A distributed spectrum redshift / starlight refraction combined navigation method and related product

Abstract

The application discloses a kind of distributed spectrum red shift / starlight refraction combined navigation method and related products, belong to spacecraft combined navigation technical field.The distributed spectrum red shift / starlight refraction combined navigation method provided by the application constructs distributed spectrum red shift / starlight refraction combined navigation system, so that each navigation source can work in parallel, do not interfere with each other, even if a navigation source fails or error is larger, it will not cause serious influence to the navigation performance of the whole system, to enhance the fault tolerance and reliability of navigation system;Adopt federated filtering framework, and combine adaptive information factor to carry out iterative information fusion, so that navigation system can dynamically adjust adaptive information factor, real-time reflect the difference between each sub-filter state variable and track its change, not only improve the accuracy of navigation estimation, also reduce the risk that state error and fault are transmitted with sub-filter reset.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of spacecraft integrated navigation, in particular to a distributed spectral redshift / starlight refraction integrated navigation method and related products. BACKGROUND

[0002] As a key support for the realization of automatic and intelligent operation of spacecraft, the core position of autonomous navigation technology is self-evident. As a leading autonomous celestial navigation method, the spectral redshift navigation system can accurately solve the radial velocity of the spacecraft by analyzing the spectral redshift information of celestial bodies, and then calculate the navigation information. This technology has great potential in the field of spacecraft autonomous navigation due to its intuitive principle, high autonomy and excellent anti-interference ability.

[0003] However, the development of spectral redshift navigation technology is not smooth. Although the early spectral redshift navigation method can directly measure the velocity, the acquisition of position information depends on the integration of velocity, which leads to significant accumulation of position error after long navigation. To solve this problem, the spectral redshift positioning navigation system is proposed in subsequent research, but this system introduces more navigation parameters, requiring the measurement of the redshift of more than six non-collinear celestial bodies to ensure the accuracy of navigation calculation. This requirement is often difficult to achieve in practical applications, especially in disturbed environments, which limits the widespread application of spectral redshift navigation systems. In order to overcome the limitations of spectral redshift navigation systems, researchers began to explore the combination with other navigation technologies, aiming to build an autonomous integrated navigation system. The optimization of spacecraft integrated navigation structure is also crucial in this process. The spacecraft integrated navigation structure usually adopts a distributed filtering structure. Compared with centralized filtering, distributed filtering divides the entire filter into a two-level structure, which has good fault tolerance. Among many distributed filters, the simplest federated filtering algorithm estimates the state of the navigation subsystem, and then obtains the final navigation state estimation value by fusing the state estimation of the sub-filter. This algorithm has high fault tolerance. However, the accuracy of this federated filtering algorithm is not high. To further improve the filtering accuracy, experts proposed a federated filtering algorithm based on information distribution principle. Based on the information distribution principle, the global state estimation of the master filter is used to replace the local state estimation of the sub-filter after filtering, and the corresponding information factor is set based on the error upper bound technique to eliminate the mutual correlation of the sub-filter caused by replacing the state estimation of the sub-filter, thereby achieving higher navigation estimation accuracy.

[0004] However, in actual integrated navigation, there are certain differences between the sub-filters constructed by different sensors. The fixed information factor selected by experience cannot reflect the differences between the state variables of each sub-filter and track their changes in real time. Instead, it will affect the estimation accuracy of all sub-filters due to the state estimation error of the master filter, and weaken the fault tolerance of the integrated navigation system.

[0005] Therefore, how to design a new distributed spectral redshift / starlight refraction combined navigation method for guaranteeing the precision and reliability of spacecraft navigation has become a technical problem to be solved by the current technical personnel. SUMMARY

[0006] The purpose of the present application is to provide a distributed spectral redshift / starlight refraction combined navigation method and related products to overcome the problem of low navigation precision and reliability caused by fixed information factors in the prior art.

[0007] The present application solves the above technical problems by the following technical solutions:

[0008] The present application provides a distributed spectral redshift / starlight refraction combined navigation method, comprising the following steps:

[0009] S1, constructing a mathematical model of a spectral redshift / starlight refraction combined navigation system;

[0010] S2, based on the mathematical model, constructing a distributed spectral redshift / starlight refraction combined navigation system;

[0011] S3, using a federated filtering framework to perform information fusion on the adaptive information factor iteration of the distributed spectral redshift / starlight refraction combined navigation system, and realizing navigation estimation of the distributed spectral redshift / starlight refraction combined navigation system.

[0012] The present application further improves in that S1 specifically comprises the following steps:

[0013] Based on the orbit dynamics equation, a state equation of the spectral redshift / starlight refraction combined navigation system is constructed; based on the spectral redshift positioning navigation system solving equation, a first measurement equation of the spectral redshift / starlight refraction combined navigation system is constructed; and based on the starlight refraction navigation system solving equation, a second measurement equation of the spectral redshift / starlight refraction combined navigation system is constructed.

[0014] The present application further improves in that S2 specifically comprises the following steps: based on the state equation and the first measurement equation, a spectral redshift navigation subsystem is constructed; and based on the state equation and the second measurement equation, a starlight refraction navigation subsystem is constructed.

[0015] The present application further improves in that the federated filtering framework comprises a main filter, a first sub-filter and a second sub-filter.

[0016] The present application further improves in that the main filter adopts a federated filter; and the first sub-filter and the second sub-filter both adopt a cubature Kalman filter.

[0017] The further improvement of the present application is that the information fusion about adaptive information factor iteration specifically comprises the following steps:

[0018] S31, locally state estimates the spectral redshift navigation subsystem through the first sub-filter to obtain the local state estimate value of the spectral redshift navigation subsystem; and locally state estimates the starlight refraction navigation subsystem through the second sub-filter to obtain the local state estimate value of the starlight refraction navigation subsystem;

[0019] S32, information fuses the local state estimate value of the spectral redshift navigation subsystem and the local state estimate value of the starlight refraction navigation subsystem through the main filter to obtain the global state estimate value of the distributed spectral redshift / starlight refraction combined navigation system;

[0020] S33, based on the local state estimate value of the spectral redshift navigation subsystem, the local state estimate value of the starlight refraction navigation subsystem and the global state estimate value, combines the probability density function and the Bayesian estimation principle to construct an adaptive information factor, resets the first sub-filter and the second sub-filter based on the adaptive information factor, and repeatedly executes steps S31-S33 until the navigation ends.

[0021] The present application also provides a distributed spectral redshift / starlight refraction combined navigation system, comprising:

[0022] The first module is used for constructing a mathematical model of the spectral redshift / starlight refraction combined navigation system;

[0023] The second module is used for constructing a distributed spectral redshift / starlight refraction combined navigation system based on the mathematical model;

[0024] The third module is used for adopting a federal filter framework to perform information fusion about adaptive information factor iteration on the distributed spectral redshift / starlight refraction combined navigation system, and realizes navigation estimation of the distributed spectral redshift / starlight refraction combined navigation system.

[0025] The present application also provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the above-mentioned distributed spectral redshift / starlight refraction combined navigation method when executing the computer program.

[0026] The present application also provides a computer readable storage medium, which stores a computer program, and the computer program realizes the steps of the above-mentioned distributed spectral redshift / starlight refraction combined navigation method when executed by a processor.

[0027] The present application also provides a computer program product comprising a computer program, and the computer program realizes the steps of the above-mentioned distributed spectral redshift / starlight refraction combined navigation method when executed by a processor.

[0028] The positive progress effect of the present application compared with the prior art is that:

[0029] The present application provides a kind of distributed spectrum redshift / starlight refraction combined navigation method, constructs distributed spectrum redshift / starlight refraction combined navigation system, so that each navigation source (spectrum redshift navigation and starlight refraction navigation) can work in parallel, do not interfere with each other, even if a navigation source fails or error is larger, it will not cause serious influence to the navigation performance of the whole system, to enhance the fault tolerance and reliability of navigation system;Adopt federated filtering framework, and combine adaptive information factor to carry out iterative information fusion, so that the navigation system can dynamically adjust adaptive information factor, real-time reflects the difference between each sub-filter state variable and tracks its change, not only improves the accuracy of navigation estimation, but also reduces the risk of state error and fault transmission with sub-filter reset. BRIEF DESCRIPTION OF DRAWINGS

[0030] The accompanying drawings are included to provide a further understanding of the present application, and are incorporated in and constitute a part of the present application, the schematic embodiments of the present application and the description thereof are used to explain the present application, and do not constitute improper limitation on the present application.

[0031] Figure 1 It is a schematic diagram of the principle of federated framework based on adaptive information factor;

[0032] Figure 2 It is a structure schematic diagram of a distributed spectrum redshift / starlight refraction combined navigation system of the present application;

[0033] Figure 3 It is a flowchart of a distributed spectrum redshift / starlight refraction combined navigation method of the present application. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0035] In the description of the present application, it should be understood that the terms "include" and "contain" indicate the existence of described features, whole, steps, operations, elements and / or components, but do not exclude the existence or addition of one or more other features, whole, steps, operations, elements, components and / or their sets.

[0036] It should also be understood that the terms used in the specification and the following claims are for the purpose of describing particular embodiments only and are not intended to be limiting, as the specific scope of the present application is disclosed herein. As used in this specification and the appended claims, the singular forms "a," "an" and "the" encompass plural referents unless the context clearly dictates otherwise.

[0037] It should also be further understood that the term "and / or" as used in the specification and the following claims, means any one of the items listed or a combination of any of the items, and includes all possible combinations thereof, for example, A and / or B can mean only A, or only B, or both A and B. In addition, the character " / " in the present application generally represents an "or" relationship between the front and rear associated objects.

[0038] It should be understood that, although the terms first, second, third, etc. can be employed in describing various embodiments of the present application, these terms are merely used to differentiate one embodiment from another, and do not imply a particular order of precedence. For example, a first predetermined range can also be referred to as a second predetermined range, and similarly, a second predetermined range can also be referred to as a first predetermined range, without departing from the scope of embodiments of the present application.

[0039] Depending on the context, the word "if" as used herein can be interpreted to mean "when" or "while" or "in response to determining" or "in response to detecting." Similarly, the phrase "if it is determined" or "if a stated condition or event occurs" can be interpreted to mean "when it is determined" or "when a stated condition or event occurs" or "in response to determining" or "in response to detecting a stated condition or event."

[0040] Various structural diagrams according to the disclosed embodiments of the present application are shown in the accompanying drawings. These drawings are not drawn to scale, in which certain details are exaggerated for the purpose of clarity and some details can be omitted. The shapes of various regions, layers, and their relative sizes and positional relationships shown in the drawings are merely exemplary, and in actuality, they can deviate due to manufacturing tolerances or technical limitations, and regions / layers with different shapes, sizes, and relative positions can be additionally designed by those skilled in the art as needed.

[0041] The present application is further described in detail in the following with reference to the accompanying drawings and specific embodiments, which are an explanation of the present application rather than a limitation.

[0042] Referring to Figure 3 The present application provides a distributed spectrum redshift / starlight refraction combined navigation method, comprising the following steps:

[0043] S1, constructing a mathematical model of a spectrum redshift / starlight refraction combined navigation system;

[0044] S2, constructing a distributed spectrum redshift / starlight refraction combined navigation system based on the mathematical model;

[0045] S3, performing information fusion on the distributed spectrum redshift / starlight refraction combined navigation system with respect to adaptive information factor iteration by using a federated filtering framework, so as to realize navigation estimation of the distributed spectrum redshift / starlight refraction combined navigation system.

[0046] The distributed spectrum redshift / starlight refraction combined navigation method provided by the application constructs a distributed spectrum redshift / starlight refraction combined navigation system, so that each navigation source (spectrum redshift navigation and starlight refraction navigation) can work in parallel and does not interfere with each other, even if a navigation source fails or has a large error, it will not seriously affect the navigation performance of the whole system, thereby enhancing the fault tolerance and reliability of the navigation system; the federated filtering framework is used, and the adaptive information factor is iterated for information fusion, so that the navigation system can dynamically adjust the adaptive information factor, real-time reflect the differences between the state variables of each sub-filter and track the changes, not only improve the accuracy of navigation estimation, but also reduce the risk of state error and fault transmission with sub-filter reset.

[0047] Preferably, S1 specifically comprises the following steps:

[0048] Based on the orbit dynamics equation, a state equation of the spectrum redshift / starlight refraction combined navigation system is constructed; based on a spectrum redshift positioning navigation system solving equation, a first measurement equation of the spectrum redshift / starlight refraction combined navigation system is constructed; based on a starlight refraction navigation system solving equation, a second measurement equation of the spectrum redshift / starlight refraction combined navigation system is constructed.

[0049] Preferably, S2 specifically comprises the following steps: based on the state equation and the first measurement equation, a spectrum redshift navigation subsystem is constructed; based on the state equation and the second measurement equation, a starlight refraction navigation subsystem is constructed.

[0050] Preferably, the federated filtering framework comprises a master filter, a first sub-filter and a second sub-filter.

[0051] Preferably, the master filter adopts a federated filter; the first sub-filter and the second sub-filter both adopt a cubature Kalman filter.

[0052] Preferably, referring to Figure 1 and Figure 2 , the information fusion with respect to adaptive information factor iteration specifically comprises the following steps:

[0053] S31, performing local state estimation on the spectral redshift navigation subsystem by a first sub-filter to obtain a local state estimation value of the spectral redshift navigation subsystem; performing local state estimation on the starlight refraction navigation subsystem by a second sub-filter to obtain a local state estimation value of the starlight refraction navigation subsystem;

[0054] S32, performing information fusion on the local state estimation value of the spectral redshift navigation subsystem and the local state estimation value of the starlight refraction navigation subsystem by a main filter to obtain a global state estimation value of the distributed spectral redshift / starlight refraction combined navigation system;

[0055] S33, based on the local state estimation value of the spectral redshift navigation subsystem, the local state estimation value of the starlight refraction navigation subsystem and the global state estimation value, combining a probability density function and a Bayesian estimation principle to construct an adaptive information factor, resetting the first sub-filter and the second sub-filter based on the adaptive information factor, and repeatedly executing steps S31-S33 until the navigation ends.

[0056] Based on the same inventive concept, the application also provides a distributed spectral redshift / starlight refraction combined navigation system, comprising:

[0057] A first module is configured to construct a mathematical model of the spectral redshift / starlight refraction combined navigation system.

[0058] A second module is configured to construct a distributed spectral redshift / starlight refraction combined navigation system based on the mathematical model.

[0059] A third module is configured to perform information fusion on the distributed spectral redshift / starlight refraction combined navigation system with respect to iteration of an adaptive information factor by using a federated filtering framework, so as to realize navigation estimation of the distributed spectral redshift / starlight refraction combined navigation system.

[0060] Embodiment one

[0061] A distributed spectral redshift / starlight refraction combined navigation method comprises the following steps:

[0062] S1, a mathematical model of a spectral redshift / starlight refraction combined navigation system is constructed; a state equation of the spectral redshift / starlight refraction combined navigation system is constructed based on an orbit dynamics equation; a first measurement equation of the spectral redshift / starlight refraction combined navigation system is constructed based on a spectral redshift positioning navigation system solution equation; and a second measurement equation of the spectral redshift / starlight refraction combined navigation system is constructed based on a starlight refraction navigation system solution equation.

[0063] Based on the orbit dynamics equation, the state equation can be obtained as follows:

[0064]

[0065] where μ represents the gravitational constant of the sun, μ i represents the gravitational constant of the i th planet, p represents the position of the spacecraft, v represents the velocity of the spacecraft, P represents the number of planets, p si represents the position of the spacecraft to the i th planet, p i represents the position of the i th planet, represents the differential of p, represents the integral of v, F () represents a state transition function obtained according to a dynamic equation, represents a continuous form of a state quantity, is process noise.

[0066] After discretization, the following can be obtained:

[0067] X k = F k (X k-1 ) + w k (2)

[0068] where F k () represents a state transition function at time k after discretization, X k represents state information at time k after discretization, w k represents process noise after discretization.

[0069] The spectral redshift velocity navigation equation is known:

[0070]

[0071] where u is a direction vector between a celestial body and a spacecraft in an inertial coordinate system, r represents a spectral redshift of an observed celestial body, v c represents the velocity of the observed celestial body, and c represents the speed of light.

[0072] wherein,

[0073]

[0074] where p c represents the position of the observed celestial body.

[0075] The spectral redshift positioning navigation solution equation can be obtained by combining equation (3) and equation (4):

[0076]

[0077] It is assumed that the spacecraft can observe the spectral redshift of m celestial bodies, and based on the spectral redshift positioning navigation solution equation, a first measurement equation of a spectral redshift / starlight refraction combined navigation system is constructed, which is specifically:

[0078]

[0079] where Z r is the spectrum redshift measurement vector, H r is the spectrum redshift measurement function, Δr is the spectrum redshift measurement error vector, r1,…,r m denotes the spectrum redshift of m celestial bodies, Δr1,…,Δr m denotes the spectrum redshift error of m celestial bodies, h r1 (X),…,h rm (X) denotes the measurement function of the spectrum redshift of m celestial bodies.

[0080] Discretization of equation (6) can be obtained as follows:

[0081] Z r，k = H r，k (X k )+ v r，k (7)

[0082] where H r,k () denotes the discretized spectrum redshift measurement function at time k, Z r,k denotes the spectrum redshift measurement at time k, v r,k = Δr k denotes the discretized spectrum redshift measurement error at time k.

[0083] At the same time, it is known that the starlight refraction navigation solution equation is:

[0084]

[0085] where a is the refraction starlight observed by the star sensor relative to the height angle of the earth, u a is the unit vector of the refraction starlight, R e is the radius of the earth, Δa is the refraction angle measurement error, and the superscript T represents the transpose operation on a vector or a matrix.

[0086] It is assumed that the spacecraft can observe the starlight refraction angles of m celestial bodies. Similarly, based on the starlight refraction navigation system solution equation, the second measurement equation of the spectrum redshift / starlight refraction combined navigation system is constructed, which is specifically:

[0087]

[0088] where Z a is the celestial body starlight refraction angle measurement vector, H a () is the celestial body starlight refraction angle measurement function, Δa is the celestial body starlight refraction angle measurement error vector, a1,…,a m denotes the celestial body starlight refraction angle of m celestial bodies, Δa1,…,Δa mh a1 (X),…,h an (X) represents the measurement function of the starlight refraction angle of m celestial bodies.

[0089] Discretization of formula (9) can obtain:

[0090] Z a，k =H a，k (X k )+v a，k (10)

[0091] In the formula, H a,k () represents the measurement function of the starlight refraction angle of celestial bodies at time k after discretization, Z a,k represents the measurement of the starlight refraction angle of celestial bodies at time k, v a,k =Δa k represents the measurement error of the starlight refraction angle of celestial bodies at time k after discretization.

[0092] S2, based on the mathematical model, a distributed spectral redshift / starlight refraction combined navigation system is constructed; based on the state equation and the first measurement equation, a spectral redshift navigation subsystem is constructed; based on the state equation and the second measurement equation, a starlight refraction subsystem is constructed.

[0093] S3, using a federated filtering framework, the distributed spectral redshift / starlight refraction combined navigation system is iterated with respect to adaptive information factors for information fusion, so as to realize navigation estimation of the distributed spectral redshift / starlight refraction combined navigation system; the federated filtering framework includes a master filter, a first sub-filter and a second sub-filter, the master filter adopts a federated filter; the first sub-filter and the second sub-filter both adopt a cubature Kalman filter;

[0094] S31, the first sub-filter is used to perform local state estimation on the spectral redshift navigation subsystem to obtain a local state estimation value of the spectral redshift navigation subsystem; the second sub-filter is used to perform local state estimation on the starlight refraction subsystem to obtain a local state estimation value of the starlight refraction subsystem;

[0095] Firstly, the state prediction of the spectral redshift navigation subsystem at time k is calculated as:

[0096]

[0097] wherein w r,i is the weight of the spectral redshift navigation subsystem state cubature point, x r,i,k|k-1 is the i th spectral redshift navigation subsystem state prediction cubature point, η r,i,k-1 is the i th spectral redshift navigation subsystem state cubature point at time k-1, which can be expressed as:

[0098]

[0099] where X k-1 is the global state estimate of the combined spectral redshift / starlight refraction navigation system at time k-1, P r,k-1 is the local state covariance matrix of the spectral redshift navigation subsystem at time k-1, ξ i is the i-th column of ξ n×2n , and ξ n×2n is the initial volume point selected according to the volume rule.

[0100] Then, the measurement volume point is calculated as:

[0101]

[0102] where Z is the measurement volume point of the spectral redshift navigation subsystem, P r,k|k-1 is the one-step prediction of the local state covariance matrix of the spectral redshift navigation subsystem, which is given by:

[0103]

[0104] where Q r,k is the process noise covariance matrix in the filter of the spectral redshift navigation subsystem at time k.

[0105] Further, the measurement prediction point of the spectral redshift navigation subsystem is given by:

[0106]

[0107] where Z r,k|k-1 is the spectral redshift measurement prediction at time k-1, and z r,i,k|k-1 is the i-th spectral redshift measurement prediction volume point.

[0108] Then, we have:

[0109]

[0110] where R is the measurement covariance matrix in the sub-filter of the spectral redshift navigation subsystem, and is the local state-measurement covariance matrix of the spectral redshift navigation subsystem.

[0111] Further, the filter gain of the spectral redshift navigation subsystem filter is given by:

[0112]

[0113] Finally, the local state estimate and its covariance matrix of the spectral redshift navigation subsystem are given by:

[0114]

[0115] wherein, P is the local state covariance matrix of the spectral redshift navigation subsystem. r,k P is the local state covariance matrix of the spectral redshift navigation subsystem.

[0116] Similar to the spectral redshift navigation subsystem, the starlight refraction navigation subsystem mainly utilizes a cubature Kalman filter as a sub-filter of the spectral redshift navigation subsystem to estimate the local state of the starlight refraction navigation subsystem based on the second measurement equation, the state equation and the related parameters, and the specific process is similar to that of the spectral redshift navigation subsystem, as follows:

[0117] First, the state prediction of the starlight refraction navigation subsystem at time k is calculated as:

[0118]

[0119] wherein, w a,i is the weight of the state cubature point of the starlight refraction navigation subsystem, x a,i,k|k-1 is the i-th state prediction cubature point of the starlight refraction navigation subsystem, and η a,i,k-1 is the i-th state cubature point of the starlight refraction navigation subsystem at time k, which is expressed as:

[0120]

[0121] wherein, P a,k-1 is the local state covariance matrix of the starlight refraction navigation subsystem at time k-1.

[0122] Then, the measurement cubature point is calculated as:

[0123]

[0124] wherein, is the measurement cubature point of the starlight refraction navigation subsystem, and P a,k|k-1 is the one-step prediction of the local state covariance matrix of the starlight refraction navigation subsystem, which is specifically:

[0125]

[0126] wherein, Q a,k is the process noise covariance matrix in the filter of the starlight refraction navigation subsystem at time k.

[0127] Further, the measurement prediction point of the starlight refraction navigation subsystem is:

[0128]

[0129] wherein, Z a,k|k-1is the starlight refraction angle measurement prediction point at k-1 moment, z a,i,k|k-1 is the starlight refraction angle measurement prediction volume point of the i th. Then, the following can be obtained:

[0130]

[0131] wherein, is the measurement covariance matrix in the starlight refraction navigation subsystem sub-filter, is the state-measurement covariance matrix in the starlight refraction navigation subsystem sub-filter.

[0132] Further, the starlight refraction navigation subsystem sub-filter filtering gain can be obtained from formula (26) and formula (27) as follows:

[0133]

[0134] Finally, the local state estimation of the starlight refraction navigation subsystem and its covariance matrix can be obtained as follows:

[0135]

[0136] wherein, is the local state estimation of the starlight refraction navigation subsystem, P a,k is the local state covariance matrix of the starlight refraction navigation subsystem.

[0137] S32, information fusion is performed on the local state estimation value of the spectral redshift navigation subsystem and the local state estimation value of the starlight refraction navigation subsystem through the main filter to obtain the global state estimation value of the distributed spectral redshift / starlight refraction combined navigation system;

[0138] The local states of the starlight refraction navigation subsystem and the spectral redshift navigation subsystem are fused through the information fusion formula in the federated filter architecture, and the specific process is as follows:

[0139]

[0140] wherein, is the global state estimation of the spectral redshift / starlight refraction combined navigation system, P k is the global state covariance matrix of the spectral redshift / starlight refraction combined navigation system.

[0141] S33, based on the local state estimation value of the spectral redshift navigation subsystem, the local state estimation value of the starlight refraction navigation subsystem and the global state estimation value, an adaptive information factor is constructed combining the probability density function and the Bayesian estimation principle, the first sub-filter and the second sub-filter are reset based on the adaptive information factor, and steps S31-S33 are repeatedly executed until the navigation is completed.

[0142] For adaptive allocation of information, the adaptive information factor based on the probability density function is designed as follows:

[0143] According to the Bayesian estimation principle, we have:

[0144]

[0145] where s represents the spectrum redshift navigation subsystem or the starlight refraction navigation subsystem, X k is the actual output of the navigation state quantity at time k, is the probability density of the local state estimation of the s navigation subsystem, is the conditional probability density of the local state estimation of the s navigation subsystem when the output of the navigation state quantity at time k is known, and

[0146]

[0147] According to the definition of the probability density function, when the conditional probability density corresponding to the local state estimation of the corresponding sub-filter of the navigation subsystem is larger, the local state estimation of the corresponding sub-filter of the navigation subsystem is closer to the output of the navigation state quantity, and the related information of the navigation state contained is more. Therefore, based on the conditional probability density of formula (34), the adaptive information factor can be constructed as follows:

[0148] Let the output of the navigation state quantity at time k be the global state estimation of the main filter:

[0149]

[0150] Assuming that all state estimations and measurements of the navigation system are subject to Gaussian distribution, we have:

[0151]

[0152] From formula (33), formula (36) and formula (37), the adaptive information factor is:

[0153]

[0154] where is the adaptive information factor corresponding to the s navigation subsystem.

[0155] Based on the probability density adaptive information factor, the adaptive reset of the sub-filter of the navigation subsystem can be performed, and the accuracy and reliability of the navigation system are further improved. The specific working steps are as follows:

[0156]

[0157] As shown in formula (26) to formula (29), the information allocation factor Instead of a fixed value, the probability density of the local state estimate and the global state estimate is adaptively adjusted according to the change.

[0158] Based on the same inventive concept, an embodiment of the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the distributed spectrum redshift / starlight refraction combined navigation method when executing the computer program. The memory can include an internal memory such as a high-speed random memory, and can also include a non-volatile memory such as at least one disk memory. The processor, network interface, and memory are connected to each other through an internal bus, which can be an industry standard architecture bus, a peripheral component interconnect standard bus, an extended industry standard architecture bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs, and specifically, the programs can include program codes, and the program codes include computer operation instructions. The memory can include an internal memory and a non-volatile memory, and provide instructions and data to the processor.

[0159] Based on the same inventive concept, an embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the distributed spectrum redshift / starlight refraction combined navigation method. Specifically, the computer readable storage medium includes but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory can include a RAM (Random Access Memory) and / or a cache memory, etc. The non-volatile memory can include a ROM (Read-Only Memory), a hard disk, a flash memory, an optical disc, a magnetic disc, etc.

[0160] Based on the same inventive concept, an embodiment of the present application provides a computer program product, which comprises a computer program stored on a computer readable storage medium, and the computer program comprises program instructions, and when the program instructions are executed by a computer device, the computer device executes the steps of the above-mentioned distributed spectrum redshift / starlight refraction combined navigation method.

[0161] Those skilled in the art will appreciate that embodiments of the present application can be readily used as software, firmware, and / or hardware implementations. Embodiments of the present application can also be implemented more tangibly, in, for example, a programmable control device or application specific computer hardware. As used herein, a "computer" or "computer device" or "computer processor" or "processor" can include any processor-based or microprocessor-based system including systems using microcontrollers, reduced instruction set computers (RISC), ASICs, logic circuits, and / or any other circuit or processor capable of executing the

[0162] The present application is described in reference to the flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processing device or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams block or blocks. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams block or blocks. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams block or blocks.

[0163] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the functions specified in the flowchart illustrations and / or block diagrams block or blocks. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams block or blocks. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams block or blocks.

[0164] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart illustrations and / or block diagrams block or blocks. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams block or blocks. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams block or blocks.

[0165] Finally, it should be noted that the above examples are only one or more specific forms of the present application, and their purpose is to clearly illustrate the concept, principle and application of the present application through specific examples, and are not intended to limit the scope of protection of the present application to these specific examples. In fact, the true value of the present application lies in its proposed technical ideas and innovative points, not in its forms or means of implementation.

[0166] For those skilled in the art, after reading and understanding the technical solutions of the present application, they have the ability to make various forms of changes, modifications or equivalent replacements to the specific embodiments of the application based on their own professional knowledge and skills. These changes may include but are not limited to adjusting the value range of technical parameters, optimizing the algorithm process to improve efficiency, replacing part of the technical components to achieve better compatibility or reduce cost, etc. As long as the technical solutions after these changes still maintain the technical features required by the original application, that is, still can realize the core function and effect of the present application, these changes should be considered as falling within the scope of protection of the claims of the present application.

[0167] In addition, with the continuous progress and development of technology, new technical means and methods are emerging, which also provides a broad space for the further improvement and perfection of the present application. Therefore, the scope of protection of the present application should also include those reasonable foreseeable improvements and extensions based on the existing technology, as long as these improvements and extensions do not deviate from the basic principles and core concept of the present application, they should be considered as the equivalent of the present application, and also be protected by the patent right.

Claims

1. A distributed spectral redshift / Starlight refraction combined navigation method, characterized in that, The method comprises the following steps: S1, constructing a mathematical model of a spectral redshift / starlight refraction combined navigation system; S2, constructing a distributed spectral redshift / starlight refraction combined navigation system based on the mathematical model; S3, performing information fusion on the distributed spectral redshift / starlight refraction combined navigation system about adaptive information factor iteration by using a federal filter framework, and realizing navigation estimation of the distributed spectral redshift / starlight refraction combined navigation system; the federal filter framework comprises a main filter, a first sub-filter and a second sub-filter; The information fusion about adaptive information factor iteration specifically comprises the following steps: S31, performing local state estimation on the spectral redshift navigation subsystem by the first sub-filter to obtain a local state estimation value of the spectral redshift navigation subsystem, and performing local state estimation on the starlight refraction navigation subsystem by the second sub-filter to obtain a local state estimation value of the starlight refraction navigation subsystem; S32, performing information fusion on the local state estimation value of the spectral redshift navigation subsystem and the local state estimation value of the starlight refraction navigation subsystem by the main filter to obtain a global state estimation value of the distributed spectral redshift / starlight refraction combined navigation system; S33, constructing an adaptive information factor based on the local state estimation value of the spectral redshift navigation subsystem, the local state estimation value of the starlight refraction navigation subsystem and the global state estimation value, combining a probability density function and a Bayesian estimation principle, resetting the first sub-filter and the second sub-filter based on the adaptive information factor, and repeatedly executing steps S31 to S33 until navigation is completed.

2. The method according to claim 1, wherein, S1 specifically comprises the following steps: Based on an orbit dynamics equation, a state equation of the spectral redshift / starlight refraction combined navigation system is constructed; based on a spectral redshift positioning navigation system solving equation, a first measurement equation of the spectral redshift / starlight refraction combined navigation system is constructed; and based on a starlight refraction navigation system solving equation, a second measurement equation of the spectral redshift / starlight refraction combined navigation system is constructed.

3. The distributed spectral redshift / Starlight refraction combined navigation method according to claim 2, characterized in that, S2 specifically comprises the following steps: based on the state equation and the first measurement equation, a spectral redshift navigation subsystem is constructed; and based on the state equation and the second measurement equation, a starlight refraction navigation subsystem is constructed.

4. The distributed spectral redshift / Starlight refraction combined navigation method according to claim 3, characterized in that, The main filter adopts a federal filter; and the first sub-filter and the second sub-filter both adopt a cubature Kalman filter.

5. A distributed spectral red-shift / starlight refraction combined navigation system, characterized in that, The method comprises the following steps: A first module is configured to construct a mathematical model of a spectral redshift / starlight refraction combined navigation system; A second module is configured to construct a distributed spectral redshift / starlight refraction combined navigation system based on the mathematical model; A third module is configured to perform information fusion on the distributed spectral redshift / starlight refraction combined navigation system about adaptive information factor iteration by using a federal filter framework, and realize navigation estimation of the distributed spectral redshift / starlight refraction combined navigation system; the federal filter framework comprises a main filter, a first sub-filter and a second sub-filter; The information fusion about adaptive information factor iteration specifically comprises the following steps: S31, performing local state estimation on the spectral redshift navigation subsystem by a first sub-filter to obtain a local state estimation value of the spectral redshift navigation subsystem, and performing local state estimation on the stellar light refraction navigation subsystem by a second sub-filter to obtain a local state estimation value of the stellar light refraction navigation subsystem; S32, performing information fusion on the local state estimation value of the spectral redshift navigation subsystem and the local state estimation value of the stellar light refraction navigation subsystem by a main filter to obtain a global state estimation value of the distributed spectral redshift / stellar light refraction combined navigation system; S33, based on the local state estimation value of the spectral redshift navigation subsystem, the local state estimation value of the stellar light refraction navigation subsystem and the global state estimation value, combining a probability density function and a Bayesian estimation principle to construct an adaptive information factor, resetting the first sub-filter and the second sub-filter based on the adaptive information factor, and repeatedly executing steps S31-S33 until the navigation ends. 6.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-5 when the computer program is executed by the processor. The processor implements the steps of the distributed spectral redshift / stellar light refraction combined navigation method according to any one of claims 1-4 when executing the computer program.

7. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by the processor, implements the steps of the distributed spectral redshift / stellar light refraction combined navigation method according to any one of claims 1-4.

8. A computer program product comprising a computer program, characterized in that, The computer program, when executed by the processor, implements the steps of the distributed spectral redshift / stellar light refraction combined navigation method according to any one of claims 1-4.

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