GNSS precision satellite clock error correction calculation method based on state space representation

Abstract

The invention discloses a GNSS (Global Navigation Satellite System) precision satellite clock error correction calculation method based on state space representation. The method comprises the following steps of: 1, selecting a data segment of 10 epochs as a fitting object, thereby effectively reducing the calculation amount, improving the speed of real-time calculation and ensuring the high efficiency and accuracy of clock correction correction fitting; 2, deducting the average value of the respective system clock correction of the current epoch according to the clock correction data of each epoch; 3, recovering the satellite clock error after the broadcast time is delayed for 5 seconds by adopting the SSR data before and after the detection, and carrying out secondary difference comparison on the clock error data after the gross error detection and the original clock error data; 4, the real-time precision clock error is recovered through the generated SSR information; and step 5, after the data of the real-time data stream received by the BNC is stored, real-time imitated clock error estimation is carried out. Compared with the prior art, the method has the advantages that high-precision positioning can be kept, and meanwhile the stability and performance of a positioning system are further improved.

Description

Technical Field

[0001] The present invention relates to the field of satellite clock error correction technology and methods, and in particular to a method for calculating GNSS precision satellite clock error correction numbers based on state space representation. Background Art

[0002] Traditional PPP technology is a positioning method that relies on satellite orbit and clock information. It provides high-precision positioning services worldwide. However, this technology faces some challenges in practical applications. Since traditional precise satellite orbit and clock data need to undergo complex processing and analysis, these products often have a certain delay, which makes it impossible to meet the needs of real-time applications. In the field of real-time positioning, ultra-fast products (IGU) stand out. This product has the characteristics of real-time acquisition and can provide preliminary satellite orbit and clock estimation in a short time. However, although the IGU product is real-time, its predicted clock error accuracy is relatively low, which to a certain extent limits its application in PPP. Summary of the invention

[0003] The technical problem to be solved by the present invention is to overcome the above technical defects and provide a method for calculating clock correction numbers that maintains high-precision positioning while further improving the stability and performance of the positioning system.

[0004] In order to solve the above problems, the technical solution of the present invention is: a method for calculating GNSS precision satellite clock correction number based on state space representation, comprising the following steps;

[0005] Step 1: Select a data segment of 10 epochs as the fitting object, which effectively reduces the amount of calculation, improves the speed of real-time solution, and ensures the efficiency and accuracy of the clock correction number fitting.

[0006]

[0007] Among them, C s (t) are the real-time clock differences of satellite s at time t; is the real-time clock difference of satellite s restored to the x system center of gravity reference at time t; m is the total number of satellites of system s at time t.

[0008] Step 2: For the clock error data of each epoch, the average value of the clock error of each system in the current epoch is deducted, and the clock error data of each satellite is restored to the center of gravity reference of each system. The key to this step is to make the satellite clock error sequence more stable by eliminating the clock error deviation in the system, so as to facilitate the subsequent gross error detection and processing.

[0009]

[0010] Where INDEX(i) is the gross error detection index of epoch i; is the real-time clock difference of satellite s at epoch i. If the clock difference conforms to the theoretical value of the gross error detection index of the linear model, it is 0. When the clock difference time series is more unstable, the gross error detection index is larger. When a gross error occurs, the index will have a larger value. For this reason, I set a threshold for the subsystem to detect. When the index exceeds the threshold, this paper excludes the abnormal clock difference value from the fitting window.

[0011] Step 3: Use the SSR data before and after detection to restore the satellite clock error after the broadcast time is delayed by 5 seconds, and compare the clock error data after the detection of gross error with the original clock error data for secondary difference.

[0012] Step 4: Generate SSR information to restore real-time precise clock error, taking into account various factors such as network delay and operation delay encountered in actual applications, and generate real-time clock difference data. The impact of network delay and operation delay on clock difference recovery will have a certain impact on the recovery of real-time clock difference, thereby generating real-time clock difference data restored by SSR information after a broadcast time delay of 5s and 30s.

[0013] Step 5: After the real-time data stream received by the BNC is saved, a pseudo-real-time clock error estimation is performed afterwards.

[0014] Furthermore, based on the clock error data of each epoch in step 2, the average clock error in the system is calculated and deducted from the original clock error data. After such processing, a satellite clock error sequence based on the system center of gravity is obtained.

[0015] Furthermore, based on the clock error data obtained in step 4, a sliding window of 10 epochs is used to fit the clock error C0 and C1 items, and the clock error is recovered for each epoch. In the absence of network delay and calculation delay, the real-time clock error recovered using the SSR information should be highly consistent with the true clock error. However, in actual applications, due to the existence of network delay and calculation delay, the recovered real-time clock error will have a certain deviation from the true clock error.

[0016] Furthermore, by analyzing the positioning accuracy and mean deviation of real-time products, 5s forecast products, and 30s forecast products, it can be concluded that the RT-PPP technology using SSR information shows good positioning performance at all forecast times and can meet the needs of actual applications, although the positioning accuracy may decrease slightly when the forecast time is longer.

[0017] The advantages of the present invention compared with the prior art are:

[0018] The present invention is based on the generation of SSR information of real-time clock difference products and broadcast ephemeris, reduces the occurrence of clock error quadratic difference constants, and thus improves the accuracy and stability of the overall fitting. The simulation experiment of generating SSR and recovering it is used, and the effects of 5-second and 30-second forecasts are tested. The reliability of clock error estimation is improved by optimizing the benchmark. The core of the real-time clock benchmark adjustment method is to reduce the interference of unstable benchmark on clock error estimation by accurately adjusting the benchmark value of real-time estimated clock error. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a SSR generation flow chart of a method for calculating GNSS precision satellite clock correction numbers based on state space representation in the present invention. DETAILED DESCRIPTION

[0020] The specific embodiments of the present invention are further described below.

[0021] In order to make the contents of the present invention more clearly understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below in combination with the embodiments of the present invention.

[0022] A method for calculating GNSS precision satellite clock correction numbers based on state space representation, comprising the following steps:

[0023] Step 1: Select a data segment of 10 epochs as the fitting object, which effectively reduces the amount of calculation, improves the speed of real-time solution, and ensures the efficiency and accuracy of the clock correction number fitting.

[0024]

[0025] Among them, C s (t) are the real-time clock differences of satellite s at time t; is the real-time clock difference of satellite s restored to the x system center of gravity reference at time t; m is the total number of satellites of system s at time t.

[0026] Step 2: For the clock error data of each epoch, the average clock error of each system in the current epoch is deducted, and the clock error data of each satellite is restored to the center of gravity benchmark of each system. The key to this step is to make the satellite clock error sequence more stable by eliminating the clock error deviation in the system, so as to facilitate the subsequent gross error detection and processing; based on the clock error data of each epoch in step 2, the average clock error in its system is calculated and deducted from the original clock error data. After such processing, the satellite clock error sequence based on the center of gravity of the system is obtained.

[0027]

[0028] Where INDEX(i) is the gross error detection index of epoch i; is the real-time clock difference of satellite s at epoch i. If the clock difference conforms to the theoretical value of the gross error detection index of the linear model, it is 0. When the clock difference time series is more unstable, the gross error detection index is larger. When a gross error occurs, the index will have a larger value. For this reason, I set a threshold for the subsystem to detect. When the index exceeds the threshold, this paper excludes the abnormal clock difference value from the fitting window.

[0029] Step 3: Use the SSR data before and after detection to restore the satellite clock error after the broadcast time is delayed by 5 seconds, and compare the clock error data after the detection of gross error with the original clock error data for secondary difference.

[0030] Step 4: Use the generated SSR information to restore the real-time precise clock error. Considering the network delay and operation delay encountered in practical applications, the real-time clock difference data is generated. The influence of network delay and operation delay on the clock error recovery will have a certain impact on the recovery of the real-time clock error. Thus, the real-time clock difference data restored by the SSR information after the broadcast time is delayed by 5s and 30s is generated. Based on the clock error data in step 4, the sliding window of 10 epochs is used to fit the clock error C0 and C1 items, and the clock error is restored for each epoch. In the absence of network delay and operation delay, the real-time clock error restored by the SSR information should be highly consistent with the real clock error. However, in practical applications, due to the existence of network delay and operation delay, the restored real-time clock error will have a certain deviation from the real clock error.

[0031] Step 5: After the real-time data stream received by the BNC is saved, a pseudo-real-time clock error estimation is performed afterwards.

[0032] By analyzing the positioning accuracy and mean deviation of real-time products, 5s forecast products and 30s forecast products, it can be concluded that the RT-PPP technology using SSR information shows good positioning performance at all forecast times and can meet the needs of actual applications, although the positioning accuracy may decrease slightly when the forecast time is longer.

[0033] In the SSR format that follows the RTCM standard, the orbit correction number refers to the correction value of the satellite position and velocity in the radial, tangential and normal directions relative to the broadcast ephemeris calculation results in the satellite-fixed system. At the same time, the clock correction number is the quadratic polynomial fitting coefficient between the precise clock product and the broadcast ephemeris. This representation method can more effectively and accurately correct and adjust the satellite's orbit and clock.

[0034]

[0035] Where: IODE represents the data age; δO r ,δOa ,δO c They represent the corrections of the satellite position in the radial, tangential and normal directions at the reference time of the SSR information t0, respectively, in m; They respectively represent the rates of change of the radial, tangential and normal corrections of the satellite position at the reference time t0 of the SSR information, in m / s; C0, C1 and C2 respectively represent the quadratic polynomial fitting coefficients of the clock correction at the reference time t0 broadcasted by the SSR precise clock information.

[0036] The linear model of orbit correction number fitting is as follows:

[0037]

[0038] Among them, [RAC] T is the satellite coordinates calculated by the precise ephemeris product at time t0 in the satellite fixed system coordinates calculated by the broadcast ephemeris, δO r ,δO a ,δO c , is the SSR satellite orbit correction number.

[0039] The SSR precise clock information is also the correction relative to the broadcast ephemeris calculation result. The difference is that it broadcasts the quadratic polynomial fitting coefficients. The clock correction model at time t is:

[0040] CC b =C0+C1(t-t0)+C2(t-t0) 2

[0041] Where C is the precise clock error at time t0; C b is the clock error calculated by broadcast ephemeris; C0 is the constant term of the fitting coefficient, C1 is the coefficient of the first-order term of the fitting coefficient, and C2 is the coefficient of the second-order term of the fitting coefficient. Because the window used for fitting is small, i.e., 10 epochs, only the constant term and the coefficient of the first-order term are fitted during fitting in this paper, and the coefficient of the second-order term is considered to be zero.

[0042] In specific use, the real-time clock benchmark adjustment method improves the reliability of clock error estimation by optimizing the benchmark. The core of the real-time clock benchmark adjustment method is to reduce the interference of unstable benchmark on clock error estimation by accurately adjusting the benchmark value of real-time estimated clock error. In practical applications, by implementing benchmark adjustment, the 100-second overlapping Allan variance of each system has been reduced by about 12%. This improvement helps to enhance the reliability and robustness of clock error estimation. The real-time clock benchmark adjustment method does not involve direct changes to the clock error accuracy, but promotes faster convergence of dynamic PPP by improving stability. This feature enables this method to further improve the stability and performance of the positioning system while maintaining high-precision positioning.

[0043] In order to evaluate the performance of the gross error detection method, this paper uses the SSR data before and after the detection to recover the satellite clock error after the broadcast time is delayed by 5 seconds. In order to verify the accuracy of the recovery result, the clock error data after the gross error detection is compared with the original clock error data. In the comparison of GPS satellite clock errors, the G03 satellite is selected as the reference satellite; for the GLONASS satellite clock error, the R07 satellite is selected as the reference; for the Galileo satellite clock error, the E30 satellite is used as the reference; and for the BDS-3 satellite clock error, the C25 satellite is used as the reference satellite.

[0044] The present invention and its implementation methods are described above, and such description is not restrictive, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design structures and embodiments similar to the technical solution without creativity, which should all fall within the protection scope of the present invention.

Claims

1. A method for calculating GNSS precision satellite clock corrections based on state space representation, characterized in that: The steps include: Step 1: Select a data segment of 10 epochs as the fitting object, which effectively reduces the amount of calculation, improves the speed of real-time solution, and ensures the efficiency and accuracy of the clock correction number fitting. Among them, C s (t) are the real-time clock differences of satellite s at time t; is the real-time clock difference of satellite s restored to the x system center of gravity reference at time t; m is the total number of satellites of system s at time t. Step 2: For the clock error data of each epoch, the average value of the clock error of each system in the current epoch is deducted, and the clock error data of each satellite is restored to the center of gravity reference of each system. The key to this step is to make the satellite clock error sequence more stable by eliminating the clock error deviation in the system, so as to facilitate the subsequent gross error detection and processing. Where INDEX(i) is the gross error detection index of epoch i; is the real-time clock difference of satellite s at epoch i. If the clock difference conforms to the theoretical value of the gross error detection index of the linear model, it is 0. When the clock difference time series is more unstable, the gross error detection index is larger. When a gross error occurs, the index will have a larger value. For this reason, this subsystem sets a threshold for detection. When the index exceeds the threshold, this paper excludes the abnormal clock difference value from the fitting window. Step 3: Use the SSR data before and after the detection to restore the satellite clock error after the broadcast time is delayed by 5 seconds, and compare the clock error data after the detection of the gross error with the original clock error data for secondary difference; Step 4: Use the generated SSR information to restore the real-time precise clock difference. Considering the network delay and operation delay that may be encountered in actual applications, the real-time clock difference data is generated. The influence of network delay and operation delay on the clock difference recovery will have a certain impact on the recovery of the real-time clock difference. Thus, the real-time clock difference data restored by the SSR information after the broadcast time is delayed by 5s and 30s is generated. Step 5: After the real-time data stream received by the BNC is saved, a pseudo-real-time clock error estimation is performed afterwards.

2. The method for calculating GNSS precision satellite clock corrections based on state space representation according to claim 1, characterized in that: Based on the clock error data of each epoch in step 2, the average clock error within the system is calculated and deducted from the original clock error data. After such processing, the satellite clock error sequence based on the system center of gravity is obtained.

3. The method for calculating GNSS precision satellite clock corrections based on state space representation according to claim 1, characterized in that: Based on the clock error data obtained in step 4, a sliding window of 10 epochs is used to fit the clock errors C0 and C1, and the clock error is recovered for each epoch. In the absence of network delay and calculation delay, the real-time clock error recovered using the SSR information should be highly consistent with the true clock error. However, in actual applications, due to the existence of network delay and calculation delay, the recovered real-time clock error will have a certain deviation from the true clock error.

4. The method for calculating GNSS precision satellite clock corrections based on state space representation according to claim 1, characterized in that: By analyzing the positioning accuracy and mean deviation of real-time products, 5s forecast products and 30s forecast products, it can be concluded that the RT-PPP technology using SSR information broadcasting shows good positioning performance at all forecast times and can meet the needs of actual applications, although the positioning accuracy may decrease slightly when the forecast time is longer.

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