A orbital maneuver optimization method for improving the observability of an autonomous navigation system

Abstract

The present invention relates to an orbital maneuver optimization method for improving the observability of an autonomous navigation system, comprising the following steps: S1, constructing a relative navigation state equation and a measurement equation; S2, constructing a pseudo-measurement equation containing an orbital maneuver distance; S3, determining an orbital maneuver distance error; S4, constructing an analytical relationship between the system's overall state estimation accuracy and the orbital maneuver amount; S5, determining an orbital maneuver amount model that satisfies a complete estimation of the system state; S6, taking fuel consumption, relative orbital position, service spacecraft collision prevention, and an orbital maneuver amount model that satisfies a complete estimation of the system state in S5 as constraints, taking the analytical relationship between the overall state estimation accuracy and the orbital maneuver amount in S4 as an objective function, solving the optimization model, and obtaining an optimal orbital maneuver amount. The present invention is used for determining the relative position of a non-cooperative target in space, so that the obtained orbital maneuver strategy helps to improve the state estimation accuracy and is more in line with actual engineering needs.

Description

Technical Field

[0001] The invention relates to a track maneuvering optimization method for improving the observability of an autonomous navigation system, and belongs to the technical field of autonomous navigation. Background Art

[0002] The autonomous relative navigation method for space non-cooperative targets is a core technical means to determine the relative orbital states of space non-cooperative targets such as enemy spacecraft, space debris, and asteroids. It has wide applications in space on-orbit services, space attack and defense, asteroid detection and other fields.

[0003] Using only sequential image measurement information can only provide line-of-sight information for the service spacecraft. The system has poor observability and cannot fully estimate the relative orbital position and velocity of non-cooperative targets in space. This requires the service spacecraft to actively maneuver a certain distance to provide scale information for the relative navigation system. However, since the direction and size of the orbital maneuver will affect the accuracy of the system state estimation, not all orbital maneuvers can provide effective scale information for the navigation system, and the distance error caused by the orbital maneuver is an important factor affecting the accuracy of the system state estimation. For example, if the service spacecraft performs an orbital maneuver along the line of sight, the orbital maneuver does not generate effective scale information, and the measurement information obtained by the system is the same as the line of sight information before the maneuver.

[0004] In the previous autonomous relative navigation orbital maneuvers of non-cooperative targets in space using only sequential images, mission constraints, fuel constraints and the optimal accuracy of system state estimation are often not considered simultaneously. Although these methods can improve the autonomous relative navigation accuracy of non-cooperative targets in space to a certain extent, they are not optimal from the overall mission level. Summary of the invention

[0005] The technical problem solved by the present invention is: to overcome the shortcomings of the prior art and propose an orbital maneuvering optimization method with improved observability of an autonomous navigation system, which is used to determine the relative position of a non-cooperative target in space, so that the obtained orbital maneuvering strategy not only helps to improve the accuracy of state estimation, but also better meets the actual needs of engineering.

[0006] The solution of the present invention is:

[0007] A method for optimizing orbital maneuvers for improving observability of an autonomous navigation system comprises the following steps:

[0008] S1. According to the laws of relative orbital dynamics and the principle of sequential image measurement, the relative navigation state equation and measurement equation are constructed;

[0009] S2, construct a pseudo-measurement equation including the orbital maneuvering distance according to the relative navigation state equation and measurement equation of S1 and the orbital maneuvering model;

[0010] S3, determining the orbital maneuvering distance error based on the relative navigation state equation in S1 and the pseudo-measurement equation in S2;

[0011] S4. Construct an analytical relationship between the system's overall state estimation accuracy and orbital maneuvering amount;

[0012] S5. Determine an orbital maneuvering model that satisfies complete estimation of the system state based on the relative orbital dynamics model and the sequence image measurement model;

[0013] S6, with fuel consumption, relative orbital position, service spacecraft collision avoidance and the orbital maneuver model that meets the system state complete estimation conditions in S5 as constraints, and the analytical relationship between the full state estimation accuracy and the orbital maneuver in S4 as the objective function, the interior point method is used to solve the optimization model to obtain the optimal orbital maneuver.

[0014] Furthermore, the state equation of the space non-cooperative target autonomous relative navigation system described in S1 is:

[0015] x k =Φx k-1 +Gu k +w k

[0016] Where k represents the time, w k represents the state noise, u k is the orbital maneuvering quantity, Φ is the state transfer matrix, and G is the control input matrix of the orbital maneuvering.

[0017] Furthermore,

[0018]

[0019] Furthermore, the measurement equation described in S1 is:

[0020]

[0021] Among them, θ k and φ k represent the azimuth and altitude respectively, represent the azimuth and altitude measurement noise respectively.

[0022] Furthermore, the pseudo measurement equation described in S2 is:

[0023]

[0024] Among them, among them, θ k and φ k Represent the azimuth and altitude angles respectively, d krepresents the distance generated by the orbital maneuver, Represents the orbital maneuver distance error.

[0025] Furthermore, the orbital maneuvering distance error described in S3 is:

[0026]

[0027] Among them, α represents the angle between the relative position vectors before and after the orbital maneuver, β represents the angle between the relative position vector before the orbital maneuver and the orbital maneuvering vector, δα is the error angle caused by the random error of the optical sensor, and δr represents the direction vector caused by the orbital maneuver.

[0028] Furthermore, the analytical relationship between the system state estimation accuracy and the orbital maneuvering amount described in S4 is:

[0029]

[0030] Where L i (j,j) is a function of the orbital maneuver u, representing the Cramer-Rao lower bound matrix L i The j-th diagonal element.

[0031] Furthermore, the diagonal elements of the Cramer-Rao lower bound matrix reflect the estimation accuracy of the corresponding system state variables, L i It is expressed as:

[0032]

[0033] in, R=diag([RRR d ]), Φ is the state transfer matrix.

[0034] Furthermore, the orbital maneuvering momentum model that satisfies the complete estimation of the system state described in S5 is:

[0035] Φ1Φ n-1 G1u≠γΦ1Φ n x k ,

[0036] Where Φ1 represents the matrix composed of the first three rows of the state transfer matrix Φ in S1, γ>-1, and n represents the time after the orbital maneuver.

[0037] Furthermore, the fuel constraint described in S6 is:

[0038]

[0039]

[0040] Among them, umax It is the maximum allowable orbital maneuvering modulus, determined by the upper limit of system fuel consumption.

[0041] Furthermore, the relative orbit position constraint described in S6 is:

[0042] x min -Φ n x k ≤Φ n-1 Gu≤x max -Φ n x k

[0043] The linear expression of the above formula is:

[0044] P u u≤b u

[0045] -P u u≤b l

[0046] in

[0047] P u =Φ n-1 G

[0048] b u =x max -Φ n x k

[0049] b l =x min -Φ n x k

[0050] x max and x min Represent the upper and lower bounds of the relative position respectively.

[0051] Furthermore, the anti-collision constraint described in S6 is:

[0052]

[0053] where ||·|| represents the vector modulus, which is used to calculate the distance between the service spacecraft and the target, and N(u) is the nonlinear expression of the anti-collision constraint.

[0054] Furthermore,

[0055] Furthermore, the optimization model described in S6 is:

[0056]

[0057] The constraints are:

[0058] -P x u<-b x

[0059]

[0060]

[0061] P u u≤b u

[0062] -P u u≤b l

[0063] N(u)<0

[0064] The optimal solution u obtained by the interior point method for the above model is the optimal orbital maneuver.

[0065] The beneficial effects of the present invention compared with the prior art are:

[0066] (1) The present invention aims to optimize the observability of the relative navigation system and solve the optimal orbital maneuver, which effectively improves the accuracy of system state estimation and provides an important source of information for subsequent on-orbit service missions;

[0067] (2) The present invention achieves optimal state estimation accuracy throughout the entire process through a one-step optimal orbit maneuver, which reduces the cumbersome process of multi-step maneuvers, guidance and control, and is suitable for autonomous implementation on service spacecraft;

[0068] (3) The optimal orbital maneuvering solution method of the present invention fully considers the engineering constraints in the process of autonomous relative navigation mission of non-cooperative space targets and is suitable for actual engineering mission scenarios of on-orbit services. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a flowchart of the present invention;

[0070] Figure 2 It is a schematic diagram of the measurement model principle of the present invention;

[0071] Figure 3 Schematic diagram of orbital maneuver distance error analysis. DETAILED DESCRIPTION

[0072] The present invention will be further described below in conjunction with the embodiments.

[0073] Aiming at the problem that orbital maneuvers in the prior art do not consider the task requirement constraints, fuel consumption, and navigation accuracy, an orbital maneuver optimization method for improving the observability of an autonomous navigation system is proposed. The present invention takes the relative navigation system state estimation accuracy of the entire process as the observability quantification target, and solves the optimal orbital maneuvering amount in one step by optimizing the target. For the autonomous relative navigation system of a space non-cooperative target that only uses sequence images, the analytical relationship between the orbital maneuvering direction, size and system observability is analyzed, and the highest navigation accuracy is used as the optimization objective function; considering that fuel consumption is one of the issues that spacecraft should focus on during on-orbit operation, an analytical relationship between orbital maneuvers and fuel consumption is established; in addition, considering the actual mission requirements of the service spacecraft on-orbit, the final arrival position of the spacecraft, fuel consumption and spacecraft safety conditions are taken as constraints, and an optimization model for the full-process autonomous relative navigation accuracy based on one-step orbital maneuvers is established. The optimization model based on the full-process relative navigation accuracy fully considers the task constraints, so that the obtained orbital maneuvering strategy not only helps to improve the state estimation accuracy, but also better meets the actual needs of the project.

[0074] The invention relates to a method for determining an optimal orbit maneuver using only sequential image space non-cooperative target autonomous relative navigation. (1) According to the law of relative orbital dynamics and the principle of measurement using only sequential images, the relative navigation state equation and measurement equation are constructed; (2) According to the relative navigation state equation and measurement equation in (1) and the orbital maneuver model, the pseudo-measurement equation containing the orbital maneuver distance is constructed; (3) According to the relative navigation state equation in (1) and the pseudo-measurement equation in (2), the orbital maneuver distance error is analyzed; (4) With the realization of high-precision complete state estimation of the system as the prerequisite, and the system full-process state estimation as the quantitative indicator of observable capability, the analytical relationship between the system full-process state estimation accuracy and the orbital maneuver amount is constructed; (5) According to the relative orbital dynamics model and the sequential image measurement model, the orbital maneuver amount model that satisfies the complete state estimation of the system is analyzed; (6) With fuel consumption, relative orbital position, service spacecraft safety requirements and the orbital maneuver amount model that satisfies the complete state estimation conditions of the system in (5) as constraints, the analytical relationship between the full-process state estimation accuracy and the orbital maneuver amount in (4) is taken as the objective function, and the optimization model is solved by the interior point method to obtain the optimal orbital maneuver amount.

[0075] The method for determining the optimal orbital maneuver for autonomous relative navigation of non-cooperative targets using only sequential image space obtained by the present invention realizes the optimal state estimation accuracy of the autonomous relative navigation system throughout the entire process, adopts a one-step orbital maneuvering method, has a simple process, and avoids multi-step maneuvering, guidance and control planning.

[0076] Depend on Figure 1 , 2 As shown in the figure, the dynamic model and observation model of the spacecraft autonomous navigation system are established.

[0077] x k =Φx k-1 +Gu k +w k

[0078] in k represents the time, w k represents state noise, which has a mean of 0 and a covariance of Gaussian white noise, u k is the orbital maneuvering quantity, which is specifically expressed as:

[0079]

[0080] Φ is the state transfer matrix in discrete form, which is specifically expressed as:

[0081]

[0082] Where Φ1 and Φ2 are composed of the first three rows and the last three rows of the matrix Φ, respectively, ω is the angular velocity of the service spacecraft in orbit, T is the sampling time interval, and G is the orbital maneuver input control matrix:

[0083]

[0084] Where G1 and G2 are composed of the first three rows and the last three rows of elements of matrix G respectively.

[0085] The observation equation described in S1 is:

[0086]

[0087] here Represent the azimuth and altitude measurement noise respectively, their means are both 0, and their covariance is Gaussian white noise, R is determined by the sensor hardware parameters, (z x ,z y ) is the coordinate of the target in the imaging plane of the optical sensor. Since the position state of the target is at the kilometer level, and the focal length and imaging coordinates of the optical sensor are at the millimeter or even micron level, it can be simplified as:

[0088]

[0089] (2) Based on the relative navigation state equation and measurement equation of (1) and the orbital maneuvering model, a pseudo-measurement equation including the orbital maneuvering distance is constructed:

[0090] Orbital maneuvers can provide distance information for the relative navigation system state estimation. Since this measurement information is not obtained by real measurement, it is called "pseudo-measurement quantity" or "pseudo-range measurement information". Combined with the image measurement equation, the pseudo-measurement equation with the pseudo-range measurement equation is obtained:

[0091]

[0092] The relative distances between the service spacecraft and the target before and after the orbital maneuver are rkr k , the two are calculated as follows k According to the position change before and after the orbital maneuver, the calculation is as follows:

[0093]

[0094] r k =Φ1x k-1 +G1u

[0095] Then the relative distance (pseudorange) after orbital maneuver is calculated as follows:

[0096] d k =|r k |=|Φ1x k-1 +G1u|

[0097] The relative distance at the (k+n)th moment can be calculated as follows:

[0098] d k+n =Φ1Φ n-2 (Φx k +Gu)

[0099] (3) According to the relative navigation state equation in (1) and the pseudo-measurement equation in (2) and Figure 3 , analyze the orbital maneuver distance error:

[0100] exist Figure 3 In x and δz y represents the image point error, δr represents the direction vector generated by the orbital maneuver, δα represents the angle error of the position vector before and after the orbital maneuver, and r ε Represents the true relative position vector caused by the optical sensor error. Combined with the sine theorem, the relative distance effect caused by the sensor error satisfies the following conditions:

[0101]

[0102] Then the relative distance error Δd can be expressed as:

[0103]

[0104] The trigonometric function sin(α+β+δa) can be expanded by Taylor as follows:

[0105]

[0106] Among them O(δa 2 ) represents a negligible high-order infinitesimal. Since the measurement accuracy of the optical sensor is very high, the error δa is relatively small. Therefore, O(δa 2 ) can be ignored, and Δd can be simplified to:

[0107]

[0108] according to Figure 3 , β satisfies the following equation:

[0109]

[0110] further,

[0111]

[0112] Here Δd also represents the standard deviation of the pseudorange measurement, and the variance of the pseudorange measurement can be obtained as

[0113] The covariance matrix R of the pseudorange measurement equation can be expressed as:

[0114] R=diag([RRR r ])

[0115] (4) Based on the premise of achieving high-precision complete state estimation of the system throughout the process, an analytical relationship between the system state estimation accuracy and orbital maneuvering amount is constructed. The measurement equation in step (1) is transformed to obtain the linear form as follows:

[0116]

[0117] The above formula can be simplified as:

[0118] H(z k )x k =0

[0119] in Assuming that there are three consecutive sampling moments after the orbital maneuver at time k, the measurement equation is obtained as follows:

[0120]

[0121] The left side of the equation is x k The coefficient matrix of After the elementary row transformation, it becomes a 6th-order unit matrix. Therefore, to achieve a complete estimation of the system state, the right side of the equation needs to satisfy That is, the following two conditions are required:

[0122] (1)u≠0

[0123] (2) Matrix The null space of is not an empty set.

[0124] According to condition (1), the orbital maneuver cannot be 0. According to condition (2), we can get:

[0125] Φ1Φ n-1 G1u≠γΦ1Φ n x k ,(γ>-1).

[0126] (5) Based on the relative orbital dynamics model and the sequence image measurement model, an orbital maneuvering momentum model that satisfies the complete estimation of the system state is constructed:

[0127] The accuracy of state estimation is analyzed by the Fisher information matrix. The Fisher information matrix at time (k+1) can be expressed as:

[0128]

[0129] Among them, Q k+1 represents the state noise covariance matrix, R k That is the covariance matrix of the pseudorange measurement equation The linear approximation matrix representing the pseudo-measurement equation is:

[0130]

[0131] Since the state covariance matrix is ​​a constant matrix, for the sake of convenience, the state covariance term will be omitted in the subsequent analysis. Assuming that the orbital impulse maneuver is performed at the kth time, the recursive form of the Fisher information matrix at the (k+n) time can be expressed as:

[0132]

[0133] Based on the Fisher information matrix, the Cramer-Rao lower bound is used to measure the lower bound of the state estimation covariance, that is, the inverse of the Fisher information matrix, which can be expressed as:

[0134]

[0135] The state estimation accuracy is mainly determined by the matrix L k It is quantified by the sum of the diagonal elements. It should be noted that this quantization method only includes the relative position state estimation accuracy. kThe right side of can be calculated as follows:

[0136]

[0137] Among them, 3×3 represents a 3×3 zero matrix, M k It can be expressed as:

[0138]

[0139] Here the matrix M k The elements are represented as follows:

[0140]

[0141]

[0142]

[0143]

[0144]

[0145]

[0146]

[0147]

[0148]

[0149] According to the relative orbital dynamics equation, the relative velocity calculation mainly depends on the relative position information. Therefore, the objective function of the orbital maneuver optimization problem mainly depends on the relative position accuracy at each sampling moment after one step of maneuver. Assuming that the relative navigation task ends at the (k+n) moment, the objective function can be expressed as:

[0150]

[0151] Where L i (j,j) is a function of the orbital maneuver u, representing the Cramer-Rao lower bound matrix L i The jth diagonal element. The diagonal elements of the Cramer-Rao lower bound matrix reflect the estimation accuracy of the corresponding system state variables. i It can be expressed as:

[0152]

[0153] Since the state estimation covariance at time k is unknown, in order to use the Fisher information matrix to obtain the optimal orbital maneuver, Fk Another reason for this assumption is that the initial value of the state estimate covariance is the same for every moment after the orbital maneuver, so this simplification does not affect the subsequent evaluation of the state estimate accuracy.

[0154] (6) The fuel constraint is constructed as:

[0155]

[0156]

[0157] where u max It is the maximum allowable orbital maneuvering modulus, determined by the upper limit of system fuel consumption.

[0158] The relative orbital position constraints are:

[0159] x min -Φ n x k ≤Φ n-1 Gu≤x max -Φ n x k

[0160] The linear expression of the above formula is:

[0161] P u u≤b u

[0162] -P u u≤b l

[0163] in

[0164] P u =Φ n-1 G

[0165] b u =x max -Φ n x k

[0166] b l =x min -Φ n x k

[0167] x max and x min Represent the upper and lower bounds of the relative position respectively.

[0168] The relative navigation task safety constraint (anti-collision constraint) is:

[0169]

[0170] Where ||·|| represents the vector modulus, which is used here to calculate the distance between the service spacecraft and the target. N(u) is expressed as:

[0171]

[0172] N(u) is a nonlinear expression of the anti-collision constraint.

[0173] The optimization solution model based on one-step optimal orbital maneuver is:

[0174]

[0175] The constraints are:

[0176] -P x u<-b x

[0177]

[0178]

[0179] P u u≤b u

[0180] -P u u≤b l

[0181] N(u)<0

[0182] The above optimization model is solved by the interior point method, and the orbital maneuver result u obtained is the optimal orbital maneuver amount.

[0183] The optimal orbital maneuvering solution method of the present invention fully considers the engineering constraints in the process of autonomous relative navigation missions of non-cooperative targets in space, and is suitable for actual engineering mission scenarios of on-orbit services; the present invention aims to optimize the observable capability of the relative navigation system, solves the optimal orbital maneuver, effectively improves the system state estimation accuracy, and provides an important source of information for subsequent on-orbit service missions; the present invention achieves the optimal state estimation accuracy throughout the process through a one-step optimal orbital maneuver, reduces the cumbersome process of multi-step maneuvers, guidance and control, and is suitable for autonomous implementation on service spacecraft.

[0184] The method of the present invention fully considers the accuracy index of autonomous relative navigation of non-cooperative targets in space, and can provide high-precision status information for subsequent on-orbit service tasks of relative navigation; the method of the present invention considers the mission requirements such as the running distance and final arrival position of on-orbit missions in space, and fully considers the actual engineering situation; the method of the present invention adopts one-step optimal orbit quantity to realize autonomous relative navigation of non-cooperative targets in space, which can effectively reduce the calculation complexity, avoid multi-step orbital maneuvers, guidance and control planning, and has strong engineering application prospects.

[0185] Although the present invention has been disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for optimizing orbital maneuvers for improving observability of an autonomous navigation system, characterized in that: The steps include: S1. According to the laws of relative orbital dynamics and the principle of sequential image measurement, the state equation and measurement equation of the autonomous relative navigation system for space non-cooperative targets are constructed; S2, construct a pseudo-measurement equation including the orbital maneuvering distance according to the relative navigation state equation and measurement equation of S1 and the orbital maneuvering model; S3, determining the orbital maneuvering distance error based on the relative navigation state equation in S1 and the pseudo-measurement equation in S2; S4. Construct an analytical relationship between the system's overall state estimation accuracy and orbital maneuvering amount; S5. Determine an orbital maneuvering model that satisfies complete estimation of the system state based on the relative orbital dynamics model and the sequence image measurement model; S6, with fuel consumption, relative orbital position, collision avoidance of service spacecraft and the orbital maneuver model that satisfies the complete system state estimation conditions in S5 as constraints, and the analytical relationship between the full state estimation accuracy and the orbital maneuver in S4 as the objective function, the optimization model is solved by the interior point method to obtain the optimal orbital maneuver; The state equation and measurement equation of the space non-cooperative target autonomous relative navigation system described in S1 are: x k =Φx k-1 +Gu k +w k Where k represents the time, w k represents the state noise, u k is the orbital maneuvering quantity, Φ is the state transfer matrix, and G is the control input matrix of the orbital maneuvering; The pseudo-measurement equation described in S2 is: Among them, among them, θ k and φ k Represent the azimuth and altitude angles respectively, d k represents the distance generated by the orbital maneuver, represents the orbital maneuver distance error, represent the measurement noise of azimuth and elevation respectively; The orbital maneuvering momentum model described in S5 that satisfies the complete estimation of the system state is: F1F n-1 G1u≠γΦ1Φ n x k , Where Φ1 represents the matrix composed of the first three rows of the state transfer matrix Φ in S1, γ>-1, n represents the time after the orbital maneuver, x k is the position state of the target relative to the service spacecraft.

2. The orbital maneuvering optimization method for improving the observability of an autonomous navigation system according to claim 1, characterized in that: in, To serve the maneuvering acceleration of the spacecraft in the x, y, and z directions in the orbital coordinate system.

3. The orbital maneuvering optimization method for improving the observability of an autonomous navigation system according to claim 1, characterized in that: The measurement equation described in S1 is: Among them, θ k and φ k represent the azimuth and altitude respectively, represent the azimuth and elevation measurement noise respectively, x k ,y k is the position state of the target relative to the service spacecraft.

4. The orbital maneuvering optimization method for improving the observability of an autonomous navigation system according to claim 1, characterized in that: The orbital maneuver distance error described in S3 is: Among them, α represents the angle between the relative position vectors before and after the orbital maneuver, β represents the angle between the relative position vector before the orbital maneuver and the orbital maneuvering vector, δα is the error angle caused by the random error of the optical sensor, and δr represents the direction vector caused by the orbital maneuver.

5. The orbital maneuvering optimization method for improving the observability of an autonomous navigation system according to claim 1, characterized in that: The analytical relationship between the system state estimation accuracy and orbital maneuvering amount described in S4 is: Where L i (j,j) is a function of the orbital maneuver u, representing the Cramer-Rao lower bound matrix L i The j-th diagonal element.

6. The orbital maneuver optimization method for improving the observability of an autonomous navigation system according to claim 5, characterized in that: The diagonal elements of the Cramer-Rao lower bound matrix reflect the estimation accuracy of the corresponding system state variables, L i It is expressed as: in, R=diag([RRR d ]), Φ is the state transfer matrix.

7. The orbital maneuvering optimization method for improving the observability of an autonomous navigation system according to claim 1, characterized in that: The fuel constraints stated in S6 are: Where u is the orbital maneuver, is the fuel constraint constant, u max It is the maximum allowable orbital maneuvering modulus, determined by the upper limit of system fuel consumption.

8. The orbital maneuvering optimization method for improving the observability of an autonomous navigation system according to claim 1, characterized in that: The relative orbital position constraints described in S6 are: x min -F n x k ≤Φ n-1 Gu≤x max -F n x k The linear expression of the above formula is: P u u≤b u -P u u≤b l in P u =Φ n-1 G b u =x max -F n x k b l =x min -F n x k x max and x min Represent the upper and lower bounds of the relative position respectively.

9. The orbital maneuver optimization method for improving the observability of an autonomous navigation system according to claim 1, characterized in that: The anti-collision constraints described in S6 are: where ||·|| represents the vector modulus, which is used to calculate the distance between the service spacecraft and the target, N(u) is the nonlinear expression of the anti-collision constraint, and O n×1 is a 0 matrix.

10. The orbital maneuvering optimization method for improving the observability of an autonomous navigation system according to claim 9, characterized in that:

11. The orbital maneuver optimization method for improving the observability of an autonomous navigation system according to claim 1, characterized in that: The optimization model described in S6 is: The constraints are: -P x u<-b x P u u≤b u -P u u≤b l N(u)<0 The optimal solution u obtained by the interior point method for the above model is the optimal orbital maneuver.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to claim 1 are implemented.

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