CN109752744B - Multi-satellite joint orbit determination method based on model error compensation - Google Patents

Abstract

The invention relates to the field of satellite orbit determination, in particular to a multi-satellite combined orbit determination method based on model error compensation, which comprises the following steps: establishing a primary multi-satellite combined orbit determination equation of the target satellite according to a dynamic model of a satellite group and the target satellite of the space-based measurement and control network and observation models of the foundation measurement and control network and the space-based measurement and control network; acquiring an orbit calculation value of a target satellite according to a primary multi-satellite combined orbit determination equation, and acquiring an OC residual error by combining an orbit observation value of the target satellite; respectively establishing an error compensation item of a dynamic model and an error compensation item of an observation model by determining an error source corresponding to the OC residual error; and establishing an earth-ground multi-satellite combined orbit determination equation of the target satellite according to the primary multi-satellite combined orbit determination equation and the error compensation terms of the dynamic model and the observation model. The invention utilizes the space and foundation combined orbit determination strategy and compensates errors of two types of models, namely a dynamic model, an observation model and the like, thereby improving the orbit determination precision of the target satellite.

Description

Multi-satellite joint orbit determination method based on model error compensation

technical field

The invention relates to the field of satellite orbit determination, in particular to a multi-satellite joint orbit determination method based on model error compensation.

Background technique

Space-based joint orbit determination is the process of comprehensively using the information of the space-based measurement and control network and the ground-based measurement and control network to comprehensively determine the orbits of space-based satellites and ground-based satellites. The constraints on space-based satellites are not only local ground-based observations, but also space-based observations. In this way, on the one hand, the use of space-based measurement and control data improves the orbit coverage and constrains the target orbit more effectively. , theoretically, the orbits of space-based satellites and space targets with higher estimation accuracy can be obtained.

From the principle of orbit determination, orbit determination is a process of reconstructing satellite orbits from orbit measurement data containing satellite orbit information according to the constraints of the satellite dynamics model.

In orbit determination, the kinematic orbit determined by the observation model ensures the uniqueness of the orbit state in the space domain, while the dynamic orbit determined by the dynamic model ensures the continuity and smoothness of the orbit state in the time domain. When there is no systematic deviation, the kinematic orbit and the dynamic orbit are coincident at the observation epoch, and the estimated orbit is unique and optimal, but when the dynamic model or the observation model has model errors, the resulting kinematics The orbit and the dynamic orbit will no longer coincide, and the estimated orbit can only be determined under a certain criterion, and a reasonable approximation can be made in the observation model and the dynamic model.

Model error has become one of the key factors restricting the improvement of satellite orbit determination accuracy, and many scholars have conducted in-depth research from both hardware and software aspects. There is still a certain gap between my country and foreign developed countries in the compensation of hardware models. The main method to improve the accuracy of orbit determination is to use mathematical processing methods to make up for the lack of hardware measurement at this stage.

Compensating the error of the dynamic model with mathematical processing method can better improve the accuracy of orbit determination, which is an important way to make up for the lack of hardware technology. However, the current research work in this area is mainly aimed at the situation of the dynamic model error and the error distribution pattern is fixed. However, there are relatively few studies on observational model errors, and even fewer studies on model error compensation for both dynamic and observational models. Due to the different effects of dynamic model error and observation model error in orbit determination, how to classify and study the corresponding compensation methods is the key to fundamentally solve the problem of model error compensation.

SUMMARY OF THE INVENTION

The embodiments of the present invention provide a multi-satellite joint orbit determination method and device based on model error compensation, which realizes space-based and ground-based joint measurement and control orbit determination, and combines the dynamic model and observation model to classify and construct a corresponding compensation method. The uncertainty model error in the satellite orbit equation is compensated.

In order to achieve the above object, an embodiment of the present invention provides a multi-satellite joint orbit determination method based on model error compensation, and the method includes:

According to the dynamic model of the space-based measurement and control network satellite group and the target satellite, as well as the observation model of the ground-based measurement and control network and the space-based measurement and control network, the primary multi-satellite joint orbit determination equation of the target satellite is established;

According to the primary multi-satellite joint orbit determination equation, obtain the orbit calculation value of the target satellite, and combine the orbit observation value of the target satellite to obtain the difference between the orbit observation value and the orbit calculation value, that is, the OC residual;

Through the OC residual and the spectral correspondence between the OC residual and the error source of the dynamic model and the error source of the observation model, the error source corresponding to the OC residual is determined, and the error compensation term of the dynamic model and the error of the observation model are respectively established accordingly. compensation;

According to the primary multi-satellite joint orbit determination equation and the error compensation terms of the dynamic model and observation model, the space-ground-based multi-satellite joint orbit determination equation of the target satellite is established;

Using the nonlinear multi-model optimal weighted estimation method, the optimal orbit parameters of the space-ground-based multi-satellite joint orbit determination equation of the target satellite are determined.

Compared with the prior art, the above-mentioned technical scheme has the following beneficial effects:

The joint orbit determination of the invention is extended to a space-ground-based mobile station, which improves the robustness and reliability of the entire orbit determination system. Use space-based measurement and control data to make up for the deficiencies of ground-based measurement and control, use joint orbit determination to suppress the impact of space-based satellite ephemeris errors on the accuracy of target satellite orbit determination, and use model compensation to make up for the deficiencies of dynamic models and observation models. According to the model structure, it is divided into dynamic According to the dynamic model and the observation model, the model error compensation strategy can be classified according to the two aspects of the dynamic model and the observation model, which can be compensated according to the decomposition of the dynamic orbit and the geometric orbit according to the different model functions, in order to improve the orbit determination accuracy of the target satellite. Provided favorable technical support.

Description of drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative efforts.

FIG. 1 is a flowchart of a multi-satellite joint orbit determination method according to an embodiment of the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

As shown in FIG. 1, a multi-satellite joint orbit determination method based on model error compensation provided by the present invention includes:

101. Establish the primary multi-satellite joint orbit determination equation of the target satellite according to the dynamic model of the space-based measurement and control network satellite group and the target satellite, as well as the observation models of the ground-based measurement and control network and the space-based measurement and control network;

102. Obtain the orbit calculation value of the target satellite according to the primary multi-satellite joint orbit determination equation, and combine the orbit observation value of the target satellite to obtain the difference between the orbit observation value and the orbit calculation value, that is, the OC residual;

103. Determine the error source corresponding to the OC residual through the OC residual and the spectral correspondence between the OC residual and the error source of the dynamic model and the error source of the observation model, and establish the error compensation term of the dynamic model and the observation model accordingly. error compensation term;

104. According to the primary multi-satellite joint orbit determination equation and the model error compensation terms of the dynamic model and the observation model, establish the space-ground-based multi-satellite joint orbit determination equation of the target satellite;

105. Using the nonlinear multi-model optimal weighted estimation method, determine the optimal orbit parameters of the space-ground-based multi-satellite joint orbit determination equation of the target satellite.

Specifically, taking the space-based TT&C network satellite constellation and the target satellite constellation as the orbit determination targets, comprehensively applying the observation data of the ground-based TT&C network and the space-based TT&C network, and adopting the ideas of physical analysis and mathematical modeling to build a unified multi-satellite joint orbit determination The framework is the primary multi-satellite joint orbit determination equation, and uses the orbital OC residuals of the target satellites to classify and construct corresponding compensation methods from the two levels of the dynamic model and the observation model to compensate for the model errors; on this basis, Combined with the primary multi-satellite joint orbit determination equation and the model error compensation terms of the dynamic model and the observation model, the space-ground-based multi-satellite joint orbit determination equation of the target satellite is constructed, and the final multi-satellite joint orbit determination equation is obtained through the nonlinear multi-model optimal weighted estimation method. The optimal parameter estimation results of the satellite orbit determination equation provide strong technical support for the establishment of my country's independent space-earth multi-satellite joint orbit determination system.

Further, according to the OC residual and the spectral correspondence between the OC residual and the dynamic model error source and the observation model error source, the error source corresponding to the OC residual is determined, including:

According to the characteristics of the OC residual in the continuous arc, the basis function of the OC residual signal is established in the time domain;

According to the basis function, using the multi-scale effect of wavelet transform, the OC residual signal is decomposed into high-frequency components and low-frequency components layer by layer, and different feature layer information is obtained;

Decomposing the trends of the different feature layer information to obtain the frequency spectrum of the different feature layer information;

According to the corresponding relationship between the spectrum of the different feature layer information and the spectrum, the error source corresponding to the different feature layer information of the OC residual is determined.

The OC residual is the residual between the orbit observation value and the orbit calculation value. The orbit calculation value is the orbit parameter estimated by the principle of satellite orbit determination, and then back-calculated to the measurement element, and then the orbit calculation value is obtained; the orbit observation value is obtained. The value is the output data obtained by the orbital observation sensor; therefore the OC residual contains orbital information and observational data information. The kinetic model error and observation model error will also be directly or indirectly reflected in the OC residuals. Therefore, by analyzing the OC residuals, the orbital dynamics model error characteristics and observation error characteristics can be obtained. However, because the OC residual is a discrete time series and is limited by the observation arcs, it is difficult for the OC residual to be composed of continuous full arcs, but often composed of some discrete short arcs. The analysis difficulty of OC residuals. Therefore, the characteristics of OC residuals under continuous arcs are firstly analyzed, and the signals represented by basis functions are constructed in the time domain.

Using the multi-scale effect of wavelet transform, the OC residual signal is decomposed into high-frequency components and low-frequency components layer by layer. The properties of the signal can be described by wavelet coefficients to obtain the information of different feature layers of the signal. According to the application requirements, the wavelet coefficients are constrained to obtain the reconstructed signal with the noise removed, the trend of the signal is decomposed, and the spectral characteristics of the error source are compared to obtain the OC residual representation information of the corresponding error source.

Still further, according to the corresponding relationship between the spectrum of the different feature layer information and the spectrum, the error sources corresponding to the different feature layers of the OC residual are determined, including:

Using the method of mathematical derivation and simulation test, the corresponding relationship between the error source of the dynamic model and the error source of the observation model and the spectral function of the OC residual is obtained;

According to the spectrum of the information of different feature layers of the OC residual and the corresponding relationship of the spectral functions, the error sources corresponding to the different feature layers of the OC residual are determined.

Through the analysis of OC residuals, several types of feature layers that have the greatest impact on the orbit determination results can be obtained, but the error sources corresponding to the feature layers need to be studied. Mathematical derivation can be used to directly obtain the functional correspondence between the residual spectrums corresponding to the error sources. For the spectrums where the functional relationship cannot be obtained directly, the numerical correspondence can be obtained by the simulation test mode, and then the function expression can be constructed by the fitting method.

Still further, the error source corresponding to the OC residual is determined, and the error compensation term of the dynamic model and the error compensation term of the observation model are respectively established accordingly, including:

When the error source corresponding to the main feature layer information of the OC residual is the error source of the dynamic model, the error compensation term of the dynamic model is established;

When the error source corresponding to the main feature layer information of the OC residual is the error source of the observation model, the error compensation term of the observation model is established;

When the main error source cannot be determined by the OC residual, the OC residual is decomposed by the mixed mode decomposition method, and the OC residual is corrected by controlling the upper limit of the total error.

Theoretically, the residuals of the dynamic model and the observation model are different in the frequency domain. When the spectral characteristics of a certain type of model error or other similar prior information are known, the wavelet method or modal decomposition can be used. method to extract details. Therefore, transforming the spectral characteristics of the model into the residual spectral characteristics and separating this kind of information with a suitable analysis method are the key to the compensation technology when the model error is coupled.

Still further, the described error compensation term for establishing the dynamic model includes:

According to the characteristics of the orbit, through the method of combining the physical model and the mathematical model, for the perturbation force that cannot be used for the modeling of the dynamic model, a mathematical model is established by fitting the perturbation force with the basis function, and the mathematical model represented by the mathematical model is constructed accordingly. Perturbation force error compensation term;

According to the requirements of orbit determination accuracy and the parameter accuracy of the dynamic model, a mathematical model represented by sparse parameters is constructed by greedy algorithm or interior point algorithm, which is used as the model error compensation item of the dynamic model;

According to the perturbation force error compensation term and the model error compensation term of the dynamic model, the error compensation term of the dynamic model is established to correct the OC residual corresponding to the error source of the dynamic model.

Uncertainty dynamics model error refers to the unrecognized or unmodeled perturbation force and the part of the perturbation force error caused by inaccurate model parameters. Since the determination and prediction of satellite orbits depend on the dynamic model, the dynamic model is firstly modeled and compensated. Through the optimization and reconstruction of the satellite orbital dynamics model, starting from the extraction of orbital features, using the method of combining physical model and mathematical model, the mathematical model is formed by basis function fitting to the part of the satellite dynamical model that cannot be accurately modeled; According to the requirements of orbit determination accuracy and the characteristics of the perturbation model, the greedy algorithm or interior point algorithm is used to search for the optimal sparse parameter representation, and the mathematical representation model of the satellite dynamic model error is established; The dynamic perturbation model of the parameters and the mathematical model based on the basis function representation are used to establish the hybrid dynamic model of satellite orbits of different orbital heights and types, and obtain a high-precision representation of the satellite dynamic model. Since the representations of the dynamic model and the observation model in the orbit equation are both reflected by the residuals, the representations of the two types of models will be coupled together, so the research content in this part is suitable for the situation where the error of the dynamic model is much larger than that of the observation model.

Still further, the described error compensation term for establishing the observation model includes:

Using non-parametric statistical method to estimate the uncertain observation system error, and obtain the non-parametric representation of the uncertainty model error compensation function;

According to the uncertainty model error compensation function and the deterministic system error compensation model of the observation model, an error compensation term of the observation model is established to correct the OC residual corresponding to the error source of the observation model.

Uncertain observational error mainly refers to the unrecognized observational systematic error and the recognized systematic error correction residual. Due to the different model performances, the compensation method for the error of the uncertainty observation model is different from the compensation method for the error of the dynamic model. In addition, because it is difficult to obtain the true trajectory of the measurement and control data, it is impossible to obtain the morphological model of the uncertain systematic error. To this end, the uncertain model error of non-parametric representation is constructed by non-parametric modeling, and the component linear model is unified by combining the parameterized observation model and the deterministic system error model. The estimation of the uncertainty observation error is completed by the research on the estimation method of the partial linear model. Also, due to coupling reasons, this section is suitable for situations where the error of the observational model is much larger than that of the dynamical model.

Still further, the OC residual is decomposed by the mixed mode decomposition method, and the OC residual is corrected by controlling the upper limit of the total error, including:

Convert the OC residual in the frequency domain, decompose the part of the OC residual corresponding to the error source through the empirical mode decomposition technology according to the prior information, and perform the OC residual correction through the error compensation term corresponding to the error source;

For the part of the OC residual where the corresponding error source cannot be determined, the OC residual is corrected by adjusting the empirical force and controlling the upper limit of the total error.

This part is mainly aimed at the situation where the error of the dynamic model and the error of the observation model are similar and coupled. Although the two types of errors are coupled, the mixed signal is converted in the frequency domain, and some of the coupled error sources are expected to be separated by using the empirical mode decomposition technique through certain prior information. The key to this part is to process the residuals through the modal decomposition technique. When the formal characteristics or spectral distribution of a certain type of model error are known, by decomposing the OC residual, this type of error can be eliminated at the feature level, and then compensation techniques can be performed.

Since each error source has specific spectral characteristics and distribution laws, although they are coupled together in the time domain, they can still be decomposed in the frequency domain. Based on the analysis of the OC residual characteristics, the OC residual signal is decomposed by the empirical mode decomposition method. For example, for the empirical force in the dynamic model, its spectral characteristics can be decomposed very effectively. The specific technical scheme can adopt the idea of combining theoretical derivation and simulation test, and the data of the CHAMP satellite accelerometer can be used to assist in the analysis of the real characteristics of the dynamic model error.

When there is no prior information, it is difficult to effectively separate the dynamic model error and the observation model error through the coupling of the OC form, that is, the degree of bias of the estimated orbit between the dynamic orbit and the geometric orbit cannot be determined. However, when the characteristics of a certain type of error source are known, such as the systematic error form of the observation model, the simultaneous compensation of the two models can be performed by adjusting the magnitude of the empirical force. However, when a model spectrum is known, the traditional method is used to obtain the OC residual, and then the mixed mode decomposition method is used to remove this feature, and then the compensation method of the two models is carried out.

Further, using the nonlinear multi-model optimal weighted estimation method to determine the optimal orbit parameters of the space-ground-based multi-satellite joint orbit determination equation of the target satellite, including:

The curvature of the space-ground-based multi-satellite joint orbit determination equation is used as a quantitative standard to measure the degree of nonlinearity and complexity of each model of the space-ground-based multi-satellite joint orbit determination equation. Combined orbit determination equation for weighted processing;

Perform interval constraints on the parameters to be estimated in the space-ground-based multi-satellite joint orbit determination equation by the parameter constraint method;

Using the biased estimation method to optimally estimate the parameters in the space-ground-based multi-satellite joint orbit determination equation;

The parameters in the space-ground-based multi-satellite joint orbit determination equation are further optimized and corrected by an iterative method.

Specifically, on the basis of the space-ground-based observation model, the dynamic model is extended, and both the space-based satellite orbit and the target satellite orbit are regarded as the orbits to be estimated, and the space-ground-based multi-satellite joint orbit determination equation is formed. According to the proportion of the dynamic model error and the observation model error, the corresponding model compensation term is constructed and added to the joint orbit determination equation. In order to prevent the curve fitting dynamic model error function from absorbing the model error excessively, so that the orbit loses the characteristics of the dynamic equation, and the estimated orbit is biased towards the geometric orbit determined by the observation data, the parameter constraint method is used to constrain the parameters to be estimated in the model, especially It is to monitor the size of the empirical force itself, and use an inhibitory factor that can characterize the explanatory ability of two types of models (physical model and mathematical model), and add it to the orbit determination equation, so that the model error term (mathematical model) can be controlled. . Due to the different degrees of nonlinearity of each model in the orbit determination equation, the explanatory ability of the model will be reduced when solving directly. For this reason, the curvature of the model is first solved, and the curvature of various models is weighted to achieve the optimal model interpretation and improve the Orbit determination accuracy. On the basis of performing interval constraints on the parameters to be estimated in the space-ground-based multi-satellite joint orbit determination equation, the parameters in the space-ground-based multi-satellite joint orbit determination equation are optimally estimated by a biased estimation method. In addition, in order to prevent the deviation of orbit determination caused by biased estimation, iterative processing is also required, and the optimal iterative strategy is studied. Finally, based on the model structure analysis method and parameter estimation theory, the joint orbit determination accuracy is quantitatively described.

Although the model compensation method has been deeply studied at home and abroad, it is mainly limited to the dynamic model, or the two models are mixed together. At the same time, the compensation of the dynamic model mainly adopts the inherent mode. The compensation strategy proposed by the present invention is divided into dynamic model and observation model according to the model structure, and can be compensated according to the decomposition of the dynamic orbit and the geometric orbit according to different model functions. The compensation strategy for error coupling, which is the first at home and abroad, is one of the features and innovations of the present invention.

The original intention of joint orbit determination is to suppress the influence of space-based satellite ephemeris errors, and the present invention extends joint orbit determination to a space-ground-based mobile station, which improves the robustness and reliability of the entire system. Use space-based measurement and control data to make up for the deficiencies of ground-based measurement and control, use joint orbit determination to suppress the impact of space-based satellite ephemeris errors on the accuracy of target satellite orbit determination, and use model compensation to make up for the deficiencies of dynamic models and observation models. The invention proposes a multi-satellite joint orbit determination model and a nonlinear multi-model optimal weighted estimation method based on model compensation. In view of the complexity of the model structure, the model curvature weighting strategy is adopted in the parameter estimation process, which further improves the orbit determination accuracy. This is also the feature and innovation of the present invention.

It is understood that the specific order or hierarchy of steps in the disclosed processes is an example of a sample approach. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the processes may be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in a sample order, and are not meant to be limited to the specific order or hierarchy presented.

In the foregoing Detailed Description, various features are grouped together in a single embodiment for the purpose of simplifying the disclosure. This method of disclosure should not be interpreted as reflecting an intention that embodiments of the claimed subject matter require more features than are expressly recited in each claim. Rather, as the following claims reflect, present invention lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby expressly incorporated into the Detailed Description, with each claim standing on its own as a separate preferred embodiment of this invention.

The disclosed embodiments are described above to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit and scope of this disclosure. Thus, the present disclosure is not intended to be limited to the embodiments set forth herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The above description includes examples of one or more embodiments. Of course, it is not possible to describe all possible combinations of components or methods in order to describe the above embodiments, but one of ordinary skill in the art will recognize that further combinations and permutations of the various embodiments are possible. Accordingly, the embodiments described herein are intended to cover all such changes, modifications and variations that fall within the scope of the appended claims. Furthermore, with respect to the term "comprising," as used in the specification or claims, the word is encompassed in a manner similar to the term "comprising," as if "comprising," were construed as a conjunction in the claims. Furthermore, any use of the term "or" in the specification of the claims is intended to mean a "non-exclusive or."

Those skilled in the art may also understand that various illustrative logical blocks (illustrative logical blocks), units, and steps listed in the embodiments of the present invention may be implemented by electronic hardware, computer software, or a combination of the two. To clearly demonstrate the interchangeability of hardware and software, the various illustrative components, units and steps described above have generally described their functions. Whether such functionality is implemented in hardware or software depends on the specific application and overall system design requirements. Those skilled in the art may use various methods to implement the described functions for each specific application, but such implementation should not be construed as exceeding the protection scope of the embodiments of the present invention.

The various illustrative logic blocks, or units described in the embodiments of the present invention can be implemented by general-purpose processors, digital signal processors, application specific integrated circuits (ASICs), field programmable gate arrays or other programmable logic devices, discrete Gate or transistor logic, discrete hardware components, or any combination of the above are designed to implement or operate the functions described. A general-purpose processor may be a microprocessor, or alternatively, the general-purpose processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented by a combination of computing devices, such as a digital signal processor and a microprocessor, multiple microprocessors, one or more microprocessors in combination with a digital signal processor core, or any other similar configuration. accomplish.

The steps of the method or algorithm described in the embodiments of the present invention may be directly embedded in hardware, a software module executed by a processor, or a combination of the two. Software modules may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art. Illustratively, a storage medium may be coupled to the processor such that the processor may read information from, and store information in, the storage medium. Optionally, the storage medium can also be integrated into the processor. The processor and storage medium may be provided in the ASIC, and the ASIC may be provided in the user terminal. Alternatively, the processor and the storage medium may also be provided in different components in the user terminal.

In one or more exemplary designs, the above functions described in the embodiments of the present invention may be implemented in hardware, software, firmware, or any combination of the three. If implemented in software, the functions may be stored on, or transmitted over, a computer-readable medium in the form of one or more instructions or code. Computer-readable media includes computer storage media and communication media that facilitate the transfer of a computer program from one place to another. Storage media can be any available media that a general-purpose or special-purpose computer can access. For example, such computer-readable media may include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other device that can be used to carry or store instructions or data structures and Other media in the form of program code that can be read by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Furthermore, any connection is properly defined as a computer-readable medium, for example, if software is transmitted from a web site, server or other remote source over a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL) Or transmitted by wireless means such as infrared, wireless, and microwave are also included in the definition of computer-readable media. The disks and disks include compact disks, laser disks, optical disks, DVDs, floppy disks and blu-ray disks. Disks usually reproduce data magnetically, while discs generally reproduce data optically with lasers. Combinations of the above can also be included in computer readable media.

The specific embodiments described above further describe the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above descriptions are only specific embodiments of the present invention and are not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims (7)

1. a multi-satellite joint orbit determination method based on model error compensation, is characterized in that, described method comprises: According to the dynamic model of the space-based measurement and control network satellite group and the target satellite, as well as the observation model of the ground-based measurement and control network and the space-based measurement and control network, the primary multi-satellite joint orbit determination equation of the target satellite is established; According to the primary multi-satellite joint orbit determination equation, obtain the orbit calculation value of the target satellite, and combine the orbit observation value of the target satellite to obtain the difference between the orbit observation value and the orbit calculation value, that is, the OC residual; Through the OC residual and the spectral correspondence between the OC residual and the error source of the dynamic model and the error source of the observation model, the error source corresponding to the OC residual is determined, and the error compensation term of the dynamic model and the error of the observation model are respectively established accordingly. compensation; According to the primary multi-satellite joint orbit determination equation and the error compensation terms of the dynamic model and observation model, the space-ground-based multi-satellite joint orbit determination equation of the target satellite is established; Using the nonlinear multi-model optimal weighted estimation method, determine the optimal orbit parameters of the space-ground-based multi-satellite joint orbit determination equation of the target satellite; The error source corresponding to the OC residual is determined through the OC residual and the spectral correspondence between the OC residual and the dynamic model error source and the observation model error source, including: According to the characteristics of the OC residual in the continuous arc, the basis function of the OC residual signal is established in the time domain; According to the basis function, using the multi-scale effect of wavelet transform, the OC residual signal is decomposed into high-frequency components and low-frequency components layer by layer, and different feature layer information is obtained; Decomposing the trends of the different feature layer information to obtain the frequency spectrum of the different feature layer information; According to the corresponding relationship between the spectrum of the different feature layer information and the spectrum, the error source corresponding to the different feature layer information of the OC residual is determined. 2. The multi-satellite joint orbit determination method based on model error compensation according to claim 1, characterized in that, according to the corresponding relationship between the spectrum of the different feature layer information and the spectrum, determine the OC residual error. Error sources corresponding to different feature layers, including: Using the method of mathematical derivation and simulation test, the corresponding relationship between the error source of the dynamic model and the error source of the observation model and the spectral function of the OC residual is obtained; According to the spectrum of the information of different feature layers of the OC residual and the corresponding relationship of the spectral functions, the error sources corresponding to the different feature layers of the OC residual are determined. 3. The multi-satellite joint orbit determination method based on model error compensation according to claim 2, is characterized in that, the described error source corresponding to the OC residual error is determined, and the error compensation term of the dynamic model and Error compensation terms of the observation model, including: When the error source corresponding to the main feature layer information of the OC residual is the error source of the dynamic model, the error compensation term of the dynamic model is established; When the error source corresponding to the main feature layer information of the OC residual is the error source of the observation model, the error compensation term of the observation model is established; When the main error source cannot be determined by the OC residual, the OC residual is decomposed by the mixed mode decomposition method, and the OC residual is corrected by controlling the upper limit of the total error. 4. the multi-satellite joint orbit determination method based on model error compensation according to claim 3, is characterized in that, the described error compensation term of establishing dynamic model, comprises: According to the characteristics of the orbit, through the method of combining the physical model and the mathematical model, for the perturbation force that cannot be used for the modeling of the dynamic model, a mathematical model is established by fitting the perturbation force with the basis function, and the mathematical model represented by the mathematical model is constructed accordingly. Perturbation force error compensation term; According to the requirements of orbit determination accuracy and the parameter accuracy of the dynamic model, a mathematical model represented by sparse parameters is constructed by greedy algorithm or interior point algorithm, which is used as the model error compensation item of the dynamic model; According to the perturbation force error compensation term and the model error compensation term of the dynamic model, the error compensation term of the dynamic model is established to correct the OC residual corresponding to the error source of the dynamic model. 5. The multi-satellite joint orbit determination method based on model error compensation according to claim 3, is characterized in that, the described error compensation term of establishing observation model, comprises: Using non-parametric statistical method to estimate the uncertain observation system error, and obtain the non-parametric representation of the uncertainty model error compensation function; According to the uncertainty model error compensation function and the deterministic system error compensation model of the observation model, an error compensation term of the observation model is established to correct the OC residual corresponding to the error source of the observation model. 6. The multi-satellite joint orbit determination method based on model error compensation according to claim 3, wherein the OC residual is decomposed by the mixed mode decomposition method, and the OC residual is decomposed by controlling the total error upper limit. Differences are corrected, including: Convert the OC residual in the frequency domain, decompose the part of the OC residual corresponding to the error source through the empirical mode decomposition technology according to the prior information, and perform the OC residual correction through the error compensation term corresponding to the error source; For the part of the OC residual where the corresponding error source cannot be determined, the OC residual is corrected by adjusting the empirical force and controlling the upper limit of the total error. 7. The multi-satellite joint orbit determination method based on model error compensation according to claim 1, wherein the described utilization of nonlinear multi-model optimal weighted estimation method determines the space-ground-based multi-satellite joint of the target satellite The optimal orbit parameters of the orbit determination equation, including: The curvature of the space-ground-based multi-satellite joint orbit determination equation is used as a quantitative standard to measure the degree of nonlinearity and complexity of each model of the space-ground-based multi-satellite joint orbit determination equation. Combined orbit determination equation for weighted processing; Perform interval constraints on the parameters to be estimated in the space-ground-based multi-satellite joint orbit determination equation by the parameter constraint method; Using the biased estimation method to optimally estimate the parameters in the space-ground-based multi-satellite joint orbit determination equation; The parameters in the space-ground-based multi-satellite joint orbit determination equation are further optimized and corrected by an iterative method.

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