Parameter assignment method for relative navigation system of spacecraft

Abstract

A parameter assignment method for a relative navigation system of a spacecraft comprises the following steps: firstly, converting a sight vector measurement value of satellite-borne tracking and pointing equipment into a three-axis relative position under a Cartesian coordinate system; then, calculating a three-axis relative position measurement noise variance of the original measurement noise of the tracking and pointing equipment under a Cartesian coordinate system after coordinate transformation and a covariance among the three-axis relative position measurement noise by using a high-precision simplified expression; and finally, endowing the calculated converted measurement noise variance and covariance information to a relative navigation system so as to complete parameter assignment. The specific subitem in the noise covariance matrix analytic expression is subjected to Taylor expansion and simplification, the calculation complexity is remarkably reduced, meanwhile, the error generated by the noise is limited to be a minimum value, the relative navigation system accurately describes the noise characteristics, and meanwhile, the processing complexity is reduced.

Description

Technical Field

[0001] This invention relates to a parameter assignment method for a spacecraft relative navigation system, belonging to the field of relative navigation technology for space rendezvous and docking missions. Background Technology

[0002] In recent years, the demand for spacecraft to perform on-orbit servicing missions such as debris removal, on-orbit maintenance, and cargo resupply has increased dramatically. Obtaining the relative state between the spacecraft and the servicing target using relative navigation technology is a prerequisite for completing on-orbit servicing missions.

[0003] When the relative distance between the spacecraft and the target is on the order of kilometers to tens of meters, the observed object is approximated as a point target. The onboard tracking and aiming equipment outputs the line-of-sight vector information of the target point relative to the origin of the measurement coordinate system in polar coordinates, including the line-of-sight distance, elevation angle, and azimuth angle. The line-of-sight vector has a non-linear mapping relationship with the relative position state of the two satellites. To facilitate the calculation by the navigation system, the polar coordinates of the line-of-sight vector are usually converted into the three-axis relative position in the Cartesian measurement coordinate system based on spatial geometry. This converted measurement information is then introduced into the relative navigation system, and the filtered estimate of the relative position of the two satellites is calculated by a linear Kalman filter. This relative orbital state estimation method based on converted measurements avoids the use of non-linear filters and the calculation of the Jacobian matrix, greatly saving onboard computing resources.

[0004] However, during the conversion of the line-of-sight vector to the relative position, the noise from the originally independent observations becomes coupled. The noise characteristics of the converted measurement information are no longer solely determined by the characteristics of the tracking and aiming equipment and the internal algorithm of a single machine, but change with the position of the target point within the tracking and aiming field of view. Because the noise characteristics of the converted measurement information are influenced by a combination of factors, the analytical expression of the parameter used to describe the noise characteristics of the measurement information in the relative navigation system—the measurement noise covariance matrix—is extremely complex. Current spaceborne relative navigation systems typically assume that the noise characteristics of the converted measurement information are consistent with the noise characteristics of the line-of-sight distance in the original measurement information. This assumption leads to inaccurate assignment of the measurement noise covariance matrix, significantly affecting the error convergence speed and state estimation accuracy of the navigation system. To address the impact of inaccurate assignment of the noise covariance matrix on the state estimation accuracy of the relative navigation system, existing methods mainly improve the theoretical accuracy of the assignment method. However, such techniques require extremely high computational costs, which is not conducive to real-time calculations by spaceborne computers with limited computing resources.

[0005] Therefore, there is an urgent need to improve the method for assigning the measurement noise covariance matrix of the converted measurement information, so that it can accurately describe the noise characteristics of the converted measurement information, while having a concise expression form and low computational complexity, which is convenient for real-time calculation by the onboard computer. Summary of the Invention

[0006] The technical problem solved by this invention is to overcome the shortcomings of existing technologies and provide a parameter assignment method for a spacecraft relative navigation system. This method simplifies the analytical expression of the noise covariance matrix by performing Taylor expansion on specific terms, significantly reducing computational complexity while limiting the error caused by noise to a minimum. This solves the problem that existing methods struggle to accurately describe the noise characteristics of converted measurement information while maintaining low complexity.

[0007] The technical solution of this invention is:

[0008] A method for assigning parameters to a spacecraft relative to a navigation system, comprising the following steps:

[0009] (1) Obtain the line-of-sight distance measurement of the target point output by the tracking device in the measurement coordinate system. Elevation and elevation measurements and azimuth measurement value Simultaneously, the standard deviation of the measurement noise of the line-of-sight distance measurement value is obtained. Standard deviation of measurement noise of elevation and depression angle measurements Measurement noise standard deviation of azimuth angle measurement values

[0010] (2) The line-of-sight distance measurement of the target point output by the tracking device Elevation and elevation measurements and azimuth measurement value This is converted into the target's three-axis position relative to the aircraft in a Cartesian measurement coordinate system; the three-axis position includes the target's X-axis position in the measurement coordinate system. Y-axis position and Z-axis position

[0011] (3) Calculate the target's X-axis position relative to the aircraft using Taylor expansion. High-precision simplified variance Y-axis position High-precision simplified variance and Z-axis position High-precision simplified variance as well as and High-precision simplified covariance and High-precision simplified covariance and High-precision simplified covariance

[0012] (4) Position the target relative to the X-axis of the aircraft High-precision simplified variance Y-axis position High-precision simplified variance and Z-axis position High-precision simplified variance Reconstruction is performed separately, and the corresponding variance r of the reconstructed X-axis position is obtained. 11 , reconstruct the variance of the Y-axis position r 22 and the variance of the reconstructed Z-axis position r 33 ;Will and High-precision simplified covariance and High-precision simplified covariance and High-precision simplified covariance Reconstructing them separately yields the corresponding reconstructed XY covariance r. 12 Reconstructing the XZ covariance r 13 And reconstructed YZ covariance r 23 ;

[0013] (5) Using the reconstructed X-axis position variance r 11 , reconstruct the variance of the Y-axis position r 22 , reconstruct the variance of the Z-axis position r 33 Reconstructing the XY covariance r 12 Reconstructing the XZ covariance r 13 And reconstructed YZ covariance r 23 Construct the measurement noise covariance matrix R;

[0014] (6) Input the measurement noise covariance matrix R into the relative navigation system to complete the parameter assignment of the relative navigation system.

[0015] Furthermore, the specific steps in step (1) for obtaining the line-of-sight distance measurement, elevation angle measurement, and azimuth angle measurement of the target point output by the tracking and aiming device in the measurement coordinate system are as follows:

[0016] (1.1) Establish the measurement coordinate system of the tracking and aiming device. Define the X-axis of the measurement coordinate system as perpendicular to the detection plane of the tracking and aiming device and pointing to the direction of the aircraft's movement. The Y-axis, Z-axis and X-axis of the measurement coordinate system satisfy the right-hand rule.

[0017] (1.2) Obtain the line-of-sight distance measurement value of the target point output by the aiming device in the measurement coordinate system. Elevation and elevation measurements and azimuth measurement value The expressions are respectively

[0018]

[0019] in, and These represent the noise levels in the line-of-sight measurement, elevation angle measurement, and azimuth angle measurement of the tracking and aiming device, respectively; ρ, α, and β represent the true line-of-sight distance, true elevation angle, and true azimuth angle between the target point tracked by the tracking and aiming device and the established measurement coordinate system, respectively. The formulas for calculating ρ, α, and β are as follows:

[0020]

[0021] Where x, y, and z are the X-axis, Y-axis, and Z-axis components of the actual relative position between the spacecraft and the target point in the measurement coordinate system, respectively.

[0022] In step (1), obtaining the standard deviation of the measurement noise corresponding to the line-of-sight distance measurement, elevation angle measurement, and azimuth angle measurement is specifically as follows: calculate the line-of-sight distance measurement noise of the tracking device respectively. Elevation / Difference Measurement Noise Azimuth measurement noise The standard deviation of the measurement noise corresponding to the line-of-sight distance measurement value. Standard deviation of measurement noise of elevation and depression angle measurements Measurement noise standard deviation of azimuth angle measurement values

[0023] Furthermore, in step (2), the line-of-sight distance measurement value of the target point output by the aiming device is... Elevation and elevation measurements and azimuth measurement value The formula for converting the target's position relative to the aircraft's three axes in a Cartesian coordinate system is as follows:

[0024]

[0025] Furthermore, in step (3), the target's X-axis position relative to the aircraft is calculated. High-precision simplified variance Y-axis position High-precision simplified variance and Z-axis position High-precision simplified variance The process is as follows:

[0026] (3.1) Calculate the target's position relative to the aircraft's X-axis. High-precision simplified variance The calculation process is as follows:

[0027] The first step is to calculate the target's position relative to the aircraft's X-axis. variance The calculation formula is:

[0028]

[0029] Where ρ, α, and β are the true line-of-sight distance, true elevation angle, and true azimuth angle between the target point and the established measurement coordinate system, respectively. In and The calculation formulas are as follows:

[0030]

[0031] The second step is to In and The Taylor expansion simplification is performed as follows:

[0032]

[0033] The third step is to and Substituting the Taylor simplification result into In the middle, completed Taylor expansion simplification;

[0034] The fourth step is to simplify the result after completing the Taylor expansion. Contains and The subexpression is approximated and simplified, specifically as follows:

[0035]

[0036] Fifth step, and Substituting the approximate simplified result into the result after Taylor expansion and simplification Thus, the target's X-axis position relative to the aircraft is obtained. High-precision simplified variance The formula is

[0037]

[0038] (3.2) Calculate the target's position relative to the aircraft's Y-axis. High-precision simplified variance The calculation process is as follows:

[0039] The first step is to calculate the target's Y-axis position relative to the aircraft. variance The calculation formula is:

[0040]

[0041] In and The calculation formulas are as follows:

[0042]

[0043] The second step is to In and The Taylor expansion simplification is performed as follows:

[0044]

[0045] The third step is to and Substituting the Taylor simplification result into In the middle, completed Taylor expansion simplification;

[0046] The fourth step is to simplify the result after completing the Taylor expansion. Contains and The subexpression is approximated and simplified, specifically as follows:

[0047]

[0048] Fifth step, and Substituting the approximate simplified result into the result after Taylor expansion and simplification Thus, the target's Y-axis position relative to the aircraft is obtained. High-precision simplified variance The formula is

[0049]

[0050] (3.3) Calculate the Z-axis position of the target relative to the aircraft High-precision simplified variance The calculation process is as follows:

[0051] The first step is to calculate the target's Z-axis position relative to the aircraft. variance The calculation formula is:

[0052]

[0053] in, In and The calculation formulas are as follows:

[0054]

[0055] The second step is to In and The Taylor expansion simplification is performed as follows:

[0056]

[0057] The third step is to and Substituting the Taylor simplification result into Thus, the Z-axis position relative to the aircraft is obtained. High-precision simplified variance The formula is

[0058]

[0059] Furthermore, in step (3), the calculation and High-precision simplified covariance and High-precision simplified covariance and High-precision simplified covariance The specific steps are as follows:

[0060] (3.4) Calculation and High-precision simplified covariance The calculation process is as follows

[0061] Step 1, Calculation and covariance The calculation formula is

[0062]

[0063] In and The calculation formulas are as follows:

[0064]

[0065] The second step is to In and The Taylor expansion simplification is performed as follows:

[0066]

[0067] The third step is to and Substituting the Taylor simplification result into In the middle, we get and High-precision simplified covariance The formula is

[0068]

[0069] (3.5) Calculation and High-precision simplified covariance The calculation process is as follows

[0070] Step 1, Calculation and covariance The calculation formula is

[0071]

[0072] In and The calculation formulas are as follows:

[0073]

[0074] The second step is to In and The Taylor expansion simplification is performed as follows:

[0075]

[0076] The third step is to and Substituting the Taylor simplification result into In the middle, we get and High-precision simplified covariance The formula is

[0077]

[0078] (3.6) Calculation and High-precision simplified covariance The calculation process is as follows

[0079] Step 1, Calculation and covariance The calculation formula is

[0080]

[0081] In and The calculation formulas are as follows:

[0082]

[0083] The second step is to In and The Taylor expansion simplification is performed as follows:

[0084]

[0085] The third step is to and Substituting the Taylor simplification result into In the middle, we get and High-precision simplified covariance The formula is

[0086]

[0087] In step (4), the variance r of the reconstructed X-axis position is obtained. 11 , reconstruct the variance of the Y-axis position r 22 and the variance of the reconstructed Z-axis position r 33 The process is as follows:

[0088] (4.1) Position the target relative to the X-axis of the aircraft High-precision simplified variance Y-axis position High-precision simplified variance and Z-axis position High-precision simplified variance The sub-items containing the true line-of-sight distance ρ, true elevation angle α, and true azimuth angle β are approximated and replaced to obtain the replaced X high-precision simplified variance. Replace Y with high-precision simplified variance and replacement Z high-precision simplified variance The approximate replacement method is as follows:

[0089]

[0090] Soon In α and β are respectively replaced with and Obtain the high-precision simplified variance of the replacement X. The expression is:

[0091]

[0092] Will In α and β are respectively replaced with and Obtain the high-precision simplified variance of the replaced Y. The expression is:

[0093]

[0094] Will In Replace α with and Obtain the high-precision simplified variance of the replacement Z. The expression is:

[0095]

[0096] (4.2) Define process parameters c4 = 2 - c3 And c9 = 1 - c8;

[0097] (4.3) Substitute c1, c2, c3, c5, and c8 into the high-precision simplified variance of the replacement X. Replace The corresponding formula sub-item is used to obtain the variance r of the reconstructed X-axis position. 11 The calculation formula is:

[0098]

[0099] (4.4) Substitute c1, c2, c4, c5, and c9 into the high-precision simplified variance of the replacement Y. Replace The corresponding formula sub-item is used to obtain the variance r of the reconstructed Y-axis position. 11 The calculation formula is:

[0100]

[0101] (4.5) Substitute c1, c7, and c6 into the high-precision simplified variance of the replacement Z. Replace The corresponding formula sub-item is used to obtain the variance r of the reconstructed Z-axis position. 33 The calculation formula is:

[0102]

[0103] Furthermore, in step (4), the XY covariance r is reconstructed. 12 Reconstructing the XZ covariance r 13 And reconstructed YZ covariance r 23 The process is as follows:

[0104] (4.6) will and High-precision simplified covariance and High-precision simplified covariance and High-precision simplified covariance The sub-items containing the true line-of-sight distance ρ, the true elevation angle α, and the true azimuth angle β are approximated and replaced to obtain the replaced XY high-precision simplified variances. Replace XZ high-precision simplified variance and replace YZ high-precision simplified variance The approximate replacement method is as follows:

[0105]

[0106] Soon ρ in 2 α and β are replaced with and Obtain the high-precision simplified variance of XY replacement. The expression is:

[0107]

[0108] Soon ρ in 2 α and β are replaced with and Obtain the replacement XZ high-precision simplified variance The expression is:

[0109]

[0110] Soon ρ in 2 α and β are replaced with and Obtain the replacement XZ high-precision simplified variance The expression is:

[0111]

[0112] (4.7) Define process parameter c 10 =c8-c9、 c 13 =2c 11 c 12 , and

[0113] (4.8) Set c1, c2, c 10 c 13 and c 15 Substitute into the high-precision simplified variance of XY replacement Replace The corresponding formula sub-terms are then used to obtain the reconstructed XY covariance r. 12 The calculation formula is:

[0114]

[0115] (4.9) c 11 and c 14 Substitute into the high-precision simplified variance of XZ Replace The corresponding formula sub-terms are then used to obtain the reconstructed XZ covariance r. 13 The calculation formula is:

[0116]

[0117] (4.10) c 12 and c 14 Substitute into the high-precision simplified variance of YZ Replace The corresponding formula sub-terms are then used to obtain the reconstructed YZ covariance r. 23 The calculation formula is:

[0118]

[0119] Furthermore, in step (5), the measurement noise covariance matrix R is constructed as follows:

[0120]

[0121] Secondly, the present invention also proposes a computer program product, characterized in that the computer program product includes a computer program, which, when executed by a processor, implements the steps of the parameter assignment method for a spacecraft relative navigation system as described in the claims above.

[0122] Thirdly, the present invention also proposes a processor, characterized in that the processor is used to run a program, wherein the program executes a parameter assignment method for a spacecraft relative navigation system as described above.

[0123] The beneficial effects of this invention compared to the prior art are:

[0124] (1) This invention simplifies the specific sub-items related to the noise variance of elevation angle and azimuth angle measurement by Taylor expansion in the analytical expression of the noise covariance matrix. This significantly reduces the computational complexity while limiting the error generated by noise to a minimum value, so that the relative navigation system can accurately describe the noise characteristics while reducing the complexity of the processing.

[0125] (2) This invention further isomorphizes the analytical expression of the noise covariance matrix after Taylor expansion. Each time the analytical expression of the noise covariance matrix is ​​performed, only the corresponding reconstruction term needs to be calculated, thereby reducing the repeated calculation of some sub-terms in the original analytical expression of the noise covariance matrix and further reducing the computational complexity. Attached Figure Description

[0126] Figure 1 This is a flowchart of a parameter assignment method for a spacecraft relative navigation system according to the present invention;

[0127] Figure 2 This is a schematic diagram illustrating the working condition of the parameter assignment method for a spacecraft relative navigation system according to the present invention when handling rendezvous and docking missions.

[0128] Figure 3 This is a schematic diagram of the azimuth and elevation angle polarity in a parameter assignment method for a spacecraft relative navigation system according to the present invention;

[0129] Figure 4 This is a schematic diagram of the conversion measurement noise change in a parameter assignment method for a spacecraft relative navigation system according to the present invention;

[0130] Figure 5 This is a comparison diagram of the relative navigation system filtering error in the parameter assignment method of a spacecraft relative navigation system of the present invention. Detailed Implementation

[0131] The specific embodiments of the present invention will now be described in further detail with reference to the accompanying drawings.

[0132] like Figure 1 As shown, this invention provides a method for assigning parameters of a spacecraft relative to a navigation system, the steps of which are as follows:

[0133] (1) Obtain the line-of-sight distance measurement of the target point output by the tracking device in the measurement coordinate system. Elevation and elevation measurements and azimuth measurement value Simultaneously, the standard deviation of the measurement noise of the line-of-sight distance measurement value is obtained. Standard deviation of measurement noise of elevation and depression angle measurements Measurement noise standard deviation of azimuth angle measurement values The tracking and aiming equipment is mounted on the spacecraft;

[0134] The specific steps for obtaining the line-of-sight distance measurement, elevation angle measurement, and azimuth angle measurement of the target point output by the tracking and aiming device in the measurement coordinate system in step (1) are as follows:

[0135] (1.1) Establish the measurement coordinate system of the tracking and aiming device. Define the X-axis of the measurement coordinate system as perpendicular to the detection plane of the tracking and aiming device and pointing to the direction of the aircraft's movement. The Y-axis, Z-axis and X-axis of the measurement coordinate system satisfy the right-hand rule.

[0136] (1.2) Obtain the line-of-sight distance measurement value of the target point output by the aiming device in the measurement coordinate system. Elevation and elevation measurements and azimuth measurement value The expressions are respectively

[0137]

[0138] in, and These represent the noise levels in the line-of-sight measurement, elevation angle measurement, and azimuth angle measurement of the tracking and aiming device, respectively; ρ, α, and β represent the true line-of-sight distance, true elevation angle, and true azimuth angle between the target point tracked by the tracking and aiming device and the established measurement coordinate system, respectively. The formulas for calculating ρ, α, and β are as follows:

[0139]

[0140] Where x, y, and z are the X-axis, Y-axis, and Z-axis components of the actual relative position between the spacecraft and the target point in the measurement coordinate system, respectively.

[0141] In step (1), obtaining the standard deviation of the measurement noise corresponding to the line-of-sight distance measurement, elevation angle measurement, and azimuth angle measurement is specifically as follows: calculate the line-of-sight distance measurement noise of the tracking device respectively. Elevation / Difference Measurement Noise Azimuth measurement noise The standard deviation of the measurement noise corresponding to the line-of-sight distance measurement value. Standard deviation of measurement noise of elevation and depression angle measurements Measurement noise standard deviation of azimuth angle measurement values

[0142] (2) Figure 3 As shown, the line-of-sight distance measurement of the target point output by the aiming device is displayed. Elevation and elevation measurements and azimuth measurement value This is converted to the target's three-axis position relative to the aircraft in a Cartesian measurement coordinate system; the three-axis position includes the target's X-axis position relative to the aircraft. Y-axis position and Z-axis position The conversion formula is:

[0143]

[0144] (3) Calculate the target's X-axis position relative to the aircraft using Taylor expansion. High-precision simplified variance Y-axis position High-precision simplified variance and Z-axis position High-precision simplified variance as well as and High-precision simplified covariance and High-precision simplified covariance and High-precision simplified covariance In actual docking conditions, the variation of measurement noise is as follows: Figure 4 As shown.

[0145] The specific process of expression evaluation is as follows:

[0146] (3.1) Calculate the target's position relative to the aircraft's X-axis. High-precision simplified variance The calculation process is as follows:

[0147] The first step is to calculate the target's position relative to the aircraft's X-axis. variance The calculation formula is:

[0148]

[0149] Where ρ, α, and β are the true line-of-sight distance, true elevation angle, and true azimuth angle between the target point and the established measurement coordinate system, respectively. In and The calculation formulas are as follows:

[0150]

[0151] The second step is to In and The Taylor expansion simplification is performed as follows:

[0152]

[0153] The third step is to and Substituting the Taylor simplification result into In the middle, completed Taylor expansion simplification;

[0154] The fourth step is to simplify the result after completing the Taylor expansion. Contains and The subexpression is approximated and simplified, specifically as follows:

[0155]

[0156] Fifth step, and Substituting the approximate simplified result into the result after Taylor expansion and simplification Thus, the target's X-axis position relative to the aircraft is obtained. High-precision simplified variance The formula is

[0157]

[0158] (3.2) Calculate the target's position relative to the aircraft's Y-axis. High-precision simplified variance The calculation process is as follows:

[0159] The first step is to calculate the target's Y-axis position relative to the aircraft. variance The calculation formula is:

[0160]

[0161] In and The calculation formulas are as follows:

[0162]

[0163] The second step is to In and The Taylor expansion simplification is performed as follows:

[0164]

[0165] The third step is to and Substituting the Taylor simplification result into In the middle, completed Taylor expansion simplification;

[0166] The fourth step is to simplify the result after completing the Taylor expansion. Contains and The subexpression is approximated and simplified, specifically as follows:

[0167]

[0168] Fifth step, and Substituting the approximate simplified result into the result after Taylor expansion and simplification Thus, the target's Y-axis position relative to the aircraft is obtained. High-precision simplified variance The formula is

[0169]

[0170] (3.3) Calculate the Z-axis position of the target relative to the aircraft High-precision simplified variance The calculation process is as follows:

[0171] The first step is to calculate the target's Z-axis position relative to the aircraft. variance The calculation formula is:

[0172]

[0173] in, In and The calculation formulas are as follows:

[0174]

[0175] The second step is to In and The Taylor expansion simplification is performed as follows:

[0176]

[0177] The third step is to and Substituting the Taylor simplification result into Thus, the Z-axis position relative to the aircraft is obtained. High-precision simplified variance The formula is

[0178]

[0179] (3.4) Calculation and High-precision simplified covariance The calculation process is as follows

[0180] Step 1, Calculation and covariance The calculation formula is

[0181]

[0182] In and The calculation formulas are as follows:

[0183]

[0184] The second step is to In and The Taylor expansion simplification is performed as follows:

[0185]

[0186] The third step is to and Substituting the Taylor simplification result into In the middle, we get and High-precision simplified covariance The formula is

[0187]

[0188] (3.5) Calculation and High-precision simplified covariance The calculation process is as follows

[0189] Step 1, Calculation and covariance The calculation formula is

[0190]

[0191] In and The calculation formulas are as follows:

[0192]

[0193] The second step is to In and The Taylor expansion simplification is performed as follows:

[0194]

[0195] The third step is to and Substituting the Taylor simplification result into In the middle, we get and High-precision simplified covariance The formula is

[0196]

[0197] (3.6) Calculation and High-precision simplified covariance The calculation process is as follows

[0198] Step 1, Calculation and covariance The calculation formula is

[0199]

[0200] In and The calculation formulas are as follows:

[0201]

[0202] The second step is to In and The Taylor expansion simplification is performed as follows:

[0203]

[0204] The third step is to and Substituting the Taylor simplification result into In the middle, we get and High-precision simplified covariance The formula is

[0205]

[0206] Based on step (3), this invention simplifies the specific sub-items related to the noise variance of elevation angle and azimuth angle measurement by Taylor expansion in the analytical expression of the noise covariance matrix. This significantly reduces the computational complexity while limiting the error generated by noise to a minimum value, enabling the relative navigation system to accurately describe the noise characteristics while reducing the complexity of the processing.

[0207] (4) Position the target relative to the X-axis of the aircraft High-precision simplified variance Y-axis position High-precision simplified variance and Z-axis position High-precision simplified variance Reconstruction is performed separately, and the corresponding variance r of the reconstructed X-axis position is obtained. 11 , reconstruct the variance of the Y-axis position r 22 and the variance of the reconstructed Z-axis position r 33 ;Will and High-precision simplified covariance and High-precision simplified covariance and High-precision simplified covariance Reconstructing them separately yields the corresponding reconstructed XY covariance r. 12 Reconstructing the XZ covariance r 13 And reconstructed YZ covariance r 23 ;

[0208] In step (4), the variance r of the reconstructed X-axis position is obtained. 11 , reconstruct the variance of the Y-axis position r 22 and the variance of the reconstructed Z-axis position r 33 The process is as follows:

[0209] (4.1) Position the target relative to the X-axis of the aircraft High-precision simplified variance Y-axis position High-precision simplified variance and Z-axis position High-precision simplified variance The sub-items containing the true line-of-sight distance ρ, true elevation angle α, and true azimuth angle β are approximated and replaced to obtain the replaced X high-precision simplified variance. Replace Y with high-precision simplified variance and replacement Z high-precision simplified variance The approximate replacement method is as follows:

[0210]

[0211] Soon In α and β are respectively replaced with and Obtain the high-precision simplified variance of the replacement X. The expression is:

[0212]

[0213] Will In α and β are respectively replaced with and Obtain the high-precision simplified variance of the replaced Y. The expression is:

[0214]

[0215] Will In Replace α with and Obtain the high-precision simplified variance of the replacement Z. The expression is:

[0216]

[0217] (4.2) Define process parameters c4 = 2 - c3 And c9 = 1 - c8;

[0218] (4.3) Substitute c1, c2, c3, c5, and c8 into the high-precision simplified variance of the replacement X. Replace The corresponding formula sub-item is used to obtain the variance r of the reconstructed X-axis position. 11 The calculation formula is:

[0219]

[0220] (4.4) Substitute c1, c2, c4, c5, and c9 into the high-precision simplified variance of the replacement Y. Replace The corresponding formula sub-item is used to obtain the variance r of the reconstructed Y-axis position. 11 The calculation formula is:

[0221]

[0222] (4.5) Substitute c1, c7, and c6 into the high-precision simplified variance of the replacement Z. Replace The corresponding formula sub-item is used to obtain the variance r of the reconstructed Z-axis position. 33 The calculation formula is:

[0223]

[0224] Furthermore, in step (4), the XY covariance r is reconstructed. 12 Reconstructing the XZ covariance r 13 And reconstructed YZ covariance r 23 The process is as follows:

[0225] (4.6) will and High-precision simplified covariance and High-precision simplified covariance and High-precision simplified covariance The sub-items containing the true line-of-sight distance ρ, the true elevation angle α, and the true azimuth angle β are approximated and replaced to obtain the replaced XY high-precision simplified variances. Replace XZ high-precision simplified variance and replace YZ high-precision simplified variance The approximate replacement method is as follows:

[0226]

[0227] Soon ρ in 2 α and β are replaced with and Obtain the high-precision simplified variance of XY replacement. The expression is:

[0228]

[0229] Soon ρ in 2 α and β are replaced with and Obtain the replacement XZ high-precision simplified variance The expression is:

[0230]

[0231] Soon ρ in 2 α and β are replaced with and Obtain the replacement XZ high-precision simplified variance The expression is:

[0232]

[0233] (4.7) Define process parameter c 10 =c8-c9、 c 13 =2c 11 c 12 , and

[0234] (4.8) Set c1, c2, c 10 c 13 and c 15 Substitute into the high-precision simplified variance of XY replacement Replace The corresponding formula sub-terms are then used to obtain the reconstructed XY covariance r. 12 The calculation formula is:

[0235]

[0236] (4.9) c 11 and c 14 Substitute into the high-precision simplified variance of XZ Replace The corresponding formula sub-terms are then used to obtain the reconstructed XZ covariance r. 13 The calculation formula is:

[0237]

[0238] (4.10) c 12 and c 14 Substitute into the high-precision simplified variance of YZ Replace The corresponding formula sub-terms are then used to obtain the reconstructed YZ covariance r. 23 The calculation formula is:

[0239]

[0240] Based on step (4), the present invention further isomorphizes the analytical expression of the noise covariance matrix after Taylor expansion and simplification. Each time the analytical expression of the noise covariance matrix is ​​performed, only the corresponding reconstruction term needs to be calculated, thereby reducing the repeated calculation of some sub-terms in the original analytical expression of the noise covariance matrix and further reducing the computational complexity.

[0241] (5) Using the reconstructed X-axis position variance r 11 , reconstruct the variance of the Y-axis position r 22 , reconstruct the variance of the Z-axis position r 33 Reconstructing the XY covariance r 12 Reconstructing the XZ covariance r 13 And reconstructed YZ covariance r 23 Construct the measurement noise covariance matrix R, with the specific expression as follows:

[0242]

[0243] (6) Input the measurement noise covariance matrix R into the relative navigation system to complete the parameter assignment of the relative navigation system; such as Figure 2 As shown, the relative navigation system completes the docking of the aircraft under the assigned parameters; during the docking process, the filter outputs the filtering result according to the assigned parameters as follows: Figure 5 As shown.

[0244] Secondly, the present invention also proposes a computer program product, characterized in that the computer program product includes a computer program, which, when executed by a processor, implements the steps of the parameter assignment method for a spacecraft relative navigation system as described in the claims above.

[0245] Thirdly, the present invention also proposes a processor, characterized in that the processor is used to run a program, wherein the program executes a parameter assignment method for a spacecraft relative navigation system as described above.

[0246] The parts of this invention not described in detail are common knowledge to those skilled in the art.

Claims

1. A method for assigning parameters to a spacecraft relative navigation system, characterized in that... The steps are as follows: (1) Obtain the line-of-sight distance measurement of the target point output by the tracking device in the measurement coordinate system. Elevation and elevation angle measurements and azimuth measurement value Simultaneously, the standard deviation of the measurement noise of the line-of-sight distance measurement value is obtained. Standard deviation of measurement noise of elevation angle measurements Measurement noise standard deviation of azimuth angle measurement values (2) The line-of-sight distance measurement of the target point output by the tracking device Elevation and elevation angle measurements and azimuth measurement value This is converted into the target's three-axis position relative to the aircraft in a Cartesian measurement coordinate system; the three-axis position includes the target's X-axis position in the measurement coordinate system. Y-axis position and Z-axis position (3) Calculate the target's position relative to the aircraft's X-axis using Taylor expansion. High-precision simplified variance Y-axis position High-precision simplified variance and Z-axis position High-precision simplified variance as well as and High-precision simplified covariance and High-precision simplified covariance and High-precision simplified covariance (4) Position the target relative to the X-axis of the aircraft High-precision simplified variance Y-axis position High-precision simplified variance and Z-axis position High-precision simplified variance Reconstruction is performed separately, and the corresponding variance r of the reconstructed X-axis position is obtained. 11 , reconstruct the variance of the Y-axis position r 22 and the variance of the reconstructed Z-axis position r 33 ;Will and High-precision simplified covariance and High-precision simplified covariance and High-precision simplified covariance Reconstructing them separately yields the corresponding reconstructed XY covariance r. 12 Reconstructing the XZ covariance r 13 And reconstructed YZ covariance r 23 ; (5) Using the reconstructed X-axis position variance r 11 , reconstruct the variance of the Y-axis position r 22 , reconstruct the variance of the Z-axis position r 33 Reconstructing the XY covariance r 12 Reconstructing the XZ covariance r 13 And reconstructed YZ covariance r 23 Construct the measurement noise covariance matrix R; (6) Input the measurement noise covariance matrix R into the relative navigation system to complete the parameter assignment of the relative navigation system.

2. The parameter assignment method for a spacecraft relative navigation system according to claim 1, characterized in that: The specific steps for obtaining the line-of-sight distance measurement, elevation angle measurement, and azimuth angle measurement of the target point output by the tracking and aiming device in the measurement coordinate system in step (1) are as follows: (1.1) Establish the measurement coordinate system of the tracking and aiming device. Define the X-axis of the measurement coordinate system as perpendicular to the detection plane of the tracking and aiming device and pointing to the direction of the aircraft's movement. The Y-axis, Z-axis and X-axis of the measurement coordinate system satisfy the right-hand rule. (1.2) Obtain the line-of-sight distance measurement value of the target point output by the aiming device in the measurement coordinate system. Elevation and elevation angle measurements and azimuth measurement value The expressions are respectively in, and These represent the noise levels in the line-of-sight measurement, elevation angle measurement, and azimuth angle measurement of the tracking and aiming device, respectively; ρ, α, and β represent the true line-of-sight distance, true elevation angle, and true azimuth angle between the target point tracked by the tracking and aiming device and the established measurement coordinate system, respectively. The formulas for calculating ρ, α, and β are as follows: Where x, y, and z are the X-axis, Y-axis, and Z-axis components of the actual relative position between the spacecraft and the target point in the measurement coordinate system, respectively. In step (1), obtaining the standard deviation of the measurement noise corresponding to the line-of-sight distance measurement, elevation angle measurement, and azimuth angle measurement is specifically as follows: calculate the line-of-sight distance measurement noise of the tracking device respectively. Elevation / Difference Measurement Noise Azimuth measurement noise The standard deviation, which corresponds to the measurement noise standard deviation of the line-of-sight distance measurement value. Standard deviation of measurement noise of elevation angle measurements Measurement noise standard deviation of azimuth angle measurement values 3. The parameter assignment method for a spacecraft relative navigation system according to claim 1, characterized in that: In step (2), the line-of-sight distance measurement of the target point output by the tracking device is... Elevation and elevation angle measurements and azimuth measurement value The formula for converting the target's position relative to the aircraft's three axes in a Cartesian coordinate system is as follows:

4. The parameter assignment method for a spacecraft relative navigation system according to claim 1, characterized in that: In step (3), the target's X-axis position relative to the aircraft is calculated. High-precision simplified variance Y-axis position High-precision simplified variance and Z-axis position High-precision simplified variance The process is as follows: (3.1) Calculate the target's position relative to the aircraft's X-axis. High-precision simplified variance The calculation process is as follows: The first step is to calculate the target's position relative to the aircraft's X-axis. variance The calculation formula is: Where ρ, α, and β are the true line-of-sight distance, true elevation angle, and true azimuth angle between the target point and the established measurement coordinate system, respectively. In and The calculation formulas are as follows: The second step is to In and The Taylor expansion simplification is performed as follows: The third step is to and Substituting the Taylor simplification result into In the middle, completed Taylor expansion simplification; The fourth step is to simplify the result after completing the Taylor expansion. Contains and The subexpression is approximated and simplified, specifically as follows: Fifth step, and Substituting the approximate simplified result into the result after Taylor expansion and simplification Thus, the target's X-axis position relative to the aircraft is obtained. High-precision simplified variance The formula is (3.2) Calculate the target's position relative to the aircraft's Y-axis. High-precision simplified variance The calculation process is as follows: The first step is to calculate the target's Y-axis position relative to the aircraft. variance The calculation formula is: In and The calculation formulas are as follows: The second step is to In and The Taylor expansion simplification is performed as follows: The third step is to and Substituting the Taylor simplification result into In the middle, completed Taylor expansion simplification; The fourth step is to simplify the result after completing the Taylor expansion. Contains and The subexpression is approximated and simplified, specifically as follows: Fifth step, and Substituting the approximate simplified result into the result after Taylor expansion and simplification Thus, the target's Y-axis position relative to the aircraft is obtained. High-precision simplified variance The formula is (3.3) Calculate the Z-axis position of the target relative to the aircraft High-precision simplified variance The calculation process is as follows: The first step is to calculate the target's Z-axis position relative to the aircraft. variance The calculation formula is: in, In and The calculation formulas are as follows: The second step is to In and The Taylor expansion simplification is performed as follows: The third step is to and Substituting the Taylor simplification result into Thus, the Z-axis position relative to the aircraft is obtained. High-precision simplified variance The formula is 5. The parameter assignment method for a spacecraft relative navigation system according to claim 4, characterized in that: In step (3), the calculation and High-precision simplified covariance and High-precision simplified covariance and High-precision simplified covariance The specific steps are as follows: (3.4) Calculation and High-precision simplified covariance The calculation process is as follows Step 1, Calculation and covariance The calculation formula is In and The calculation formulas are as follows: The second step is to In and The Taylor expansion simplification is performed as follows: The third step is to and Substituting the Taylor simplification result into In the middle, we obtained and High-precision simplified covariance The formula is (3.5) Calculation and High-precision simplified covariance The calculation process is as follows Step 1, Calculation and covariance The calculation formula is In and The calculation formulas are as follows: The second step is to In and The Taylor expansion simplification is performed as follows: The third step is to and Substituting the Taylor simplification result into In the middle, we obtained and High-precision simplified covariance The formula is (3.6) Calculation and High-precision simplified covariance The calculation process is as follows Step 1, Calculation and covariance The calculation formula is In and The calculation formulas are as follows: The second step is to In and The Taylor expansion simplification is performed as follows: The third step is to and Substituting the Taylor simplification result into In the middle, we obtained and High-precision simplified covariance The formula is 6. The parameter assignment method for a spacecraft relative navigation system according to claim 5, characterized in that: In step (4), the variance r of the reconstructed X-axis position is obtained. 11 , reconstruct the variance of the Y-axis position r 22 and the variance of the reconstructed Z-axis position r 33 The process is as follows: (4.1) Position the target relative to the X-axis of the aircraft High-precision simplified variance Y-axis position High-precision simplified variance and Z-axis position High-precision simplified variance The sub-items containing the true line-of-sight distance ρ, true elevation angle α, and true azimuth angle β are approximated and replaced to obtain the replaced X high-precision simplified variance. Replace Y with high-precision simplified variance and replacement Z-high precision simplified variance The approximate replacement method is as follows: Soon In α and β are respectively replaced with and Obtain the high-precision simplified variance of the replacement X. The expression is: Soon In α and β are respectively replaced with and Obtain the high-precision simplified variance of the replaced Y. The expression is: Soon In Replace α with and Obtain the high-precision simplified variance of the replacement Z. The expression is: (4.2) Define process parameters c4 = 2 - c3 And c9 = 1 - c8; (4.3) Substitute c1, c2, c3, c5, and c8 into the high-precision simplified variance of the replacement X. Replace The corresponding formula sub-item is used to obtain the variance r of the reconstructed X-axis position. 11 The calculation formula is: (4.4) Substitute c1, c2, c4, c5, and c9 into the high-precision simplified variance of the replacement Y. Replace The corresponding formula sub-item is used to obtain the variance r of the reconstructed Y-axis position. 11 The calculation formula is: (4.5) Substitute c1, c7, and c6 into the high-precision simplified variance of the replacement Z. Replace The corresponding formula sub-item is used to obtain the variance r of the reconstructed Z-axis position. 33 The calculation formula is:

7. The parameter assignment method for a spacecraft relative navigation system according to claim 6, characterized in that: In step (4), the XY covariance r is reconstructed. 12 Reconstructing the XZ covariance r 13 And reconstructed YZ covariance r 23 The process is as follows: (4.6) will and High-precision simplified covariance and High-precision simplified covariance and High-precision simplified covariance The sub-items containing the true line-of-sight distance ρ, the true elevation angle α, and the true azimuth angle β are approximated and replaced to obtain the replaced XY high-precision simplified variances. Replace XZ high-precision simplified variance and replace YZ high-precision simplified variance The approximate replacement method is as follows: Soon ρ in 2 α and β are replaced with and Obtain the high-precision simplified variance of XY replacement. The expression is: Soon ρ in 2 α and β are replaced with and Obtain the replacement XZ high-precision simplified variance The expression is: Soon ρ in 2 α and β are replaced with and Obtain the replacement XZ high-precision simplified variance The expression is: (4.7) Define process parameter c 10 =c8-c9、 c 13 =2c 11 c 12 , and (4.8) Set c1, c2, c 10 c 13 and c 15 Substitute into the high-precision simplified variance of XY replacement Replace The corresponding formula sub-terms are then used to obtain the reconstructed XY covariance r. 12 The calculation formula is: (4.9) c 11 and c 14 Substitute into the high-precision simplified variance of XZ Replace The corresponding formula sub-terms are then used to obtain the reconstructed XZ covariance r. 13 The calculation formula is: (4.10) c 12 and c 14 Substitute into the high-precision simplified variance of YZ Replace The corresponding formula sub-terms are then used to obtain the reconstructed YZ covariance r. 23 The calculation formula is:

8. The parameter assignment method for a spacecraft relative navigation system according to claim 1, characterized in that: In step (5), the measurement noise covariance matrix R is constructed as follows:

9. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of a parameter assignment method for a spacecraft relative navigation system as described in any one of claims 1 to 8.

10. A processor, characterized in that, The processor is used to run a program, wherein the program executes a parameter assignment method for a spacecraft relative navigation system according to any one of claims 1 to 8.

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