Walker Constellation Orbit Parameter Optimization Method, Device, Equipment and Medium

Abstract

The present invention provides a method, device, equipment and medium for optimizing the orbital parameters of a Walker constellation, relating to the field of space technology, including: obtaining a plurality of first alternative parameter values of a first orbital parameter item to be optimized for the Walker constellation; for any first alternative parameter value of the first orbital parameter item, optimizing the second alternative parameter values of the second orbital parameter item to be optimized for the Walker constellation, and continuously calling an orbital simulation model during the optimization process to output an evaluation result corresponding to the second alternative parameter value until the second alternative parameter value corresponding to the optimal evaluation result is determined to obtain a parameter value combination; screening out a first target parameter value and a second target parameter value from a plurality of parameter value combinations according to the evaluation results. The present invention effectively reduces the workload of designers, and at the same time solves the problem of incomplete optimization caused by individual differences of designers, and effectively improves the design efficiency and design quality in the constellation demonstration stage.

Description

Technical Field

[0001] The present invention relates to the field of aerospace technology, and in particular, to a method, device, equipment and medium for optimizing the orbital parameters of a Walker constellation. Background Art

[0002] Currently, constellation design is carried out through professional software modeling, and parameters such as single satellite orbital parameters and constellation configuration parameters are configured during modeling. Among them, to achieve better constellation design effects, it is necessary to optimize the parameters configured during modeling. However, the existing optimization process has low optimization efficiency and requires a lot of manual participation, which poses a challenge to the work efficiency of constellation design. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide a method, device, equipment and medium for optimizing the orbital parameters of a Walker constellation, which effectively reduces the workload of designers, and at the same time solves the problem of incomplete optimization caused by individual differences of designers, and effectively improves the design efficiency and design quality in the constellation demonstration stage.

[0004] In a first aspect, the present invention provides a method for optimizing the orbital parameters of a Walker constellation, including:

[0005] Obtaining a plurality of first alternative parameter values of a first orbital parameter item to be optimized for a Walker constellation; wherein, the first orbital parameter item is a discrete parameter item;

[0006] For any first alternative parameter value of the first orbital parameter item, optimizing the second alternative parameter values of the second orbital parameter item to be optimized for the Walker constellation, and continuously calling an orbital simulation model during the optimization process to output an evaluation result corresponding to the second alternative parameter value until the second alternative parameter value corresponding to the optimal evaluation result is determined to obtain a parameter value combination; wherein, the second orbital parameter item is a continuous parameter item, and the parameter value combination includes the first alternative parameter value and the second alternative parameter value corresponding to the optimal evaluation result;

[0007] According to the evaluation results, screening out a first target parameter value of the first orbital parameter item and a second target parameter value of the second orbital parameter item from a plurality of parameter value combinations.

[0008] In an implementation manner, the first orbital parameter item includes a phase factor parameter item, the first alternative parameter value is a phase factor parameter value, the second orbital parameter item includes a right ascension of ascending node distribution range parameter item, and the second alternative parameter value is a right ascension of ascending node distribution range;

[0009] For any first alternative parameter value of the first orbital parameter item, optimize the second alternative parameter value of the second orbital parameter item to be optimized in the Walker constellation, and continuously call the orbital simulation model during the optimization process to output the evaluation result corresponding to the second alternative parameter value until the second alternative parameter value corresponding to the optimal evaluation result is determined, including:

[0010] For any phase factor parameter value, optimize the right ascension of the ascending node distribution range of the Walker constellation, and continuously call the orbital simulation model during the optimization process to output the evaluation result corresponding to the right ascension of the ascending node distribution range until the right ascension of the ascending node distribution range corresponding to the optimal evaluation result is determined, realizing the one-dimensional optimization design of the right ascension of the ascending node distribution range.

[0011] In one implementation, for any phase factor parameter value, optimize the right ascension of the ascending node distribution range of the Walker constellation, and continuously call the orbital simulation model during the optimization process to output the evaluation result corresponding to the right ascension of the ascending node distribution range until the right ascension of the ascending node distribution range corresponding to the optimal evaluation result is determined, including:

[0012] Obtain the initial interval of the second parameter value of the right ascension of the ascending node distribution range parameter item;

[0013] Call the orbital simulation model to determine the right ascension of the ascending node distribution range from the initial interval of the second parameter value based on the phase factor parameter value;

[0014] Perform compliance determination on the right ascension of the ascending node distribution range;

[0015] If the right ascension of the ascending node distribution range fails to pass the compliance determination, expand the initial interval of the second parameter value, and determine a new right ascension of the ascending node distribution range from the expanded initial interval of the second parameter value until the new right ascension of the ascending node distribution range passes the compliance determination, and the new right ascension of the ascending node distribution range is the right ascension of the ascending node distribution range corresponding to the optimal evaluation result.

[0016] In one implementation, call the orbital simulation model to determine the right ascension of the ascending node distribution range from the initial interval of the second parameter value based on the phase factor parameter value, including:

[0017] Determine the second parameter value at the splitting point from the initial interval of the second parameter value based on the preset splitting coefficient;

[0018] Call the orbital simulation model to perform simulation calculation on the Walker constellation based on the phase factor parameter value and the second parameter value at the splitting point, and use the result of the simulation calculation to evaluate the second parameter value at the splitting point, and the evaluation result is used to determine the search interval of the second parameter value;

[0019] Determine a new second parameter value at the segmentation point from within the second parameter value search interval based on a preset segmentation coefficient until the length of the updated second parameter value search interval is less than a preset tolerance, and use the updated second parameter value as the right ascension of the ascending node distribution range.

[0020] In one implementation, performing compliance determination on the right ascension of the ascending node distribution range includes:

[0021] Determine whether the right ascension of the ascending node distribution range is outside the initial interval of the second parameter value or on the boundary of the initial interval of the second parameter value;

[0022] If so, determine that the right ascension of the ascending node distribution range fails the compliance determination; if not, determine that the right ascension of the ascending node distribution range passes the compliance determination.

[0023] In one implementation, the first orbital parameter term includes a phase factor parameter term, the first alternative parameter value is a phase factor parameter value, the second orbital parameter term includes a right ascension of the ascending node distribution range parameter term and an orbital inclination parameter term, and the second alternative parameter value is an orbital inclination value;

[0024] For any first alternative parameter value of the first orbital parameter term, optimize the second alternative parameter value of the second orbital parameter term to be optimized for the Walker constellation, and continuously call the orbital simulation model during the optimization process to output the evaluation result corresponding to the second alternative parameter value until the second alternative parameter value corresponding to the optimal evaluation result is determined. It also includes:

[0025] For any phase factor parameter value, optimize the right ascension of the ascending node distribution range and the orbital inclination value of the Walker constellation, and continuously call the orbital simulation model during the optimization process to output the evaluation results corresponding to the right ascension of the ascending node distribution range and the orbital inclination value until the right ascension of the ascending node distribution range and the orbital inclination value corresponding to the optimal evaluation result are determined, realizing the two-dimensional optimization design of the right ascension of the ascending node distribution range and the orbital inclination value.

[0026] In one implementation, the result of the simulation calculation for the Walker constellation includes the maximum revisit time, and the maximum revisit time shows a first-order differential monotonic change trend with the right ascension of the ascending node distribution range;

[0027] According to the evaluation results, screening out the first target parameter value of the first orbital parameter term and the second target parameter value of the second orbital parameter term from multiple parameter value combinations includes:

[0028] Compare the maximum revisit times corresponding to each parameter value combination, and use the first alternative parameter value and the second alternative parameter value in the parameter value combination corresponding to the minimum maximum revisit time as the first target parameter value of the first orbital parameter term and the second target parameter value of the second orbital parameter term, respectively.

[0029] In a second aspect, the present invention further provides a Walker constellation orbit parameter optimization device, comprising:

[0030] a parameter acquisition module, configured to acquire a plurality of first alternative parameter values for a first orbit parameter item to be optimized of the Walker constellation; wherein, the first orbit parameter item is a discrete parameter item;

[0031] a parameter optimization module, configured to, for any first alternative parameter value of the first orbit parameter item, optimize a second alternative parameter value of a second orbit parameter item to be optimized of the Walker constellation, and continuously call an orbit simulation model during the optimization process to output an evaluation result corresponding to the second alternative parameter value until determining the second alternative parameter value corresponding to the optimal evaluation result, so as to obtain a parameter value combination; wherein, the second orbit parameter item is a continuous parameter item, and the parameter value combination includes the first alternative parameter value and the second alternative parameter value corresponding to the optimal evaluation result;

[0032] a parameter determination module, configured to screen out a first target parameter value of the first orbit parameter item and a second target parameter value of the second orbit parameter item from a plurality of parameter value combinations according to the evaluation result.

[0033] In a third aspect, the present invention further provides an electronic device, comprising a processor and a memory, where the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of the first aspect.

[0034] In a fourth aspect, the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores computer executable instructions, and when the computer executable instructions are called and executed by a processor, the computer executable instructions cause the processor to implement the method according to any one of the first aspect.

[0035] The Walker constellation orbit parameter optimization method, device, equipment and medium provided by the present invention first obtain multiple first alternative parameter values of a first orbit parameter item to be optimized in the Walker constellation; wherein, the first orbit parameter item is a discrete parameter item; then, for any first alternative parameter value of the first orbit parameter item, optimize the second alternative parameter value of the second orbit parameter item to be optimized in the Walker constellation, and continuously call the orbit simulation model during the optimization process to output the evaluation result corresponding to the second alternative parameter value until the second alternative parameter value corresponding to the optimal evaluation result is determined to obtain a parameter value combination; wherein, the second orbit parameter item is a continuous parameter item, and the parameter value combination includes the first alternative parameter value and the second alternative parameter value corresponding to the optimal evaluation result; finally, according to the evaluation result, screen out the first target parameter value of the first orbit parameter item and the second target parameter value of the second orbit parameter item from multiple parameter value combinations, thereby realizing the full-automatic evaluation of the Walker constellation orbit parameters, and being able to repeatedly practice and try, and improve by trial and error during the constellation demonstration and design stage, effectively reducing the workload of designers, and at the same time solving the situation of incomplete optimization caused by individual differences of designers, and effectively improving the design efficiency and design quality during the constellation demonstration stage.

[0036] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention are realized and obtained by the structures specifically pointed out in the specification, claims and drawings.

[0037] To make the above objectives, features and advantages of the present invention more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, makes a detailed description as follows. Brief Description of the Drawings

[0038] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0039] Figure 1 It is a schematic flowchart of a method for optimizing Walker constellation orbit parameters provided by an embodiment of the present invention;

[0040] Figure 2 It is a schematic flowchart of an optimization process provided by an embodiment of the present invention;

[0041] Figure 3 It is a scene example of an orbit simulation software provided by an embodiment of the present invention;

[0042] Figure 4 A schematic diagram of ground elevation angle constraint provided by an embodiment of the present invention;

[0043] Figure 5 An example of the calculation process for optimizing the orbital parameters of a Walker constellation provided by an embodiment of the present invention;

[0044] Figure 6 A schematic structural diagram of a device for optimizing the orbital parameters of a Walker constellation provided by an embodiment of the present invention;

[0045] Figure 7 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0046] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0047] Currently, there are situations of low optimization efficiency and much manual participation in constellation design. Based on this, the embodiments of the present invention provide a method, device, equipment, and medium for optimizing the orbital parameters of a Walker constellation, which effectively reduces the workload of designers and at the same time solves the situation of incomplete optimization caused by individual differences among designers, effectively improving the design efficiency and design quality in the constellation demonstration stage.

[0048] To facilitate the understanding of this embodiment, a method for optimizing the orbital parameters of a Walker constellation disclosed in the embodiments of the present invention will be introduced in detail first. Refer to Figure 1 The flowchart of a method for optimizing the orbital parameters of a Walker constellation shown in the figure. This method mainly includes the following steps S102 to step S106:

[0049] Step S102, obtain multiple first alternative parameter values of the first orbital parameter item to be optimized for the Walker constellation. Among them, the first orbital parameter item is a discrete parameter item, the first orbital parameter item includes a phase factor parameter item, and the first alternative parameter value is a phase factor parameter value.

[0050] Step S104: For any first alternative parameter value of the first orbit parameter item, optimize the second alternative parameter value of the second orbit parameter item to be optimized in the Walker constellation, and continuously call the orbit simulation model during the optimization process to output the evaluation result corresponding to the second alternative parameter value until the second alternative parameter value corresponding to the optimal evaluation result is determined, so as to obtain a parameter value combination.

[0051] Wherein, the second orbit parameter item is a continuous parameter item, and the parameter value combination includes the first alternative parameter value and the second alternative parameter value corresponding to the optimal evaluation result.

[0052] In one example, the second orbit parameter item may include the right ascension of the ascending node distribution range parameter item, and the second alternative parameter value is also the right ascension of the ascending node distribution range. For any phase factor parameter value, the right ascension of the ascending node distribution range can be optimized, and the orbit simulation model is continuously called during the optimization process to evaluate the right ascension of the ascending node distribution range until the right ascension of the ascending node distribution range corresponding to the optimal evaluation result is determined, so as to achieve one-dimensional optimization design (such as the golden section search method, etc.). In another example, the second orbit parameter item may include the right ascension of the ascending node distribution range parameter item and the orbit inclination parameter item, and the second alternative parameter value is also the right ascension of the ascending node distribution range and the orbit inclination value. For any phase factor parameter value, the right ascension of the ascending node distribution range and the orbit inclination value can be optimized, and the orbit simulation model is continuously called during the optimization process to evaluate the right ascension of the ascending node distribution range and the orbit inclination value until the right ascension of the ascending node distribution range and the orbit inclination value corresponding to the optimal evaluation result are determined, so as to achieve two-dimensional optimization design (such as the Newton iteration algorithm, etc.).

[0053] Wherein, the process of calling the orbit simulation model for evaluation is as follows: Input the alternative parameter values of the above parameter items into the orbit simulation model to perform simulation calculations on the Walker constellation using the orbit simulation model. The result of the simulation calculation is the maximum revisit time, and the maximum revisit time and the right ascension of the ascending node distribution range show a first-order differential monotonic change trend. In one example, in the embodiment of the present invention, the right ascension of the ascending node distribution range is evaluated using the maximum revisit time.

[0054] Step S106: According to the evaluation results, screen out the first target parameter value of the first orbit parameter item and the second target parameter value of the second orbit parameter item from multiple parameter value combinations.

[0055] In one example, with the constraint that the value of the maximum revisit time is the smallest, determine the target parameter combination from multiple parameter value combinations, and respectively determine the first alternative parameter value and the second alternative parameter value within the target parameter combination as the first target parameter value of the first orbit parameter item and the second target parameter value of the second orbit parameter item.

[0056] The Walker constellation orbit parameter optimization method provided by the embodiments of the present invention runs fully automatically. By means of optimal design, the second alternative parameter values of the second orbit parameter item corresponding to each first alternative parameter value of the first orbit parameter item are determined, and the orbit simulation model is continuously called during the optimization process to evaluate the alternative parameter values of the two parameter items, so as to obtain multiple parameter value combinations and their corresponding evaluation results. Finally, the target parameter values of the two parameter items are further selected from the multiple parameter value combinations according to the evaluation results. The embodiments of the present invention repeatedly practice and attempt, and improve by trial and error during the constellation demonstration and design stage, effectively reducing the workload of designers. At the same time, the situation of incomplete optimization caused by individual differences of designers is solved, and the design efficiency and design quality in the constellation demonstration stage are effectively improved.

[0057] In one implementation manner, the embodiments of the present invention face the problem of constellation orbit design evaluation and optimization for large field-of-view payloads. Based on the system underlying transmission protocol, given the number of satellites, orbit altitude, payload visible range, number of planes, and number of satellites, the inter-plane phase factor and the distribution range of the right ascension of the ascending node of the Walker constellation are designed. Investigations show that for the above target problem, given the constellation orbit parameter configuration, the objective function value (i.e., the maximum revisit time) and the parameter to be optimized (i.e., the distribution range of the right ascension of the ascending node) show a first-order differential monotonic change trend, and the basic convex optimization idea can be used for optimization. The optimal value can be obtained after a finite number of evaluations. The same idea is adopted for other inter-plane phase factors. After repeated execution, the optimal constellation orbit parameters under the specified configuration can be statistically obtained.

[0058] For ease of understanding, the embodiments of the present invention provide a specific implementation manner of the Walker constellation orbit parameter optimization method.

[0059] For the foregoing step S104, it is specifically divided into the following two cases:

[0060] Case 1, the first orbit parameter item includes a phase factor parameter item, and the second orbit parameter item includes a distribution range parameter item of the right ascension of the ascending node. On this basis, the embodiments of the present invention provide an implementation manner of optimal design. For any phase factor parameter value, the distribution range of the right ascension of the ascending node of the Walker constellation is optimized, and the orbit simulation model is continuously called during the optimization process to output the evaluation result corresponding to the distribution range of the right ascension of the ascending node until the distribution range of the right ascension of the ascending node corresponding to the optimal evaluation result is determined, realizing the one-dimensional optimal design of the distribution range of the right ascension of the ascending node.

[0061] Case 2: The first orbital parameter term includes a phase factor parameter term, and the second orbital parameter term includes a right ascension of the ascending node distribution range parameter term and an orbital inclination parameter term. On this basis, an embodiment of the present invention provides an optimized design implementation. For any phase factor parameter value, the right ascension of the ascending node distribution range and the orbital inclination value of the Walker constellation are optimized, and the orbital simulation model is continuously called during the optimization process to output the evaluation results corresponding to the right ascension of the ascending node distribution range and the orbital inclination value until the right ascension of the ascending node distribution range and the orbital inclination value corresponding to the optimal evaluation result are determined, realizing the two-dimensional optimization design of the right ascension of the ascending node distribution range and the orbital inclination value.

[0062] The embodiment of the present invention reserves the scalability of the design dimension at the architecture level, that is, the increase of the second orbital parameter term to be optimized. For example, this architecture is expected to be further expanded to add the design of the orbital inclination in the underlying optimization logic to form a two-dimensional optimization problem, and the expanded problem can still be solved according to the convex optimization problem.

[0063] In a specific implementation, taking Case 1 as an example, the foregoing step S104 is explained, that is, the case of optimizing the phase factor parameter term InterPlanePhase and the right ascension of the ascending node distribution range parameter term RAANSpacing between planes. The first alternative parameter value (i.e., the phase factor parameter value) of the phase factor parameter term InterPlanePhase is denoted as the alternative InterPlanePhase value, and the second alternative parameter value (i.e., the right ascension of the ascending node distribution range) of the right ascension of the ascending node distribution range parameter term RAANSpacing is denoted as the alternative RAANSpacing value. For the discrete variable phase factor parameter term InterPlanePhase, a simple loop is used to form a one-dimensional optimization problem of the right ascension of the ascending node distribution range parameter term RAANSpacing in each loop. The evaluation function provided by the orbital simulation software is used, combined with the optimizer, to obtain the optimal alternative RAANSpacing value corresponding to the alternative RAANSpacing value.

[0064] The embodiment of the present invention processes the optimization problem of two orbital parameter terms to be optimized with two-layer logic. Refer to Figure 2 the flowchart of an optimization process shown. In the upper-layer logic, the discrete phase factor parameter term InterPlanePhase is examined, and each possible value, which is also the first alternative parameter value, is evaluated in a loop. In the lower-layer logic, a one-dimensional optimization problem of the continuous right ascension of the ascending node distribution range parameter term RAANSpacing is executed.

[0065] The two orbital parameter items to be optimized and the two-layer optimization logic mentioned in the embodiments of the present invention are determined through prior investigation and research. The investigation found that in the problem of optimizing the orbital efficiency evaluation of large field-of-view payload constellations faced by the embodiments of the present invention, if the constellation orbital parameters and the payload semi-cone angle configuration are given, the maximum revisit time and the range of the right ascension of the ascending node distribution show a monotonic change trend of the first-order differential, and the basic convex optimization idea can be used for optimization.

[0066] Optionally, the one-dimensional optimization design algorithm is carried out by using the Golden Section Search method. The application of this algorithm to the embodiments of the present invention is determined through prior investigation and research. Compared with the Newton-like convex optimization algorithm that requires gradient information, this algorithm does not require gradient information, avoiding potential problems of convergence failure or low convergence efficiency caused by the untrustworthy gradient information due to the differential sensitivity of the problem. Specifically, for each specified alternative InterPlanePhase value, the alternative RAANSpacing values are repeatedly tried by the Golden Section Search method and input into the orbital simulation software to obtain the corresponding maximum revisit time. Finally, the corresponding optimal maximum revisit time and its corresponding alternative RAANSpacing value are found, which are regarded as the optimal solution under this alternative InterPlanePhase value.

[0067] Furthermore, the embodiments of the present invention provide a specific implementation manner for determining the optimal alternative RAANSpacing value for each alternative InterPlanePhase value by using the Golden Section Search method, including the following (1) to (4):

[0068] (1) Obtain the initial interval of the second parameter value of the range parameter item of the right ascension of the ascending node distribution. In one example, the initial interval of the second parameter value is also the initial interval of the range of the right ascension of the ascending node distribution, and a second parameter value initial interval [a, b] containing the extreme point is selected.

[0069] (2) Call the orbital simulation model to determine the range of the right ascension of the ascending node distribution from the initial interval of the second parameter value based on the phase factor parameter value. Specifically, refer to the following (2.1) to (2.3):

[0070] (2.1) Determine the second parameter value at the segmentation point from the initial interval of the second parameter value based on the preset segmentation coefficient. Among them, the segmentation point is also the golden section point, and the second parameter value is also the range of the right ascension of the ascending node distribution. In one example, two internal points (i.e., the golden section points) c and d are calculated according to the following formula so that the interval is divided into the golden ratio:

[0071] c = b - r·(b - a);

[0072] d = a + r·(b - a);

[0073] where r is the golden ratio coefficient, equal to

[0074] (2.2) Invoke the orbit simulation model. Based on the phase factor parameter value and the second parameter value at the segmentation point, perform simulation calculations on the Walker constellation. Use the results of the simulation calculations to evaluate the second parameter value at the segmentation point. The evaluation results are used to determine the search interval of the second parameter value, which is also the search interval of the right ascension of the ascending node distribution range.

[0075] In one example, input the alternative InterPlanePhase value and the RAANSpacing value at the internal point c into the orbit simulation model, so that it outputs the corresponding maximum revisit time, denoted as f(c); similarly, input the alternative InterPlanePhase value and the RAANSpacing value at the internal point d into the orbit simulation model, so that it outputs the corresponding maximum revisit time, denoted as f(d). Among them, f(c) and f(d) are also the results of the simulation calculations.

[0076] In one example, compare the values of f(c) and f(d), and narrow the search interval of the second parameter value according to the following rules: If f(c) < f(d), then the minimum value is within the interval [a, d], and update b = d; If f(c) > f(d), then the minimum value is within the interval [c, b], and update a = c.

[0077] (2.3) Determine a new second parameter value at the segmentation point from the search interval of the second parameter value based on a preset segmentation coefficient until the length of the updated search interval of the second parameter value is less than the preset tolerance. Take the updated second parameter value as the right ascension of the ascending node distribution range.

[0078] In one example, for the narrowed search interval of the second parameter value, repeat steps (2.1) to (2.2) until the length of the updated search interval of the second parameter value is less than the preset tolerance. At this time, the RAANSpacing value of the alternative InterPlanePhase value can be obtained.

[0079] (3) Perform compliance determination on the right ascension of the ascending node distribution range.

[0080] In one example, determine whether the right ascension of the ascending node distribution range is outside the initial interval of the second parameter value or on the boundary of the initial interval of the second parameter value; if so, determine that the right ascension of the ascending node distribution range fails the compliance determination; if not, determine that the right ascension of the ascending node distribution range passes the compliance determination.

[0081] (4) If the range of the right ascension of the ascending node does not pass the compliance determination, expand the initial interval of the second parameter value, and determine a new range of the right ascension of the ascending node from the expanded initial interval of the second parameter value until the new range of the right ascension of the ascending node passes the compliance determination. At this time, the new range of the right ascension of the ascending node is the range of the right ascension of the ascending node corresponding to the optimal evaluation result.

[0082] Judge whether the RAANSpacing value falls outside the initial interval of the second parameter value or on the boundary of the initial interval of the second parameter value. When the judgment is yes, adjust to the new initial interval of the second parameter value and re-execute (2) and (3) until the RAANSpacing value falls within the currently expanded initial interval of the second parameter value, and use the RAANSpacing value at this time as the alternative RAANSpacing value corresponding to the alternative InterPlanePhase value.

[0083] For the optimal value compliance determination process provided by the embodiments of the present invention, in the case where the optimal value falls outside the initial interval of the second parameter value, an automatic recognition mechanism is configured. After recognition, the initial interval of the second parameter value is automatically expanded and the search is restarted to ensure that the initial interval of the second parameter value can cover the optimal value drop point, ensuring the convergence stability and reliability of this method.

[0084] Further, for the foregoing (2.2), the embodiments of the present invention provide a specific implementation manner for evaluating the range of the right ascension of the ascending node by calling an orbital simulation model, including two links of setting calculation conditions and professional software modeling and calculation.

[0085] (1) Set calculation conditions: Input calculation conditions, including orbital altitude, orbital inclination, number of constellation planes, number of stars per plane, elevation angle constraint, and other information required for scene setting. The other information includes parameter settings necessary for simulation such as scene start / end time, orbital epochs of each star, orbital parameters of epochs other than orbital altitude and inclination of each star, longitude and latitude range of the simulation area, finite element mesh size, etc.

[0086] (2) Professional software modeling and calculation:

[0087] The evaluation function is repeatedly called by step S104. Based on the parameters set in (1), drive the orbital simulation software STK through the system underlying transmission protocol to establish an orbital scene and perform a finite element calculation of the maximum revisit time. Wait until the calculation is completed. The orbital simulation software returns the calculation result of the maximum revisit time.

[0088] The automatic execution process in the orbital simulation software is driven by the underlying transmission protocol of the Windows system. The scenario is modeled through code rather than manual operation. The automatically established scenario model includes functions such as the sample satellite model, payload model, Walker constellation satellite / payload model, finite element coverage calculation model, simulation calculation report, and geographical distribution mapping of coverage data, such as Figure 3 An example of an orbital simulation software scenario as shown.

[0089] Specifically:

[0090] (a) Through the underlying transmission protocol, the orbital simulation software is made to set the start / end time of the scenario.

[0091] (b) Through the underlying transmission protocol, the orbital simulation software is made to set the sample satellite orbit epoch and epoch orbit (according to the specified alternative InterPlanePhase value). Based on the sample satellite, it is extended to the Walker constellation with the specified number of orbital planes, number of satellites, and alternative RAANSpacing value.

[0092] (c) Through the underlying transmission protocol, the orbital simulation software is made to set the payload and its half-cone angle. The calculation method of the payload half-cone angle C is as follows:

[0093]

[0094] where E is the ground elevation angle constraint, such as Figure 4 A schematic diagram of a ground elevation angle constraint as shown, h is the orbital altitude, and R e is the radius of the Earth.

[0095] (d) Through the underlying transmission protocol, the orbital simulation software is made to set the longitude and latitude range and the finite element grid size of the simulation area.

[0096] (e) Through the underlying transmission protocol, the orbital simulation software is made to perform simulation calculations and output the maximum revisit time. Draw the geographical distribution map of the maximum revisit time and display it when needed.

[0097] In one embodiment, the result of the simulation calculation of the Walker constellation includes the maximum revisit time. The maximum revisit time shows a monotonic change trend of the first-order differential with the distribution range of the right ascension of the ascending node. Based on this, the embodiments of the present invention provide a specific implementation manner of the foregoing step S106, including: comparing the maximum revisit times corresponding to each parameter value combination, and using the first alternative parameter value and the second alternative parameter value in the parameter value combination corresponding to the minimum maximum revisit time as the first target parameter value of the first orbital parameter item and the second target parameter value of the second orbital parameter item respectively. In a specific implementation, under each first alternative parameter value, according to the optimal maximum revisit time obtained by the optimization design, the alternative InterPlanePhase value and the alternative RAANSpacing value corresponding to the minimum maximum revisit time are used as the target InterPlanePhase value and the target RAANSpacing value.

[0098] Exemplarily, referring to Figure 5 An example of the orbital parameter optimization process of a Walker constellation as shown. Here, P×S is the number of planes × the number of satellites per plane, F is the alternative InterPlanePhase value, the abscissa is the alternative RAANSpacing value corresponding to the alternative InterPlanePhase value, and the ordinate is the maximum revisit time MaxRevisit corresponding to the alternative InterPlanePhase value. In one example, for each alternative InterPlanePhase value and its corresponding alternative RAANSpacing value, when input into the orbital simulation software, the corresponding maximum revisit time can be output. With the minimum value of the maximum revisit time as the constraint, that is, the alternative InterPlanePhase value and the alternative RAANSpacing value corresponding to the minimum maximum revisit time are used as the target InterPlanePhase value and the target RAANSpacing value.

[0099] In summary, the method is an automated optimization solution for the design of the ascending node longitude range of a constellation, including: a calculation condition setting link, a professional software modeling and calculation link, a design optimization link, an optimal value compliance determination link, and a comparison and output link. For the problem of orbital efficiency evaluation and optimization of a large field of view payload, under the premise of a given number of satellites, orbital altitude, payload visible range, number of planes, and number of satellites, it provides an optimization design solution for the core orbital parameters of the constellation. The embodiments of the invention operate fully automatically without manual intervention. On the one hand, it effectively reduces the workload of designers. The easy and efficient evaluation means help to interpret the relationship between design variables and design goals and clarify the design logic. On the other hand, the systematic design method avoids the incomplete optimization caused by individual differences of designers in manual optimization design, and effectively improves the design efficiency and design quality in the constellation demonstration stage.

[0100] Based on the foregoing embodiments, an embodiment of the present invention provides a Walker constellation orbit parameter optimization device. Refer to Figure 6 the structural schematic diagram of a Walker constellation orbit parameter optimization device shown in the figure. The device mainly includes the following parts:

[0101] A parameter acquisition module 602, configured to acquire multiple first alternative parameter values of a first orbit parameter item to be optimized for a Walker constellation; wherein, the first orbit parameter item is a discrete parameter item;

[0102] A parameter optimization module 604, configured to, for any first alternative parameter value of the first orbit parameter item, optimize the second alternative parameter value of the second orbit parameter item to be optimized for the Walker constellation, and continuously call an orbit simulation model during the optimization process to output an evaluation result corresponding to the second alternative parameter value until the second alternative parameter value corresponding to the optimal evaluation result is determined, so as to obtain a parameter value combination; wherein, the second orbit parameter item is a continuous parameter item, and the parameter value combination includes the first alternative parameter value and the second alternative parameter value corresponding to the optimal evaluation result;

[0103] A parameter determination module 606, configured to screen out a first target parameter value of the first orbit parameter item and a second target parameter value of the second orbit parameter item from multiple parameter value combinations according to the evaluation result.

[0104] The Walker constellation orbit parameter optimization device provided by the embodiment of the present invention runs fully automatically. By optimizing the design, the second alternative parameter value of the second orbit parameter item corresponding to each first alternative parameter value of the first orbit parameter item is determined, so as to call an orbit simulation model to evaluate the alternative parameter values of the two parameter items, and then the target parameter values of the two parameter items are determined. The embodiment of the present invention repeatedly practices and tries, and corrects mistakes and improves during the constellation demonstration and design stage, effectively reducing the workload of designers, and at the same time solving the problem of incomplete optimization caused by individual differences of designers, and effectively improving the design efficiency and design quality during the constellation demonstration stage.

[0105] In an implementation manner, the first orbit parameter item includes a phase factor parameter item, the first alternative parameter value is a phase factor parameter value, the second orbit parameter item includes a right ascension of ascending node distribution range parameter item, and the second alternative parameter value is a right ascension of ascending node distribution range; the parameter optimization module 604 is specifically configured to:

[0106] For any phase factor parameter value, optimize the right ascension of ascending node distribution range of the Walker constellation, and continuously call an orbit simulation model during the optimization process to output an evaluation result corresponding to the right ascension of ascending node distribution range until the right ascension of ascending node distribution range corresponding to the optimal evaluation result is determined, so as to realize the one-dimensional optimization design of the right ascension of ascending node distribution range.

[0107] In one embodiment, the parameter optimization module 604 is specifically configured to:

[0108] Obtain the initial interval of the second parameter value of the right ascension of the ascending node distribution range parameter item;

[0109] Call the orbit simulation model to determine the right ascension of the ascending node distribution range from the initial interval of the second parameter value based on the phase factor parameter value;

[0110] Perform compliance determination on the right ascension of the ascending node distribution range;

[0111] If the right ascension of the ascending node distribution range fails to pass the compliance determination, expand the initial interval of the second parameter value, and determine a new right ascension of the ascending node distribution range from the expanded initial interval of the second parameter value until the new right ascension of the ascending node distribution range passes the compliance determination. At this time, the new right ascension of the ascending node distribution range is the right ascension of the ascending node distribution range corresponding to the optimal evaluation result.

[0112] In one embodiment, the parameter optimization module 604 is specifically configured to:

[0113] Determine the second parameter value at the segmentation point from the initial interval of the second parameter value based on the preset segmentation coefficient;

[0114] Call the orbit simulation model to perform simulation calculation on the Walker constellation based on the phase factor parameter value and the second parameter value at the segmentation point, and evaluate the second parameter value at the segmentation point using the result of the simulation calculation. The evaluation result is used to determine the search interval of the second parameter value;

[0115] Determine a new second parameter value at the segmentation point from the search interval of the second parameter value based on the preset segmentation coefficient until the length of the updated search interval of the second parameter value is less than the preset tolerance, and use the updated second parameter value as the right ascension of the ascending node distribution range.

[0116] In one embodiment, the parameter optimization module 604 is specifically configured to:

[0117] Judge whether the right ascension of the ascending node distribution range is outside the initial interval of the second parameter value or on the boundary of the initial interval of the second parameter value;

[0118] If so, determine that the right ascension of the ascending node distribution range fails to pass the compliance determination; if not, determine that the right ascension of the ascending node distribution range passes the compliance determination.

[0119] In one embodiment, the first orbital parameter item includes a phase factor parameter item, the first alternative parameter value is a phase factor parameter value, the second orbital parameter item includes a right ascension of ascending node distribution range parameter item and an orbital inclination parameter item, and the second alternative parameter value is an orbital inclination value; specifically, the parameter optimization module 604 is further configured to:

[0120] For any phase factor parameter value, optimize the right ascension of ascending node distribution range and the orbital inclination value of the Walker constellation, and continuously call the orbital simulation model during the optimization process to output the evaluation results corresponding to the right ascension of ascending node distribution range and the orbital inclination value until the right ascension of ascending node distribution range and the orbital inclination value corresponding to the optimal evaluation result are determined, so as to realize the two-dimensional optimization design of the right ascension of ascending node distribution range and the orbital inclination value.

[0121] In one embodiment, the result of the simulation calculation of the Walker constellation includes the maximum revisit time. The maximum revisit time and the right ascension of ascending node distribution range first-order differential monotonic change trend determination module 606 is specifically configured to:

[0122] Compare the maximum revisit times corresponding to each parameter value combination, and use the first alternative parameter value and the second alternative parameter value in the parameter value combination corresponding to the minimum maximum revisit time as the first target parameter value of the first orbital parameter item and the second target parameter value of the second orbital parameter item, respectively.

[0123] The device provided in the embodiments of the present invention has the same implementation principle and the same technical effects as those in the foregoing method embodiments. For the sake of brief description, for the parts not mentioned in the device embodiments, reference may be made to the corresponding content in the foregoing method embodiments.

[0124] The embodiments of the present invention provide an electronic device. Specifically, the electronic device includes a processor and a storage device; a computer program is stored on the storage device, and the computer program executes the method according to any one of the foregoing embodiments when being run by the processor.

[0125] Figure 7 FIG. is a schematic structural diagram of an electronic device provided in an embodiment of the present invention. The electronic device 100 includes: a processor 70, a memory 71, a bus 72, and a communication interface 73. The processor 70, the communication interface 73, and the memory 71 are connected through the bus 72; the processor 70 is configured to execute an executable module stored in the memory 71, such as a computer program.

[0126] Among them, the memory 71 may include high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 73 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used.

[0127] The bus 72 can be an ISA bus, a PCI bus, an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 7 only a bidirectional arrow is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0128] Among them, the memory 71 is used to store programs. After receiving the execution instruction, the processor 70 executes the programs. The methods executed by the devices defined by the flow processes disclosed in any of the embodiments of the foregoing embodiments of the present invention can be applied to the processor 70 or implemented by the processor 70.

[0129] The processor 70 may be an integrated circuit chip with the ability to process signals. In the implementation process, the steps of the above method can be completed by the integrated logic circuit of the hardware in the processor 70 or the instructions in the form of software. The above-mentioned processor 70 may be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it may also be a digital signal processor (DSP for short), an application specific integrated circuit (ASIC for short), a field-programmable gate array (FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of the hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory 71, and the processor 70 reads the information in the memory 71 and combines its hardware to complete the steps of the above method.

[0130] The computer program product of the readable storage medium provided by the embodiments of the present invention includes a computer-readable storage medium storing program code, and the instructions included in the program code can be used to execute the methods described in the foregoing method embodiments. For the specific implementation, reference can be made to the foregoing method embodiments, and details are not described herein again.

[0131] If the above-described functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0132] Finally, it should be noted that the above-described embodiments are only specific embodiments of the present invention, used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that any person skilled in the art within the technical scope disclosed by the present invention can still modify the technical solutions described in the foregoing embodiments or easily conceive of changes, or make equivalent replacements for some of the technical features; and these modifications, changes, or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention and should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for optimizing the orbital parameters of a Walker constellation, characterized in that, Including: Obtaining a plurality of first alternative parameter values of a first orbital parameter item to be optimized for the Walker constellation; wherein, the first orbital parameter item is a discrete parameter item; For any one of the first alternative parameter values of the first orbital parameter item, optimizing a second alternative parameter value of a second orbital parameter item to be optimized for the Walker constellation, and continuously invoking an orbital simulation model during the optimization process to output an evaluation result corresponding to the second alternative parameter value until the second alternative parameter value corresponding to the optimal evaluation result is determined to obtain a parameter value combination; wherein, the second orbital parameter item is a continuous parameter item, and the parameter value combination includes the first alternative parameter value and the second alternative parameter value corresponding to the optimal evaluation result; According to the evaluation results, screening out a first target parameter value of the first orbital parameter item and a second target parameter value of the second orbital parameter item from a plurality of the parameter value combinations, including: determining a target parameter combination from a plurality of the parameter value combinations with the constraint that the numerical value of the maximum revisit time is the smallest, and respectively determining the first alternative parameter value and the second alternative parameter value within the target parameter combination as the first target parameter value of the first orbital parameter item and the second target parameter value of the second orbital parameter item.

2. The Walker constellation orbit parameter optimization method according to claim 1, wherein The first orbital parameter item includes a phase factor parameter item, the first alternative parameter value is a phase factor parameter value, the second orbital parameter item includes a right ascension of ascending node distribution range parameter item, and the second alternative parameter value is a right ascension of ascending node distribution range; For any one of the first alternative parameter values of the first orbital parameter item, optimizing a second alternative parameter value of a second orbital parameter item to be optimized for the Walker constellation, and continuously invoking an orbital simulation model during the optimization process to output an evaluation result corresponding to the second alternative parameter value until the second alternative parameter value corresponding to the optimal evaluation result is determined, including: For any one of the phase factor parameter values, optimizing the right ascension of ascending node distribution range of the Walker constellation, and continuously invoking an orbital simulation model during the optimization process to output an evaluation result corresponding to the right ascension of ascending node distribution range until the right ascension of ascending node distribution range corresponding to the optimal evaluation result is determined to achieve a one-dimensional optimization design of the right ascension of ascending node distribution range.

3. The Walker constellation orbit parameter optimization method according to claim 2, characterized in that, For any one of the phase factor parameter values, optimizing the right ascension of ascending node distribution range of the Walker constellation, and continuously invoking an orbital simulation model during the optimization process to output an evaluation result corresponding to the right ascension of ascending node distribution range until the right ascension of ascending node distribution range corresponding to the optimal evaluation result is determined, including: Obtaining a second parameter value initial interval of the right ascension of ascending node distribution range parameter item; Invoking an orbital simulation model to determine a right ascension of ascending node distribution range from the second parameter value initial interval based on the phase factor parameter value; Performing a compliance determination on the right ascension of ascending node distribution range; If the right ascension of ascending node distribution range does not pass the compliance determination, expand the initial interval of the second parameter value, and determine a new right ascension of ascending node distribution range from the expanded initial interval of the second parameter value, until when the new right ascension of ascending node distribution range passes the compliance determination, the new right ascension of ascending node distribution range is the right ascension of ascending node distribution range corresponding to the optimal evaluation result.

4. The Walker constellation orbit parameter optimization method according to claim 3, characterized in that Call the orbit simulation model to determine the right ascension of ascending node distribution range from the initial interval of the second parameter value based on the phase factor parameter value, including: Determine the second parameter value at the segmentation point from the initial interval of the second parameter value based on a preset segmentation coefficient; Call the orbit simulation model to perform simulation calculation on the Walker constellation based on the phase factor parameter value and the second parameter value at the segmentation point, and use the result of the simulation calculation to evaluate the second parameter value at the segmentation point, and the evaluation result is used to determine the second parameter value search interval; Determine a new second parameter value at the segmentation point from the second parameter value search interval based on the preset segmentation coefficient, until the length of the updated second parameter value search interval is less than a preset tolerance, and use the updated second parameter value as the right ascension of ascending node distribution range.

5. The Walker constellation orbit parameter optimization method according to claim 3, wherein Perform compliance determination on the right ascension of ascending node distribution range, including: Judge whether the right ascension of ascending node distribution range is outside the initial interval of the second parameter value or on the boundary of the initial interval of the second parameter value; If so, determine that the right ascension of ascending node distribution range does not pass the compliance determination; if not, determine that the right ascension of ascending node distribution range passes the compliance determination.

6. The Walker constellation orbit parameter optimization method according to claim 1, characterized in that The first orbit parameter item includes a phase factor parameter item, the first alternative parameter value is the phase factor parameter value, the second orbit parameter item includes a right ascension of ascending node distribution range parameter item and an orbit inclination parameter item, and the second alternative parameter value is the orbit inclination value; For any first alternative parameter value of the first orbit parameter item, optimize the second alternative parameter value of the second orbit parameter item to be optimized of the Walker constellation, and continuously call the orbit simulation model to output the evaluation result corresponding to the second alternative parameter value during the optimization process, until the second alternative parameter value corresponding to the optimal evaluation result is determined. It also includes: For any phase factor parameter value, optimize the right ascension of ascending node distribution range and the orbit inclination value of the Walker constellation, and continuously call the orbit simulation model to output the evaluation result corresponding to the right ascension of ascending node distribution range and the orbit inclination value during the optimization process, until the right ascension of ascending node distribution range and the orbit inclination value corresponding to the optimal evaluation result are determined, so as to realize the two-dimensional optimization design of the right ascension of ascending node distribution range and the orbit inclination value.

7. The Walker constellation orbit parameter optimization method according to claim 2 or 6, characterized in that The result of the simulation calculation on the Walker constellation includes the maximum revisit time, and the maximum revisit time shows a first-order differential monotonic change trend with the right ascension of ascending node distribution range; Determine a target parameter combination from multiple parameter value combinations with the constraint of minimizing the value of the maximum revisit time, and respectively determine the first alternative parameter value and the second alternative parameter value within the target parameter combination as the first target parameter value of the first orbital parameter item and the second target parameter value of the second orbital parameter item, including: Compare the maximum revisit time corresponding to each parameter value combination, and respectively use the first alternative parameter value and the second alternative parameter value in the parameter value combination corresponding to the minimum maximum revisit time value as the first target parameter value of the first orbital parameter item and the second target parameter value of the second orbital parameter item.

8. An apparatus for optimizing the orbital parameters of a Walker constellation, characterized in that, Including: A parameter acquisition module, configured to acquire multiple first alternative parameter values of a first orbital parameter item to be optimized for a Walker constellation; wherein, the first orbital parameter item is a discrete parameter item; A parameter optimization module, configured to optimize the second alternative parameter value of the second orbital parameter item to be optimized for the Walker constellation for any first alternative parameter value of the first orbital parameter item, and continuously call an orbital simulation model during the optimization process to output an evaluation result corresponding to the second alternative parameter value until the second alternative parameter value corresponding to the optimal evaluation result is determined to obtain a parameter value combination; wherein, the second orbital parameter item is a continuous parameter item, and the parameter value combination includes the first alternative parameter value and the second alternative parameter value corresponding to the optimal evaluation result; A parameter determination module, configured to screen out the first target parameter value of the first orbital parameter item and the second target parameter value of the second orbital parameter item from multiple parameter value combinations according to the evaluation result, including: determining a target parameter combination from multiple parameter value combinations with the constraint of minimizing the value of the maximum revisit time, and respectively determining the first alternative parameter value and the second alternative parameter value within the target parameter combination as the first target parameter value of the first orbital parameter item and the second target parameter value of the second orbital parameter item.

9. An electronic device, characterized in that, Including a processor and a memory, the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer executable instructions, and when the computer executable instructions are called and executed by a processor, the computer executable instructions cause the processor to implement the method according to any one of claims 1 to 7.

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