CN115616634A - GNSS information-based flying satellite relative navigation method - Google Patents

Abstract

The invention relates to the technical field of orbiting satellite navigation, and provides an orbiting satellite relative navigation method based on GNSS information. The method for the relative navigation of the orbiting satellite based on the GNSS information can acquire the relative position and speed data of the orbiting satellite relative to the main satellite only through the existing GNSS positioning data and inter-satellite communication without installing relative measuring devices such as a microwave radar, binocular vision measurement and the like on the orbiting small satellite; through verification, the method for the relative navigation of the orbiting satellite based on the GNSS information can acquire relative position and speed data with higher precision than that of the GNSS data by directly performing difference operation in a Kalman filtering mode, and the precision can be improved by 1 order of magnitude.

Description

A method of relative navigation around flying satellites based on GNSS information

technical field

The invention relates to the technical field of fly-around satellite navigation, in particular to a relative navigation method for fly-around satellites based on GNSS information.

Background technique

Micro-satellite formation orbiting means that one or several micro-satellites orbit a main star and fly around the main star in a certain configuration. Small satellites flying around can communicate with the main star, monitor the key actions of the main star, and can also cooperate with the main star to complete some distributed tasks. The orbiting satellite will be affected by the space perturbation force, which will affect the orbiting configuration, so the configuration needs to be controlled. The premise of the orbiting configuration control is to determine the position and velocity information of the orbiting small satellite relative to the main star.

At present, the relative navigation algorithm is mainly based on the relative measurement devices installed on the orbiting small satellite, such as microwave radar, binocular vision measurement, etc., which can obtain information such as distance and angle relative to the main star. However, due to limited resources on orbiting small satellites, most small satellites in actual engineering cannot be equipped with relative measurement sensors. Therefore, it is necessary to obtain measurement data based on the necessary sensors on orbiting small satellites. Usually, GNSS receivers are necessary sensors for tiny satellites, and small satellites flying around are equipped with inter-satellite communication sensors to communicate with the main star.

Based on the GNSS receiver and inter-satellite communication equipment, the GNSS positioning data of both the main star and the orbiting small satellite can be obtained, and the relative position and velocity information can be obtained through coordinate conversion and other processing. On this basis, the present invention proposes an on-satellite orbit recursion based on the relative motion equation, using the GNSS positioning data of the main star and the orbiting small satellite to measure and update the relative position and velocity information, and using the extended Kalman filter (EKF) Relative Navigation Method for Improving the Accuracy of Relative Navigation Data.

Contents of the invention

In order to solve the problems existing in the background technology, the present invention provides a kind of relative navigation method based on GNSS information flying around satellites, which comprises the following steps:

A relative navigation method for orbiting satellites based on GNSS information, characterized in that it uses the GNSS positioning data of both the main star and the orbiting small satellites to perform relative position and velocity information measurement and update, and uses the extended Kalman filter to obtain Higher precision relative position and velocity data of the orbiting satellite relative to the main star.

Specifically include the following steps:

S1: Obtain the position r _{d_84} and velocity v _{d_84} of the orbiting satellite t in the WGS84 coordinate system through the GNSS of the orbiting satellite:

S2. Obtain the position r _{c_84} and velocity v _{c_84} of the main star t in the WGS84 coordinate system through the inter-satellite communication of the flying satellite:

S3. Establish a relative motion coordinate system, that is, the second orbital coordinate system of the main star, denoted as ox _o y _o z _o ;

S4. Calculate the relative position r _rel and velocity v _rel of the orbiting satellite in the main star orbital coordinate system:

r _rel ＝R _oi ·R _i84 ·(r _{d_84} -r _{c_84} ),

为R_i84的导数，R_oi为地心惯性坐标系到相对运动坐标系的转换矩阵，

为R_oi的导数；In the formula, R _i84 is the conversion matrix from the WGS84 coordinate system to the earth-centered inertial coordinate system,

is the derivative of R _i84 , R _oi is the conversion matrix from the earth-centered inertial coordinate system to the relative motion coordinate system,

is the derivative of R _oi ;

S5. Establish the relative motion equation of the orbiting satellite under the orbital coordinate system of the main star:

r_T为主星的地心距。f_x、f_y、f_z分别表示绕飞卫星受到的相对摄动加速度在主星轨道坐标系下的分量；In the formula, x, y, and z represent the position of the orbiting satellite in the orbital coordinate system of the main star, respectively. for circular orbit

r _T is the earth-center distance of the main star. f _x , f _y , f _z represent the components of the relative perturbation acceleration received by the orbiting satellite in the orbital coordinate system of the main star, respectively;

S6. Based on the relative motion equation, the state variable can be expressed as:

Then, the matrix form of the relative motion equation can be expressed as:

In the formula,

G=[0 _3×3 I _3×3 ] ^T , W is the projection of the relative perturbation acceleration difference between the orbits of the two satellites and the three channels on the orbital system of the main star, and W=f;

S7, the position and velocity of the orbiting satellite in the main star orbital coordinate system are used as the observation equation;

In the formula, V is the system measurement noise;

S8. Use the extended Kalman filter to discretize the system state equation at the optimal estimation point after linearization, and the system model is obtained as:

The discrete form of the filter is:

In the formula,

Φ _k,k-1 =I+F(t _k-1 )·T=I+A·T.

Wherein, the concrete process of described step S3 comprises:

The coordinate origin o of the defined coordinate system is the mass center of the main star, the oz _o axis points to the center of the earth, the ox _o axis is located in the instantaneous orbital plane of the main star, and is perpendicular to the oz _o axis and points to the velocity direction of the main star, and the oy _o axis is normal to the instant orbital plane of the main star The directions of the lines are opposite, and x _o -y _o -z _o form a right-handed orthogonal coordinate system.

The beneficial effects achieved by the present invention are:

First, the relative navigation method of flying around satellites based on GNSS information of the present invention only uses existing GNSS positioning data and inter-satellite communication, and does not need to install relative measuring devices on small flying satellites, such as microwave radar, binocular vision measurement, etc. , the relative position and velocity data of the orbiting satellite relative to the main star can be obtained;

Second, through verification, the relative navigation method of flying around satellites based on GNSS information of the present invention can obtain relative position and velocity data with higher accuracy than GNSS data direct difference calculation by means of extended Kalman filtering, and the accuracy can be improved by 1 order of magnitude.

Description of drawings

Fig. 1 present invention is based on the design flowchart of the relative navigation method of flying around satellites based on GNSS information;

Fig. 2 is a schematic diagram of the orbital motion of the present invention and the main star orbital coordinate system;

Fig. 3 is a schematic diagram of an unfiltered phase position error in Embodiment 1;

Fig. 4 is the unfiltered relative velocity error schematic diagram in embodiment 1;

Fig. 5 is a schematic diagram of the phase position error after filtering in Embodiment 1;

FIG. 6 is a schematic diagram of the filtered relative speed error in Embodiment 1. FIG.

detailed description

In order to make it easier for those skilled in the art to understand the present invention, the specific implementation manners of the present invention will be described below in conjunction with the examples and accompanying drawings.

The present invention does not install a relative measurement device (such as microwave radar, binocular vision measurement, etc.) Higher precision relative position and velocity data of the satellite relative to the host star.

Referring to the algorithm design process in Figure 1,

The specific implementation steps of the relative navigation algorithm based on GNSS information are as follows:

Step 1. Obtain the position r _{d_84} and velocity v _{d_84} of the orbiting satellite t in the WGS84 coordinate system through the GNSS of the orbiting satellite:

Step 2. Obtain the position r _{c_84} and velocity v _{c_84} of the main star t in the WGS84 coordinate system through the inter-satellite communication of the orbiting satellite:

Step 3. Establish a relative motion coordinate system:

The relative motion coordinate system is the second orbital coordinate system of the main star, which is recorded as ox _o y _o z _o , as shown in Figure 2, the coordinate origin o of this coordinate system is defined as the mass center of the main star, the oz _o axis points to the center of the earth, and the ox _o axis is located at In the instantaneous orbit plane of the host star, the oz _o axis is perpendicular to the velocity direction of the host star, the oy _o axis is opposite to the normal direction of the host star’s instantaneous orbit plane, and x _o -y _o -z _o constitutes a right-handed orthogonal coordinate system.

Step 4. Calculate the relative position r _rel and velocity v _rel of the orbiting satellite in the orbital coordinate system of the main star:

r _rel ＝R _oi ·R _i84 ·(r _{d_84} -r _{c_84} ),

为R_i84的导数，R_oi为地心惯性坐标系到相对运动坐标系的转换矩阵，

为R_oi的导数。In the formula, R _i84 is the conversion matrix from the WGS84 coordinate system to the earth-centered inertial coordinate system,

is the derivative of R _i84 , R _oi is the conversion matrix from the earth-centered inertial coordinate system to the relative motion coordinate system,

is the derivative of R _oi .

Step 5. Establish the relative motion equation of the orbiting satellite under the orbital coordinate system of the main star:

r_T为主星的地心距。f_x、f_y、f_z分别表示绕飞卫星受到的相对摄动加速度在主星轨道坐标系下的分量。In the formula, x, y, and z represent the position of the orbiting satellite in the orbital coordinate system of the main star, respectively. for circular orbit

r _T is the earth-center distance of the main star. f _x , f _y , and f _z represent the components of the relative perturbation acceleration received by the orbiting satellite in the orbital coordinate system of the main star, respectively.

Step 6. Based on the relative motion equation, the state variable can be expressed as:

Then, the matrix form of the relative motion equation can be expressed as:

In the formula,

G=[0 _3×3 I _3×3 ] ^T , W is the projection of the relative perturbation acceleration difference of the orbits of the two satellites and the three channels on the orbital system of the main star, and W=f.

Step 7. The position and velocity of the orbiting satellite in the orbital coordinate system of the main star are used as the observation equation.

In the formula, V is the system measurement noise.

Step 8. Use extended Kalman filter to discretize the system state equation at the optimal estimation point after linearization, and the system model is obtained as follows:

The discrete form of the filter is:

In the formula,

Φ _k,k-1 ＝I+F(t _k-1 )·T＝I+A·T

Example 1,

This embodiment verifies the above method by simulation:

Set the GNSS positioning error of the flying satellite to 10m (1σ), and the constant speed error to 0.2m/s (1σ). The positioning error of the main star received by the orbiting satellite inter-satellite communication is 10m (1σ), and the fixed velocity error is 0.2m/s (1σ). The main star runs on a circular orbit with an orbital height of 500km and an inclination of 55°. The orbiting satellites fly around the main star in an ellipse with a semi-major axis of 3.4km and a semi-minor axis of 1.7km.

Figures 3-4 show the relative position and velocity errors of the orbiting satellites in the orbital coordinate system of the main star without filtering. It can be seen from Figure 3 and Figure 4 that the relative position error is about 30m (3σ) and the relative velocity error is about 0.6m/s (3σ) without filtering. Figures 5-6 show the relative position and velocity errors of the orbiting satellites in the main star orbit coordinate system after filtering. It can be seen from Fig. 5 and Fig. 6 that after filtering, the relative position error is about 4m (3σ), the relative velocity error is about 0.02m/s (3σ), and the accuracy is improved by an order of magnitude.

Therefore, the method in the present invention can obtain the relative measurement device of the orbiting satellite relative to the main satellite without installing a relative measurement device on the orbiting small satellite, such as microwave radar, binocular vision measurement, etc., only through the existing GNSS positioning data and inter-satellite communication. At the same time, the relative navigation method of flying around satellites in the present invention can obtain relative position and velocity data with higher accuracy than GNSS data directly doing difference calculation by means of extended Kalman filtering.

The above embodiments of the present invention are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the claims of the present invention.

Claims (4)

1. A relative navigation method based on GNSS information for flying around satellites, characterized in that it uses the GNSS positioning data of both the main star and the small satellites flying around to carry out relative position velocity information measurement and update, and utilizes the extended Kalman filter This method is used to obtain relatively high-precision relative position and velocity data of the orbiting satellite relative to the main star. 2. a kind of relative navigation method based on GNSS information according to claim 1, is characterized in that, it comprises the steps: S1: Obtain the position r _{d_84} and velocity v _{d_84} of the orbiting satellite t in the WGS84 coordinate system through the GNSS of the orbiting satellite:

S2. Obtain the position r _{c_84} and velocity v _{c_84} of the main star t in the WGS84 coordinate system through the inter-satellite communication of the flying satellite:

S3. Establish a relative motion coordinate system, that is, the second orbital coordinate system of the main star, denoted as ox _o y _o z _o ; S4. Calculate the relative position r _rel and velocity v _rel of the orbiting satellite in the main star orbital coordinate system: r _rel ＝R _oi ·R _i84 ·(r _{d_84} -r _{c_84} ),

In the formula, R _i84 is the conversion matrix from the WGS84 coordinate system to the earth-centered inertial coordinate system,

is the derivative of R _i84 , R _oi is the conversion matrix from the earth-centered inertial coordinate system to the relative motion coordinate system,

is the derivative of R _oi ; S5. Establish the relative motion equation of the orbiting satellite under the orbital coordinate system of the main star:

In the formula, x, y, and z represent the position of the orbiting satellite in the orbital coordinate system of the main star, respectively. for circular orbit

r _T is the earth-center distance of the main star. f _x , f _y , f _z represent the components of the relative perturbation acceleration received by the orbiting satellite in the orbital coordinate system of the main star, respectively; S6. Based on the relative motion equation, the state variable can be expressed as:

Then, the matrix form of the relative motion equation can be expressed as:

In the formula,

G=[0 _3×3 I _3×3 ] ^T , W is the projection of the relative perturbation acceleration difference between the orbits of the two satellites and the three channels on the orbital system of the main star, and W=f; S7, the position and velocity of the orbiting satellite in the main star orbital coordinate system are used as the observation equation;

In the formula, V is the system measurement noise; S8. Using the extended Kalman filter to linearize the state equation of the system at the optimal estimation point and then discretize it. 3. a kind of relative navigation method based on GNSS information according to claim 1, is characterized in that: the concrete process of described step S3 comprises: The coordinate origin o of the defined coordinate system is the mass center of the main star, the oz _o axis points to the center of the earth, the ox _o axis is located in the instantaneous orbital plane of the main star, and is perpendicular to the oz _o axis and points to the velocity direction of the main star, and the oy _o axis is normal to the instant orbital plane of the main star The directions of the lines are opposite, and x _o -y _o -z _o form a right-handed orthogonal coordinate system. 4. A kind of relative navigation method based on GNSS information according to claim 1, characterized in that: in the step S8, the system state equation is discretized after linearizing the optimal estimation point with extended Kalman filter Transformation, the system model is:

The discrete form of the filter is:

In the formula, Φ _k,k-1 =I+F(t _k-1 )·T=I+A·T.

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