Phased deployment method and device based on low-orbit large-scale constellation parking orbit

Abstract

The present invention relates to the field of constellation deployment, and discloses a phased deployment method and device based on a parking orbit of a large-scale low-orbit constellation. Obtain constellation target deployment data and satellite-related performance data, confirm the initial deployment outline and launch mode, use the Monte Carlo method to simulate and analyze the navigation performance of the low-orbit constellation, obtain the optimal launch batch and performance indicators, sort and group the same batch of satellites according to the satellite NORAD number, confirm the satellite deployment sequence, establish a parking orbit delay orbit lifting model, and the satellite uses ion thrusters to perform orbit climbing and constellation networking while phase separation, construct a parking orbit satellite operation time model and a satellite orbit climbing time model, optimize the objective function of deployment time and fuel consumption according to the NSGA-II optimization algorithm, and confirm the optimal constellation deployment plan. Satisfy the flexibility and scalability of the constellation's phased deployment, minimize the constellation deployment cost, and make up for the shortcomings of the constellation's direct orbit entry or one-shot orbital plane deployment and long deployment cycle.

Description

Technical Field

[0001] The present invention relates to the field of constellation deployment, and in particular to a phased deployment method and device based on a low-orbit large-scale constellation parking orbit. Background Art

[0002] With the rapid iteration of low-orbit satellite technology, the rocket launch and recovery capabilities, and the maturity of one-shot multi-satellite multi-orbit technology, large-scale low-orbit constellations have been booming. At the same time, low-orbit satellites have low orbit altitudes and are subject to large atmospheric resistance. The semi-major axis of satellites will continue to decrease, requiring more energy to maintain orbital operation, greatly reducing the service life of satellites. The scale of low-orbit constellations continues to expand, the number of satellites increases, and constellation deployment is constrained by many factors such as production capacity, manufacturing costs, launch sites, and launch capabilities. The deployment cost of large-scale low-orbit constellations and the performance improvement of phased deployment directly affect the early service level of constellations. Due to factors such as the atmosphere and production, low-orbit satellite deployment is bound to fail. When uncertain events (climb delays, satellite failures) occur in satellites, deterministic deployment plans will be difficult to apply, and deployment plans and resource reallocation need to be replanned. With the continuous expansion of the scale of low-orbit constellations, the number of satellites increases, and constellation deployment is constrained by many factors such as time, performance, and cost, the traditional deployment methods of direct entry into orbit or one-shot orbital plane are no longer suitable for large-scale inclined low-orbit constellation deployment.

[0003] The present invention provides a parking orbit and phased deployment performance improvement optimization design method for a large-scale low-orbit constellation. Aiming at the phased deployment and performance improvement optimization design problems of low-orbit constellations, a three-stage batch deployment scheme for low-orbit constellations considering the parking orbit is proposed. The satellite state under uncertain events, the constellation ascending node right ascension and phase deployment analysis are analyzed. The ascending node right ascension separation model between the parking orbit and the target orbit, the parking orbit satellite delayed orbit lifting model under continuous small thrust, and the deployment time and fuel model between the satellite-rocket separation to the parking orbit and the parking orbit to the target orbit are established. The satellite-rocket separation height and the parking orbit height are used as decision variables, and the constellation deployment time and fuel consumption are used as the objective function. The NSGA-Ⅱ optimization algorithm is used to give the optimal parking orbit. The present invention is deployed in stages based on the premise of constellation performance improvement, which not only meets the flexibility of constellation phased deployment, but also can minimize the constellation deployment cost, make up for the shortcomings of the constellation directly entering the orbit or the one-rocket dedicated orbital plane deployment and the long deployment cycle, minimize the constellation deployment cost, and at the same time improve the satellite on-orbit service life, which can provide a reference for the deployment of low-orbit constellations. Summary of the invention

[0004] In view of the above problems, an object of the present invention is to provide a phased deployment method based on a low-orbit large-scale constellation parking orbit.

[0005] The second object of the present invention is to provide a phased deployment device based on a low-orbit large-scale constellation parking orbit.

[0006] The first technical solution adopted by the present invention is: S1, obtaining constellation target deployment data and satellite-related performance data, and determining whether the launch mode is one rocket with multiple satellites and one rocket with three orbital planes; S2, based on the constellation target deployment data, using the Monte Carlo method to simulate and analyze the low-orbit constellation navigation performance, and obtain the optimal launch batch and performance indicators; S3, according to the optimal launch batch, sorting and grouping the satellites in the same batch according to the satellite NORAD number, and confirming the satellite deployment order; S4, based on the satellite deployment order and the satellite-related performance data, establishing a parking orbit delay lift model, and using the parking orbit The orbit delay model realizes phase separation while the satellite is performing orbit climbing and constellation networking through its own ion thrusters; S5, using the ascending node right ascension drift formula and the parameters of the ion thrusters, constructs a parking orbit satellite operation time model and a satellite orbit climbing time model, and uses the satellite-rocket separation altitude and the parking orbit altitude as decision variables, and the constellation deployment time and fuel consumption as the objective function; S7, based on the satellite orbit climbing time model and the parking orbit satellite operation time model, uses the NSGA-II optimization algorithm to optimize the objective function, and introduces the evaluation index HV to determine the optimal constellation deployment plan.

[0007] Optionally, S2 includes: S21, obtaining the longitude and latitude of China and surrounding areas, and confirming the minimum observation elevation angle; S22, drawing a grid and presetting the simulation time and step size based on the minimum observation elevation angle; S23, after executing the simulation, based on the simulation situation, using the Monte Carlo method to perform simulation analysis to determine the optimal launch batch and the performance indicators.

[0008] Optionally, the parking orbit delayed orbit raising model is constructed based on the following formula:

[0009]

[0010] Where u is the satellite phase offset, f is the thrust acceleration, T is the time it takes for the satellite to climb from the parking orbit to the target orbit, a is the semi-major axis, and t x is the orbit raising delay of the parking orbit satellite, and t is the time before the climb.

[0011] Optionally, the satellite orbit climb time model is constructed based on the following formula:

[0012]

[0013]

[0014] Where Δt4 and Δt5 are the time for the satellite to climb once and twice, respectively; λ is a constant; m0 is the initial mass of the satellite; a0 is the semi-major axis of the satellite-rocket separation orbit; μ is the Earth's gravitational constant; and a is the gravitational constant of the Earth. p is the semi-major axis of the parking orbit satellite, is the mass flow rate, a t is the semi-major axis of the target orbit satellite;

[0015] Δt1=Δt4+Δt5

[0016]

[0017]

[0018] Where t0 is the initial time, and m is the satellite mass after time t1.

[0019] Optionally, the parking orbit satellite operation time model includes:

[0020]

[0021]

[0022] In the formula, is the right ascension interval between the ascending nodes of the second and third satellite groups and the first satellite group, n p is the angular velocity of the satellite in parking orbit, n t is the angular velocity of the target orbit satellite, a p is the semi-major axis of the parking orbit satellite, a t is the semi-major axis of the target orbit satellite, J2 is the non-spherical perturbation of the earth, R is the radius of the earth, and i is the inclination of the satellite orbit.

[0023] The second technical solution adopted by the present invention is: a data acquisition module, which acquires constellation target deployment data and satellite-related performance data to determine whether the launch mode is one rocket with multiple satellites and one rocket with three orbital planes; a simulation analysis module, which is used to simulate and analyze the low-orbit constellation navigation performance based on the constellation target deployment data using the Monte Carlo method to obtain the optimal launch batch and performance indicators; a sequence confirmation module, which is used to sort and group satellites in the same batch according to the satellite NORAD number according to the optimal launch batch, and confirm the satellite deployment sequence; a delayed orbit raising module, which is used to establish a parking orbit delayed orbit raising model based on the satellite deployment sequence and the satellite-related performance data, and use the parking orbit delayed orbit raising model to determine the parking orbit delayed orbit raising model when the satellite passes through the self The ion thruster is used to perform orbit climbing and constellation networking while achieving phase separation; a model construction module is used to use the ascending node right ascension drift formula and the parameters of the ion thruster to construct a parking orbit satellite operation time model and a satellite orbit climbing time model; an objective function construction module is used to use the satellite-rocket separation height and the parking orbit height as decision variables based on the constellation deployment data and the satellite-related performance data, and the constellation deployment time and fuel consumption as the objective function; an optimal solution confirmation module is used to optimize the objective function based on the satellite orbit climbing time model and the parking orbit satellite operation time model using the NSGA-II optimization algorithm, and introduce the evaluation index HV to determine the optimal constellation deployment solution.

[0024] Optionally, the simulation analysis module includes: an elevation angle confirmation submodule, used to obtain the longitude and latitude of China and surrounding areas to confirm the minimum observation elevation angle; a preset submodule, used to draw a grid and preset the simulation time and step size according to the minimum observation elevation angle; a simulation analysis submodule, used to perform simulation analysis based on the simulation situation after executing the simulation, using the Monte Carlo method to determine the optimal launch batch and the performance indicators.

[0025] Optionally, the parking orbit delayed orbit raising model is constructed based on the following formula:

[0026]

[0027] Where u is the satellite phase offset, f is the thrust acceleration, T is the time it takes for the satellite to climb from the parking orbit to the target orbit, a is the semi-major axis, and t x is the orbit raising delay of the parking orbit satellite, and t is the time before the climb.

[0028] Optionally, the satellite orbit climb time model is constructed based on the following formula:

[0029]

[0030] Where Δt4 and Δt5 are the time for the satellite to climb once and twice, respectively, λ is a constant, m0 is the initial mass of the satellite, a0 is the semi-major axis of the satellite-rocket separation orbit, μ is the Earth's gravitational constant, and a is p is the semi-major axis of the parking orbit satellite, is the mass flow rate, a t is the semi-major axis of the target orbit satellite;

[0031] Δt1=Δt4+Δt5

[0032]

[0033]

[0034] Where t0 is the initial time, and m is the satellite mass after time t1.

[0035] Optionally, the parking orbit satellite operation time model includes:

[0036]

[0037]

[0038] In the formula, is the right ascension interval between the ascending nodes of the second and third satellite groups and the first satellite group, n p is the angular velocity of the satellite in parking orbit, n t is the angular velocity of the target orbit satellite, a p is the semi-major axis of the parking orbit satellite, a t is the semi-major axis of the target orbit satellite, J2 is the non-spherical perturbation of the earth, R is the radius of the earth, and i is the inclination of the satellite orbit.

[0039] Beneficial effects of the above technical solution:

[0040] The present invention aims at the phased deployment of low-orbit constellations and the optimization design of performance improvement, and proposes a three-phase batch deployment scheme for low-orbit constellations that takes parking orbits into consideration. Phased deployment based on constellation performance improvement not only meets the flexibility of phased deployment of constellations, but also minimizes the cost of constellation deployment, making up for the shortcomings of direct orbit entry or one-rocket orbital deployment and long deployment cycle of constellations, which can provide a reference for low-orbit constellation deployment. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flow chart of a phased deployment method based on a low-orbit large-scale constellation parking orbit provided for one embodiment of the present invention;

[0042] Figure 2 for Figure 1A flow chart of step S2 is provided;

[0043] Figure 3 A schematic structural diagram of a phased deployment device based on a low-orbit large-scale constellation parking orbit provided by one embodiment of the present invention;

[0044] Figure 4 for Figure 3 The structural diagram of the simulation analysis module provided;

[0045] Figure 5 A schematic diagram of the phased deployment of the constellation;

[0046] Figure 6(a) shows the deployment climb and phase separation of the constellation satellites Figure 1 ;

[0047] Figure 6(b) shows the deployment climb and phase separation of the constellation satellites Figure 2 ;

[0048] Figure 7 This is a schematic diagram of the phase separation of a parking orbit satellite;

[0049] Figure 8(a) is a schematic diagram of the space orbital plane and phase of a low-orbit inclined constellation;

[0050] Figure 8(b) is a schematic diagram of the optimal launch batch for a low-orbit tilted constellation;

[0051] Fig. 9 It is a schematic diagram of the space orbital plane and phase of the low-orbit polar-orbit satellite constellation;

[0052] Figure 10(a) is a schematic diagram of the parking orbit optimization results;

[0053] Figure 10(b) is a schematic diagram of the parking trajectory optimization evaluation index; DETAILED DESCRIPTION

[0054] The following detailed description of the embodiments of the present invention is further described in detail in conjunction with the accompanying drawings and examples. The detailed description of the following embodiments and the accompanying drawings are used to exemplarily illustrate the principles of the present invention, but cannot be used to limit the scope of the present invention, that is, the present invention is not limited to the preferred embodiments described, and the scope of the present invention is defined by the claims.

[0055] Embodiment 1

[0056] An embodiment of the present invention provides a phased deployment method based on a low-orbit large-scale constellation parking orbit, such as Figure 1 shown.

[0057] Large-scale low-orbit satellites adopt a three-stage deployment method of one batch of three groups, that is, the same batch of satellites are deployed in three groups. In the first stage, the satellite's own thrusters are used to achieve satellite ascent. In the second stage, the earth's perturbation is used to adjust the RAAN of the parking orbit satellite to reduce fuel consumption. In the third stage, the delayed orbit lift is used to adjust the satellite phase in the parking orbit. Using the three-stage deployment method of one batch of three groups, the satellite always maintains a circular orbit during operation, and the parking orbit is consistent with the inclination of the target orbit. Figure 5 As shown, the first stage: using the satellite's own thrusters to achieve satellite ascent, one rocket with multiple satellites is divided into three groups of satellites, one group of satellites directly climbs to the target orbit after the separation of the rocket and satellite and realizes phase adjustment during the ascent, and serves as a reference orbital plane, while the remaining satellites wait in a suitable parking orbit. The second stage: the remaining two groups are in parking operation, and the earth perturbation is used to achieve RAAN adjustment of parking orbit satellites to reduce fuel consumption. The satellites operating in the parking orbit are affected by the perturbation at the same time as the first group of satellites climbing to the target orbit. The satellites operating in the parking orbit cannot meet the specific ascending node right ascension separation conditions, and need to continue to adjust during the ascent. The third stage: the second and third groups of satellites use delayed orbit lifting to achieve satellite phase adjustment in the parking orbit, and the satellites complete satellite phase adjustment when they climb to the target orbital plane.

[0058] It should be noted that Figure 5 In the p 、a t They are respectively the orbital altitude at the time of satellite-rocket separation, the parking orbit altitude and the target orbit. Δt1 is the time required for the first group of satellites to climb from the satellite-rocket separation altitude to the target orbit, and Δt2 and Δt3 are respectively the time required for the second and third groups of satellites to run in the parking orbit until phase separation. F represents the thrust stage used by the satellite, and J2 represents the satellite's use of perturbation to perform right ascension separation of the ascending node. Among them, satellite-rocket separation refers to the process in which the satellite separates from the rocket at a certain relative speed after the launch vehicle reaches a predetermined altitude and speed and has undergone attitude adjustment; the parking orbit refers to the elliptical (circular) orbit where the spacecraft temporarily stays in order to transfer to another orbit, also known as the resident orbit. The satellite-rocket separation altitude mentioned refers to the altitude at which the satellite is located after entering orbit, and the parking orbit altitude refers to the altitude at which the satellite is located in the resident orbit.

[0059] S1. Obtain constellation target deployment data and satellite-related performance data to determine whether the launch method is multiple satellites per rocket and three orbital planes per rocket.

[0060] Taking into account factors such as launch and deployment costs and time, the traditional direct-orbit or one-rocket-dedicated orbital plane deployment method is no longer suitable for large-scale low-orbit inclined constellation deployment. The deployment plan involves the adjustment of the satellite ascending node right ascension and phase, the parking orbit operation time, and the timing of raising the orbit from the parking orbit to the target orbit.

[0061] like Figure 2 As shown, S2, based on the constellation target deployment data, the Monte Carlo method is used to simulate and analyze the low-orbit constellation navigation performance to obtain the optimal launch batch and performance indicators.

[0062] During the phased deployment of the constellation, it is necessary to consider the improvement of the phased service capability of the constellation deployment configuration. The constellation service performance first considers the country and surrounding areas. At the same time, the low-orbit constellation no longer simulates between stars, but analyzes the performance of the constellation deployed with different orbital plane combinations. The Monte Carlo method can be used to simulate and analyze the performance of different orbital plane combinations of the low-orbit constellation. The performance indicators are the number of visible satellites and the PDOP value, and the optimal launch batch, performance indicators and deployment time are given. At the same time, the deployment purpose of the low-orbit polar constellation is different from that of the low-orbit inclined constellation, and the two are deployed in different ways.

[0063] S21. Obtain the longitude and latitude of China and surrounding areas and confirm the minimum observation elevation angle;

[0064] S22, drawing a grid and presetting a simulation time and step size according to the minimum observation elevation angle;

[0065] S23, after executing the simulation, based on the simulation situation, the Monte Carlo method is used to perform simulation analysis to determine the optimal launch batch and the performance index. The specific calculation is described in Example 3, and will not be repeated here.

[0066] S3. According to the optimal launch batch, the satellites in the same batch are sorted and grouped according to the satellite NORAD numbers to confirm the satellite deployment order.

[0067] Each batch of constellation deployment is grouped according to the satellite NORAD number. The satellites climb to the target orbit after running in the parking orbit until the ascending node separation condition is met. During the climbing process, the distance and phase between the satellites gradually increase to achieve phase adjustment. During the climbing process, the satellites encounter inconsistent behaviors such as re-entering the atmosphere, and the phase needs to be readjusted. The actual deployment time is delayed than the original plan.

[0068] S4. Based on the satellite deployment sequence and the satellite-related performance data, a parking orbit delay raising model is established, and the parking orbit delay raising model is used to achieve phase separation while the satellite is performing orbit climbing and constellation networking through its own ion thrusters;

[0069] The parking orbit delay lift model is constructed based on the following formula:

[0070]

[0071] t∈[0,t x )

[0072] Where u is the satellite phase offset, f is the thrust acceleration, T is the time it takes for the satellite to climb from the parking orbit to the target orbit, a is the semi-major axis, and t x is the orbit raising delay of the parking orbit satellite, and t is the time before the climb.

[0073] S5. Using the ascending node right ascension drift formula and the parameters of the ion thruster, a parking orbit satellite operation time model and a satellite orbit climb time model are constructed, and the satellite-rocket separation altitude and the parking orbit altitude are used as decision variables, and the constellation deployment time and fuel consumption are used as objective functions.

[0074] The time it takes to raise a satellite's orbit is not only related to the satellite's climbing altitude, but also to the various parameters of the satellite's electric thrusters. Take the electric thruster parameters of the Starlink satellite as an example. Thrust formula F, mass flow The formula is:

[0075]

[0076] Where g0 = 9.8006 m / s 2 is the Earth's gravity parameter, δ is the satellite engine efficiency, P eng Engine input power, I sp is the specific impulse,

[0077] The satellite orbit climb time model is constructed based on the following formula:

[0078]

[0079]

[0080] Where Δt4 and Δt5 are the time of the satellite's first and second ascent, respectively; λ is a constant; m0 is the satellite's initial mass; a0 is the semi-major axis of the satellite-rocket separation orbit; μ = 398600.44 km 3 / s 2 is the Earth's gravitational constant, a p is the semi-major axis of the parking orbit satellite, is the mass flow rate, a t is the semi-major axis of the target orbit satellite;

[0081] Δt1=Δt4+Δt5

[0082]

[0083]

[0084] Where t0 is the initial time, and m is the satellite mass after time t1.

[0085] According to the ascending node right ascension drift formula It can be seen that the parking orbit satellite operation time models of the second and third groups include:

[0086]

[0087]

[0088] In the formula, is the right ascension interval between the ascending nodes of the second and third satellite groups and the first satellite group, n p is the angular velocity of the satellite in parking orbit, n t is the angular velocity of the target orbit satellite, a p is the semi-major axis of the parking orbit satellite, a t is the semi-major axis of the target orbit satellite, J2=1.0826×10 -3 is the non-spherical perturbation of the earth, R = 6378.137 km is the radius of the earth, i is the inclination of the satellite orbit, is the right ascension drift of the ascending node. The higher the orbital altitude of the rocket-satellite separation, the less fuel the satellite consumes and the longer its life in orbit. At the same time, the rocket launch cost will also increase, and the overall deployment cost of the constellation will increase significantly. For the satellite's Hall thrusters, they do not work all the time. Therefore, the actual fuel consumption is less than the calculated fuel consumption data.

[0089] S6. Based on the satellite orbit climbing time model and the parking orbit satellite operation time model, the objective function is optimized using the NSGA-II optimization algorithm to determine the optimal constellation deployment plan.

[0090] The phased deployment of low-orbit constellation takes the satellite-rocket separation altitude and the parking orbit altitude as decision variables, and the constellation deployment time and fuel consumption as objective functions. The NSGA-II optimization algorithm is used to determine the optimal parking orbit, and the hypervolume (HV) indicator in the diversity evaluation index is introduced as a measurement criterion.

[0091] This embodiment analyzes the satellite status under uncertain events, the right ascension of the ascending node of the constellation, and the phase deployment analysis. The phased deployment based on the improvement of constellation performance not only meets the flexibility of phased deployment of the constellation, but also minimizes the cost of constellation deployment, making up for the shortcomings of direct orbital insertion or one-rocket orbital plane deployment and long deployment cycle of the constellation, which can provide reference for the deployment of low-orbit constellations.

[0092] Embodiment 2

[0093] An embodiment of the present invention provides a phased deployment device 200 based on a low-orbit large-scale constellation parking orbit, such as Figure 3As shown, it includes: a data acquisition module 201, which is used to acquire constellation target deployment data and satellite-related performance data, and determine whether the launch mode is one rocket with multiple satellites and one rocket with three orbital planes; a simulation analysis module 202, which is used to simulate and analyze the low-orbit constellation navigation performance based on the constellation target deployment data using the Monte Carlo method to obtain the optimal launch batch and performance indicators; a sequence confirmation module 203, which is used to sort and group satellites in the same batch according to the satellite NORAD number according to the optimal launch batch, and confirm the satellite deployment order; a delayed orbit raising module 204, which is used to establish a parking orbit delayed orbit raising model based on the satellite deployment order and the satellite-related performance data, and use the parking orbit delayed orbit raising module 204 to determine the parking orbit delayed orbit raising model. The parking orbit delayed orbit raising model realizes phase separation while the satellite is performing orbit climbing and constellation networking through its own ion thrusters; the model building module 205 is used to construct a parking orbit satellite operation time model and a satellite orbit climbing time model by using the ascending node right ascension drift formula and the parameters of the ion thrusters, and use the satellite-rocket separation altitude and the parking orbit altitude as decision variables, and the constellation deployment time and fuel consumption as the objective function; the optimal solution confirmation module 206 is used to optimize the objective function based on the satellite orbit climbing time model and the parking orbit satellite operation time model by using the NSGA-II optimization algorithm, and introduce the evaluation index HV to determine the optimal constellation deployment solution.

[0094] Furthermore, the parking orbit delay raising model is constructed based on the following formula:

[0095]

[0096] Where u is the satellite phase offset, f is the thrust acceleration, T is the time it takes for the satellite to climb from the parking orbit to the target orbit, a is the semi-major axis, and t x is the orbit raising delay of the parking orbit satellite, and t is the time before the climb.

[0097] Furthermore, the satellite orbit climb time model is constructed based on the following formula:

[0098]

[0099]

[0100] Where Δt4 and Δt5 are the time for the satellite to climb once and twice, respectively; λ is a constant; m0 is the initial mass of the satellite; a0 is the semi-major axis of the satellite-rocket separation orbit; μ is the Earth's gravitational constant; and a is the gravitational constant of the Earth. p is the semi-major axis of the parking orbit satellite, is the mass flow rate, a t is the semi-major axis of the target orbit satellite;

[0101] Δt1=Δt4+Δt5

[0102]

[0103] Where t0 is the initial time, and m is the satellite mass after time t1.

[0104] Furthermore, the parking orbit satellite operation time model includes:

[0105]

[0106]

[0107] In the formula, is the right ascension interval between the ascending nodes of the second and third satellite groups and the first satellite group, n p is the angular velocity of the satellite in parking orbit, n t is the angular velocity of the target orbit satellite, a p is the semi-major axis of the parking orbit satellite, a t is the semi-major axis of the target orbit satellite, J2=1.0826×10 -3 is the non-spherical perturbation of the earth, R=6378.137km is the radius of the earth, and i is the inclination of the satellite orbit.

[0108] Embodiment 3

[0109] The following is a simulation experiment of optimizing the design of parking orbit and phased deployment performance of low-orbit navigation constellation. The experimental process is as follows:

[0110] Step 1: Given the simulation parameters of the low-orbit large-scale navigation constellation, the low-orbit inclined constellation is Walker297 / 27 / 8:1175 / 50 (N=297, P=27, F=8, h=1175km, i=50°); the low-orbit polar constellation is Walker80 / 10 / 7:1150 / 87 (N=80, P=10, F=7, h=1150km, i=87°).

[0111] Step 2: A three-group, three-stage deployment method is used. The deployment plan involves the satellite ascending node right ascension and phase adjustment, parking orbit operation time, and the timing of raising the orbit from the parking orbit to the target orbit.

[0112] Phase 1: Multiple satellites are launched in three groups. One group of satellites directly climbs to the target orbit after the separation of the rocket and satellite, and serves as the reference orbital plane. The remaining satellites wait in a suitable parking orbit. Phase 2: The remaining two groups are in parking operation until the separation condition is met in the J2 perturbation term RAAN. The second group of satellites begins to climb to the target orbit one after another. Phase 3: The third group of satellites stays longer than the second group of satellites until the climbing condition is met. Satellites in all three phases complete satellite phase adjustment when climbing to the target orbital plane. Phased deployment as follows: Figure 5 Shown:

[0113] Step 3: Each batch of constellation deployment is sorted and grouped according to the satellite NORAD number. The satellites climb to the target orbit after operating in the parking orbit until the ascending node separation condition is met. During the climbing process, the distance and phase between the satellites gradually increase to achieve phase adjustment. During the climbing process, the satellites encounter inconsistent behaviors such as re-entry into the atmosphere, and the phase needs to be readjusted. The actual deployment time is delayed than the original plan. The satellite climb and phase separation are shown in Figure 6 (a)-(b).

[0114] Step 4: The deployment method of the low-orbit satellite constellation is to launch multiple satellites in multiple orbits with one rocket. The satellites use their own ion thrusters to complete orbital climb and constellation networking. Delayed orbit lift is used to enable each group of satellites to complete phase separation when all climb to the target orbit. The schematic diagram of delayed orbit lift is shown in the figure below. Figure 7 shown.

[0115] t x is the orbit raising delay of the parking orbit satellite, and the formula is:

[0116]

[0117] Among them, T is the time for the satellite to climb from the parking orbit to the target orbit, u is the inter-satellite phase, f is the acceleration generated by the thrust, and a is the semi-major axis of the satellite.

[0118] The operation time of the second and third groups of satellites in the parking orbit is:

[0119]

[0120]

[0121] Where a is the semi-major axis of the satellite orbit, μ=398600.44km 3 / s 2 is the Earth's gravitational constant. n is the right ascension interval between the ascending nodes of the second and third satellite groups and the first satellite group, p is the angular velocity of the satellite in parking orbit, n t is the angular velocity of the target orbit satellite, a p is the semi-major axis of the parking orbit satellite, a t is the semi-major axis of the target orbit satellite, J2=1.0826×10 -3 is the non-spherical perturbation of the earth, R=6378.137km is the radius of the earth, and i is the inclination of the satellite orbit.

[0122] The satellite orbit raising time is not only related to the satellite climbing altitude, but also to the various parameters of the satellite electric thrusters. According to the data released by the Starlink satellite, the thruster parameters of the two generations of satellites are shown in Table 1.

[0123] Table 1 Comparison of satellite thruster parameters

[0124]

[0125]

[0126] The electric propulsion parameters given in the table above, thrust formula F, mass flow The formula is:

[0127]

[0128] Where g0 = 9.8006 m / s 2 is the Earth's gravity parameter,

[0129] The time required for the satellite to climb from the separation altitude to the parking orbit and the parking orbit to the target orbit is Δt4 and Δt5 respectively. The formula is as follows:

[0130]

[0131]

[0132] In the formula, λ is a constant, λ = 0.058, m0 is the initial mass of the satellite, and a0 is the semi-major axis of the satellite-rocket separation orbit. Among them, Δt1 = Δt4 + Δt5, the formula is:

[0133]

[0134] Satellite fuel consumption is related to mass flow and thruster working time. t0 is the initial time. After time t, the satellite mass is:

[0135]

[0136] Step 5: The latitude and longitude of China and its surrounding areas are: -70°~70° for latitude and 30°~180° for longitude. The minimum observation elevation angle is 5°, the grid is 5°×5°, the simulation time is 1 day, and the step length is 60 seconds. The Monte Carlo method is used to simulate and analyze the navigation performance of the low-orbit constellation. Table 3 gives the optimal launch batch and performance indicators.

[0137] Table 3 Constellation navigation performance of different launch batches of low-orbit inclined constellations

[0138]

[0139]

[0140] The low-orbit inclined constellation is deployed in batches of nine, with three orbital planes deployed in each batch. The launch order is obtained by simulating the performance data of three batches of low-orbit inclined satellites, thereby effectively improving the service performance in mid-latitude areas. The phases of different batches of satellites deployed by the low-orbit inclined constellation are shown in Figure 8(a)-(b).

[0141] The satellites entered the predetermined orbits one after another as originally planned, with different launch batches and different batches completing deployment times.

[0142] The Monte Carlo method is used to simulate and analyze the polar orbit constellation navigation performance. Table 4 gives the optimal launch batch and performance indicators.

[0143] Table 4 Constellation navigation performance of different launch batches of polar orbit constellations

[0144]

[0145] Polar-orbiting constellations have a small number of satellites in each batch and cannot provide services independently. By simulating the performance data of three batches of polar-orbiting satellites to obtain the launch order, the service performance in the polar regions and the overall navigation performance of the constellation can be effectively improved. Fig. 9 shown.

[0146] Step 6: Ignoring the fuel consumption caused by atmospheric drag and other perturbations on the constellation configuration, the upper and lower limits of the satellite-rocket separation altitude and the parking orbit altitude are:

[0147]

[0148] The objective function is the constellation satellite deployment time and the satellite and rocket fuel consumption. fire :

[0149]

[0150] Among them, N j represents the deployment time of the jth batch of satellites, with a total of 9 batches, Δt i represents the time taken by the satellite in the i-th stage.

[0151] The constraints are:

[0152]

[0153] In order to avoid extreme values ​​in the optimization results, the parking orbit height h p It is much larger than the satellite-rocket separation height h0, which is conducive to monitoring the health status of the satellite and making backup plans for uncertain events. The satellite orbit transfer consumes as little fuel as possible to ensure the satellite's on-orbit service life.

[0154] The NSGA-II optimization algorithm is used to optimize the objective function. By adjusting the algorithm parameters, the population size is 50, the maximum evolutionary generation is 3500, and the optimization results and evaluation index HV are shown in Figure 10 (a)-(b). Table 5 gives the parking orbit solutions corresponding to different satellite-rocket separation heights.

[0155] Table 5 Optimized parking orbit scheme

[0156]

[0157] Weighing the fuel consumption and deployment time, the constellation deployment plan selects plan 4. The fuel consumption is calculated through mass flow and deployment time. For the Hall thrusters of the satellite, they do not work all the time. Therefore, the actual fuel consumption is less than the calculated fuel consumption data.

[0158] Table 6 gives the relationship between the operation time of the parking orbit for different deployments of the ascending node right ascension.

[0159] Table 6 Relationship between the right ascension separation of the ascending node of the low-orbit inclined constellation and the operation time of the parking orbit

[0160]

[0161]

[0162] Table 7 gives the number of days of operation in the parking orbit that satisfies the right ascension separation of the ascending node.

[0163] Table 7 Polar orbit constellation ascending node right ascension separation and parking orbit operation time

[0164]

[0165] The right ascension interval of the ascending node of the polar orbit constellation is 36°. The time required to adjust the ascending node using the one-rocket, multiple-orbit deployment method is as long as one year, which does not meet the deployment requirements.

[0166] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A phased deployment method based on a large-scale low-orbit constellation parking orbit, characterized in that: include: S1. Obtain constellation target deployment data and satellite-related performance data to determine whether the launch method is multiple satellites per rocket and three orbital planes per rocket; S2. Based on the constellation target deployment data, a Monte Carlo method is used to simulate and analyze the navigation performance of the low-orbit constellation to obtain the optimal launch batch and performance indicators; S3. According to the optimal launch batch, the satellites in the same batch are sorted and grouped according to the satellite NORAD numbers to confirm the satellite deployment order; S4. Based on the satellite deployment sequence and the satellite-related performance data, a parking orbit delay raising model is established, and the parking orbit delay raising model is used to achieve phase separation while the satellite performs orbit climbing and constellation networking through its own ion thrusters; the parking orbit delay raising model is constructed based on the following formula: t∈[0,t x ) Where u is the satellite phase offset, f is the thrust acceleration, T is the time it takes for the satellite to climb from the parking orbit to the target orbit, a is the semi-major axis, and t x is the orbit raising delay of the parking orbit satellite, and t is the time before the climbing; S5. Using the ascending node right ascension drift formula and the parameters of the ion thruster, a parking orbit satellite operation time model and a satellite orbit climb time model are constructed, and the satellite-rocket separation altitude and the parking orbit altitude are used as decision variables, and the constellation deployment time and fuel consumption are used as the objective function; S6. Based on the satellite orbit climbing time model and the parking orbit satellite operation time model, the objective function is optimized using the NSGA-II optimization algorithm, and an evaluation index HV is introduced to determine the optimal constellation deployment plan.

2. The phased deployment method based on low-orbit large-scale constellation parking orbit according to claim 1 is characterized in that: The S2 includes: S21. Obtain the longitude and latitude of China and surrounding areas and confirm the minimum observation elevation angle; S22, drawing a grid and presetting a simulation time and step size according to the minimum observation elevation angle; S23. After executing the simulation, based on the simulation situation, the Monte Carlo method is used to perform simulation analysis to determine the optimal launch batch and the performance index.

3. The phased deployment method based on low-orbit large-scale constellation parking orbit according to claim 1 is characterized in that: The satellite orbit climb time model is constructed based on the following formula: Where Δt4 and Δt5 are the time for the satellite to climb once and twice, respectively; λ is a constant; m0 is the initial mass of the satellite; a0 is the semi-major axis of the satellite-rocket separation orbit; μ is the Earth's gravitational constant; and a is the gravitational constant of the Earth. p is the semi-major axis of the parking orbit satellite, is the mass flow rate, a t is the semi-major axis of the target orbit satellite; Δt1=Δt4+Δt5 Where t0 is the initial time, and m is the satellite mass after time t1.

4. The phased deployment method based on low-orbit large-scale constellation parking orbit according to claim 1 is characterized in that: The parking orbit satellite operation time model includes: In the formula, is the right ascension interval between the ascending nodes of the second and third satellite groups and the first satellite group, n p is the angular velocity of the satellite in parking orbit, n t is the angular velocity of the target orbit satellite, a p is the semi-major axis of the parking orbit satellite, a t is the semi-major axis of the target orbit satellite, J2 is the non-spherical perturbation of the earth, R is the radius of the earth, and i is the inclination of the satellite orbit.

5. A phased deployment device based on a low-orbit large-scale constellation parking orbit, characterized in that: include: The data acquisition module is used to obtain constellation target deployment data and satellite-related performance data to determine whether the launch method is multiple satellites per rocket and three orbital planes per rocket; A simulation analysis module, used to simulate and analyze the navigation performance of the low-orbit constellation based on the constellation target deployment data using the Monte Carlo method to obtain the optimal launch batch and performance indicators; A sequence confirmation module is used to sort and group satellites in the same batch according to the satellite NORAD numbers according to the optimal launch batch, and confirm the satellite deployment order; The delayed orbit raising module is used to establish a parking orbit delayed orbit raising model based on the satellite deployment sequence and the satellite-related performance data, and use the parking orbit delayed orbit raising model to achieve phase separation while the satellite performs orbit climbing and constellation networking through its own ion thrusters; the parking orbit delayed orbit raising model is constructed based on the following formula: t∈[0,t x ) Where u is the satellite phase offset, f is the thrust acceleration, T is the time it takes for the satellite to climb from the parking orbit to the target orbit, a is the semi-major axis, and t x is the orbit raising delay of the parking orbit satellite, and t is the time before the climbing; A model building module is used to build a parking orbit satellite operation time model and a satellite orbit climb time model using the ascending node right ascension drift formula and the parameters of the ion thruster, and use the satellite-rocket separation altitude and the parking orbit altitude as decision variables, and the constellation deployment time and fuel consumption as the objective function; The optimal solution confirmation module is used to optimize the objective function based on the satellite orbit climb time model and the parking orbit satellite operation time model using the NSGA-II optimization algorithm, and introduce the evaluation index HV to determine the optimal constellation deployment solution.

6. The phased deployment device based on low-orbit large-scale constellation parking orbit according to claim 5 is characterized in that: The simulation analysis module includes: The elevation angle confirmation submodule is used to obtain the longitude and latitude of China and surrounding areas and confirm the minimum observation elevation angle; A preset submodule, used for drawing a grid and presetting a simulation time and a step size according to the minimum observation elevation angle; The simulation analysis submodule is used to perform simulation analysis based on the simulation situation after executing the simulation using the Monte Carlo method to determine the optimal launch batch and the performance indicators.

7. The phased deployment device based on low-orbit large-scale constellation parking orbit according to claim 5 is characterized in that: The parking orbit delay lift model is constructed based on the following formula: t∈[0,t x ) Where u is the satellite phase offset, f is the thrust acceleration, T is the time it takes for the satellite to climb from the parking orbit to the target orbit, a is the semi-major axis, and t x is the orbit raising delay of the parking orbit satellite, and t is the time before the climb.

8. The phased deployment device based on low-orbit large-scale constellation parking orbit according to claim 5 is characterized in that: The satellite orbit climb time model is constructed based on the following formula: Where Δt4 and Δt5 are the time for the satellite to climb once and twice, respectively; λ is a constant; m0 is the initial mass of the satellite; a0 is the semi-major axis of the satellite-rocket separation orbit; μ is the Earth's gravitational constant; and a is the gravitational constant of the Earth. p is the semi-major axis of the parking orbit satellite, is the mass flow rate, a t is the semi-major axis of the target orbit satellite; Δt1=Δt4+Δt5 Where t0 is the initial time, and m is the satellite mass after time t1.

9. The phased deployment device based on low-orbit large-scale constellation parking orbit according to claim 5 is characterized in that: The parking orbit satellite operation time model includes: In the formula, is the right ascension interval between the ascending nodes of the second and third satellite groups and the first satellite group, n p is the angular velocity of the satellite in parking orbit, n t is the angular velocity of the target orbit satellite, a p is the semi-major axis of the parking orbit satellite, a t is the semi-major axis of the target orbit satellite, J2 is the non-spherical perturbation of the earth, R is the radius of the earth, and i is the inclination of the satellite orbit.

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