Klobuchar ionosphere improved model modeling method considering night delay amount change characteristics

Abstract

A Klobuchar ionized layer improved model modeling method considering night retardation change characteristics comprises the following steps: introducing ionized layer puncture point data at a plurality of geographic positions at a plurality of historical moments, and extracting statistical values of night ionized layer retardation on different latitude zones by taking day as a unit; constructing a forecasting model of the night ionosphere delay amount, and obtaining night delay amount forecasting parameters on different latitude zones; obtaining coordinates and calculation time of a puncture point of which the ionosphere delay amount needs to be calculated in real time, interpolating a night delay amount forecast parameter on the puncture point, and obtaining a night delay forecast amount on the real-time ionosphere puncture point by using a night ionosphere delay amount forecast model calculation formula; performing weighting processing on the forecast quantity of the night delay quantity and the night constant to obtain the night ionosphere delay quantity which is finally calculated by the ionosphere improved model considering the change characteristics of the night delay quantity; and constructing an ionosphere improved model considering the change of the night delay amount, and obtaining the optimized ionosphere delay calculation amount under the real-time geographic position.

Description

Technical Field

[0001] The present invention relates to the technical field of satellite navigation and positioning, and more specifically, to a method for modeling an improved Klobuchar ionosphere model considering the variation characteristics of night delay. Background Art

[0002] Ionospheric delay is one of the main error sources affecting satellite navigation and positioning. The error caused by it can reach several meters to dozens of meters. Whether this error can be corrected correctly will directly affect the positioning, navigation, and timing effects of GNSS satellites. Different types of receiver users adopt different correction methods. Among them, dual-frequency or multi-frequency receiver users generally eliminate the influence of ionospheric delay error by means of linear combination of observations. For the vast majority of single-frequency users, various ionospheric correction models and algorithms are needed.

[0003] The broadcast ionospheric model algorithms and parameters broadcast by different GNSS systems are different. Among them, the Klobuchar model is one of the most widely used broadcast ionospheric models at present. This model regards the night delay as a constant of 5 ns and uses a semi-positive cosine wave with a constant deviation to describe the diurnal variation of the vertical ionospheric delay. However, actual analysis shows that the night ionospheric delay varies significantly with factors such as latitude, solar activity, and season. The constant setting will introduce large errors. Currently, the BDS Klobuchar broadcast by the Beidou system and the GPS Klobuchar model broadcast by the GPS system are both derived from the Klobuchar model and are affected by the night constant setting of the Klobuchar model. Therefore, optimizing the prediction method of the night delay of the Klobuchar model to correctly reflect the changes with solar activity, season, and latitude is the problem that needs to be solved to improve the positioning accuracy of GNSS single-frequency users.

[0004] It can be seen that in the prior art, when the Klobuchar ionosphere model is modeled, the night ionospheric delay is directly regarded as a constant of 5 ns without considering its actual variation characteristics. This will result in the night constant setting of the Klobuchar model not conforming to the actual variation of the ionospheric delay, and large model errors will be introduced. At the same time, the currently proposed improvement methods for the night delay of this model generally need to increase the number of parameters or change the model structure, which is not convenient for actual implementation and application. Summary of the Invention

[0005] The present invention aims to overcome at least one defect (shortcoming) of the above-mentioned prior art, and provides a method for modeling an improved Klobuchar ionosphere model considering the variation characteristics of the night delay amount, so as to solve the problems in the prior art that the night constant setting of the Klobuchar model does not conform to the actual variation of the ionospheric delay amount, which will introduce a large model error, and the existing improvement methods for the night delay amount of this model generally need to increase the number of parameters or change the model structure, resulting in inconvenience in actual implementation and application, etc.

[0006] The technical solution adopted by the present invention is a method for modeling an improved Klobuchar ionosphere model considering the variation characteristics of the night delay amount, and the method includes the following steps:

[0007] S1: Introduce the ionospheric piercing point data at multiple geographical locations at multiple historical moments, and extract the statistical values of the night ionospheric delay amount in different latitude bands in units of days;

[0008] S2: Construct a prediction model for the night ionospheric delay amount, and combine the statistical values of the night ionospheric delay amount obtained in step S1 to obtain the night delay amount prediction parameters in different latitude bands;

[0009] S3: Obtain the coordinates of the piercing point and the calculation time that need to calculate the ionospheric delay amount in real time, combine the prediction parameters obtained in step S2, interpolate the night delay amount prediction parameters at the piercing point, and use the calculation formula of the night ionospheric delay amount prediction model to obtain the night delay prediction amount at the real-time ionospheric piercing point;

[0010] S4: According to the local time corresponding to the real-time piercing point to be calculated, combine the night delay amount prediction amount obtained in step S3 and the night constant set by the Klobuchar ionosphere model for weighted processing to obtain the night ionospheric delay amount finally used for calculating the improved ionosphere model considering the variation characteristics of the night delay amount;

[0011] S5: Use the coordinates of the piercing point and the calculation time to construct an improved ionosphere model considering the variation of the night delay amount in combination with the night ionospheric delay amount obtained in step S4, so as to obtain the optimized ionospheric delay calculation amount under the real-time geographical location.

[0012] This method models the variation of the night ionospheric delay amount with solar activity, season and latitude through historical data, obtains the corresponding prediction parameters and solidifies the parameters, so that the night ionospheric delay amount calculated using this improved model is different from the constant setting, can reflect the variation with factors such as latitude, season and solar activity, can improve the ionospheric delay correction effect of the Klobuchar model, effectively reduce the model error, and further improve the positioning accuracy of single-frequency users.

[0013] Preferably, in step S1, the specific process of extracting the nighttime ionospheric delay amounts in different latitude bands includes:

[0014] First, introduce the ionospheric pierce point data at multiple geographical locations at multiple historical times, then divide the historical ionospheric pierce point data by latitude, calculate the local times corresponding to all the historical ionospheric pierce point data in each latitude band, and statistically calculate the mean value of the ionospheric delay amounts corresponding to the pierce point data in the nighttime period in each latitude band on a daily basis, and use this mean value as the statistical value of the nighttime ionospheric delay amount in this latitude band on this day.

[0015] Thus, in this application, by statistically analyzing historical data, the data range obtained can cover different stages of the solar activity cycle, can capture the true variation law of the nighttime ionospheric delay amount, reduce the systematic error of the model, and the zonal division by latitude can adapt to the ionospheric characteristics of different geographical locations, making the statistical results more regional and time-effective.

[0016] Preferably, in step S2, the forecast model for the nighttime ionospheric delay amount constructed is:

[0017]

[0018] where, is the pierce point latitude; D is the day of the year corresponding to the calculation time; represents the predicted value of the nighttime delay amount at the ionospheric pierce point at the calculation time; represents the annual mean value parameter of the nighttime delay amount in each latitude band; represents the seasonal variation parameter of the nighttime delay amount in each latitude band; D min is the reference day of the year.

[0019] By constructing a forecast model for the nighttime ionospheric delay amount, the delay amount of the nighttime ionosphere can be accurately predicted, and correction can be performed during the signal propagation process, thereby eliminating the ionospheric delay error and improving the positioning accuracy.

[0020] Preferably, step S2 further includes: statistically calculating the mean value of the statistical values of the nighttime ionospheric delay amounts in different latitude bands obtained in step S1 on an annual basis, so as to obtain the annual mean value parameter of the nighttime delay amount in each latitude band Then, use the statistical values of the nighttime ionospheric delay amounts in different latitude bands obtained in step S1 to subtract According to the seasonal term variation formula in the nighttime ionospheric delay amount forecast model formula, fit to obtain the seasonal variation parameter of the nighttime delay amount in each latitude band

[0021] Thus, by calculating the annual average value of the nighttime ionospheric delay in different latitude bands, the average state of the ionosphere over a complete year can be obtained, providing a stable benchmark for further ionospheric forecasting. This helps to reduce the influence of other changing factors and provide more accurate predictions. At the same time, since the state of the ionosphere usually changes with seasons, the seasonal changes are usually the result of the combined action of factors such as solar radiation, geomagnetic activity, and seasonal atmospheric conditions. After subtracting the annual average value, the seasonal change parameters are obtained by fitting using the seasonal term change formula, which can accurately reflect the fluctuations and characteristics of the ionosphere in different seasons. Such seasonal change parameters help to better capture the periodic fluctuations of the ionosphere at night, improve the timeliness and accuracy of forecasting, and further enhance the ability to predict signal delays, reducing the interference of the ionosphere on navigation and communication systems. This solves the problem in the prior art that the nighttime constant of the Klobuchar model is directly regarded as a constant of 5 ns without considering its actual change characteristics, resulting in the inconsistency between the nighttime constant setting of the Klobuchar model and the actual changes in the ionospheric delay, and introducing a large model error.

[0022] Further preferably, according to the different types of Klobuchar models, the obtained annual average value parameters and seasonal change parameters can be converted, and the conversion formula is:

[0023]

[0024] Where, ION GPS,ns represents the value of the nighttime ionospheric delay in the GPS Klobuchar model in ns; ION BDS,ns represents the value of the nighttime ionospheric delay in the BDS Klobuchar model in ns; f B1I is the frequency corresponding to the BDS B1I frequency point; f L1 is the frequency corresponding to the GPS L1 frequency point.

[0025] In this application, considering that the annual average value parameters and seasonal change parameters obtained according to different types of Klobuchar models are different, therefore, a special conversion formula is set in this application to convert the annual average value parameters and seasonal change parameters obtained from different Klobuchar model types, thereby further improving the universality of this method.

[0026] Preferably, in the step S3, it includes: searching for the corresponding latitude band according to the coordinates of the ionospheric piercing point to be calculated in real time, then calculating the mean parameter and seasonal change parameter of the nighttime delay corresponding to the latitude of the piercing point to be calculated in real time using the interpolation calculation formula, and then obtaining the day of the year corresponding to the calculation time, and combining the forecasting model to calculate the nighttime delay forecast value at the real-time ionospheric piercing point.

[0027] In this step, the latitude band, mean parameter, seasonal variation parameter, and day of the year are combined to calculate the predicted value of the night-time delay at the real-time ionospheric pierce point, making the prediction more in line with the actual situation, capable of promptly responding to changes in the ionospheric state, providing more accurate and timely ionospheric data, enabling more accurate positioning and signal transmission in the satellite positioning system, reducing ionospheric interference, and ensuring the stability and reliability of the satellite system.

[0028] Preferably, the interpolation calculation formula is:

[0029]

[0030] Wherein, is the mean parameter of the night-time delay corresponding to the latitude of the pierce point to be calculated in real time; is the seasonal variation parameter of the night-time delay corresponding to the latitude of the pierce point to be calculated in real time; index is the serial number of the lower latitude band among the two latitude bands in step S2 corresponding to the latitude of the pierce point to be calculated in real time; Δlat is the latitude band interval; and are respectively the annual mean parameter and seasonal variation parameter of the night-time delay on the latitude band corresponding to index.

[0031] Through the above interpolation calculation formula, a more accurate local estimate can be obtained compared to directly using the preset mean, reflecting the specific ionospheric characteristics of this location, rather than only using the large-scale mean, thus effectively improving the prediction accuracy.

[0032] Preferably, in step S4, the formula for the weighting process is:

[0033]

[0034] Wherein, IPPNightIono is the night-time ionospheric delay calculated by the improved ionospheric model finally used to account for the variation characteristics of the night-time delay after the weighting process; N Const is the night-time constant; is the predicted value of the night-time delay at the real-time ionospheric pierce point obtained in step S3; dCoef is the weighting coefficient.

[0035] In this application, through the weighting process, the part of the night-time delay is replaced from a constant to a predicted value that varies with solar activity, latitude, and season, making the calculated amount of the night-time delay of the obtained model more in line with the actual spatio-temporal variation of the ionosphere, effectively improving the ionospheric delay correction effect of the Klobuchar model, and further improving the overall accuracy and applicability of the model.

[0036] Preferably, the weighting coefficient is related to the local time and the puncture point latitude at the puncture point to be calculated, and the value of the weighting coefficient is determined according to the value ranges of the local time and the puncture point latitude.

[0037] Furthermore, in the present application, the value of the weighting coefficient is also determined according to different value ranges of the local time and the puncture point latitude, so that the accuracy of the nighttime ionospheric delay calculated by the ionospheric improvement model obtained by weighting processing to take into account the variation characteristics of the nighttime delay amount is higher, thereby improving the overall accuracy of the model, and the variation of the ionospheric delay amount can be predicted more accurately.

[0038] Preferably, in step S5, the calculation formula of the ionospheric improvement model taking into account the variation of the nighttime delay amount is:

[0039]

[0040] wherein, I z (t) is the ionospheric vertical delay correction at the puncture point calculated by using the improved model; IPPNightIono is the nighttime ionospheric delay amount finally obtained by weighting processing for calculating by the ionospheric improvement model taking into account the variation characteristics of the nighttime delay amount; A and P are respectively the amplitude term and the period term of the cosine function; T0 is the initial phase value; t is the local time at the ionospheric puncture point.

[0041] Therefore, in the present application, by improving the model, the nighttime ionospheric delay amount calculated by using the improved model is different from the constant setting, and it can reflect the changes with latitude, season and solar activity factors without changing the structure and parameter settings of the original model, so that the calculated nighttime delay amount of the obtained model is more in line with the actual spatio-temporal variation of the ionosphere, thereby improving the overall accuracy and applicability of the model.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0043] Aiming at the influence of regarding the nighttime delay amount as a constant of 5 ns on the model correction performance in the Klobuchar model, considering the variation of the ionospheric nighttime delay amount with solar activity, latitude and season, the present invention creatively proposes a method for modeling an improved Klobuchar ionospheric model taking into account the variation characteristics of the nighttime delay amount. The improved model does not change the structure and parameter settings of the original model, and replaces the nighttime delay amount part therein with a predicted value varying with solar activity, latitude and season. The calculated nighttime delay amount of the model obtained by this method is more in line with the actual spatio-temporal variation of the ionosphere, effectively improving the ionospheric delay correction effect of the Klobuchar model, thereby improving the overall accuracy and applicability of the model and improving the positioning accuracy of single-frequency users. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a schematic diagram of the method flow of the present invention.

[0045] Figure 2 This is a flow chart of weight assignment for calculating the weighted value of the night delay amount in the present invention. Specific embodiments

[0046] The accompanying drawings of the present invention are only for illustrative purposes and should not be construed as limitations on the present invention. For better illustration of the following embodiments, some components in the drawings may be omitted, enlarged or reduced, and do not represent the dimensions of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0047] Embodiment 1

[0048] As Figure 1 shown, this embodiment provides a method for modeling an improved Klobuchar ionospheric model considering the variation characteristics of the night delay amount. The method includes the following steps:

[0049] Step S1: Introduce the ionospheric pierce point data at multiple geographical locations at multiple historical times, and extract the statistical values of the night ionospheric delay amount in different latitude bands on a daily basis;

[0050] Preferably, in step S1, the specific process of extracting the night ionospheric delay amount in different latitude bands includes:

[0051] S11: First, introduce the ionospheric pierce point data at multiple geographical locations at multiple historical times, and define the ionospheric pierce point data corresponding to the i-th geographical location at the t-th historical time as follows:

[0052] Diono(lon t,i ,lat t,i )

[0053] where lon t,i and lat t,i respectively represent the longitude and latitude of the i-th geographical location at the t-th historical time; time t ∈ [1, T], where T represents the total number of historical times introduced; location serial number i ∈ [1, N], where N represents the total number of geographical locations of the introduced historical pierce points.

[0054] S12: Then, divide the historical ionospheric pierce point data into bands according to latitude, calculate the local time corresponding to all historical ionospheric pierce point data in each latitude band, and statistically calculate the mean value of the ionospheric delay amount corresponding to the pierce point data in the night period in each latitude band on a daily basis, and use this mean value as the statistical value of the night ionospheric delay amount in this latitude band on this day.

[0055] In this embodiment, the specific data source for introducing historical ionospheric piercing point data can be selected according to actual requirements and conditions. This embodiment provides a reference data source. Specifically, IGS GIM data is taken as the data source. This data product provides a global ionospheric grid VTEC data map every two hours in IONEX format. Among them, the longitude range of the grid data is 180°W to 180°E, with an interval of 5°; the latitude range is 87.5°S to 87.5°N, with an interval of 2.5°. The unit of IGS GIM data is TECU. Considering that the unit of the night delay of the Klobuchar model is ns, the unit of IGS GIM data is converted from TECU to ns, and the conversion formula is as follows:

[0056]

[0057] where ION tecu and ION ns represent the ionospheric delay in TECU and ns respectively; c is the speed of light, taking 2.99792458×10 8 m / s; f is the frequency point based on when the Klobuchar model is modeled. For the BDS Klobuchar model, it takes 1.561098×10 9 Hz, and for the GPS Klobuchar model, it takes 1.57542×10 9 Hz.

[0058] And in this step, the night time period, latitude range and division method, and the length and quantity of historical data when extracting the night ionospheric delay statistic can be selected according to actual requirements and conditions. This embodiment provides a reference selection method as follows:

[0059] (1) The night time period can be taken as local time 20:00 to 6:00;

[0060] (2) The latitude zones can be divided at intervals of 15°, specifically divided into: 0 - 15°, 15 - 30°, 30 - 45°, 45 - 60°, 60 - 75°, 75 - 90°, a total of six latitude zones.

[0061] (3) Considering the characteristics of the solar activity cycle, the time period for obtaining historical ionospheric piercing point data can be taken as 2013 - 2023 for a total of 11 years, and the data range covers different stages of the solar activity cycle.

[0062] Therefore, in this application, by statistically analyzing historical data, the statistical data range can cover different stages of the solar activity cycle, capture the true variation law of the nighttime ionospheric delay, reduce the systematic error of the model, and the zonal division by latitude can adapt to the ionospheric characteristics of different geographical locations, making the statistical results more regional and time-effective.

[0063] Step S2: Construct a prediction model for the nighttime ionospheric delay, and combine the statistical values of the nighttime ionospheric delay obtained in Step S1 to obtain the nighttime delay prediction parameters for different latitudes.

[0064] Preferably, in the said Step S2, the constructed prediction model for the nighttime ionospheric delay is:

[0065]

[0066] Wherein, is the latitude of the piercing point; D is the day of the year corresponding to the calculation time; represents the predicted value of the nighttime delay at the ionospheric piercing point at the calculation time; represents the annual mean value parameter of the nighttime delay for each latitude band; represents the seasonal variation parameter of the nighttime delay for each latitude band; D min is the reference day of the year. In this embodiment, referring to the tropospheric UNB series model, the reference day of the year is taken as 28.

[0067] By constructing a prediction model for the nighttime ionospheric delay, the delay of the nighttime ionosphere can be accurately predicted, which can be corrected during the signal propagation process, thereby eliminating the ionospheric delay error and improving the positioning accuracy.

[0068] Preferably, in the said Step S2, it further includes: According to the statistical values of the nighttime ionospheric delay for different latitudes extracted in Step S1, statistically calculate its mean value in units of years, so as to obtain the annual mean value parameter of the nighttime delay for each latitude band Then use the statistical values of the nighttime ionospheric delay for different latitudes extracted in Step S1 to subtract According to the seasonal term variation formula in the nighttime ionospheric delay prediction model formula, fit to obtain the seasonal variation parameter of the nighttime delay for each latitude band

[0069] Wherein, the seasonal term variation formula is:

[0070]

[0071] Wherein, is the parameter value to be solved, denoted as X; the parameter derivative is Denoted as B; the formula for iterative calculation of this parameter is:

[0072]

[0073] where k is the number of iterations; is the parameter correction value before and after iteration; the least squares calculation method for each iteration is:

[0074] According to the known conditions, the observation equation can be listed as:

[0075]

[0076] where X 0 is the initial value of the parameter, which can be set to zero; L represents the historical nighttime ionospheric delay after deducting the annual average value at the corresponding piercing point. According to the least squares adjustment calculation formula, the normal equation can be listed as:

[0077]

[0078] where:

[0079] N BB = B T B

[0080] W = B T (L - BX 0 )

[0081] The solved parameter correction is:

[0082]

[0083] Iterative calculation until The parameter after meeting the tolerance is:

[0084]

[0085] The finally output X is the seasonal variation parameter of the nighttime delay at each latitude band obtained by fitting Thus, the forecast parameter table obtained according to the data source and processing method in this embodiment is shown in the following table:

[0086]

[0087] Table 1 Annual average value parameter of nighttime delay (unit: ns)

[0088]

[0089]

[0090] Table 2 Seasonal variation parameter of nighttime delay (unit: ns)

[0091] Further preferably, the parameter values in Table 1 and Table 2 are the results based on the BDS Klobuchar model. According to the different types of Klobuchar models, the annual average value parameters and seasonal variation parameters obtained can be converted. For the GPS Klobuchar model, when using it, the parameters in the table need to be converted according to the following formula:

[0092]

[0093] where, ION GPS,ns represents the value of the nighttime ionospheric delay in the GPS Klobuchar model in units of ns; ION BDS,ns represents the value of the nighttime ionospheric delay in the BDS Klobuchar model in units of ns; f B1I is the frequency corresponding to the BDS B1I frequency band; f L1 is the frequency corresponding to the GPS L1 frequency band.

[0094] Step S3: Obtain the puncture point coordinates and calculation time for which the ionospheric delay needs to be calculated in real time. Combine with the prediction parameters obtained in Step S2 to interpolate the nighttime delay prediction parameters at the puncture point, and use the calculation formula of the nighttime ionospheric delay prediction model to obtain the nighttime delay prediction value at the real-time ionospheric puncture point;

[0095] Preferably, in the said Step S3, it specifically includes: Search for the corresponding latitude zone according to the real-time ionospheric puncture point coordinates to be calculated, then use the interpolation calculation formula to calculate the average value parameter and seasonal variation parameter of the nighttime delay corresponding to the latitude of the real-time puncture point to be calculated. Then obtain the day of the year corresponding to the calculation time, and combine with the prediction model to calculate the nighttime delay prediction value at the real-time ionospheric puncture point.

[0096] Specifically, the interpolation calculation formula is:

[0097]

[0098] where, is the average value parameter of the nighttime delay corresponding to the latitude of the real-time puncture point to be calculated; is the seasonal variation parameter of the nighttime delay corresponding to the latitude of the real-time puncture point to be calculated; ndex is the serial number of the lower latitude zone among the two latitude zones in Step S2 corresponding to the latitude of the real-time puncture point to be calculated; Δlat is the latitude zone interval, which is selected as 15° in this embodiment; and are respectively the annual average value parameter and seasonal variation parameter of the nighttime delay on the latitude zone corresponding to index.

[0099] Step S4: Based on the local time corresponding to the real-time puncture point to be calculated, perform weighted processing by combining the predicted amount of night delay obtained in Step S3 and the night constant set by the Klobuchar ionosphere model to obtain the final night ionospheric delay amount used for calculating the improved ionosphere model that takes into account the variation characteristics of the night delay amount;

[0100] Preferably, in the said Step S4, the formula for the weighted processing is:

[0101]

[0102] wherein, IPPNightIono is the final night ionospheric delay amount obtained after weighted processing and used for calculating the improved ionosphere model that takes into account the variation characteristics of the night delay amount; N Const is the night constant, and its value is 5 ns; is the predicted amount of night delay at the real-time ionospheric puncture point obtained in Step S3; dCoef is the weighting coefficient.

[0103] Further preferably, as Figure 2 shown, Figure 2 is the flow chart of the reference selection method of the weighting coefficient dCoef. The weighting coefficient is related to the local time and the puncture point latitude at the puncture point to be calculated. According to the local time ionoT and the puncture point latitude to determine the value of the weighting coefficient.

[0104] Specifically, in this embodiment, the classification of the weighting coefficient is as follows, where the unit of the local time ionoT is taken as s:

[0105] Case 1: If ionoT ∈ (50400, 61200):

[0106] Case 1.1: If the absolute value of the latitude of the puncture point to be calculated is within 35°, the calculation formula of dCoef is as follows:

[0107]

[0108] Case 1.2: If the absolute value of the latitude of the puncture point to be calculated is outside 35°, dCoef = 1.0;

[0109] Case 2: If ionoT ∈ (0, 28800) ∪ (64800, 86400):

[0110] The calculation formula of dCoef is as follows:

[0111]

[0112] Case 3: For cases other than Case 1 and Case 2, dCoef = 1.0.

[0113] After calculating the weighted coefficient dCoef according to the local time and latitude at the puncture point to be calculated in different cases, the weighted processing formula is used to calculate the final night ionospheric delay amount for improving the model calculation.

[0114] Step S5: Using the puncture point coordinates and the calculation time, combined with the night ionospheric delay amount obtained in step S4, construct an ionospheric improvement model considering the change of the night delay amount, so as to obtain the optimized ionospheric delay calculation amount at the real-time geographical location.

[0115] Preferably, in step S5, the calculation formula of the ionospheric improvement model considering the change of the night delay amount is:

[0116]

[0117] where, I z (t) is the ionospheric vertical delay correction at the puncture point calculated by using the improvement model, based on the B1I frequency point in the BDS Klobuchar model and the L1 frequency point in the GPS Klobuchar model; IPPNightIono is the night ionospheric delay amount finally used for calculating the ionospheric improvement model considering the change characteristics of the night delay amount after weighted processing; A and P are the amplitude term and the period term of the cosine function respectively; T0 is the initial phase value, which is taken as 50400s in this embodiment; t is the local time at the ionospheric puncture point, with the unit of s.

[0118] Therefore, in the method provided in this embodiment, the changes of the night ionospheric delay amount with solar activity, season and latitude are modeled through historical data, and the corresponding prediction parameters are obtained and solidified, so that the night ionospheric delay amount calculated by using this improvement model is different from the constant setting, can reflect the changes with factors such as latitude, season and solar activity, can improve the ionospheric delay correction effect of the Klobuchar model, effectively reduce the model error, and further improve the positioning accuracy of single-frequency users.

[0119] Obviously, the above embodiments of the present invention are only examples for clearly illustrating the technical solutions of the present invention, rather than limitations on the specific implementation manners of the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principle of the claims of the present invention shall be included in the protection scope of the claims of the present invention.

Claims

1. A method for modeling an improved Klobuchar ionosphere model taking into account the night-time delay variation characteristics, characterized in that: The method comprises the following steps: S1: Introduce the ionospheric puncture point data at multiple geographical locations at multiple historical moments, and extract the statistical values ​​of the nighttime ionospheric delay at different latitudes in units of days; S2: construct a prediction model for nighttime ionospheric delay, and obtain nighttime delay prediction parameters at different latitudes by combining the statistical value of nighttime ionospheric delay obtained in step S1; S3: obtaining the coordinates of the puncture point where the ionospheric delay needs to be calculated and the calculation time in real time, interpolating the night delay prediction parameters at the puncture point in combination with the prediction parameters obtained in step S2, and obtaining the night delay prediction at the real-time ionospheric puncture point by using the calculation formula of the night ionospheric delay prediction model; S4: when the location corresponding to the real-time puncture point to be calculated is used, a weighted process is performed on the night delay amount forecast obtained in step S3 and the night constant set by the Klobuchar ionosphere model to obtain the night ionosphere delay amount calculated by the improved ionosphere model that takes into account the night delay amount variation characteristics; S5: Using the puncture point coordinates and calculation time combined with the nighttime ionospheric delay obtained in step S4, an improved ionospheric model that takes into account the nighttime delay variation is constructed, thereby obtaining an optimized ionospheric delay calculation amount under the real-time geographic location.

2. The Klobuchar ionosphere improved model modeling method taking into account the night-time delay variation characteristics according to claim 1, characterized in that: In step S1, the specific process of extracting the nighttime ionospheric delay amounts at different latitudes includes: First, the ionospheric piercing point data at multiple geographical locations at multiple historical moments are introduced, and then the historical ionospheric piercing point data are divided into bands according to latitude. The local time corresponding to all the historical ionospheric piercing point data in each latitude band is calculated, and the mean value of the ionospheric delay corresponding to the piercing point data in the night period in each latitude band is statistically calculated on a daily basis. The mean value is used as the statistical value of the nighttime ionospheric delay in the latitude band on that day.

3. The Klobuchar ionosphere improved model modeling method taking into account the night-time delay variation characteristics according to claim 1, characterized in that: In step S2, the prediction model of the nighttime ionospheric delay amount is constructed as follows: in, is the latitude of the puncture point; D is the annual day corresponding to the calculation time; It represents the predicted value of night delay at the ionospheric piercing point at the calculation time; The annual mean value parameter of the night delay in each latitude band; The seasonal variation parameter representing the night delay at each latitude band; D min The reference year is the cumulative date.

4. The Klobuchar ionosphere improved model modeling method taking into account the night-time delay variation characteristics according to claim 3 is characterized in that: The step S2 also includes: according to the statistical values ​​of the nighttime ionospheric delays at different latitudes extracted in step S1, the average values ​​are calculated in units of years, so as to obtain the annual average value parameter of the nighttime delay at each latitude. Then, the statistical values ​​of the nighttime ionospheric delays in different latitudes extracted in step S1 are used to deduct According to the seasonal variation formula in the nighttime ionospheric delay prediction model, the seasonal variation parameters of the nighttime delay in each latitude band are obtained by least squares iterative fitting.

5. The Klobuchar ionosphere improved model modeling method taking into account the night-time delay variation characteristics according to claim 4 is characterized in that: According to the different types of Klobuchar models, the annual mean parameters and seasonal variation parameters can be converted. The conversion formula is: Among them, ION GPS,ns Indicates the nighttime ionospheric delay in the GPS Klobuchar model in ns; ION BDS,ns represents the nighttime ionospheric delay in the BDS Klobuchar model in ns; f B1I is the frequency corresponding to the BDS B1I frequency point; f L1 It is the frequency corresponding to GPS L1 frequency point.

6. The Klobuchar ionosphere improved model modeling method taking into account the night-time delay variation characteristics according to claim 4 is characterized in that: The step S3 includes: searching for the corresponding latitude band according to the coordinates of the real-time ionospheric piercing point to be calculated, and then using the interpolation calculation formula to calculate the mean parameter and seasonal variation parameter of the night delay amount corresponding to the latitude of the real-time ionospheric piercing point to be calculated, and then obtaining the annual accumulated day corresponding to the calculation time, and combining the forecast model to calculate the night delay forecast amount at the real-time ionospheric piercing point.

7. The method for modeling the Klobuchar ionosphere improved model taking into account the night-time delay variation characteristics according to claim 6, characterized in that: The interpolation calculation formula is: in, is the mean parameter of the night delay corresponding to the latitude of the puncture point to be calculated in real time; is the seasonal variation parameter of the night delay corresponding to the latitude of the puncture point to be calculated in real time; index is the serial number of the lower latitude band of the two latitude bands in step S2 corresponding to the latitude of the puncture point to be calculated in real time; Δlat is the latitude band interval; and They are the annual mean parameter and seasonal variation parameter of the night delay in the latitude band corresponding to index.

8. The Klobuchar ionosphere improved model modeling method taking into account the night-time delay variation characteristics according to claim 1 is characterized in that: In step S4, the weighted processing formula is: Wherein, IPPNightIono is the nighttime ionospheric delay obtained after weighted processing and calculated by the improved ionospheric model taking into account the nighttime delay variation characteristics; N Const is the night constant; is the night delay forecast at the real-time ionospheric piercing point obtained in step S3; dCoef is the weighting coefficient.

9. The method for modeling the Klobuchar ionosphere improved model taking into account the night-time delay variation characteristics according to claim 8, characterized in that: The weighting coefficient is related to the local time at the puncture point to be calculated and the latitude of the puncture point, and the value of the weighting coefficient is determined according to the value range of the local time and the latitude of the puncture point.

10. The method for modeling the Klobuchar ionosphere improved model taking into account the night-time delay variation characteristics according to claim 1, characterized in that: In step S5, the calculation formula of the improved ionosphere model taking into account the night-time delay variation is: Among them, I z (t) is the ionospheric vertical delay correction at the puncture point calculated using the improved model; IPNightIono is the nighttime ionospheric delay calculated by the improved ionospheric model after weighted processing, which is used to take into account the nighttime delay variation characteristics; A and P are the amplitude and period terms of the cosine function, respectively; T0 is the initial phase value; t is the local time at the ionospheric puncture point.

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