the number of background photons in the low-order channel.

[0032] 4.3) Calculate the uncertainty introduced by photon noise in the low-order channel

[0033] Calculate the measurement uncertainty introduced by photon noise in the low-order channel according to the following formula.

[0034]

[0035] 4.4) Calculate the sensitivity coefficient of the measurement uncertainty component

[0036] Calculate its sensitivity coefficient c1 according to the following formula

[0037]

[0038] Among them, N B2 (z) The number of echo photons after saturation correction of the high-order channel (calculated later in the text).

[0039] 4.5) Calculate the measurement uncertainty component u1

[0040] Calculate the measurement uncertainty component according to the following formula

[0041] u1 = c1u(N R1 (z))

[0042] Step 5. Calculate the uncertainty and sensitivity coefficient introduced by the high-order channel photon noise

[0043] 5.1) Calculate the number of photons after saturation correction of the high-order channel;

[0044] Calculate the number of photons N C2 (z) after saturation correction according to the following formula.

[0045]

[0046] Among them, N R2 (z) is the number of photons of the original echo signal of Raman scattering in the high-order channel received by the lidar, τ is the dead time, c is the speed of light, δz is the height resolution, and L is the number of accumulated pulses.

[0047] 5.2) Calculate the number of photons after background noise correction of the high-order channel;

[0048] Calculate the number of photons N B2 (z) after background noise correction according to the following formula.

[0049] N B2 (z) = N C2 (z) - B2

[0050] Among them, N C2 (z) is the number of echo photons after saturation correction of the high-order channel, and B2 is the number of background photons of the high-order channel.

[0051] 5.3) Calculate the uncertainty introduced by the high-order channel photon noise;

[0052] Calculate the measurement uncertainty introduced by the low-order channel photon noise according to the following formula.

[0053]

[0054] 5.4) Calculate the sensitivity coefficient of this measurement uncertainty component.

[0055] Calculate its sensitivity coefficient c2 according to the following formula

[0056]

[0057] 5.5) Calculate the uncertainty component u2 of the measurement

[0058] Calculate the uncertainty component of the measurement according to the following formula

[0059] u2 = c2u(N R2 (z))

[0060] Step 6. Calculate the uncertainty and sensitivity coefficient introduced by the background noise of the low-order channel

[0061] 6.1) Calculate the uncertainty introduced by the background noise;

[0062] Calculate the measurement uncertainty introduced by the background noise according to the following formula.

[0063]

[0064] 6.2) Calculate the sensitivity coefficient of this measurement uncertainty component.

[0065] Calculate its sensitivity coefficient c3 according to the following formula

[0066]

[0067] 6.3) Calculate the uncertainty component u3 of the measurement

[0068] Calculate the uncertainty component of the measurement according to the following formula

[0069] u3 = c3u(B1)

[0070] Step 7. Calculate the uncertainty and sensitivity coefficient introduced by the background noise of the high-order channel 7.1) Calculate the uncertainty introduced by the background noise;

[0071] Calculate the measurement uncertainty introduced by the background noise according to the following formula.

[0072]

[0073] 7.2) Calculate the sensitivity coefficient of this measurement uncertainty component.

[0074] Calculate its sensitivity coefficient C4 according to the following formula

[0075]

[0076] 7.3) Calculate the uncertainty component u4 of the measurement

[0077] Calculate the uncertainty component of the measurement according to the following formula

[0078] u4 = c4u(B2)

[0079] Step 8. Calculate the uncertainty and sensitivity coefficient introduced by the dead time of the high-order channel to the low-order channel 8.1) Calculate the uncertainty introduced by the dead time of the low-order channel;

[0080] Calculate the measurement uncertainty introduced by the dead time of the high-order channel according to the following formula.

[0081] u(τ1) = 0.01 ns

[0082] 8.2) Calculate the sensitivity coefficient of this measurement uncertainty component.

[0083] Calculate its sensitivity coefficient c5 according to the following formula

[0084]

[0085] 8.3) Calculate the measurement uncertainty component u5

[0086] Calculate the measurement uncertainty component according to the following formula

[0087] u5 = c5u(τ1)

[0088] Step 9. Calculate the uncertainty and sensitivity coefficient introduced by the low-order channel to the high-order channel 9.1) Calculate the uncertainty introduced by the dead time of the high-order channel;

[0089] Calculate the measurement uncertainty introduced by the dead time of the high-order channel according to the following formula.

[0090] u(τ2) = 0.01 ns

[0091] 9.2) Calculate the sensitivity coefficient of this measurement uncertainty component.

[0092] Calculate its sensitivity coefficient c5 according to the following formula

[0093]

[0094] 9.3) Calculate the measurement uncertainty component u6

[0095] Calculate the measurement uncertainty component according to the following formula

[0096] u6 = c6u(τ2)

[0097] Step 10. Combine the standard uncertainties.

[0098] Calculate the combined standard uncertainty according to the following formula

[0099]

[0100] Step 11. Calculate the expanded uncertainty

[0101] Calculate the expanded uncertainty according to the following formula

[0102] U = k·u c (T)

[0103] The infinite atmospheric temperature detections obey the normal distribution. Select the confidence probability according to the following table and look up the coverage factor k

[0104] Table 1 Correspondence table between confidence probability and coverage factor

[0105] Confidence probability p 0.999 0.9973 0.99 0.954 0.95 0.90 0.683 0.6745 Coverage factor k 3.3 3 2.58 2 1.96 1.645 1 0.5

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate 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 a ground-based Raman lidar according to the GUM, characterized in that After determining the explicit ground-based Raman lidar temperature measurement model and its main parameters, identify the sources of measurement uncertainty, which include: low-order channel photon noise, high-order channel photon noise, low-order channel background noise, high-order channel background noise, low-order channel dead time, and high-order channel dead time. Calculate the measurement uncertainty and sensitivity coefficient introduced by each of these sources of uncertainty respectively, obtain the measurement uncertainty components of each source of uncertainty, and finally synthesize the standard measurement uncertainty of temperature. The temperature measurement of the ground-based Raman lidar uses the following inversion model. By substituting the ratio of the echo photon numbers of the high-order channel and the low-order channel into the temperature inversion formula, the temperature value at the corresponding altitude is obtained. Among them, a, b, and c are system parameters given by the developer, and Q is the ratio of the echo photon numbers of the high-order channel and the low-order channel. Among them, N B1 and N B2 respectively correspond to the echo signal intensities of the high-order channel and the low-order channel after saturation correction and background noise correction.

2. The GUM evaluation method for the temperature measurement uncertainty of the ground-based Raman lidar according to claim 1, wherein The calculation methods for the uncertainty and sensitivity coefficient introduced by the low-order channel photon noise are as follows: 1) Calculate the number of photons N after low-order channel saturation correction C1 Among them, N R1 (z) is the number of photons of the low-order channel Raman scattering original echo signal received by the lidar, 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 low-order channel background noise correction B1 (z) N B1 ψ(z) = N C1 ψ(z) - B1 Among them, N c1 (z) The number of echo photons after saturation correction of the low-order channel, and B1 is the number of background photons of the low-order channel; 3) Calculate the uncertainty u(N R1 (z)) 4) Calculate the sensitivity coefficient c1 of the measurement uncertainty component Among them, N B2 (z) The number of echo photons after saturation correction of the high-order channel; 5) Calculate the measurement uncertainty component u1 u1 = c1u(N R1 (z)).

3. The GUM evaluation method for the temperature measurement uncertainty of the ground-based Raman lidar according to claim 1, wherein The calculation methods for the uncertainty and sensitivity coefficient introduced by the high-order channel photon noise are as follows: 1) Calculate the number of photons N after high-order channel saturation correction C2 (z) Among them, N R2 (z) is the number of photons of the original echo signal of the high-order channel Raman scattering received by the lidar, 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 high-order channel background noise correction B2 (z) N B2 (z) = N C2 (z) - B2 Among them, N C2 (z) is the number of echo photons after saturation correction of the high-order channel, and B2 is the number of background photons of the high-order channel; 3) Calculate the uncertainty introduced by the high-order channel photon noise; 4) Calculate the sensitivity coefficient c2 of this measurement uncertainty component 5) Calculate the measurement uncertainty component u2 u2 = c2u(N R2 (z)).

4. The method for evaluating the uncertainty of the ground-based Raman lidar temperature measurement according to claim 1 is characterized in that, The calculation methods for the uncertainty and sensitivity coefficient introduced by the low-order channel background noise are as follows: 1) Calculate the uncertainty introduced by the background noise; 2) Calculate the sensitivity coefficient c3 of this measurement uncertainty component 3) Calculate the measurement uncertainty component u3 u3 = c3u(B1).

5. The method for evaluating the temperature measurement uncertainty of the ground-based Raman lidar according to the GUM as claimed in claim 1, wherein The calculation methods for the uncertainty and sensitivity coefficient introduced by the high-order channel background noise are as follows: 1) Calculate the uncertainty introduced by the background noise 2) Calculate the sensitivity coefficient C4 of this measurement uncertainty component 3) Calculate the measurement uncertainty component u4 Calculate the measurement uncertainty component according to the following formula u4 = c4u(B2).

6. The GUM evaluation method for the temperature measurement uncertainty of the ground-based Raman lidar according to claim 1, characterized in that The calculation methods for the uncertainty and sensitivity coefficient introduced by the high-order channel dead time in the low-order channel are as follows: 1) Calculate the uncertainty introduced by the low-order channel dead time; u(τ1) = 0.01ns 2) Calculate the sensitivity coefficient c5 of this measurement uncertainty component 3) Calculate the measurement uncertainty component u5 u5 = c5u(τ1).

7. The GUM evaluation method for the temperature measurement uncertainty of the ground-based Raman lidar according to claim 1, characterized in that The calculation methods for the uncertainty and sensitivity coefficient introduced by the low-order channel dead time in the high-order channel are as follows: 1) Calculate the uncertainty introduced by the high-order channel dead time u(τ2) = 0.01ns 2) Calculate the sensitivity coefficient c5 of this measurement uncertainty component 3) Calculate the measurement uncertainty component u6 u6 = c6u(τ2).

8. The method for evaluating the uncertainty of the ground-based Raman lidar temperature measurement according to the GUM as claimed in claim 1, wherein The calculation method for synthesizing the standard uncertainty is: Among them, u1 is the uncertainty component introduced by the low-order channel photon noise, u2 is the uncertainty component introduced by the high-order channel photon noise, u3 is the uncertainty component introduced by the low-order channel background noise, u4 is the uncertainty component introduced by the background noise, u5 is the uncertainty component introduced by the high-order channel dead time in the low-order channel, and u6 is the uncertainty component introduced by the low-order channel dead time in the high-order channel.

9. The method for evaluating the uncertainty of the ground-based Raman lidar temperature measurement according to claim 8, wherein Calculate the expanded uncertainty, and the formula is as follows: U = k·u c (T) The infinite atmospheric temperature detections follow a normal distribution. Select the confidence probability according to Table 1 and look up the coverage factor k. Table 1 Correspondence Table between Confidence Probability and Coverage Factor 。

Images