Distributed ground-based radar atmospheric refraction error calculation method for celestial body observation

Abstract

The invention discloses a distributed ground-based radar atmospheric refraction error calculation method for celestial body observation. According to the method, a local numerical weather forecast model is corrected by using real-time surface meteorological parameters, atmospheric refractive index profile data containing elevation meteorological information is obtained, a geometric elevation angle of a celestial body target is taken as a standard, and a neutral atmospheric refractive index error is searched in combination with a corrected data source and a ray tracing method, so that the atmospheric refractive index is obtained. And finally, neutral atmospheric refraction error calculation and correction are realized. The effectiveness of the algorithm is verified through simulation.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of radar signal processing, in particular to a distributed ground-based radar atmospheric refraction error calculation method for celestial observation. BACKGROUND

[0002] The distributed ground-based radar system is an important research content in the future radar development, and can realize high-precision observation of extremely far targets. The distributed ground-based radar can be observed all day round and all weather, and also has the advantages of not being limited by the transmission power, aperture and other physical conditions. The present application will be introduced by taking the distributed ground-based radar atmospheric refraction error calculation method for celestial observation as an example. The observation of celestial bodies by the distributed ground-based radar is mainly realized through high-precision signal transmission and reception phase tracking technology, that is, by correcting the phase and time delay differences of the transmission and reception signals between the sub-radar units in the distributed radar, so that they have the same phase and envelope time delay, thereby realizing the maximum phase tracking efficiency of the superimposed signals. However, when the uplink and downlink electromagnetic waves of the distributed ground-based radar pass through the neutral atmosphere, the propagation trajectory will be bent, resulting in a decrease in the received signal strength, and ultimately making it impossible to realize high-precision detection or imaging of celestial targets. In order to ensure that the distributed ground-based radar can realize high-precision observation of celestial targets, it is necessary to correct the refraction error introduced by the neutral atmosphere, so as to improve the transmission and reception phase tracking efficiency of the distributed ground-based radar.

[0003] At present, the methods commonly used for correcting the refraction error of the neutral atmosphere of the distributed ground-based radar are divided into two categories: one is to use the empirical formula based on the measurement data of previous years, and the representative formula is the ITUR model; the other is to use the formula combined with the real-time ground meteorological measurement data of the system location, and the representative formula is the first-order approximation formula of astronomical atmospheric refraction, which has higher precision. However, the above methods all ignore the significant influence of the height neutral atmosphere, and also face the problem of mismatch between the meteorological data source and the space where the system is located, which will greatly reduce the working performance of the distributed ground-based radar. SUMMARY

[0004] Therefore, the present application proposes a search-type ray tracing method based on a modified numerical weather prediction model, which is used for calculating and correcting the refraction error of the neutral atmosphere in celestial observation. The technical scheme of the present application is as follows: a distributed ground-based radar atmospheric refraction error calculation method for celestial observation, comprising:

[0005] Step one, obtaining the refractive index profile based on the numerical weather prediction model: based on the obtained numerical weather prediction model data, extracting the height profile information of key meteorological elements including air pressure, temperature and humidity, and establishing the atmospheric refractive index profile varying with height according to the standard refractive index formula;

[0006] Step two, refractive index profile correction based on real-time surface meteorological data: introduce real-time ground meteorological observation data to correct and optimize the original numerical weather prediction refractive index profile;

[0007] Step three, atmospheric refraction error calculation based on search formula ray tracing method: based on the obtained corrected refractive index profile, with the geometric elevation angle of the celestial target as the reference, the ray tracing algorithm is applied to search the propagation path of electromagnetic wave in the neutral atmosphere along different paths and the target elevation angle, so as to realize the accurate calculation and subsequent correction of the neutral atmospheric refraction error.

[0008] Beneficial effects:

[0009] The present application first proposes a distributed ground-based radar atmospheric refraction error calculation method for celestial observation, including a numerical weather prediction model correction scheme based on real-time surface meteorological parameters and a search strategy based ray tracing atmospheric refraction error calculation method; compared with the prior art, it has the following advantages:

[0010] 1. Higher accuracy: compared with the atmospheric refractive index profile extracted by the numerical weather prediction height meteorological model, the real-time surface meteorological measurement can better reflect the real atmospheric state during the measurement; the search formula ray tracing method for refractive error can consider the rigorous physical process of electromagnetic propagation compared with the traditional empirical formula, so as to effectively improve the accuracy of refractive error calculation;

[0011] 2. Lower cost: the surface sensor required by the present application is low in cost and easy to deploy; the numerical prediction data is an open source resource and is easy to obtain; it avoids the high cost of purchasing, constructing and operating sounding stations or height meteorological detection professional equipment. BRIEF DESCRIPTION OF DRAWINGS

[0012] Figure 1 : Invention implementation flowchart;

[0013] Figure 2 : Data source point position schematic diagram;

[0014] Figure 3 : Profile data correction effect schematic diagram (taking July 1, 2022, UTC 00 as an example);

[0015] Figure 4 : Atmospheric refraction error calculation result and comparison;

[0016] Figure 5 : Simulation distributed ground-based radar configuration schematic diagram;

[0017] Figure 6 : System correction effect schematic diagram based on calculation result. DETAILED DESCRIPTION

[0018] The present application is described in detail below with reference to the accompanying drawings and embodiments, and the flow chart is shown in the accompanying drawings Figure 1 .

[0019] Step one, refractive index profile acquisition based on numerical weather prediction model

[0020] The numerical weather prediction model is open source data, which is published by meteorological departments or research units at multiple specific time points every day. The numerical weather prediction model data of the nearest time point to the observation time period of the distributed ground-based radar system is selected, and the meteorological data in the observation time period is converted into refractive index profile data, which is expressed by the formula:

[0021]

[0022] In the formula, N is the atmospheric refractive index, P d is the dry atmospheric pressure, P w is the wet atmospheric pressure, and T is the open temperature.

[0023] In the embodiments, the sounding data of the sounding station located in Chongqing, China in July 2022 is selected to simulate the atmospheric conditions during the observation period of the virtual simulation system, as shown in the accompanying drawings Figure 2 , and the corresponding surface data is used as the accurate meteorological measurement data.

[0024] Step two, refractive index profile correction based on real-time surface meteorological data

[0025] The actual complex random changes of the atmosphere will cause certain errors in the numerical weather prediction model based on the meteorological physical model, so the measured surface refractive index parameters are used to correct the numerical weather prediction model. In order to ensure that the correction does not destroy the height structure of the refractive index profile of the numerical weather prediction model, the correction formula is as follows:

[0026]

[0027] In the formula, N calib (h) is the corrected refractive index profile, N nwp (h) is the refractive index profile of the numerical weather prediction model, h s is the surface height. The accurate surface meteorological parameters measured by the meteorological sensor in real time or near real time are extracted, and the formula (1)~(3) is also used to calculate the accurate atmospheric refractive index parameters N s .

[0028] The same time in the implementation example, Chongqing mesoscale numerical weather prediction model data is used to verify the effectiveness of the present application. Combined with the surface meteorological data and numerical weather prediction model data, the corrected atmospheric refractive index profile data is calculated by using formula (1) to (4). The atmospheric refractive index profile reference true value, the atmospheric refractive index profile based on the numerical weather prediction model and the corrected profile are shown in FIGS. 8 to 10. Figure 3

[0029] Step three, atmospheric refraction error calculation based on the search ray tracing method

[0030] For the distributed ground-based radar system for astronomical observation, the observation target is usually known to be an accurate ephemeris, which contains a theoretical geometric elevation angle. Therefore, the present application combines the application characteristics of the system, and takes the target geometric elevation angle as the precision cost function of atmospheric refraction error calculation. The cost function is as follows:

[0031] J = a0-F [e, N calib (h)] (5)

[0032] In the formula, J is the cost function, a0 is the theoretical geometric elevation angle calculated from the target ephemeris, e is the apparent observation elevation angle of the distributed ground-based radar unit, and F(·) is the simulated geometric elevation angle of the target calculated by using the search ray tracing method under the above conditions.

[0033] Since the atmospheric refraction error and the observation elevation angle have a clear monotonic decrease relationship, the present application uses the ray tracing method based on the dichotomy search strategy to calculate the apparent observation elevation angle e. In addition, since the refraction error introduced by the neutral atmosphere does not exceed 1 degree under the condition of non-extremely low elevation angle, the initial range of dichotomy search is set to [a0, a0+1°]. In addition, since the observation accuracy requirement of the distributed ground-based radar system is very high, the threshold value for stopping the search of the cost function is set to 1e-4 arcseconds. When the search is stopped, the atmospheric refraction error calculation formula is as follows:

[0034] a = e-a0 (6)

[0035] In the formula, a is the atmospheric refraction error.

[0036] The atmospheric refractive index profile data obtained in steps one and two and the sounding data representing the reference true value are calculated by using the above search ray tracing method to obtain the reference atmospheric refraction error value; at the same time, the corrected atmospheric refractive index profile obtained by the present application is calculated to obtain the atmospheric refraction error calculation value, as shown in FIG. 11. Figure 4 The error statistics of the above calculation results are shown in FIG. 12. Figure 4 The root mean square error calculated by the present application is 0.1595 arcseconds, and the standard deviation is 0.1580 arcseconds.

[0037] Speed of light 2.99792458 x 10 8 m / s Main radar to target range 7 x 10 9 m]] Main radar elevation angle 15° Main radar azimuth angle 0° Radar aperture 34m Frequency 21 GHz Radar unit baseline 100m ​

[0038] Table 1. Simulation parameter settings

[0039] To further verify the effect of the present invention, the residuals of the atmospheric refraction error calculation and the residuals of the uncorrected profile calculation results of the present invention are introduced into the virtual simulation system. This virtual simulation system is a Y-shaped distributed ground-based radar system, which consists of three radar sub-units with a baseline length of 100 meters between the units. Figure 5 The simulated operating frequency band and target parameters of the virtual distributed ground-based radar system are shown in Table 1. The performance improvement of the transmission coherence efficiency index of the simulated distributed ground-based radar under the above-mentioned neutral atmospheric refraction error calculation results is shown in the attached figure. Figure 6 As shown by the blue line, the performance of the method of the present invention is significantly improved and stable.

[0040] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. The present invention proposes a method for calculating atmospheric refraction error of distributed ground-based radar for celestial observation, which is characterized by: The steps include: Step 1: Acquisition of refractive index profile based on numerical weather forecast model: Based on the acquired numerical weather forecast model data, elevation profile information including key meteorological elements such as air pressure, temperature, and humidity is extracted, and an atmospheric refractive index profile that varies with altitude is established according to the standard refractive index formula; Step 2: Correction of refractive index profile based on real-time surface meteorological data: Introducing real-time surface meteorological observation data to correct and optimize the original numerical weather forecast refractive index profile; Step 3. Calculation of atmospheric refraction error based on the search ray tracing method: Based on the corrected refractive index profile, with the geometric elevation angle of the celestial target as a reference, the ray tracing algorithm is applied to search for the propagation path of electromagnetic waves in the neutral atmosphere and the target elevation angle along different paths, so as to achieve accurate calculation and subsequent correction of the neutral atmospheric refraction error.

2. The method according to claim 1, wherein In step 2, the accurate surface meteorological parameters measured by meteorological sensors in real time or near real time are extracted to calculate the accurate surface atmospheric refractive index parameter N s Calculation, the calculation formula is expressed as: Where N is the atmospheric refractive index, P d is the dry atmospheric pressure, P w is the wet atmospheric pressure, and T is the Kelvin temperature.

3. The method according to claim 1, wherein In step 2, the measured surface refractivity parameter is used to correct the numerical weather forecast model. The correction formula is as follows: Where N calib (h) is the corrected refractive index profile, N nwp (h) is the refractivity profile of the numerical weather forecast model, h s is the ground surface height.

4. The method according to claim 1, wherein In step 3, the target geometric elevation angle is used as the atmospheric refraction error calculation accuracy cost function. The cost function is as follows: J=α0-F[ε,N calib (h)] where J is the cost function, α0 is the theoretical geometric elevation angle calculated from the target ephemeris, ε is the apparent observation elevation angle of the distributed ground-based radar unit, and F(·) is the target simulated geometric elevation angle calculated using the search ray tracing method under the above conditions.

5. The method according to claim 1, wherein In step 3, the apparent observation elevation angle ε is calculated using a ray tracing method based on a binary search strategy. The initial range of the binary search is set to [α0, α0+1°]. The threshold for stopping the search in the cost function is set to 1e-4 arc seconds. After stopping the search, the atmospheric refraction error is calculated as follows: Δα=ε-α0 Where Δα is the atmospheric refraction error.

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