CN111272177B - Indirect filtering relative navigation method and system based on time alignment - Google Patents

Indirect filtering relative navigation method and system based on time alignment Download PDF

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CN111272177B
CN111272177B CN202010129670.9A CN202010129670A CN111272177B CN 111272177 B CN111272177 B CN 111272177B CN 202010129670 A CN202010129670 A CN 202010129670A CN 111272177 B CN111272177 B CN 111272177B
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CN111272177A (en
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刘礼城
徐晨
艾奇
张晓彤
王焕杰
方圆
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Shanghai Aerospace Control Technology Institute
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments

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Abstract

The invention discloses an indirect filtering relative navigation method and system based on time alignment, which utilize a single measurement machine to perform relative measurement on a target satellite, and perform filtering processing on the relative measurement result to obtain the required relative navigation information. Measuring the inconsistency of the output frequency of the single machine and the navigation filtering algorithm period, so that delay exists between data, and reducing the influence of the delay on the navigation filtering algorithm precision by aligning the time of the single machine and the time of the navigation filtering algorithm; the method is limited by the limitation of a measurement range, a plurality of single measurement units are usually arranged in an ultra-close range of the tracking satellite, the relative measurement information output by each single measurement unit is inconsistent, in order that a navigation algorithm does not need to be converged again in the process of switching different single measurement units to carry out relative navigation filtering, the output quantities of different single measurement units are preprocessed, and the filtering output of relative navigation is carried out by using an indirect filtering method.

Description

Indirect filtering relative navigation method and system based on time alignment
Technical Field
The invention relates to an indirect filtering relative navigation method and system based on time alignment, and belongs to the technical field of space navigation.
Background
The spacecraft with high cost is influenced by the severe space environment, so that part of equipment is aged and damaged, some functions are lost, huge economic loss is caused, and the failed spacecraft occupies precious orbit resources for a long time and poses potential safety threats to other spacecrafts. In the face of such situations, how to perform equipment maintenance, orbit correction, fuel filling and the like on the failed spacecrafts so as to enable the failed spacecrafts to continue to operate normally becomes one of the problems of important research in the aerospace field of various countries, and the in-orbit service technology is generated along with the problem, so that the in-orbit service technology has wide application value.
The precondition for the on-orbit service of the target spacecraft is the completion of its relative measurements and relative navigation. In the long-distance and short-distance stages, the microwave radar can be used for detecting point targets of the target star, so that relative navigation is completed. However, in the ultra-short distance section, high-precision body target relative navigation is required, and the microwave radar cannot meet the use requirement, so that the laser radar and the vision camera can be adopted to obtain the relative information between the target star and the tracking star so as to complete the high-precision relative navigation, and the method is simple and has high reliability.
At present, relative navigation of point targets and relative navigation methods of cooperative targets of volume targets are becoming mature. In the current relative navigation algorithm processing process of the ultra-close distance non-cooperative target, the output frequency of a single measuring machine is lower than the processing frequency of a system navigation algorithm, so that the precision of the navigation algorithm is limited; the relative information definitions of the measurement outputs of different measurement single machines are inconsistent, so that a plurality of filters need to be designed when different single machine measurement data are used, and the complexity of the algorithm is increased.
Disclosure of Invention
The technical problem solved by the invention is as follows: the method and the system overcome the defects of the prior art, provide the indirect filtering relative navigation method and the system based on time alignment, reduce the complexity of using a plurality of measurement single machines to carry out non-cooperative target ultra-close distance relative navigation algorithm, and improve the accuracy of the algorithm.
The technical solution of the invention is as follows: the indirect filtering relative navigation method based on time alignment comprises the following steps:
obtaining relative position information and relative attitude information between a target satellite and a tracking satellite by using a single measuring machine on the tracking satellite;
preprocessing the acquired relative position information and relative attitude information to recur the relative position information and the relative attitude information to the time of a satellite tracking navigation filtering algorithm in a time dimension to obtain the relative position information and the relative attitude information after time alignment;
and reprocessing the relative position information and the relative attitude information after time alignment, unifying the relative position information and the relative attitude information output by the single measurement machine with different sources, taking the unified relative position information and the unified relative attitude information as the input of an indirect filtering relative navigation algorithm based on the extended Kalman filtering, and using the obtained output for subsequent control.
Further, the method for preprocessing the acquired relative position information and relative attitude information comprises: the relative speed of the tracking satellite and the target satellite output by the navigation filtering algorithm is multiplied by the time difference between the time of outputting data by the measuring single machine and the time of the navigation filtering algorithm of the tracking satellite, and the relative position information output by the measuring single machine is added, so that the relative position information output by the measuring single machine is promoted to the time of the navigation filtering algorithm of the tracking satellite, and the alignment in the time dimension is completed.
Further, the measuring stand-alone comprises a laser radar and a vision camera.
Further, when the single measuring machine is a laser radar, the relative positions of two satellites under the orbit of the target satellite are as follows:
Figure BDA0002395448000000021
wherein the content of the first and second substances,
Figure BDA0002395448000000022
in order to track the installation position of the laser radar under the satellite system,
Figure BDA0002395448000000023
for the relative position information of the time-aligned lidar output,
Figure BDA0002395448000000024
is the coordinate of the target star centroid under the target star centroid coordinate system,
Figure BDA0002395448000000025
a rotation matrix from the target star centroid coordinate system to the tracking star body coordinate system.
Further, when the surveying stand-alone is a vision camera, the relative positions of two stars under the target star orbit system are:
Figure BDA0002395448000000026
wherein the content of the first and second substances,
Figure BDA0002395448000000031
to track the mounting position of the vision camera under the satellite system,
Figure BDA0002395448000000032
relative position information output for the time-aligned vision camera,
Figure BDA0002395448000000033
is the coordinate of the target star centroid under the target star centroid coordinate system,
Figure BDA0002395448000000034
the coordinates of the center of the target star docking ring under the target star centroid coordinate system,
Figure BDA0002395448000000035
a rotation matrix from the target star centroid coordinate system to the tracking star body coordinate system.
An indirect filtering relative navigation system based on time alignment, comprising
The first module is used for acquiring relative position information and relative attitude information between a target satellite and a tracking satellite by using a single measurement machine on the tracking satellite;
the second module is used for preprocessing the acquired relative position information and relative attitude information to ensure that the relative position information and the relative attitude information are recurred to the time of a satellite tracking navigation filtering algorithm in a time dimension to obtain the relative position information and the relative attitude information after time alignment;
and the third module is used for reprocessing the relative position information and the relative attitude information after time alignment, unifying the relative position information and the relative attitude information output by different source measurement single machines, taking the unified relative position information and the unified relative attitude information as the input of an indirect filtering relative navigation algorithm based on the extended Kalman filtering, and obtaining the output for subsequent control.
Further, the preprocessing is performed on the acquired relative position information and the acquired relative posture information, and the specific method is as follows: the relative speed of the tracking satellite and the target satellite output by the navigation filtering algorithm is multiplied by the time difference between the time of outputting data by the measuring single machine and the time of the navigation filtering algorithm of the tracking satellite, and the relative position information output by the measuring single machine is added, so that the relative position information output by the measuring single machine is promoted to the time of the navigation filtering algorithm of the tracking satellite, and the alignment in the time dimension is completed.
Further, the measuring stand-alone comprises a laser radar and a vision camera.
Further, when the single measuring machine is a laser radar, the relative positions of two satellites under the orbit of the target satellite are as follows:
Figure BDA0002395448000000036
wherein the content of the first and second substances,
Figure BDA0002395448000000037
in order to track the installation position of the laser radar under the satellite system,
Figure BDA0002395448000000038
for the relative position information of the time-aligned lidar output,
Figure BDA0002395448000000039
is the coordinate of the target star centroid under the target star centroid coordinate system,
Figure BDA00023954480000000310
a rotation matrix from the target star centroid coordinate system to the tracking star body coordinate system.
Further, when the surveying stand-alone is a vision camera, the relative positions of two stars under the target star orbit system are:
Figure BDA0002395448000000041
wherein the content of the first and second substances,
Figure BDA0002395448000000042
for the visual camera to catch upThe installation position under the star system is tracked,
Figure BDA0002395448000000043
relative position information output for the time-aligned vision camera,
Figure BDA0002395448000000044
is the coordinate of the target star centroid under the target star centroid coordinate system,
Figure BDA0002395448000000045
the coordinates of the center of the target star docking ring under the target star centroid coordinate system,
Figure BDA0002395448000000046
a rotation matrix from the target star centroid coordinate system to the tracking star body coordinate system.
Compared with the prior art, the invention has the advantages that:
(1) in the algorithm processing process, the problem that the output frequency of the single measurement machine is inconsistent with the processing frequency of the system navigation algorithm is considered, and the unification is carried out on the time dimension, so that the accuracy of the algorithm is improved;
(2) the algorithm designed by the invention preprocesses the relative information output by different measuring single machines, designs the indirect filter based on the extended Kalman, and reduces the complexity of the algorithm.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic diagram of the lidar measurement output of the present invention;
FIG. 3 is a schematic view of the measurement output of the vision camera of the present invention;
FIG. 4 is a graph of the navigation output versus position error according to an embodiment of the present invention;
FIG. 5 is a graph of the navigation output versus position error according to an embodiment of the present invention;
FIG. 6 is a graph of the navigation output relative position error at a single machine switch according to an embodiment of the present invention.
Detailed Description
The invention relates to an indirect filtering relative navigation method based on time alignment, which solves the problem of the influence of data delay on the navigation precision of a system by using the time alignment method, and solves the problem of the performance reduction of the system caused by the fact that a navigation filtering algorithm needs to be converged again in the process of switching different measuring single machines. And by utilizing the relative information output by the single measuring machine, the data output by the single measuring machine is forwarded to the time of a system navigation filtering algorithm through preprocessing, so that the alignment in the time dimension is completed. And further preprocessing the data after the time alignment is finished, unifying relative measurement information output by different measurement single machines, taking the relative measurement information as an observed quantity by a relative navigation filtering algorithm, and finally obtaining the relative position and the relative speed of the two stars under the target star orbit, which are required by the relative orbit control, by taking the relative position speed of the two stars under the target star orbit as a state quantity.
Referring to fig. 1, the indirect filtering relative navigation method based on time alignment includes:
acquiring relative position information and relative attitude information between a target satellite and a tracking satellite by using a single measuring machine on the tracking satellite;
preprocessing the acquired relative position information and relative attitude information to ensure that the relative position information and the relative attitude information are recurred to the time of a satellite tracking navigation filtering algorithm in a time dimension to obtain the relative position information and the relative attitude information after time alignment;
and step three, reprocessing the relative position information and the relative attitude information after time alignment, unifying the relative position information and the relative attitude information output by different source measurement single machines, taking the unified relative position information and the unified relative attitude information as the input of an indirect filtering relative navigation algorithm based on the extended Kalman filtering, and using the obtained output for subsequent control.
In the first step, the relative position information between the target star and the tracking star output by the laser radar is defined as the three-dimensional coordinates of the centroid of the target star in the measurement coordinate system of the laser radar, such as the vector in fig. 2
Figure BDA0002395448000000051
As shown.
The relative position information between the target star and the tracking star output by the vision camera is defined as the three-dimensional coordinates of the center of the docking ring of the target star in the measurement coordinate system of the vision camera, such as the vector in fig. 3
Figure BDA0002395448000000052
As shown.
The second step is to pre-process the data output by the single measuring machine, and utilize the relative speed between the target satellite and the tracking satellite output by the navigation filtering algorithm in the last period, namely the output value of the last period of the Kalman filtering algorithm
Figure BDA0002395448000000053
Rear three-dimensional quantity of
Figure BDA0002395448000000054
Measuring time t of single machine output dataldOr txjAnd system navigation filter algorithm time tGNCIs recorded as Δ tld＝tGNC-tldOr Δ txj＝tGNC-txjThe input value to the navigation filter algorithm after the time alignment is completed is
Figure BDA0002395448000000055
Or
Figure BDA0002395448000000056
In the third step, as shown in fig. 2, when the measuring unit is a laser radar, the projection of the connecting line between the target satellite and the centroid of the tracking satellite in the system of the tracking satellite can be known:
Figure BDA0002395448000000061
wherein the content of the first and second substances,
Figure BDA0002395448000000062
system for tracking satellite body for laser radarThe lower part of the mounting position is provided with a mounting hole,
Figure BDA0002395448000000063
for the relative position information of the time-aligned lidar output,
Figure BDA0002395448000000064
is the coordinate of the target star centroid under the target star centroid coordinate system,
Figure BDA0002395448000000065
a rotation matrix from the target star centroid coordinate system to the tracking star body coordinate system.
As shown in fig. 3, it can be seen that when the surveying stand-alone is a vision camera, the projection of the connecting line between the target star and the centroid of the tracking star is under the system of the tracking star:
Figure BDA0002395448000000066
wherein the content of the first and second substances,
Figure BDA0002395448000000067
to track the mounting position of the vision camera under the satellite system,
Figure BDA0002395448000000068
relative position information output for the time-aligned vision camera,
Figure BDA0002395448000000069
is the coordinate of the target star centroid under the target star centroid coordinate system,
Figure BDA00023954480000000610
the coordinates of the center of the target star docking ring under the target star centroid coordinate system,
Figure BDA00023954480000000611
a rotation matrix from the target star centroid coordinate system to the tracking star body coordinate system.
Target star orbit systemThe relative positions of the next two stars are:
Figure BDA00023954480000000612
wherein
Figure BDA00023954480000000613
To track the rotation matrix of the satellite system to the inertial system, obtained by absolute attitude determination,
Figure BDA00023954480000000614
for the transformation matrix from the inertial frame to the target star orbital frame, the ultra-short distance segment can approximately consider this rotation matrix equal to the rotation matrix from the inertial frame to the tracking star orbital frame, as a known quantity.
From the above analysis, when the single measurement machine is a laser radar, the relative positions of two satellites under the orbit of the target satellite are as follows:
Figure BDA00023954480000000615
when the single measuring machine is a vision camera, the relative positions of two stars under the target star orbit system are as follows:
Figure BDA00023954480000000616
establishing an extended Kalman filter by taking the relative position of a target satellite and a tracking satellite under a target satellite orbit system as an observed quantity, wherein an observation equation is as follows:
Figure BDA00023954480000000617
wherein H ═ I3×3 03×3]，X＝[x y z vx vy vz]Is the state quantity in the Kalman filtering algorithm, the method is the relative position and the relative speed of two stars under a target star orbit system,
and (4) combining the two-star relative orbit kinetic equation and adopting a filtering technology to output in real time.
Examples
The application of the method in the aspect of relative navigation of the ultra-short distance non-cooperative target is verified through a simulation example by taking a certain high orbit satellite GNC system as an object and adopting a laser radar and a vision camera as a measurement single machine.
(1) State equation establishment
Establishing a coordinate system of a relative orbit in a target star orbit system, taking the relative position, the relative speed and the target mass center coordinate of two stars as state quantities, and taking a state equation as follows:
Figure BDA0002395448000000071
wherein: x ═ X y z vx vy vz]T；
x, y and z are projections of relative positions of two stars under the target star orbit system;
vx，vy，vzthe projection of the relative speed of the two stars under the target star orbit system;
after discretization processing, a predicted value of one step is obtained:
Figure BDA0002395448000000072
wherein:
Figure BDA0002395448000000073
Figure BDA0002395448000000074
initial value:
Figure BDA0002395448000000075
(2) observation equation establishment
The observation equation is established by the relative position of the single machine output, and is defined by the single machine measurement information to obtain
When the single measuring machine is a laser radar, the relative positions of two satellites under the orbit of the target satellite are as follows:
Figure BDA0002395448000000081
when the single measuring machine is a vision camera, the relative positions of two stars under the target star orbit system are as follows:
Figure BDA0002395448000000082
establishing an extended Kalman filter by taking the relative position of a target satellite and a tracking satellite under a target satellite orbit system as an observed quantity, wherein an observation equation is as follows:
Figure BDA0002395448000000083
wherein H ═ I3×3 03×3]，X＝[x y z vx vy vz]The state quantities in the kalman filter algorithm are the relative positions and relative velocities of two stars under the target star trajectory system in this example.
Figure BDA0002395448000000084
(3) Simulation conditions
Laser radar measurement accuracy:
relative position measurement accuracy: less than or equal to 0.1 m;
relative angle measurement error: 3 degrees.
The measurement precision of the vision camera is as follows:
relative position measurement accuracy: less than or equal to 0.05 m;
relative angle measurement error: 2 deg.
Simulation track: the initial tracking star approaches to the rear 30m at the rear of the target 60m → the rear of the target 30m approaches to the rear 10m → the rear of the target 10m approaches to the rear 2 m.
10m single machine is switched from laser radar to vision camera (simulation time 1000s)
(3) Simulation result
As shown in fig. 4, 5 and 6.
As can be seen from the simulation result curve: the relative position error in the whole process is better than 0.05 m; the relative speed error is better than 0.01m/s, the navigation algorithm at the single machine switching position does not need to be converged again, and the requirement of the ultra-close distance non-cooperative target relative navigation can be met. The above simulations illustrate the effectiveness of indirect filtering based on time alignment versus navigation methods.
Those skilled in the art will appreciate that those matters not described in detail in the present specification are well known in the art.

Claims (8)

1. The indirect filtering relative navigation method based on time alignment is characterized by comprising the following steps:
obtaining relative position information and relative attitude information between a target satellite and a tracking satellite by using a single measuring machine on the tracking satellite;
preprocessing the acquired relative position information and relative attitude information to recur the relative position information and the relative attitude information to the time of a satellite tracking navigation filtering algorithm in a time dimension to obtain the relative position information and the relative attitude information after time alignment;
the relative position information and the relative attitude information after time alignment are reprocessed, the relative position information and the relative attitude information output by different source measurement single machines are unified, the unified relative position information and the unified relative attitude information are used as the input of an indirect filtering relative navigation algorithm based on extended Kalman filtering, and the obtained output is used for subsequent control;
the method for preprocessing the acquired relative position information and the acquired relative attitude information comprises the following steps: the relative speed of the tracking satellite and the target satellite output by the navigation filtering algorithm is multiplied by the time difference between the time of outputting data by the measuring single machine and the time of the navigation filtering algorithm of the tracking satellite, and the relative position information output by the measuring single machine is added, so that the relative position information output by the measuring single machine is promoted to the time of the navigation filtering algorithm of the tracking satellite, and the alignment in the time dimension is completed.
2. The indirect filtering relative navigation method based on time alignment of claim 1, wherein the measurement stand-alone comprises a laser radar and a vision camera.
3. The indirect filtering relative navigation method based on time alignment according to claim 2, wherein when the measurement unit is a laser radar, the relative positions of two satellites under the orbit of the target satellite are:
Figure FDA0003291080320000011
wherein the content of the first and second substances,
Figure FDA0003291080320000012
in order to track the installation position of the laser radar under the satellite system,
Figure FDA0003291080320000013
for the relative position information of the time-aligned lidar output,
Figure FDA0003291080320000014
is the coordinate of the target star centroid under the target star centroid coordinate system,
Figure FDA0003291080320000015
a rotation matrix from the target star centroid coordinate system to the tracking star body coordinate system.
4. The indirect filtering relative navigation method based on time alignment of claim 2, wherein when the measuring unit is a visual camera, the relative positions of two stars in the target star trajectory system are:
Figure FDA0003291080320000021
wherein the content of the first and second substances,
Figure FDA0003291080320000022
to track the mounting position of the vision camera under the satellite system,
Figure FDA0003291080320000023
relative position information output for the time-aligned vision camera,
Figure FDA0003291080320000024
is the coordinate of the target star centroid under the target star centroid coordinate system,
Figure FDA0003291080320000025
the coordinates of the center of the target star docking ring under the target star centroid coordinate system,
Figure FDA0003291080320000026
a rotation matrix from the target star centroid coordinate system to the tracking star body coordinate system.
5. An indirect filtering relative navigation system based on time alignment, comprising
The first module is used for acquiring relative position information and relative attitude information between a target satellite and a tracking satellite by using a single measurement machine on the tracking satellite;
the second module is used for preprocessing the acquired relative position information and relative attitude information to ensure that the relative position information and the relative attitude information are recurred to the time of a satellite tracking navigation filtering algorithm in a time dimension to obtain the relative position information and the relative attitude information after time alignment;
the third module is used for reprocessing the relative position information and the relative attitude information after time alignment, unifying the relative position information and the relative attitude information output by different source measurement single machines, taking the unified relative position information and the unified relative attitude information as the input of an indirect filtering relative navigation algorithm based on extended Kalman filtering, and using the obtained output for subsequent control;
the method for preprocessing the acquired relative position information and the acquired relative attitude information comprises the following specific steps: the relative speed of the tracking satellite and the target satellite output by the navigation filtering algorithm is multiplied by the time difference between the time of outputting data by the measuring single machine and the time of the navigation filtering algorithm of the tracking satellite, and the relative position information output by the measuring single machine is added, so that the relative position information output by the measuring single machine is promoted to the time of the navigation filtering algorithm of the tracking satellite, and the alignment in the time dimension is completed.
6. The time-alignment based indirect filtering relative navigation system of claim 5, wherein the measurement stand-alone comprises a lidar and a vision camera.
7. The indirect filtering relative navigation system based on time alignment of claim 6, wherein when the measurement unit is a lidar, the relative positions of two satellites under the orbit of the target satellite are:
Figure FDA0003291080320000031
wherein the content of the first and second substances,
Figure FDA0003291080320000032
in order to track the installation position of the laser radar under the satellite system,
Figure FDA0003291080320000033
for the relative position information of the time-aligned lidar output,
Figure FDA0003291080320000034
is the coordinate of the target star centroid under the target star centroid coordinate system,
Figure FDA0003291080320000035
a rotation matrix from the target star centroid coordinate system to the tracking star body coordinate system.
8. The indirect filtering relative navigation system based on time alignment of claim 6, wherein when the measuring stand-alone is a vision camera, the relative positions of two stars in the target star trajectory system are:
Figure FDA0003291080320000036
wherein the content of the first and second substances,
Figure FDA0003291080320000037
to track the mounting position of the vision camera under the satellite system,
Figure FDA0003291080320000038
relative position information output for the time-aligned vision camera,
Figure FDA0003291080320000039
is the coordinate of the target star centroid under the target star centroid coordinate system,
Figure FDA00032910803200000310
the coordinates of the center of the target star docking ring under the target star centroid coordinate system,
Figure FDA00032910803200000311
a rotation matrix from the target star centroid coordinate system to the tracking star body coordinate system.
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