A method, system, electronic device and medium for inter-satellite ranging
By using virtual timescales and implicit phase entanglement elimination methods, the error problem in traditional inter-satellite ranging was solved, ranging accuracy was improved, and higher data processing accuracy was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-03-15
- Publication Date
- 2026-04-07
AI Technical Summary
Traditional inter-satellite ranging methods are prone to introducing numerical errors in time-scale processing and phase wrapping, which affects ranging accuracy.
The method employs virtual timescales and implicit phase entanglement elimination. By splitting the time marker into virtual timescales and virtual clock biases, outliers are removed, data is completed and resampled, and two-way one-way ranging is applied to calculate inter-satellite distances.
This improves the measurement accuracy of K-band inter-satellite rangefinders, avoids numerical errors introduced by time scale rounding errors and phase entanglement, and ensures the precision of data processing.
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Figure CN116256740B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of inter-satellite telemetry and control, and in particular to an inter-satellite ranging method, system, electronic device and medium. Background Technology
[0002] The Earth's gravitational field and its time-varying characteristics reflect the spatial distribution, movement, and changes of matter on the Earth's surface and interior, while also determining the undulations and variations of the geoid. Therefore, determining the fine structure and time-varying characteristics of the Earth's gravitational field is not only a requirement for geodesy, oceanography, and space science, but also provides crucial information for resource discovery, environmental protection, and disaster prediction. Satellite gravity measurement systems primarily employ methods such as high-orbit satellites tracking low-orbit satellites (high-low tracking), low-orbit satellites tracking low-orbit satellites (low-low tracking), and satellite gravity gradients to detect the Earth's gravitational field. Among these, the GRACE / GRACE Follow-On satellites utilize a combination of high-low and low-low tracking (referred to as low-low tracking gravity satellites) to detect the Earth's gravitational field. The K-band inter-satellite ranging instrument (KBR), as the core payload of the low-low tracking gravity satellite, is used to observe the relative distance and its rate of change between the two satellites with micrometer-level precision. Combined with non-conservative force data observed by accelerometers and precise satellite orbit and attitude data, the Earth's gravitational field can be inverted. Therefore, accurately acquiring observation information from gravity satellite payloads is a prerequisite for determining a high-precision Earth's gravity field. For KBR rangefinder data preprocessing, inter-satellite ranging is essentially a time measurement, making time synchronization between the two satellites crucial. Simultaneously, to ensure the accuracy of phase observations, the onboard KBR rangefinder deducts a constant (i.e., phase winding) after accumulating a certain value. When the data is transmitted to the ground for post-processing, the phase winding needs to be restored. Improper handling of phase winding can also introduce numerical errors, affecting the accuracy of the final product.
[0003] Traditional timescale processing methods involve directly correcting the clock error of the observed timescales, followed by data processing such as interpolation and resampling to achieve binary satellite time synchronization. Simultaneously, phase entanglement in the observations is directly corrected to restore the continuity of K and Ka data. However, KBR observations have micrometer-level precision, and directly correcting for timescales and phase entanglement introduces numerical errors. Summary of the Invention
[0004] The purpose of this invention is to provide a method, system, electronic device, and medium for inter-satellite ranging, which can improve the accuracy of K-band inter-satellite distance measurement.
[0005] To achieve the above objectives, the present invention provides the following solution:
[0006] A method for inter-satellite ranging, the method comprising:
[0007] Based on KBR 1A level data from the low-low tracking gravity measurement satellite, frequency band observations are extracted; the frequency band observations include K-band observations and Ka-band observations.
[0008] Based on a preset numerical precision, the time stamp of each frequency band observation is split to obtain a corresponding virtual time stamp and virtual clock bias; wherein, the virtual time stamp is the part of the time stamp that meets the preset numerical precision requirement; and the virtual clock bias is the part of the time stamp that does not meet the preset numerical precision requirement.
[0009] Outlier removal and data completion are performed on the frequency band observations corresponding to the virtual time markers to obtain preprocessed frequency band observations;
[0010] Based on the time stamp of the preprocessed frequency band observations and the virtual clock difference, the preprocessed frequency band observations are converted into frequency band observations corresponding to the GNSS time scale;
[0011] The frequency band observations corresponding to the GNSS time mark are resampled to obtain time mark-aligned frequency band observations;
[0012] Based on the time-aligned frequency band observations, the inter-satellite distances are calculated using two-way one-way ranging.
[0013] Optionally, outlier removal and data imputation are performed on the frequency band observations corresponding to the virtual time markers to obtain preprocessed frequency band observations, specifically including:
[0014] Determine the cycle slip observation and its corresponding first time identifier, as well as the gross error observation and its corresponding second time identifier, in the frequency band observations corresponding to the virtual time marker;
[0015] By removing outlier observations from the frequency band observations corresponding to the virtual time scale, outlier-free frequency band observations are obtained.
[0016] An interpolation algorithm is applied to obtain the first interpolated observation corresponding to the second time identifier in the no gross error frequency band observation, and the no gross error frequency band observation and the first interpolated observation are used as the first corrected observation;
[0017] The first corrected observation is segmented according to the first time identifier to obtain the second corrected observation;
[0018] Determine the time marker corresponding to the observation with a value of zero in the second corrected observation to obtain the third time marker;
[0019] When the length of the time period composed of continuous time identifiers in the third time identifier is greater than a preset time threshold, the second corrected observation is segmented according to the time period to obtain the third corrected observation.
[0020] An interpolation algorithm is applied to the observations with a value of zero in the third corrected observation to obtain the second interpolated observation, and the third corrected observation and the second interpolated observation are used as preprocessed observations.
[0021] Optionally, before performing "outlier removal and data imputation on the frequency band observations corresponding to the virtual time marker to obtain preprocessed frequency band observations", the method further includes:
[0022] The difference is obtained by subtracting the observations of adjacent epochs of the frequency band observations corresponding to the virtual time scale;
[0023] When the absolute value of the difference is greater than the phase entanglement threshold, the adjacent epoch observation is a phase entanglement observation;
[0024] The number of phase-wrapped observations is counted to obtain the number of phase-wrapping truncations.
[0025] Optionally, based on the time-stamped frequency band observations, two-way one-way ranging is applied to calculate the inter-satellite distance, specifically including:
[0026] Based on the time-aligned frequency band observations, the differential phase measurements of the satellites are determined; the differential phase measurements of the satellites include the differential phase measurements of the first satellite, the differential phase measurements of the second satellite, the nominal reception time, the clock error of the first satellite, the clock error of the second satellite, the local reference phase signal of the first satellite, the phase signal of the second satellite received by the first satellite, the local reference phase signal of the second satellite, the phase signal of the first satellite received by the second satellite, the integer ambiguity of the first satellite, the integer ambiguity of the second satellite, the ionospheric delay of the first satellite, the ionospheric delay of the second satellite, the number of truncations of the phase winding of the first satellite, and the number of truncations of the phase winding of the second satellite.
[0027] Based on the differential phase measurement values of the satellite, the inter-satellite distance is calculated using two-way one-way ranging.
[0028] Optionally, the formula for the bidirectional one-way distance measurement is:
[0029]
[0030] in, These are the differential phase measurements from satellite A. This is the differential phase measurement value of satellite B, where t is the nominal reception time, and Δt is the differential phase measurement value of satellite B. A , Δt B It's the clock error between the two satellites. This is the local reference phase signal for satellite A. This refers to the phase signal from satellite B received by satellite A. This is the local reference phase signal for satellite B. This refers to the phase signal received by satellite B from satellite A. It is the integer ambiguity of satellite A. It is the integer ambiguity of satellite B. For the ionospheric delay of satellite A, For the ionospheric delay of satellite B, It represents the number of times the phase of satellite A at frequency K is truncated when it wraps around satellite B. It represents the number of times the phase of satellite B is truncated when it wraps around satellite A at the K-frequency point. This refers to the residual error of satellite A. Let W be the residual error of satellite B, and W be a constant.
[0031] Optionally, before performing the step of "resampling the frequency band observations corresponding to the GNSS time mark to obtain time mark-aligned frequency band observations", the method further includes:
[0032] Low-pass filtering is applied to the frequency band observations corresponding to the GNSS time mark.
[0033] An inter-satellite ranging system, applied to the aforementioned inter-satellite ranging method, the system comprising:
[0034] The extraction module is used to extract frequency band observations based on KBR 1A level data from low-low tracking gravity measurement satellites; the frequency band observations include K-band observations and Ka-band observations.
[0035] The first time signature conversion module is used to split the time signature of each frequency band observation according to a preset numerical precision to obtain a corresponding virtual time signature and virtual clock error; wherein, the virtual time signature is the part of the time signature that meets the preset numerical precision requirement; and the virtual clock error is the part of the time signature that does not meet the preset numerical precision requirement.
[0036] The preprocessing module is used to remove outliers and complete data for the frequency band observations corresponding to the virtual time scale, so as to obtain preprocessed frequency band observations.
[0037] The second time-scale conversion module is used to convert the preprocessed frequency band observations into frequency band observations corresponding to the GNSS time scale based on the time identifier of the preprocessed frequency band observations and the virtual clock difference.
[0038] The resampling module is used to resample the frequency band observations corresponding to the GNSS time mark to obtain time mark aligned frequency band observations;
[0039] The calculation module is used to calculate the inter-satellite distance based on the time-aligned frequency band observations and by applying two-way one-way ranging.
[0040] An electronic device includes a memory and a processor, the memory storing a computer program and the processor running the computer program to enable the electronic device to perform the above-described inter-satellite ranging method.
[0041] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described inter-satellite ranging method.
[0042] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:
[0043] This invention provides an inter-satellite ranging method that introduces a virtual timescale, processing the integer and fractional parts of the timescale separately. This avoids data interpolation or fitting errors caused by timescale rounding errors during data interpolation and resampling. Furthermore, based on the characteristics of the observations from the binary KBR1A satellite, phase entanglement is implicitly eliminated, thereby avoiding direct correction of numerical errors introduced by phase entanglement and improving the accuracy of inter-satellite distance measurement using a K-band inter-satellite rangefinder. Attached Figure Description
[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0045] Figure 1 A flowchart of an inter-satellite ranging method provided by the present invention;
[0046] Figure 2 A block diagram of an inter-satellite ranging system provided by the present invention.
[0047] Explanation of reference numerals in the attached figures:
[0048] Extraction module—101, First time scale conversion module—102, Preprocessing module—103, Second time scale conversion module—104, Resampling module—105, Calculation module—106. Detailed Implementation
[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0050] The purpose of this invention is to provide a method, system, electronic device, and medium for inter-satellite ranging, which can improve the accuracy of K-band inter-satellite distance measurement.
[0051] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0052] Example 1
[0053] like Figure 1 As shown, the present invention provides a method for inter-satellite ranging, the method comprising:
[0054] Step 1: Extract frequency band observations based on KBR 1A level data from the low-low tracking gravity measurement satellite; the frequency band observations include K-band observations and Ka-band observations.
[0055] Step 2: Based on the preset numerical precision, the time stamp of each frequency band observation is split to obtain the corresponding virtual time stamp and virtual clock difference; wherein, the virtual time stamp is the portion of the time stamp that meets the preset numerical precision requirement; the virtual clock difference is the portion of the time stamp that does not meet the preset numerical precision. Specifically, the preset numerical precision is the number of decimal places, for example, if the preset numerical precision is 2 decimal places, the virtual clock is the portion with 2 decimal places, and the virtual clock difference is the portion of the time stamp minus the virtual time stamp. For example, if the preset numerical precision is 2 decimal places and the time stamp is 2.783, then the virtual clock is 2.78, and the virtual clock difference is 0.003.
[0056] In practical applications, KBR 1A level data from low-low tracking gravity measurement satellites are read, and K-band and Ka-band observations are extracted. Simultaneously, the original time stamps of the data are converted into virtual time stamps, i.e., the original time stamps are split into virtual time stamps and virtual clock errors according to equation (1). The virtual time stamp processing is as follows:
[0057] To address the non-uniformity of the KBR timescale, a virtual timescale data processing method is proposed. This method replaces the non-uniform timescale of the original observations with a virtual timescale, attributing the difference between the two timescales to virtual clock bias, thus ensuring numerical accuracy during AB satellite timescale processing. The KBR1A observation timescale is then represented as:
[0058]
[0059] Among them, t r This is the original timescale of the KBR rangefinder. Δt is the virtual time scale (a neat decimal, such as 0.1 seconds), and Δt is the virtual clock difference, representing the difference between the original time scale and the virtual time scale.
[0060] Step 3: Perform outlier removal and data completion on the frequency band observations corresponding to the virtual time scale to obtain preprocessed frequency band observations.
[0061] As a specific implementation method, step 3 specifically includes:
[0062] Step 31: Determine the cycle slip observation and its corresponding first time identifier, as well as the gross error observation and its corresponding second time identifier in the frequency band observations corresponding to the virtual time mark.
[0063] Step 32: Remove the gross error observations from the frequency band observations corresponding to the virtual time scale to obtain the frequency band observations without gross errors.
[0064] Step 33: Apply an interpolation algorithm to obtain the first interpolated observation corresponding to the second time identifier in the gross error-free frequency band observation, and use the gross error-free frequency band observation and the first interpolated observation as the first corrected observation.
[0065] Step 34: Segment the first corrected observation according to the first time identifier to obtain the second corrected observation.
[0066] Step 35: Determine the time marker corresponding to the observation with a value of zero in the second corrected observation, and obtain the third time marker.
[0067] Step 36: When the length of the time period composed of continuous time identifiers in the third time identifier is greater than a preset time threshold, the second corrected observation is segmented according to the time period to obtain the third corrected observation.
[0068] Step 37: Apply an interpolation algorithm to the observations with a value of zero in the third corrected observation to obtain the second interpolated observation, and use the third corrected observation and the second interpolated observation as preprocessed observations.
[0069] Step 4: Based on the time signature of the preprocessed frequency band observation and the virtual clock difference, convert the preprocessed frequency band observation into frequency band observation corresponding to the GNSS time scale.
[0070] As a specific implementation method, when the virtual observation timescale of the two stars is changed to GNSS, the virtual timescale is corrected by adding the virtual clock error and the precision clock error according to formula (2) to obtain the GNSS timescale and expressed in the form of formula (3).
[0071] Specifically:
[0072] With the introduction of a virtual timescale, the KBR rangefinder's timescale becomes a neat decimal, accurate to only one decimal place (0.1 seconds), allowing for conventional data preprocessing. The only difference is that correcting the receiver time to GNSS time requires considering the virtual clock error.
[0073]
[0074] Further expressed as
[0075]
[0076] In the formula, clk is the precision clock error of the KBR rangefinder. This is the sum of the precise clock error and the virtual clock error. The above time-scale processing method effectively avoids numerical errors caused by time-scale rounding errors during KBR data processing, such as data interpolation and resampling, thus ensuring the accuracy of KBR data processing.
[0077] Step 5: Resample the frequency band observations corresponding to the GNSS time mark to obtain time mark aligned frequency band observations; specifically, the time mark of the observations is not uniform decimal after correction, so the data needs to be resampled. The resampling process is to use a low-order polynomial to fit the data and output the corresponding observations at the required time mark, thus adjusting the GNSS time mark to a uniform decimal.
[0078] Step 6: Calculate the inter-satellite distance using two-way one-way ranging based on the time-aligned frequency band observations.
[0079] As a specific implementation method, step 6 specifically includes:
[0080] Step 61: Determine the differential phase measurement values of the satellite based on the time-aligned frequency band observations. The differential phase measurement values of the satellite include the differential phase measurement values of the first satellite, the differential phase measurement values of the second satellite, the nominal reception time, the clock error of the first satellite, the clock error of the second satellite, the local reference phase signal of the first satellite, the phase signal of the second satellite received by the first satellite, the local reference phase signal of the second satellite, the phase signal of the first satellite received by the second satellite, the integer ambiguity of the first satellite, the integer ambiguity of the second satellite, the ionospheric delay of the first satellite, the ionospheric delay of the second satellite, the number of truncations in the phase winding of the first satellite, and the number of truncations in the phase winding of the second satellite.
[0081] Step 62: Calculate the inter-satellite distance using two-way one-way ranging based on the differential phase measurement value of the satellite.
[0082] In practical applications, the time-aligned binary star data is used to form a double one-way inter-satellite distance (DOWR) according to formula (6), while phase wrapping correction is performed. Specifically:
[0083] Phase wrapping is a limitation on the effective number of bits in satellite storage devices. When KBR phase data accumulates to a certain value, a fixed constant W (e.g., 10) is subtracted. 8 The constant (of which the phase value is constant) is used to control the phase value within the effective number of bits. During numerical preprocessing, phase winding needs to be recovered. Adding the phase winding to the KBR phase observations will recover the original KBR observations. Taking the K-frequency phase observations of satellites A and B as an example, as shown below:
[0084]
[0085]
[0086] In practical data processing, directly introducing phase entanglement correction leads to the continuous accumulation of observational values, and rounding errors occur during data interpolation and resampling, thus introducing noise. This invention proposes a high-precision data processing method that implicitly eliminates phase entanglement, based on the characteristics of the observations from the binary star KBR1A. Since the accumulated phase observations of stars A and B are opposite, i.e., the phase entanglement signs are opposite, when the binary star observations form a double one-way distance (DOWR), the phase entanglement cutoff coefficients of the binary stars will cancel each other out. The formula for the bidirectional one-way distance measurement is as follows:
[0087]
[0088] in, These are the differential phase measurements from satellite A. This is the differential phase measurement value of satellite B, where t is the nominal reception time, and Δt is the differential phase measurement value of satellite B. A , Δt B It's the clock error between the two satellites. This is the local reference phase signal for satellite A. This refers to the phase signal from satellite B received by satellite A. This is the local reference phase signal for satellite B. This refers to the phase signal received by satellite B from satellite A. It is the integer ambiguity of satellite A. It is the integer ambiguity of satellite B. For the ionospheric delay of satellite A, For the ionospheric delay of satellite B, It represents the number of times the phase of satellite A at frequency K is truncated when it wraps around satellite B. It represents the number of times the phase of satellite B is truncated when it wraps around satellite A at the K-frequency point. This refers to the residual error of satellite A. Let W be the residual error of satellite B, and W be a constant.
[0089] In practical applications, Both Δt and t can be obtained from the KBR1A observation file. A and Δt B It can be obtained from the CLK1B clock difference product. According to formulas (4) and (5),
[0090] and yes and The components of the expression.
[0091] Therefore, only detection and marking are performed on phase entanglement. During the preprocessing process, the effects caused by phase entanglement jumps are taken into account in the cycle slip detection, interrupted data interpolation, and resampling after clock error correction, so as to ensure the accuracy of the original observation values.
[0092] As a specific implementation, between step 4 and step 5, the method further includes: performing low-pass filtering on the frequency band observations corresponding to the GNSS time mark.
[0093] In practical applications, low-pass filtering and downsampling are used to generate KBR1B-level products. The original data is a 10Hz observation, while the 1B-level product is 0.2Hz, therefore downsampling is required. The downsampling process, for example, skips ten data points from one per second and outputs one data point every 10 seconds. To prevent high-frequency noise from affecting the low-frequency signal during downsampling, low-pass filtering is performed first, followed by downsampling. The final processed data output is the KBR1B product. This product represents the numerically stable data after processing using the described method.
[0094] Furthermore, the KBR1B-class product undergoes both optical timing correction and antenna phase center correction. Antenna phase center correction: Since the satellite antenna phase center and the satellite's center of mass are not at the same location, the phase center needs to be corrected to the satellite's center of mass. This process is called antenna phase center correction, which involves multiplying the satellite's antenna vector by the line-of-sight vector between the two satellites to obtain the antenna phase center correction amount. Optical timing correction: For low-altitude tracking satellites, both satellites are in flight, resulting in different propagation times for two-way K-band ranging (due to the finite speed of light). To obtain the instantaneous distance between the two satellites, this correction is called optical timing correction. The K-band inter-satellite rangefinder measures the instantaneous distance between the phase centers of the two satellite antennas, while the final product requires the distance between the centers of mass of the two satellites. Therefore, antenna phase center correction is necessary. Additionally, microwaves propagate in space. Due to the finite speed of light and the high-speed motion of the two satellites, the propagation time of microwaves between the two satellites differs, thus requiring optical timing correction. This results in a more accurate inter-satellite distance measured using the K-band inter-satellite rangefinder.
[0095] As a specific implementation, before step 31, the inter-satellite ranging method provided by the present invention further includes phase entanglement detection and marking; specifically, the adjacent epoch observations of the frequency band observations corresponding to the virtual time scale are subtracted to obtain a difference value; when the absolute value of the difference value is greater than the phase entanglement threshold, the adjacent epoch observations are phase entanglement observations, and the number of phase entanglement observations is counted to obtain the number of phase entanglement truncations.
[0096] The difference (subtraction) is performed based on the preceding and following epochs (two consecutive observations) of the K-band and Ka-band observations. Here, preceding and following epochs refer to two consecutive observations, and the difference is the subtraction of the two observations. The phase wrapping threshold is a fixed constant; in this embodiment, the phase wrapping threshold is 10. 8 The values may vary between different satellites. If the absolute value of the difference is greater than the phase entanglement threshold, this area will be marked as phase entanglement and will not be corrected at this time.
[0097] In practical applications, data anomalies mainly include cycle slips and gross errors. Gross error cycle slip detection and marking are performed on K-band and Ka-band observations that have been marked with phase wrapping. Based on the phase wrapping markings, data anomalies caused by phase wrapping are eliminated.
[0098] 1) Gross errors, also known as outliers, are errors larger than the maximum error that could occur under normal observation conditions. A detection and removal strategy can be employed. This can be done using empirical thresholding or median filtering to detect gross errors. Then, outliers are marked and removed. Empirical thresholding compares an observation to a fixed value; if the value exceeds a certain range, the observation is deleted and marked as a gross error. Median filtering works similarly, comparing the current observation to the median of nearby observations; if the value exceeds a threshold, it is marked as a gross error and removed. Subsequent steps involve interpolating and restoring the removed data.
[0099] 2) For cycle slips, a cycle slip refers to a jump in the carrier observation of the K-waveguide inter-satellite ranging instrument. When a cycle slip occurs, all subsequent observations will experience the same jump, while gross errors only occur at the current moment. A detection and marking processing strategy is adopted, in which detected cycle slips are only marked.
[0100] After removing the detected gross errors, the missing data are filled in using linear interpolation or low-order polynomial interpolation methods.
[0101] For cases where original observation data is missing, if the duration of the missing observation is less than a set threshold duration, the missing observation is considered a short-term data gap, which is filled using low-order polynomial interpolation. If the duration of the missing observation is not less than the set threshold duration, the missing observation is considered a long-term data gap. For long-term data gaps, interpolation is not recommended; instead, a data segmentation strategy should be adopted. This is because the missing original observation data is not a cycle slip, but rather due to equipment malfunction causing the data to be unrecorded. Data segmentation divides the missing data into two parts, before and after the missing data, to avoid introducing additional errors through interpolation.
[0102] For observations labeled as cycle slips, a data segmentation strategy is applied, where a cycle slip is a change in carrier phase.
[0103] This invention proposes a method for handling timescale and phase entanglement effects in K-band inter-satellite rangefinder observations, addressing the numerical stability problem in KBR data processing and overcoming the shortcomings of traditional methods. Firstly, it introduces a virtual timescale, processing the integer and fractional parts of the timescale separately to avoid data interpolation or fitting errors caused by timescale rounding errors during data interpolation and resampling. Secondly, it employs an implicit phase entanglement elimination method, implicitly eliminating phase entanglement based on the characteristics of KBR1A binary satellite observations, thereby avoiding direct correction of numerical errors introduced by phase entanglement.
[0104] Example 2
[0105] To implement the method corresponding to Embodiment 1 above and achieve the corresponding functions and technical effects, an inter-satellite ranging system is provided below, such as... Figure 2 As shown, the system includes:
[0106] Extraction module 101 is used to extract frequency band observations based on KBR 1A level data from low-low tracking gravity measurement satellites; the frequency band observations include K-band observations and Ka-band observations.
[0107] The first time signature conversion module 102 is used to split the time signature of each frequency band observation according to a preset numerical precision to obtain a corresponding virtual time signature and virtual clock difference; wherein, the virtual time signature is the part of the time signature that meets the preset numerical precision requirement; and the virtual clock difference is the part of the time signature that does not meet the preset numerical precision requirement.
[0108] The preprocessing module 103 is used to remove outliers and complete data for the frequency band observations corresponding to the virtual time marker, so as to obtain preprocessed frequency band observations.
[0109] The second time-scale conversion module 104 is used to convert the preprocessed frequency band observations into frequency band observations corresponding to the GNSS time scale based on the time stamp of the preprocessed frequency band observations and the virtual clock difference.
[0110] The resampling module 105 is used to resample the frequency band observations corresponding to the GNSS time mark to obtain time mark aligned frequency band observations.
[0111] The calculation module 106 is used to calculate the inter-satellite distance based on the time-aligned frequency band observations and by applying two-way one-way ranging.
[0112] Example 3
[0113] This invention provides an electronic device, including a memory and a processor. The memory stores a computer program, and the processor runs the computer program to enable the electronic device to perform the inter-satellite ranging method of Embodiment 1.
[0114] Alternatively, the aforementioned electronic device may be a server.
[0115] In addition, embodiments of the present invention also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the inter-satellite ranging method of Embodiment 1.
[0116] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.
[0117] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.
Claims
1. A method for inter-satellite ranging, characterized in that, The method includes: Based on KBR 1A level data from the low-low tracking gravity measurement satellite, frequency band observations are extracted; the frequency band observations include K-band observations and Ka-band observations. Based on a preset numerical precision, the time stamp of each frequency band observation is split to obtain a corresponding virtual time stamp and virtual clock bias; wherein, the virtual time stamp is the part of the time stamp that meets the preset numerical precision requirement; and the virtual clock bias is the part of the time stamp that does not meet the preset numerical precision requirement. Outlier removal and data completion are performed on the frequency band observations corresponding to the virtual time markers to obtain preprocessed frequency band observations; Before performing "outlier removal and data completion on the frequency band observations corresponding to the virtual timescale to obtain preprocessed frequency band observations", the process also includes: The difference is obtained by subtracting the observations of adjacent epochs of the frequency band observations corresponding to the virtual time scale; When the absolute value of the difference is greater than the phase entanglement threshold, the adjacent epoch observation is a phase entanglement observation; The number of phase-wound observations is counted to obtain the number of phase-wound truncations; Based on the time stamp of the preprocessed frequency band observations and the virtual clock difference, the preprocessed frequency band observations are converted into frequency band observations corresponding to the GNSS time scale; The frequency band observations corresponding to the GNSS time mark are resampled to obtain time mark-aligned frequency band observations; Based on the time-aligned frequency band observations, the inter-satellite distances are calculated using two-way one-way ranging. Specifically, it includes: Based on the time-aligned frequency band observations, the differential phase measurements of the satellites are determined; the differential phase measurements of the satellites include the differential phase measurements of the first satellite, the differential phase measurements of the second satellite, the nominal reception time, the clock error of the first satellite, the clock error of the second satellite, the local reference phase signal of the first satellite, the phase signal of the second satellite received by the first satellite, the local reference phase signal of the second satellite, the phase signal of the first satellite received by the second satellite, the integer ambiguity of the first satellite, the integer ambiguity of the second satellite, the ionospheric delay of the first satellite, the ionospheric delay of the second satellite, the number of truncations of the phase winding of the first satellite, and the number of truncations of the phase winding of the second satellite. Based on the differential phase measurement values of the satellite, the inter-satellite distance is calculated using two-way one-way ranging. The formula for bidirectional one-way distance measurement is: ； in, These are the differential phase measurements from satellite A. This is the differential phase measurement value of satellite B, where t is the nominal reception time. , It's the clock error between the two satellites. This is the local reference phase signal for satellite A. This refers to the phase signal received by satellite A from satellite B. This is the local reference phase signal for satellite B. This refers to the phase signal received by satellite B from satellite A. It is the integer ambiguity of satellite A. It is the integer ambiguity of satellite B. For the ionospheric delay of satellite A, For the ionospheric delay of satellite B, It represents the number of times the phase of satellite A at frequency K is truncated when it wraps around satellite B. It represents the number of times the phase of satellite B is truncated when it wraps around satellite A at the K-frequency point. This refers to the residual error of satellite A. Let W be the residual error of satellite B, and W be a constant.
2. The inter-satellite ranging method according to claim 1, characterized in that, Outlier removal and data imputation are performed on the frequency band observations corresponding to the virtual timescale to obtain preprocessed frequency band observations, specifically including: Determine the cycle slip observation and its corresponding first time identifier, as well as the gross error observation and its corresponding second time identifier, in the frequency band observations corresponding to the virtual time marker; By removing outlier observations from the frequency band observations corresponding to the virtual time scale, outlier-free frequency band observations are obtained. An interpolation algorithm is applied to obtain the first interpolated observation corresponding to the second time identifier in the no gross error frequency band observation, and the no gross error frequency band observation and the first interpolated observation are used as the first corrected observation; The first corrected observation is segmented according to the first time identifier to obtain the second corrected observation; Determine the time marker corresponding to the observation with a value of zero in the second corrected observation to obtain the third time marker; When the length of the time period composed of continuous time identifiers in the third time identifier is greater than a preset time threshold, the second corrected observation is segmented according to the time period to obtain the third corrected observation. An interpolation algorithm is applied to the observations with a value of zero in the third corrected observation to obtain the second interpolated observation, and the third corrected observation and the second interpolated observation are used as preprocessed observations.
3. The inter-satellite ranging method according to claim 1, characterized in that, Before performing the step of "resampling the frequency band observations corresponding to the GNSS time mark to obtain time mark-aligned frequency band observations", the following steps are also included: Low-pass filtering is applied to the frequency band observations corresponding to the GNSS time mark.
4. An inter-satellite ranging system, characterized in that, The system includes: The extraction module is used to extract frequency band observations based on KBR 1A level data from low-low tracking gravity measurement satellites; the frequency band observations include K-band observations and Ka-band observations. The first time signature conversion module is used to split the time signature of each frequency band observation according to a preset numerical precision to obtain a corresponding virtual time signature and virtual clock error; wherein, the virtual time signature is the part of the time signature that meets the preset numerical precision requirement; and the virtual clock error is the part of the time signature that does not meet the preset numerical precision requirement. The preprocessing module is used to remove outliers and complete data for the frequency band observations corresponding to the virtual time scale, so as to obtain preprocessed frequency band observations. Before performing "outlier removal and data completion on the frequency band observations corresponding to the virtual timescale to obtain preprocessed frequency band observations", the process also includes: The difference is obtained by subtracting the observations of adjacent epochs of the frequency band observations corresponding to the virtual time scale; When the absolute value of the difference is greater than the phase entanglement threshold, the adjacent epoch observation is a phase entanglement observation; The number of phase-wound observations is counted to obtain the number of phase-wound truncations; The second time-scale conversion module is used to convert the preprocessed frequency band observations into frequency band observations corresponding to the GNSS time scale based on the time identifier of the preprocessed frequency band observations and the virtual clock difference. The resampling module is used to resample the frequency band observations corresponding to the GNSS time mark to obtain time mark aligned frequency band observations; The calculation module is used to calculate the inter-satellite distance based on the time-aligned frequency band observations and by applying two-way one-way ranging. Specifically, it includes: Based on the time-aligned frequency band observations, the differential phase measurements of the satellites are determined; the differential phase measurements of the satellites include the differential phase measurements of the first satellite, the differential phase measurements of the second satellite, the nominal reception time, the clock error of the first satellite, the clock error of the second satellite, the local reference phase signal of the first satellite, the phase signal of the second satellite received by the first satellite, the local reference phase signal of the second satellite, the phase signal of the first satellite received by the second satellite, the integer ambiguity of the first satellite, the integer ambiguity of the second satellite, the ionospheric delay of the first satellite, the ionospheric delay of the second satellite, the number of truncations of the phase winding of the first satellite, and the number of truncations of the phase winding of the second satellite. Based on the differential phase measurement values of the satellite, the inter-satellite distance is calculated using two-way one-way ranging. The formula for bidirectional one-way distance measurement is: ； in, These are the differential phase measurements from satellite A. This is the differential phase measurement value of satellite B, where t is the nominal reception time. , It's the clock error between the two satellites. This is the local reference phase signal for satellite A. This refers to the phase signal received by satellite A from satellite B. This is the local reference phase signal for satellite B. This refers to the phase signal received by satellite B from satellite A. It is the integer ambiguity of satellite A. It is the integer ambiguity of satellite B. For the ionospheric delay of satellite A, For the ionospheric delay of satellite B, It represents the number of times the phase of satellite A at frequency K is truncated when it wraps around satellite B. It represents the number of times the phase of satellite B is truncated when it wraps around satellite A at the K-frequency point. This refers to the residual error of satellite A. Let W be the residual error of satellite B, and W be a constant.
5. An electronic device, characterized in that, The device includes a memory and a processor, the memory being used to store a computer program, and the processor running the computer program to cause the electronic device to perform the inter-satellite ranging method according to any one of claims 1 to 3.
6. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the inter-satellite ranging method as described in any one of claims 1 to 3.