CN103217177B - A kind of radio wave refractive correction method, Apparatus and system - Google Patents

Abstract

The invention discloses a kind of radio wave refractive correction method, Apparatus and system, the method comprises based on history meteorological sounding data and ground temperature and humidity pressure data, obtains tropospheric refraction rate section in real time; Based on the GNSS signal that ground list station GNSS receiver collects, the vertical total electron content measured value in Real-time Obtaining ionosphere, on the basis of the vertical total electron content measured value in ionosphere, hereditary nonlinear optimization algorithm real time inversion is utilized to go out ionospheric electron density section; According to tropospheric refraction rate section and ionospheric electron density section, ray tracing method is utilized to calculate wave environments refraction error; And target detection data are revised.The present invention can promote wave environments perception in engineering, accurately provides wave environments refraction error, effectively improves the detection accuracy of target.

Description

Radio wave refraction correction method, device and system

Technical Field

The invention relates to the technical field of electric wave environment detection and radio application, in particular to an electric wave refraction correction method, device and system.

Background

Due to the existence of the electric wave environment, the atmospheric refractive index is different from the refractive index in vacuum, and the signal generates a refraction effect in the transmission process, so that the speed and the direction of signal transmission are changed to a certain extent, and a certain measurement deviation is generated. In high-precision measurement and control systems such as aerospace measurement and control, radar detection, navigation positioning and the like, refraction error correction must be carried out on system measurement values so as to compensate errors caused by electric wave environments. The sensing and detection of the radio wave environment are the key points for determining the accuracy of atmospheric refraction correction.

At present, the troposphere detection generally adopts a sounding technology, but the sounding balloon needs about 1 hour or even longer for one-time detection, the cost is high, the operation is complex,and the general exploration station only carries out detection twice a day, cannot realize 24-hour continuous observation, and cannot meet the requirement of real-time application. The ionosphere is typically probed using ionosphere verticality techniques, which, on the one hand, only yields ionosphere F₂Layer maximum electron density hmF₂The bottom ionosphere profile below the corresponding height, on the other hand, the equipment cost is high, the antenna size is large, the mobility is poor, and the popularization and the application are inconvenient.

The developed electric wave environment detection method based on the satellite beacon mainly comprises two remote sensing detection methods of occultation detection and ground-based receiver network chromatography CT. Both methods have the problems of high cost, complex technology and the like. For example, the occultation detection needs to be matched with the low-orbit satellite joint observation and is limited by occultation events; network tomography requires that a plurality of receivers are arranged in a certain location in a certain area range, which needs to solve the problems of communication and data transmission among each other well and has long calculation time.

By combining the above analysis, the existing troposphere and ionosphere detection methods respectively have the defects of complex operation, high operation cost, low real-time performance, poor mobility, limited continuous observation capability and the like, are inconvenient for actual operation and application in engineering, restrict the precision of equipment such as navigation, positioning, measurement and control to a certain extent, greatly limit the functions of the equipment, and become the bottleneck for improving the performance of the equipment and the system. Therefore, it is necessary to develop a low-cost, portable, real-time and high-precision detection method and device which are convenient for engineering application, so as to make up for the defect of insufficient sensing capability of the radio wave environment in the engineering of China, and provide support for improving and enhancing the performance of equipment such as navigation, positioning, measurement and control.

Disclosure of Invention

The invention aims to provide a method, a device and a system for correcting electric wave refraction, which improve the electric wave environment sensing capability in engineering so as to improve the accuracy of atmospheric refraction correction on a system measurement value.

The technical scheme adopted by the invention is that the electric wave refraction correction method comprises the following steps:

the method comprises the steps of firstly, acquiring a troposphere refractive index profile in real time based on historical meteorological sounding data and ground temperature and humidity pressure data;

acquiring a vertical total electron content measured value of an ionized layer in real time based on a GNSS signal acquired by a foundation single-station GNSS (Global Navigation Satellite System) receiver, and performing real-time inversion on the electron density profile of the ionized layer by using a genetic nonlinear optimization algorithm on the basis of the vertical total electron content measured value of the ionized layer;

thirdly, calculating the refraction error of the electric wave environment in real time by using a ray tracing method according to the refractive index profile of the troposphere and the electron density profile of the ionosphere;

and step four, correcting the target detection data according to the refraction error of the electric wave environment.

Further, the first step specifically includes:

a1, substituting historical meteorological sounding data into a temperature-humidity-pressure refractive index formula to calculate a refractive index meteorological sounding profile;

a2, determining a section of the troposphere refractive index segmented model based on the troposphere refractive index segmented model and a refractive index meteorological sounding section corresponding to historical meteorological sounding data;

and A3, substituting the measured data of ground temperature and humidity into a temperature and humidity refractive index formula to calculate the measured ground refractive index, replacing the ground refractive index value in the section of the troposphere refractive index segmented model with the measured ground refractive index, and obtaining the section of the troposphere refractive index in real time.

Further, the step a2 specifically includes:

and obtaining the optimal parameters of the troposphere refractive index segmented model based on the refractive index meteorological sounding profile corresponding to the historical meteorological sounding data, and substituting the optimal parameters into the troposphere refractive index segmented model to obtain the troposphere refractive index segmented model profile.

Further, the troposphere refractive index segmentation model is as follows:

<math> <mrow> <mi>N</mi> <mrow> <mo>(</mo> <mi>h</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfenced open='{' close=''> <mtable> <mtr> <mtd> <msub> <mi>N</mi> <mn>0</mn> </msub> <mo>-</mo> <mi>&Delta;</mi> <msub> <mi>N</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>h</mi> <mo>-</mo> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>)</mo> </mrow> </mtd> <mtd> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>&le;</mo> <mi>h</mi> <mo>&le;</mo> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>+</mo> <mn>1</mn> <mi>km</mi> </mtd> </mtr> <mtr> <mtd> <msub> <mi>N</mi> <mn>1</mn> </msub> <mi>exp</mi> <mo>[</mo> <mo>-</mo> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>h</mi> <mo>-</mo> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>]</mo> </mtd> <mtd> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>+</mo> <mn>1</mn> <mi>km</mi> <mo>&lt;</mo> <mi>h</mi> <mo>&le;</mo> <mn>9</mn> <mi>km</mi> </mtd> </mtr> <mtr> <mtd> <msub> <mi>N</mi> <mn>9</mn> </msub> <mi>exp</mi> <mo>[</mo> <mo>-</mo> <msub> <mi>c</mi> <mn>9</mn> </msub> <mrow> <mo>(</mo> <mi>h</mi> <mo>-</mo> <mn>9</mn> <mo>)</mo> </mrow> <mo>]</mo> </mtd> <mtd> <mn>9</mn> <mi>km</mi> <mo>&lt;</mo> <mi>h</mi> <mo>&lt;</mo> <mn>60</mn> <mi>km</mi> </mtd> </mtr> </mtable> </mfenced> </mrow> </math>

wherein N is₀Is the ground refractive index; h is_sIs the ground altitude; delta N₁A negative gradient of refractive index within 1km of the near-ground; n is a radical of₁Refractive index at 1km above ground; c. C₁An exponential decay rate from 1km above ground to 9km above sea level; n is a radical of₉The refractive index at a height of 9km above sea level, which is very stable, may be taken as 105N units; c. C₉Exponential decay rate for altitude of 9km to 60km, parameter N₀、ΔN₁、c₁And c₉The optimal value of (a) is to be determined;

the determination process of the optimal parameters is as follows:

a21, grouping historical meteorological sounding data according to months and moments, and substituting the historical meteorological sounding data into a temperature-humidity pressure refractive index formula to obtain each group of refractive index meteorological sounding profiles; it should be noted that, because the troposphere has obvious regional differences, in order to ensure the accuracy of the refractive index model, historical meteorological exploration data of at least the last decade of local construction sites needs to be collected, and the troposphere refractive index model needs to be reconstructed.

A22, substituting the corresponding relation between different heights and refractive indexes in a meteorological sounding section with refractive index below 1km into a segment model, and calculating parameter N by using a least square method₀、ΔN₁Then N is₁＝N₀-ΔN₁；

A23, substituting the corresponding relations between different heights and refractive indexes in the 1-9 km refractive index meteorological sounding section into a segmented model, and calculating the parameter c by using a nonlinear regression algorithm₁And then:

N₉＝N₁exp[-c₁(8-h_s)]

a24, substituting the corresponding relations between different heights and refractive indexes in the meteorological sounding section of the refractive index of 9-60 km into a segmented model, and calculating the parameter c by using a nonlinear regression algorithm₉。

Further, the GNSS signals include: satellite ephemeris data and observation data for the satellites;

the second step specifically comprises:

b1, calculating the carrier phase integer ambiguity and the carrier phase difference by using the satellite observation data;

b2, calculating the GNSS system hardware error by using the self-adaptive grid method;

b3, calculating the electron content at the ionosphere puncture point IPP (ionosphere puncture point) of the propagation path between each satellite and the GNSS receiver according to the carrier phase integer ambiguity, the carrier phase difference and the GNSS system hardware error;

b4, converting the electron content at the IPP of the ionosphere puncture point of the propagation path between each satellite and the GNSS receiver into the vertical electron content at the ionosphere puncture point of each propagation path by using a projection function, and calculating the actual measurement value of the vertical total electron content of the ionosphere above the GNSS receiver by using an interpolation method;

and B5, based on the ionosphere IRI model and the ionosphere vertical total electron content measured value, optimizing and selecting the ionosphere key parameters by using a genetic optimization algorithm, and performing the ionosphere electron density profile in real time.

Further, the step B5 specifically includes:

b51: utilizing a genetic algorithm in a set search range to carry out NmF on four key parameters of an ionosphere IRI model₂、hmF₂、M(3000)F₂、F_10.7Searching is carried out, and when the difference value between the ionized layer vertical total electron content model value obtained by corresponding ionized layer IRI model integration and the ionized layer vertical total electron content measured value is minimum, the four optimized key parameters are obtained; the set search range can be determined in a weighting mode according to historical ionosphere vertical measurement data and forecast data of an IRI model;

b52: and then judging whether the optimized four key parameters meet the set precision requirement and constraint condition, and if so, substituting the optimized four key parameters into an IRI model to obtain the ionosphere electron density profile in real time.

Further, the third step specifically includes:

c1, calculating the real altitude of the target according to the apparent distance of the target, the calculation process is as follows:

let apparent distance of target be R_aWhen R is_a≤R_atWhen the target is within troposphere height, R_atRepresenting the distance corresponding to the top height of the convection layer and the real altitude h of the target_T：

<math> <mrow> <msub> <mi>R</mi> <mi>a</mi> </msub> <mo>=</mo> <msubsup> <mo>&Integral;</mo> <msub> <mi>h</mi> <mn>0</mn> </msub> <msub> <mi>h</mi> <mi>T</mi> </msub> </msubsup> <mfrac> <mrow> <msup> <mi>n</mi> <mn>2</mn> </msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mi>dh</mi> </mrow> <msqrt> <msup> <mi>n</mi> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>-</mo> <msup> <msub> <mi>n</mi> <mn>0</mn> </msub> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <msub> <mi>h</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> <msup> <mi>cos</mi> <mn>2</mn> </msup> <msub> <mi>&theta;</mi> <mn>0</mn> </msub> </msqrt> </mfrac> </mrow> </math>

When R is_a＞R_atWhen the target is within the ionization layer, the true altitude h of the target_T：

<math> <mrow> <msub> <mi>R</mi> <mi>a</mi> </msub> <mo>=</mo> <msubsup> <mo>&Integral;</mo> <msub> <mi>h</mi> <mn>0</mn> </msub> <msub> <mi>h</mi> <mi>t</mi> </msub> </msubsup> <mfrac> <mrow> <msup> <mi>n</mi> <mn>2</mn> </msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mi>dh</mi> </mrow> <msqrt> <msup> <mi>n</mi> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>-</mo> <msup> <msub> <mi>n</mi> <mn>0</mn> </msub> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <msub> <mi>h</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> <msup> <mi>cos</mi> <mn>2</mn> </msup> <msub> <mi>&theta;</mi> <mn>0</mn> </msub> </msqrt> </mfrac> </mrow> </math>

<math> <mrow> <mo>+</mo> <msubsup> <mo>&Integral;</mo> <msub> <mi>h</mi> <mi>t</mi> </msub> <msub> <mi>h</mi> <mi>T</mi> </msub> </msubsup> <mfrac> <mrow> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mi>dh</mi> </mrow> <msqrt> <msup> <mi>n</mi> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>-</mo> <msup> <msub> <mi>n</mi> <mn>0</mn> </msub> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <msub> <mi>h</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> <msup> <mi>cos</mi> <mn>2</mn> </msup> <msub> <mi>&theta;</mi> <mn>0</mn> </msub> </msqrt> </mfrac> </mrow> </math>

Wherein h is_tIs the height of the top of the convective layer;

c2, calculating the geocentric angle and the real elevation angle of the target based on the troposphere refractive index profile, wherein the calculation process is as follows:

the true elevation of the target is:

wherein,in order to detect the geocentric angle of the station and the target, the calculation formula is as follows:

c3, calculating the real distance of the target based on the geocentric angle, the real elevation angle of the target and the real sea wave height of the target, wherein the calculation process is as follows:

true distance R of target point₀The calculation formula of (a) is as follows:

c4, calculating the refraction error of the electric wave environment, comprising:

distance refraction error: Δ R ═ R_a-R₀

Elevation refraction error:₀＝θ₀-α₀

r is the radius of the earth;

h₀、n₀altitude and refractive index of the detection station;

h. n is the altitude and the refractive index of a certain point on the ray respectively;

R_a、θ₀the apparent distance and the apparent elevation angle from the detection station to the target are respectively obtained by detection of the detection station and comprise errors caused by a radio wave environment;

R₀、α₀the actual distance and the actual elevation angle from the detection station to the target are respectively.

The present invention also provides an apparatus for implementing the electric wave refraction correction method, including:

the convective layer data processing unit is used for acquiring a refractive index profile of the convective layer in real time based on historical meteorological sounding data and ground temperature and humidity pressure data;

the ionosphere data processing unit is used for acquiring a vertical total electron content measured value of an ionosphere in real time based on a GNSS signal acquired by a foundation single-station GNSS receiver, and performing real-time inversion on an ionosphere electron density profile by using a genetic nonlinear optimization algorithm on the basis of the vertical total electron content measured value of the ionosphere;

the refractive index error calculation unit is used for calculating the refractive error of the electric wave environment in real time by using a ray tracing method according to the refractive index profile of the troposphere and the electron density profile of the ionosphere;

and the target detection data correction unit is used for correcting the target detection data according to the refraction error of the electric wave environment.

The present invention also provides a system for implementing the electric wave refraction correction method, including: an apparatus for implementing the radio wave refraction correction method, and a data acquisition device,

the data acquisition device includes: the system comprises a ground-based single-station GNSS receiver for acquiring GNSS signals and a meteorological data acquisition unit for acquiring temperature and humidity data; and the meteorological data acquisition unit is fixedly connected with the GNSS receiver.

Further, the GNSS receiver includes: the GNSS receiver antenna, the antenna support and the GNSS satellite monitoring module; the meteorological data unit includes: a temperature and humidity sensor, an air pressure sensor and an analog-to-digital converter; the GNSS receiving antenna is installed at the topmost end of the antenna support, the temperature and humidity sensor and the air pressure sensor are both fixed on the antenna support and are lower than the GNSS receiving antenna, and the installation height of the air pressure sensor is not lower than 0.5 m;

the GNSS receiving antenna is connected with the GNSS satellite monitoring module through a radio frequency line, and the GNSS satellite monitoring module outputs the acquired GNSS signals to the ionization layer data processing unit;

the temperature and humidity sensor and the air pressure sensor respectively convert the collected analog signals into digital signals through the analog-to-digital converter and then input the digital signals into the convection layer data processing unit.

By adopting the technical scheme, the invention at least has the following advantages:

the radio wave refraction correction method, the device and the system realize real-time detection of the radio wave environment (mainly comprising the troposphere and the ionosphere) within the height range from the ground to 2000km, overcome the defect that other conventional equipment can only detect partial high radio wave environment, and calculate the refraction error of the radio wave environment in real time. Compared with other existing electric wave environment detection equipment, the equipment provided by the invention has the advantages of small volume, light weight, strong mobility, simple operation, low observation cost and strong anti-interference capability, can realize 24-hour unmanned continuous observation, is convenient to apply in actual engineering, and better meets the requirement of real-time refraction error correction in engineering. In addition, the invention is an open system, along with the continuous improvement and development of a GNSS satellite navigation system, especially the input of the Beidou system COMPASS in China, the number of satellites and the signal precision for detecting the electric wave environment are further increased and improved, and the electric wave environment detection precision and the refraction error correction precision are further improved.

Drawings

FIG. 1 is a flowchart illustrating a wave refraction correction method according to a first embodiment of the present invention;

FIG. 2 is a flowchart illustrating the step S101 according to the first embodiment of the present invention;

FIG. 3 is a flowchart illustrating the step S102 according to the first embodiment of the present invention;

FIG. 4 is a flowchart illustrating the step S103 according to the first embodiment of the present invention;

FIG. 5 is a schematic view of a wave refraction correction apparatus according to a second embodiment of the present invention;

FIG. 6 is a schematic diagram of a beam refraction correction system according to a third embodiment of the present invention;

FIG. 7 is a schematic diagram illustrating the connection and installation relationship of outdoor equipment of a wave refraction correction system according to a third embodiment of the present invention;

FIG. 8 is a diagram illustrating exemplary effects of distance refraction error correction according to an embodiment of the present invention;

FIG. 9 is a diagram illustrating exemplary effects of elevation refractive error correction according to an embodiment of the present invention;

FIGS. 10 (a) and (b) are schematic diagrams illustrating comparison before and after multiple distance refraction error corrections according to an embodiment of the present invention;

FIGS. 11 (a) and (b) are schematic diagrams comparing the multiple elevation refractive error corrections according to the embodiment of the present invention.

Detailed Description

To further explain the technical means and effects of the present invention adopted to achieve the intended purpose, the present invention will be described in detail with reference to the accompanying drawings and preferred embodiments.

A first embodiment of the present invention, a wave refraction correction method, as shown in fig. 1, includes the following steps:

and S101, acquiring a troposphere refractive index profile in real time based on historical meteorological sounding data and ground temperature and humidity pressure data.

Specifically, as shown in fig. 2, step S101 includes the following processes:

and A1, substituting the historical meteorological sounding data into a temperature-humidity-pressure refractive index formula to calculate the refractive index meteorological sounding profile.

The tropospheric refractive index N' can be expressed as a function of atmospheric state parameters (atmospheric pressure P, air temperature T and water vapor pressure E), i.e. a temperature-humidity-pressure refractive index formula, as follows:

<math> <mrow> <msup> <mi>N</mi> <mo>&prime;</mo> </msup> <mo>=</mo> <mn>77.6</mn> <mfrac> <mi>P</mi> <mi>T</mi> </mfrac> <mo>-</mo> <mn>5.6</mn> <mfrac> <mi>E</mi> <mi>T</mi> </mfrac> <mo>+</mo> <mn>3.75</mn> <mo>&times;</mo> <msup> <mn>10</mn> <mn>5</mn> </msup> <mfrac> <mi>E</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> </mfrac> <mo>&ap;</mo> <mn>77.6</mn> <mfrac> <mi>P</mi> <mi>T</mi> </mfrac> <mo>+</mo> <mn>3.73</mn> <mo>&times;</mo> <msup> <mn>10</mn> <mn>5</mn> </msup> <mfrac> <mi>E</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </math>

wherein P, T, e has units of hPa (1hPa =1mb) and K, hPa.

And A2, determining a section of the troposphere refractive index segmented model based on the troposphere refractive index segmented model and the refractive index meteorological sounding section corresponding to the historical meteorological sounding data.

Specifically, the tropospheric refractive index segmentation model is shown by the following equation (2). The troposphere refractive index model of the embodiment of the invention adopts a sectional type, namely a linear mode is adopted from the ground to 1km, and different index modes are respectively adopted between 1 km-9 km and 9 km-60 km:

<math> <mrow> <mi>N</mi> <mrow> <mo>(</mo> <mi>h</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfenced open='{' close=''> <mtable> <mtr> <mtd> <msub> <mi>N</mi> <mn>0</mn> </msub> <mo>-</mo> <mi>&Delta;</mi> <msub> <mi>N</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>h</mi> <mo>-</mo> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>)</mo> </mrow> </mtd> <mtd> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>&le;</mo> <mi>h</mi> <mo>&le;</mo> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>+</mo> <mn>1</mn> <mi>km</mi> </mtd> </mtr> <mtr> <mtd> <msub> <mi>N</mi> <mn>1</mn> </msub> <mi>exp</mi> <mo>[</mo> <mo>-</mo> <msub> <mi>c</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>h</mi> <mo>-</mo> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>]</mo> </mtd> <mtd> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>+</mo> <mn>1</mn> <mi>km</mi> <mo>&lt;</mo> <mi>h</mi> <mo>&le;</mo> <mn>9</mn> <mi>km</mi> </mtd> </mtr> <mtr> <mtd> <msub> <mi>N</mi> <mn>9</mn> </msub> <mi>exp</mi> <mo>[</mo> <mo>-</mo> <msub> <mi>c</mi> <mn>9</mn> </msub> <mrow> <mo>(</mo> <mi>h</mi> <mo>-</mo> <mn>9</mn> <mo>)</mo> </mrow> <mo>]</mo> </mtd> <mtd> <mn>9</mn> <mi>km</mi> <mo>&lt;</mo> <mi>h</mi> <mo>&lt;</mo> <mn>60</mn> <mi>km</mi> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow> </math>

wherein N is₀Is the ground refractive index (in international units of refractive index N); h is_sGround altitude (km); delta N₁A negative gradient of refractive index (1/km) within 1km of the ground; n is a radical of₁Refractive index at 1km above ground; c. C₁An exponential decay rate (1/km) from 1km above ground to 9km above sea level; n is a radical of₉The refractive index at a height of 9km above sea level, which is very stable, may be taken as 105N units; c. C₉An exponential decay rate (1/km) of an altitude of 9km to 60 km. N is a radical of₀、ΔN₁、c₁And c₉Is the amount to be requested.

According to the embodiment of the invention, historical meteorological sounding data needs to be collected, and the optimal parameters of the troposphere refractive index segmentation model are obtained based on the refractive index meteorological sounding profile corresponding to the historical meteorological sounding data: n is a radical of₀、ΔN₁、c₁And c₉And substituting the optimal parameters into the troposphere refractive index segmented model to obtain a troposphere refractive index segmented model section.

The determination process of the optimal parameters is as follows:

a21, grouping the historical meteorological sounding data according to the month and the moment, and substituting the data into a temperature-humidity pressure refractive index formula to obtain each group of refractive index meteorological sounding profiles. It should be noted that, because the troposphere has obvious regional differences, in order to ensure the accuracy of the refractive index model, historical meteorological exploration data of at least the last decade of local construction sites needs to be collected, and the troposphere refractive index model needs to be reconstructed.

A22, substituting the corresponding relation between different heights and refractive indexes in a meteorological sounding section with refractive index below 1km into a segment model, and calculating parameter N by using a least square method₀、ΔN₁Then N is₁＝N₀-ΔN₁。

A23, substituting the corresponding relations between different heights and refractive indexes in the 1-9 km refractive index meteorological sounding section into a segmented model, and calculating the parameter c by using a nonlinear regression algorithm₁And then:

N₉＝N₁exp[-c₁(8-h_s)]

a24, substituting the corresponding relations between different heights and refractive indexes in the meteorological sounding section of the refractive index of 9-60 km into a segmented model, and calculating the parameter c by using a nonlinear regression algorithm₉。

And A3, substituting the measured data of ground temperature and humidity into a temperature and humidity refractive index formula to calculate the measured ground refractive index, replacing the ground refractive index value in the section of the troposphere refractive index segmented model with the measured ground refractive index, and obtaining the section of the troposphere refractive index in real time.

Specifically, the collection and processing of ground temperature, humidity and pressure data. Acquiring meteorological environment parameters by using temperature, humidity and pressure sensors, wherein the acquisition time interval is 1min, taking complete observation every 5min, preprocessing the acquired data, removing observation field values in the acquired data, and smoothing the acquired data to obtain effective observation data.

Converting the processed effective temperature, humidity and pressure data into a ground refractive index measured value through a temperature and humidity pressure refractive index formula (1), and replacing the ground refractive index N in the section of the tropospheric refractive index segmental model by using the measured value₀And acquiring the refractive index profile of the troposphere in real time.

And S102, acquiring a vertical total electron content measured value of an ionized layer in real time based on a GNSS signal acquired by a foundation single-station GNSS receiver, and performing real-time inversion on the electron density profile of the ionized layer by using a genetic nonlinear optimization algorithm on the basis of the vertical total electron content measured value of the ionized layer.

The GNSS signals include: satellite ephemeris data and observation data for the satellites.

Specifically, as shown in fig. 3, step S102 includes the following processes:

b1, calculating the carrier phase integer ambiguity and the carrier phase difference based on the satellite observation data.

Specifically, the satellite observation data collected by the GNSS receiver includes: carrier phase observations, pseudorange observations, and the like. The GNSS system operates in dual frequency, has two operating frequencies (1.57542 GHz and 1.2276 GHz), and can obtain a carrier phase difference according to an observed value of carrier phases of the two operating frequencies of the GNSS receiver, and can obtain a pseudo-range difference P according to a pseudo-range observed value of the two operating frequencies of the GNSS receiver.

The carrier phase integer ambiguity is:

<math> <mrow> <mover> <msub> <mi>B</mi> <mi>ion</mi> </msub> <mo>&OverBar;</mo> </mover> <mo>=</mo> <mfrac> <mrow> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </msubsup> <mo>{</mo> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mi>ion</mi> </msub> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>L</mi> <mi>ion</mi> </msub> <msub> <mi>t</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>/</mo> <mi>&sigma;</mi> <msup> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>}</mo> </mrow> <mrow> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </msubsup> <mn>1</mn> <mo>/</mo> <mi>&sigma;</mi> <msup> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow> </math>

in the formula, the carrier phase difference L_ion＝L₁-L₂Pseudorange difference P_ion＝P₁-P₂，P_iAnd L_i(the numbers i =1,2 of the two operating frequencies of the GNSS receiver) represent the observed values of the pseudoranges and the carrier phases of the two frequencies, respectively, and M is the number of samples of the observation period. Weight coefficient σ (t)_i) Noise and satellite elevation, reception of received signalsThe type of machine is related to the manner in which the satellite is received.

Wherein e is the elevation angle of the satellite, and the coefficient a in the above formula₀、a₁、a₂、a₃、a₄Respectively taking the values of 39.4273, -2.77934, 0.0916714, -0.00152106 and 9.976 multiplied by 10^-6When the satellite elevation angle is low, the influence of the multipath effect on the vertical total electron content VTEC of the ionized layer is great, and the result is not credible, so that the satellite elevation angle of the embodiment of the invention is selected to be more than 30 degrees.

And B2, calculating the GNSS system hardware error by using the adaptive grid method.

GNSS system hardware errors are a general term for the time delay in propagation of two operating frequency signals caused by satellite and receiver hardware and can be described in units of electronic content (TECU). After the US SA interference policy of 5-month-1-year 2000 is cancelled, the hardware delay of the system becomes the maximum error source of the system, and in the calculation process of total electron content TEC of an ionized layer, the deviation caused by hardware error of a GNSS system is as high as 30TECU, even higher than the background value of the total electron content at night and in the lower years of solar activity. Therefore, when solving for TEC, the effect of GNSS system hardware error must be eliminated as much as possible.

The specific process of the step B2 is as follows: the ionosphere is divided into uniform grids according to longitude and latitude, the vertical electron content corresponding to the electron content at the ionosphere puncture point of the propagation path between different satellites and the GNSS receiver in the same grid is equal, an overdetermined linear equation set is listed, and the GNSS system hardware error is obtained through solving according to a least square method. The total ionospheric electron content (i.e., the measured value of the vertical total ionospheric electron content) of the propagation path between the satellite and the GNSS receiver is = the measured value of the total ionospheric electron content of the propagation path between the satellite and the GNSS receiver — the GNSS system hardware error.

Furthermore, the carrier phase integer ambiguity and the carrier phase difference can be calculated through satellite observation data, and further the ionospheric total electron content measurement value of the propagation path between the satellite and the GNSS receiver is calculated, wherein the measurement value comprises the GNSS system hardware error.

In this embodiment, the GNSS system hardware error estimation adopts an adaptive grid method, i.e., adaptive filtering, which has the advantages that data sampling is not time-controlled, and the calculation accuracy is high. Specifically, the method divides the ionosphere into uniform grids according to local time a (i.e., longitude) and latitude b, with the size a × b, a = 0.1-0.2 h, b = 0.2-0.25 °, and h is an hour unit. The preferred grid sizes are: 0.2 h.times.0.25 deg.C. TEC for electron content at ionospheric puncture points assuming propagation paths between different satellites and GNSS receivers within each grid_IPPCorresponding vertical electron content VTEC_IPPEqual, VTEC_IPP=(TEMP_IPP-q)S(e)，TEMP_IPPIs the electron content measurement value at the ionospheric puncture point of the propagation path between the satellite and the GNSS receiver, q is the GNSS system hardware error, e is the elevation angle of the satellite, and s (e) is the tangent value of the satellite elevation angle. The following equation holds true:

$({\mathrm{TEMP}}_{\mathrm{IPP}}^j-q^j)S\left(e^j\right)=({\mathrm{TEMP}}_{\mathrm{IPP}}^k-q^k)S\left(e^k\right)---\left(4\right)$

conversion to:

<math> <mrow> <mi>S</mi> <mrow> <mo>(</mo> <msup> <mi>e</mi> <mi>k</mi> </msup> <mo>)</mo> </mrow> <mo>&times;</mo> <msup> <mi>q</mi> <mi>j</mi> </msup> <mo>-</mo> <mi>S</mi> <mrow> <mo>(</mo> <msup> <mi>e</mi> <mi>k</mi> </msup> <mo>)</mo> </mrow> <mo>&times;</mo> <msup> <mi>q</mi> <mi>j</mi> </msup> <mo>=</mo> <msubsup> <mi>TEMP</mi> <mi>IPP</mi> <mi>j</mi> </msubsup> <mi>S</mi> <mrow> <mo>(</mo> <msup> <mi>e</mi> <mi>k</mi> </msup> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>TEMP</mi> <mi>IPP</mi> <mi>k</mi> </msubsup> <mi>S</mi> <mrow> <mo>(</mo> <msup> <mi>e</mi> <mi>j</mi> </msup> <mo>)</mo> </mrow> </mrow> </math>

in the formulaR (R6731 km) and H (H350 km) respectively represent the earth radius and the equivalent height of the ionosphere in the single-layer ionosphere model. Parameter q to be solved^jAnd q is^k(j, k represent different satellite numbers, and for the GPS system, 32 satellites in orbit can participate in the calculation), namely the GNSS system hardware error. Through each satellite observation data, a plurality of groups of equations shown as the formula (4) can be obtained, and according to the actual situation, the daily size of the GNSS receiver for 30 seconds of satellite observation data is largeAnd (3) about 300-400 sets of equations such as the equation (4) are provided, the number of the equations is far larger than the number of the unknowns, the equations are an overdetermined linear equation set, and the equation set is solved according to a least square method to obtain the optimal solution of the GNSS system hardware error, which is used as the GNSS system hardware error q.

B3, calculating the electron content STEC at the ionosphere puncture point IPP (ionosphere Pierce Point) of the propagation path between each satellite and the GNSS receiver_IPP。

STEC_IPPThe calculation formula of (a) is as follows:

<math> <mrow> <msub> <mi>STEC</mi> <mi>IPP</mi> </msub> <mo>=</mo> <mfrac> <mn>1</mn> <mi>&alpha;</mi> </mfrac> <mrow> <mo>(</mo> <msub> <mi>l</mi> <mi>ion</mi> </msub> <mo>-</mo> <mover> <msub> <mi>B</mi> <mi>ion</mi> </msub> <mo>&OverBar;</mo> </mover> <mo>)</mo> </mrow> <mo>-</mo> <mi>q</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </mrow> </math>

wherein,f1 and f2 are two working frequencies of the GNSS receiver, L_ionA phase difference of the carrier waves representing two operating frequencies of the GNSS receiver,The carrier phase integer ambiguity is shown, and q represents the GNSS system hardware error.

B4, using projection function to make the electron content STEC at the ionosphere puncture point IPP of the propagation path between each satellite and the GNSS receiver_IPPVertical electron content VTEC at ionosphere puncture point converted into various propagation paths_IPP(VTEC_IPP＝STEC_IPPcos (Δ z)), and then an interpolation method is used to calculate the vertical total electron content VTEC measured value of the air ionosphere on the GNSS receiver.

Specifically, the geocentric angle between the GNSS receiver and the ionosphere puncture point is calculated according to the elevation angle of each satellite (calculated according to GNSS ephemeris data), the radius of the earth and the height of the ionosphere (350 km), and a calculation formula of the geocentric angle Δ z between the GNSS receiver and the ionosphere puncture point IPP is as follows:

<math> <mrow> <mi>&Delta;z</mi> <mo>=</mo> <mfrac> <mi>&pi;</mi> <mn>2</mn> </mfrac> <mo>-</mo> <mi>e</mi> <mo>-</mo> <mi>acr</mi> <mi>sin</mi> <mrow> <mo>(</mo> <mfrac> <mrow> <mi>cos</mi> <mi>e</mi> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>H</mi> <mo>/</mo> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>H</mi> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> </mrow> </math>

wherein e is the satellite elevation angle, and R and H are the earth radius and the ionosphere height, respectively.

The position of the satellite is calculated by using satellite ephemeris data, the position of an intersection point (namely an ionosphere puncture point) of a connecting line of the GNSS receiver and the satellite position and the ionosphere height (350 km) is further obtained, and after the position of the connecting line of the GNSS receiver and the satellite position at the ionosphere puncture point is determined, the vertical total electron content VTEC measured value of the ionosphere above the GNSS receiver can be calculated by using an interpolation method.

And B5, based on the ionosphere IRI model and the ionosphere vertical total electron content VTEC measured value, optimizing and selecting the ionosphere key parameters by using a genetic optimization algorithm, and performing the ionosphere electron density profile in real time.

Specifically, NmF₂、hmF₂、M(3000)F₂、F_10.7And the key parameters of the isoelectric layer are regarded as key inversion parameters. Step B5 includes the following processes:

b51: and searching four key parameters of the ionosphere IRI model by utilizing a genetic algorithm in a set search range, and obtaining four optimized key parameters when the difference value between the ionosphere vertical total electron content VTEC model value obtained by integrating the corresponding ionosphere IRI model and the ionosphere vertical total electron content VTEC measured value is minimum. The set search range can be determined by weighting according to the historical ionospheric sag data and the forecast data of the IRI model, because the historical ionospheric sag data includes the ionospheric key parameter, the ionospheric key parameter can be calculated by the IRI model, and the set search range in this embodiment is determined by weighting according to the historical ionospheric sag data and the forecast data of the IRI model.

B52: and then judging whether the optimized four key parameters meet the set precision requirement and constraint condition, and if so, substituting the optimized four key parameters into an IRI model to obtain the ionosphere electron density profile in real time.

Further, the constraint condition is that the observation values NmF are respectively divided into high-solar activity years and low-solar activity years according to the multi-year historical detection data of the digital altimeter and the solar activity index R12₂、hmF₂、M(3000)F₂、F_10.7And (5) performing statistical analysis. The genetic algorithm constraint condition can effectively overcome the multivalue problem of the genetic algorithm and ensure the stability of the algorithm. The accuracy requirements can be set as required.

And step S103, calculating the refraction error of the radio wave environment, such as the distance refraction error, the elevation refraction error and the like, in real time by using a ray tracing method according to the refractive index profile of the troposphere and the electron density profile of the ionosphere.

The radio wave refraction error calculation is mainly to calculate the distance error and the elevation angle error of the target under different apparent distances and apparent elevation angles by utilizing a ray tracing method according to a troposphere refractive index profile and an ionosphere electron density profile.

Specifically, as shown in fig. 4, step S103 includes the following processes:

c1, calculating the real altitude of the target according to the apparent distance of the target.

Let apparent distance of target be R_aWhen R is_a≤R_atWhen the target is within troposphere height, R_atRepresenting the distance corresponding to the top height of the convection layer and the real altitude h of the target_T：

<math> <mrow> <msub> <mi>R</mi> <mi>a</mi> </msub> <mo>=</mo> <msubsup> <mo>&Integral;</mo> <msub> <mi>h</mi> <mn>0</mn> </msub> <msub> <mi>h</mi> <mi>T</mi> </msub> </msubsup> <mfrac> <mrow> <msup> <mi>n</mi> <mn>2</mn> </msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mi>dh</mi> </mrow> <msqrt> <msup> <mi>n</mi> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>-</mo> <msup> <msub> <mi>n</mi> <mn>0</mn> </msub> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <msub> <mi>h</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> <msup> <mi>cos</mi> <mn>2</mn> </msup> <msub> <mi>&theta;</mi> <mn>0</mn> </msub> </msqrt> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>7</mn> <mo>)</mo> </mrow> </mrow> </math>

When R is_a＞R_atWhen the target is within the ionization layer, the true altitude h of the target_T：

<math> <mrow> <msub> <mi>R</mi> <mi>a</mi> </msub> <mo>=</mo> <msubsup> <mo>&Integral;</mo> <msub> <mi>h</mi> <mn>0</mn> </msub> <msub> <mi>h</mi> <mi>t</mi> </msub> </msubsup> <mfrac> <mrow> <msup> <mi>n</mi> <mn>2</mn> </msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mi>dh</mi> </mrow> <msqrt> <msup> <mi>n</mi> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>-</mo> <msup> <msub> <mi>n</mi> <mn>0</mn> </msub> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <msub> <mi>h</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> <msup> <mi>cos</mi> <mn>2</mn> </msup> <msub> <mi>&theta;</mi> <mn>0</mn> </msub> </msqrt> </mfrac> </mrow> </math>

（8）

<math> <mrow> <mo>+</mo> <msubsup> <mo>&Integral;</mo> <msub> <mi>h</mi> <mi>t</mi> </msub> <msub> <mi>h</mi> <mi>T</mi> </msub> </msubsup> <mfrac> <mrow> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mi>dh</mi> </mrow> <msqrt> <msup> <mi>n</mi> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <mi>h</mi> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>-</mo> <msup> <msub> <mi>n</mi> <mn>0</mn> </msub> <mn>2</mn> </msup> <msup> <mrow> <mo>(</mo> <mi>R</mi> <mo>+</mo> <msub> <mi>h</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> <msup> <mi>cos</mi> <mn>2</mn> </msup> <msub> <mi>&theta;</mi> <mn>0</mn> </msub> </msqrt> </mfrac> </mrow> </math>

Wherein h is_tIs the height of the top of the convective bank.

C2, calculating the geocentric angle, the true elevation of the target based on the tropospheric refractive index profile.

The true elevation of the target is:

wherein,in order to detect the geocentric angle of the station and the target, the calculation formula is as follows:

c3, calculating the real distance of the target based on the geocentric angle, the real elevation angle of the target and the real sea wave height of the target. True distance R of target point₀The calculation formula of (a) is as follows:

c4, calculating the refraction error of the electric wave environment, comprising:

distance refraction error:

ΔR＝R_a-R₀ （12）

elevation refraction error:₀＝θ₀-α₀ （13）

r is the radius of the earth;

h₀、n₀altitude and refractive index of the detection station;

h. n is the altitude and the refractive index of a certain point on the ray respectively;

R_a、θ₀the apparent distance and the apparent elevation angle from the detection station to the target are respectively obtained by detection of the detection station and comprise errors caused by a radio wave environment;

R₀、α₀the actual distance and the actual elevation angle from the detection station to the target are respectively.

And step S104, correcting the target detection data according to the electric wave environment refraction error. The detection data of the target specifically refers to a detection distance or a detection elevation angle.

A second embodiment of the present invention, an apparatus for implementing the wave refraction correction method in the first embodiment, as shown in fig. 5, includes the following components:

the troposphere data processing unit 100 is used for obtaining a troposphere refractive index profile in real time based on historical meteorological sounding data and ground temperature and humidity pressure data;

the ionosphere data processing unit 200 is configured to obtain an ionosphere vertical total electron content measured value in real time based on a GNSS signal acquired by a foundation single-station GNSS receiver, and invert an ionosphere electron density profile in real time by using a genetic nonlinear optimization algorithm on the basis of the ionosphere vertical total electron content measured value;

the refractive index error calculation unit 300 is configured to calculate a refractive error of an electric wave environment in real time by using a ray tracing method according to a troposphere refractive index profile and an ionosphere electron density profile, and includes: distance refraction error, and elevation refraction error.

And a target detection data correction unit 400, configured to correct target detection data according to the refraction error of the radio wave environment, where the target detection data specifically refers to a detection distance or a detection elevation.

A third embodiment of the present invention is a system for implementing the wave refraction correction method in the first embodiment, which is located at a detection station, and includes: a data acquisition device, and a data processing module (i.e., a device operating in a computer that implements the wave refraction correction method), wherein,

the data acquisition equipment specifically comprises: the system comprises a GNSS receiver used for acquiring GNSS signals and a meteorological data acquisition unit used for acquiring temperature and humidity data; and the meteorological data acquisition unit is fixedly connected with the GNSS receiver.

Further, as shown in fig. 6 and 7, the GNSS receiver includes: a GNSS receiving antenna 501, an antenna mount 502, and a GNSS satellite monitoring module 503 (the GNSS satellite monitoring module is operated in a computer); the meteorological data unit includes: a temperature and humidity sensor 504, an air pressure sensor 505 and an analog-to-digital converter 506; the GNSS receiving antenna 501 is mounted at the topmost end of the antenna support 502, the GNSS receiving antenna 501 is connected with the GNSS satellite monitoring module 503 through a low-loss radio frequency line, and the GNSS satellite monitoring module 503 is embedded into a computer in an API bus mode; the temperature and humidity sensor 504 and the air pressure sensor 505 are both fixed on the antenna bracket 502 at a position lower than the GNSS receiving antenna 501, and the installation height of the air pressure sensor 505 is not lower than 0.5 m;

the GNSS receiving antenna 501 is connected to the GNSS satellite monitoring module 503 through a radio frequency line, and the GNSS satellite monitoring module 503 outputs the acquired GNSS signal to the ionization layer data processing unit 200 in the computer;

the temperature and humidity sensor 504 and the air pressure sensor 505 respectively convert the collected analog signals into digital signals through the analog-to-digital converter 506, and then input the digital signals into the tropospheric data processing unit 100 in the computer through the cable.

Further, the connection and erection method of the components in the data acquisition equipment is as follows:

the outdoor antenna adopts an integrated erection method, so that the operation flexibility and the mobility of the equipment can be improved. The equipment on the antenna support 502 is respectively provided with a GNSS receiving antenna 501, a temperature and humidity sensor 504, an air pressure sensor 505 and an analog-to-digital converter 506 from top to bottom. The GNSS receiving antenna 501 is installed at the topmost end of the antenna bracket, and the antenna is ensured to be horizontally arranged during installation; the temperature and humidity sensor 504 is fixed on the antenna bracket 502 through a support arm, and the installation height is lower than that of the GNSS receiving antenna 501, so that the interference to GNSS signals can be effectively prevented; meanwhile, the installation height of the air pressure sensor 505 and the analog-to-digital converter 506 is not less than 0.5m, so that the air pressure measurement is prevented from being seriously affected by the ground environment. The base of the antenna bracket 502 is circular, and the bracket is fixed on a concrete ground, an asphalt ground, a roof of a building or other firm ground by using expansion bolts, so that the stability of the bracket can be greatly improved.

In order to effectively reduce the observation error caused by the environment, the outdoor equipment (the equipment within the dashed box in fig. 6) should be installed at a proper position. When selecting addresses, the following points need attention:

a) the site should be selected at a place with a solid and stable foundation to avoid an unstable geological structure area;

b) the station is selected in a flat area with open space and wide visual field, and the satellite communication condition of the horizon height angle above 0 degree is ensured so as to prevent signals from being absorbed or shielded;

c) the distance between the land features (such as tall buildings, trees, water bodies, beaches and water accumulation regions) which are easy to generate multipath effect is not less than 300m, and the influence of the multipath effect is eliminated as much as possible;

d) the distance between the site and the surrounding high-power radio emission source (such as a television station, a radio station, a communication base station, a substation and the like) is more than 300 m; the distance between the microwave channel and the high-voltage transmission line is more than 100 m.

The data processing module specifically comprises:

the troposphere data processing unit 100 is used for obtaining a troposphere refractive index profile in real time based on historical meteorological sounding data and ground temperature and humidity pressure data;

the ionosphere data processing unit 200 is configured to obtain an ionosphere vertical total electron content measured value in real time based on a GNSS signal acquired by a foundation single-station GNSS receiver, and invert an ionosphere electron density profile in real time by using a genetic nonlinear optimization algorithm on the basis of the ionosphere vertical total electron content measured value;

the refractive index error calculation unit 300 is configured to calculate a refractive error of an electric wave environment in real time by using a ray tracing method according to a troposphere refractive index profile and an ionosphere electron density profile, and includes: distance refraction error, and elevation refraction error.

And a target detection data correction unit 400, configured to correct target detection data according to the radio wave environment refraction error, where the target detection data specifically refers to a detection distance or a detection elevation.

The implementation process of the above units is described in detail in the first embodiment, and will not be described in detail here.

In 2011, 10 months, the invention has been successfully embedded into the radar system in the P-band. Fig. 8 shows a comparative example before and after the range error correction, in which a dotted line indicates a radar range error, and a solid line indicates a range error correction residue after a refraction error caused by a radio wave environment is removed. The horizontal axis represents the radar detection elevation angle unit in degrees (deg.), the vertical axis represents the distance error before and after correction (in meters), and the dotted line represents the radar distance measurement error Δ F (Δ F — F)₀) With the curve of elevation, F denotes the radar measurement, F₀Is a target precision orbit parameter (F)₀The accuracy is high, the error is small and can be ignored, and the error is regarded as a reference value for comparison). At low elevation angles, the radar detection range error is larger, more than 150 meters, even larger, and the range error is obviously reduced along with the increase of the elevation angle. Namely, the radar detection error is closely related to the elevation angle, when the elevation angle is low, the distance error is larger, otherwise, when the elevation angle is large, the distance error is reduced, which shows that the radar detection distance error is caused by the radio wave environment (mainly including the troposphere and the ionosphere); the solid line shows the removal of the distance error Δ F using the present invention_reResidual error of₁（ΔF₁＝F-F₀-ΔF_re) It can be seen that after the refraction error is corrected, the residual error Δ F of the radar detection range is obtained₁Almost a horizontal line, namely: radar detection range residual error delta F₁Is almost flattened, which means that the radar detection range error caused by the electric wave environment is basically removed, and the radar detection precision is obviously improved.

Fig. 9 shows a comparative example before and after elevation refraction error correction, and the respective parameters have the same meanings as those in fig. 8, in which a solid line shows a correction margin of the refraction error after removal of the radio wave environment, and a dotted line shows a radar distance measurement error Δ Ele (Δ Ele ═ Ele-E)le₀) Curve with change in elevation Ele shows radar measurements, Ele₀Is a target precision orbit parameter (Ele)₀The accuracy is high, the error is small and can be ignored, and the error is regarded as a reference value for comparison). Namely: when the elevation angle is low, the detection error of the radar elevation angle is large and can reach more than 7mrad at most, and the error of the elevation angle is obviously reduced along with the increase of the elevation angle. Namely, the error of the radar elevation angle has a close relation with the detection elevation angle, when the apparent (detection) elevation angle is low, the error of the elevation angle distance is larger, and on the contrary, when the apparent (detection) elevation angle is larger, the distance error is reduced. This indicates that radar elevation errors are caused by the radio wave environment (mainly the troposphere and the ionosphere); the solid line shows the removal of the distance error Δ Ele using the present invention_reThe residual Δ Ele₁（ΔEle₁＝Ele-Ele₀-ΔEle_re) It can be seen that after the refraction error is corrected, the residual error Δ Ele of the radar detection range is remained₁Almost a horizontal line, namely: radar detection range residual Δ Ele₁Is almost flattened, which means that the radar detection range error caused by the electric wave environment is basically removed, and the radar detection precision is obviously improved.

Fig. 10 and fig. 11 respectively show statistical analysis results of multiple radar detection distances and elevation errors, wherein the left side respectively shows statistical analysis results of radar detection distances and elevation errors before environmental error correction, and the right side shows residual errors of distances and elevations after refraction error correction. The distance and elevation angle errors of the radar before correction show the same characteristics: when the elevation angle is detected, the distance and elevation angle errors of the radar are large, and when the detection elevation angle is large, the distance and elevation angle refraction errors are relatively reduced. After the refraction error is corrected, the residual errors of the distance and the elevation angle of the radar are almost flattened, and the size of the residual errors is almost independent of the elevation angle. The method can detect the whole electric wave environments of the troposphere and the ionosphere in real time, and the provided distance and elevation angle refraction errors can effectively remove the refraction errors caused by the electric wave environments, thereby obviously improving the detection accuracy of the distance and the elevation angle of the radar.

And because the invention has characteristics such as small, light in weight, easy operation, mobility are strong, make the invention have very strong using value, can make up the insufficient defect of electric wave environmental perception ability in the engineering application of our country effectively, promote the navigation of our country, position, observe and control the precision comprehensively.

The invention discloses a method, a device and a system for correcting radio wave refraction based on a foundation single-station GNSS and a meteorological sensor, which realize near real-time detection of a radio wave environment (mainly comprising a troposphere and an ionosphere) within a height range from the ground to 2000km, overcome the defect that other conventional equipment can only detect partial high radio wave environment, and calculate the radio wave environment refraction error in real time. Compared with other existing electric wave environment detection equipment, the equipment provided by the invention has the advantages of small volume, light weight, strong mobility, simple operation, low observation cost and strong anti-interference capability, can realize 24-hour unmanned continuous observation, is convenient to apply in actual engineering, and better meets the requirement of real-time refraction error correction in engineering. In addition, the invention is an open system, along with the continuous improvement and development of a GNSS satellite navigation system, especially the input of the Beidou system COMPASS in China, the number of satellites and the signal precision for detecting the electric wave environment are further increased and improved, and the electric wave environment detection precision and the refraction error correction precision are further improved.

While the invention has been described in connection with specific embodiments thereof, it is to be understood that it is intended by the appended drawings and description that the invention may be embodied in other specific forms without departing from the spirit or scope of the invention.

Claims (8)

1. A radio wave refraction correction method is characterized by comprising the following steps:

the method comprises the steps of firstly, acquiring a troposphere refractive index profile in real time based on historical meteorological sounding data and ground temperature and humidity pressure data;

acquiring a vertical total electron content measured value of an ionized layer in real time based on a GNSS signal acquired by a GNSS receiver of a foundation single-station global navigation satellite system, and performing real-time inversion on an electron density profile of the ionized layer by using a genetic nonlinear optimization algorithm on the basis of the vertical total electron content measured value of the ionized layer;

thirdly, calculating the refraction error of the electric wave environment in real time by using a ray tracing method according to the refractive index profile of the troposphere and the electron density profile of the ionosphere;

correcting target detection data according to the refraction error of the electric wave environment;

the GNSS signals include: satellite ephemeris data and observation data for the satellites;

the second step specifically comprises:

b1, calculating the carrier phase integer ambiguity and the carrier phase difference by using the satellite observation data;

b2, calculating the GNSS system hardware error by using the self-adaptive grid method;

b3, calculating the electron content at the IPP position of the ionosphere puncture point of the propagation path between each satellite and the GNSS receiver according to the carrier phase integer ambiguity, the carrier phase difference and the GNSS system hardware error;

b4, converting the electron content at the IPP of the ionosphere puncture point of the propagation path between each satellite and the GNSS receiver into the vertical electron content at the ionosphere puncture point of each propagation path by using a projection function, and calculating the actual measurement value of the vertical total electron content of the ionosphere above the GNSS receiver by using an interpolation method;

b5, based on the ionosphere IRI model and the ionosphere vertical total electron content measured value, optimizing and selecting the ionosphere key parameters by using a genetic optimization algorithm, and performing an ionosphere electron density profile in real time;

the step B5 specifically includes:

b51: utilizing a genetic algorithm in a set search range to carry out NmF on four key parameters of an ionosphere IRI model₂、hmF₂、M(3000)F₂、F_10.7Searching is carried out, and when the difference value between the ionized layer vertical total electron content model value obtained by corresponding ionized layer IRI model integration and the ionized layer vertical total electron content measured value is minimum, the four optimized key parameters are obtained; the set search range is determined according to historical ionosphere vertical measurement data and forecast data of an IRI model in a weighting mode;

b52: and then judging whether the optimized four key parameters meet the set precision requirement and constraint condition, and if so, substituting the optimized four key parameters into an IRI model to obtain the ionosphere electron density profile in real time.

2. A wave refraction correction method according to claim 1, wherein the first step specifically comprises:

a1, substituting historical meteorological sounding data into a temperature-humidity-pressure refractive index formula to calculate a refractive index meteorological sounding profile;

a2, determining a section of the troposphere refractive index segmented model based on the troposphere refractive index segmented model and a refractive index meteorological sounding section corresponding to historical meteorological sounding data;

and A3, substituting the measured data of ground temperature and humidity into a temperature and humidity refractive index formula to calculate the measured ground refractive index, replacing the ground refractive index value in the section of the troposphere refractive index segmented model with the measured ground refractive index, and obtaining the section of the troposphere refractive index in real time.

3. The radio wave refraction correction method according to claim 2, wherein the step a2 specifically includes:

and obtaining the optimal parameters of the troposphere refractive index segmented model based on the refractive index meteorological sounding profile corresponding to the historical meteorological sounding data, and substituting the optimal parameters into the troposphere refractive index segmented model to obtain the troposphere refractive index segmented model profile.

4. The radiorefraction correction method according to claim 3, wherein the troposphere refractive index segment model is as follows:

wherein N is₀Is the ground refractive index; h is_sIs the ground altitude; delta N₁A negative gradient of refractive index within 1km of the near-ground; n is a radical of₁Refractive index at 1km above ground; c. C₁1km to above groundAn exponential decay rate of altitude 9 km; n is a radical of₉Refractive index at altitude 9 km; c. C₉Exponential decay rate for altitude of 9km to 60km, parameter N₀、△N₁、c₁And c₉The optimal value of (a) is to be determined;

the determination process of the optimal parameters is as follows:

a21, grouping historical meteorological sounding data according to months and moments, and substituting the historical meteorological sounding data into a temperature-humidity pressure refractive index formula to obtain each group of refractive index meteorological sounding profiles;

a22, substituting the corresponding relation between different heights and refractive indexes in a meteorological sounding section with refractive index below 1km into a segment model, and calculating parameter N by using a least square method₀、△N₁Then N is₁＝N₀-△N₁；

A23, substituting the corresponding relations between different heights and refractive indexes in the 1-9 km refractive index meteorological sounding section into a segmented model, and calculating the parameter c by using a nonlinear regression algorithm₁And then:

N₉＝N₁exp[-c₁(8-h_s)]

a24, substituting the corresponding relations between different heights and refractive indexes in the meteorological sounding section of the refractive index of 9-60 km into a segmented model, and calculating the parameter c by using a nonlinear regression algorithm₉。

5. The radio wave refraction correction method according to claim 1, wherein the third step specifically includes:

c1, calculating the real altitude of the target according to the apparent distance of the target, the calculation process is as follows:

let apparent distance of target be R_aWhen R is_a≤R_atWhen the target is within troposphere height, R_atRepresenting the distance corresponding to the top height of the convection layer and the real altitude h of the target_T：

When R is_a>R_atWhen the target is within the ionization layer, the true altitude h of the target_T：

Wherein h is_tIs the height of the top of the convective layer;

c2, calculating the geocentric angle and the real elevation angle of the target based on the troposphere refractive index profile, wherein the calculation process is as follows:

the true elevation of the target is:

wherein,in order to detect the geocentric angle of the station and the target, the calculation formula is as follows:

c3, calculating the real distance of the target based on the geocentric angle, the real elevation angle of the target and the real sea wave height of the target, wherein the calculation process is as follows:

true distance R of target point₀The calculation formula of (a) is as follows:

c4, calculating the refraction error of the electric wave environment, comprising:

distance refraction error: Δ R ═ R_a-R₀

Elevation refraction error:₀＝θ₀-α₀

r is the radius of the earth;

h₀、n₀altitude and refractive index of the detection station;

h. n is the altitude and the refractive index of a certain point on the ray respectively;

R_a、θ₀the apparent distance and the apparent elevation angle from the detection station to the target are respectively obtained by detection of the detection station and comprise errors caused by a radio wave environment;

R₀、α₀the actual distance and the actual elevation angle from the detection station to the target are respectively.

6. An apparatus for implementing the wave refraction correction method according to claim 1, comprising:

the convective layer data processing unit is used for acquiring a refractive index profile of the convective layer in real time based on historical meteorological sounding data and ground temperature and humidity pressure data;

the ionosphere data processing unit is used for acquiring a vertical total electron content measured value of an ionosphere in real time based on a GNSS signal acquired by a foundation single-station GNSS receiver, and performing real-time inversion on an ionosphere electron density profile by using a genetic nonlinear optimization algorithm on the basis of the vertical total electron content measured value of the ionosphere;

the refractive index error calculation unit is used for calculating the electric wave environment refraction error by using a ray tracing method according to the troposphere refractive index profile and the ionosphere electron density profile;

and the target detection data correction unit is used for correcting the target detection data according to the refraction error of the electric wave environment.

7. A system for implementing the wave refraction correction method according to claim 1, comprising: the device for electric wave refraction correction method and data acquisition apparatus according to claim 8, wherein,

the data acquisition device includes: the system comprises a ground-based single-station GNSS receiver for acquiring GNSS signals and a meteorological data acquisition unit for acquiring temperature and humidity data; and the meteorological data acquisition unit is fixedly connected with the GNSS receiver.

8. The system of claim 7, wherein the GNSS receiver comprises: the GNSS receiver antenna, the antenna support and the GNSS satellite monitoring module; the meteorological data unit includes: a temperature and humidity sensor, an air pressure sensor and an analog-to-digital converter; the GNSS receiving antenna is installed at the topmost end of the antenna support, the temperature and humidity sensor and the air pressure sensor are both fixed on the antenna support and are lower than the GNSS receiving antenna, and the installation height of the air pressure sensor is not lower than 0.5 m;

the GNSS receiving antenna is connected with the GNSS satellite monitoring module through a radio frequency line, and the GNSS satellite monitoring module outputs the acquired GNSS signals to the ionization layer data processing unit;

the temperature and humidity sensor and the air pressure sensor respectively convert the collected analog signals into digital signals through the analog-to-digital converter and then input the digital signals into the convection layer data processing unit.