CN106017480B - Depth Combinated navigation method towards deep space exploration capture section - Google Patents
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Abstract
The present invention provides a kind of depth Combinated navigation method towards deep space exploration capture section, including preproduction phase and filtering stage；Establish that the dynamics of orbits model of deep space probe, direction finding model, ranging model, test the speed model the preproduction phase；The filtering stage is filtered using extended Kalman filter, state transition model in Navigation Filter is dynamics of orbits model, measurement model in Navigation Filter is optionally comprised in pulse observation cycle, direction finding model or the model that tests the speed are selected when not obtaining ranging information, and the received pulse signal of X-ray sensitive device is compensated；When pulse signal accumulation, which finishes, obtains ranging information, ranging model is selected；Navigation Filter utilizes ranging model, according to acquisition navigation desired position and velocity vector.Present invention inhibits pulse arrival time Doppler's deviations, filter convergence, and positioning accuracy is high, and very low to sensor requirements.Therefore, the present invention has important practical significance to Spacecraft Autonomous Navigation.
Description
Technical Field
The invention belongs to the field of autonomous navigation of spacecrafts, and particularly relates to a direction-finding/distance-measuring/speed-measuring depth combined navigation method for a deep space exploration capturing section.
Background
Navigation information is the premise of guidance and is important for success or failure of deep space exploration. Due to the influence of the ultra-long distance and the long time delay caused by the ultra-long distance, the ground station cannot provide real-time high-precision navigation information, particularly in a capturing section. Since 1990, the deep space exploration task failed 7 times in total, 4 of which were related to the acquisition segment. The spacecraft autonomous navigation system can provide real-time high-precision autonomous navigation for the deep space probe by measuring and calculating celestial body information. Thus, astronomical autonomous navigation is extremely important for capturing segments. The capture segment is a highly dynamic environment whose orbit dynamics model is strongly non-linear, time-varying. It is also extremely difficult to realize high-precision autonomous navigation in this environment.
Currently, in the deep space exploration field, there are mainly the following autonomous navigation measurement methods: (1) and (4) X-ray pulsar ranging navigation. The X-ray pulsar ranging navigation can acquire a high signal-to-noise ratio cumulative contour by observing pulsar radiation signals and accumulating according to a pulse period, and can acquire a pulse TOA (time-of-arrival) by comparing the cumulative contour with a standard contour, and can acquire high-precision ranging information by resolving the TOA. However, in the high dynamic environment of the acquisition section, the pulsar radiation signal is greatly affected by the doppler effect and is difficult to compensate due to the variable acceleration flight of the spacecraft. The pulse profile is greatly distorted and the arrival time of the pulse has large deviation. This will seriously affect the navigation performance. (2) And (6) direction finding navigation. The direction-finding navigation is a traditional astronomical navigation mode, and obtains the azimuth information of the spacecraft relative to a celestial body by measuring the near celestial body. However, this method cannot provide high-precision information on the distance between the spacecraft and the near celestial body. Particularly for planets without natural satellites, such as Venus, the spacecraft can only obtain azimuth information relative to one celestial body. The information of the distance between the spacecraft and the near celestial body is completely unavailable. This navigation filter is extremely divergent. (3) And (5) speed measurement and navigation. The speed measurement navigation obtains the speed information of the spacecraft relative to the fixed star by measuring the spectral frequency shift of the sun. The speed measurement precision is higher. However, the speed measurement navigation method cannot directly provide position information, and the position information is obtained by integrating speed information. Therefore, the speed error is accumulated for a long time, and the position information has a large integral error. Generally, speed measurement navigation cannot work alone, and is often used as an auxiliary means for other navigation modes.
The above three methods have merits and disadvantages respectively. The scholars combine them, such as: combined angular/distance measurement navigation (Majie, Liu jin, Tianjin, a pulsar/CNS combined navigation method, national invention patent, ZL 2009100632674), combined distance/speed measurement navigation (Liu J, Kang Z W, White P, Ma J, Tian J W. Doppler/XNAV-integration navigation system using small-area X-ray sensor, IET Radar, Sonar analysis.5 (9): 1010) 1017). However, the method is not a depth combination, does not consider the influence of the pulsar ranging navigation doppler effect, and is further not suitable for the high dynamic environment of the acquisition section.
In summary, in a high dynamic environment of a deep space exploration capture section, the X-ray pulsar ranging navigation system is seriously affected by the doppler effect, and the measurement information has a large deviation; speed measurement and navigation cannot provide high-precision positioning information; the direction-finding navigation has good tangential precision, but has extremely low precision in the radial direction. Namely, a single navigation mode cannot be competent for the task of high-precision autonomous navigation of a deep space exploration capturing segment.
Disclosure of Invention
The invention provides a direction finding/distance measuring/speed measuring depth combined navigation method facing a deep space exploration capturing section, and aims to provide high-precision positioning and constant-speed autonomous navigation information for a spacecraft in the deep space exploration capturing section. The depth character type is used for assisting in obtaining distance measurement information by utilizing direction measurement and speed measurement information, specifically, high-precision three-dimensional speed estimation information is provided by utilizing the direction measurement and speed measurement information, and the high-precision three-dimensional speed estimation information is used for compensating the arrival time error of pulsar photons caused by the high-speed flight of a spacecraft, so that the effect of inhibiting Doppler deviation is achieved. The combined navigation uses direction finding, distance measuring and speed measuring information to update the state of a navigation filter, and realizes multi-source information fusion.
The invention provides a deep space exploration capturing section-oriented depth combination navigation method, which comprises a preparation stage and a filtering stage,
the preparation phase, including the building of the various models required for navigation filtering, includes the following steps,
step A1, building an orbit dynamics model of the deep space probe, which is realized as follows,
the state vector X of the deep space probe is set as,
wherein r ═ x, y, z]TAnd v ═ vx,vy,vz]TRespectively the position and velocity vector of the deep space probe, x, y, z are the components of the position of the deep space probe in three axes, respectively, vx,vy,vzThe components of the speed of the deep space probe on three axes are respectively;
the orbit dynamics of the deep space probe is modeled as,
wherein,are respectively x, y, z, vx,vy,vzThe derivative of (a) of (b),
the formula (2) is represented by the formula,
wherein,is the derivative of the state vector X and,at a time tf (X, t) is the state transition model of the deep space probe, [ X ]1,y1,z1]And [ x ]2,y2,z2]Respectively, the relative position vectors, mu, of the Venus and Earth with respect to the center of mass of the solar systems,μv,μeThe gravitational constants, r, of the sun, the Vena, and the Earth, respectivelyps,rpv,rpeThe distances from the deep space probe to the sun centroid, the golden star centroid and the earth centroid are respectively; r issv,rseThe distances from the star centroid and the earth centroid to the sun centroid respectively; omega (t) is the navigation system noise of the deep space probe at the moment t;
step A2, establishing a direction-finding model;
step A3, establishing a distance measurement model;
step A4, establishing a speed measurement model;
the filtering stage utilizes an extended Kalman filter for filtering, the state transition model included in the navigation filter is an orbit dynamics model, the measurement model selection in the navigation filter comprises the following steps,
the filtering stage utilizes an extended Kalman filter for filtering, the state transition model included in the navigation filter is an orbit dynamics model, the measurement model selection in the navigation filter comprises the following steps,
step B1, when the distance measurement information of the current pulse observation period is not obtained in the current pulse observation period, selecting a direction-finding model or a speed-measuring model, and compensating the pulse signal received by the X-ray sensor by using an epoch stacking method based on Doppler compensation, wherein the compensation is realized as follows,
step B11, the X-ray sensor records the arrival time of the single X-ray photon;
step B12, doppler compensation is performed on the X-ray photon arrival time, as follows,
(a) estimating a current velocity of a spacecraftWhen the filter has feedback, the value adopts a feedback value; otherwise, obtaining the result through an integral formula III;
(b) by usingCompensating the X-ray photon arrival time according to the formula four;
i sub-pulse Doppler compensation quantityAs shown below, the following description is given,
wherein the ith pulse period is PiThe number of pulses in the pulsar observation period is N, tiIs the arrival time of the ith sub-pulse, n is the orientation vector of the pulsar, T represents transposition, c is the speed of light, k is the pulse period Pk，Is the spacecraft velocity vector in the kth pulse period;
step B13, overlapping the photons according to the predicted pulse period to obtain a pulse TOA and obtain ranging information;
step B2, when the pulse signal is accumulated and the ranging information is obtained, selecting a ranging model;
step B3, the navigation filter processes according to the received pulse TOA, the Venus azimuth and the Doppler velocity by using a ranging model to obtain a state vector and obtain a position and a velocity vector required by navigation; after the current pulse observation period is finished, the procedure returns to step B1 to continue the navigation of the next pulse observation period.
In step a2, moreover, a direction-finding model is established as follows,
wherein Z is a direction finding value, rvIs a Venus position vector, upsilon is direction finding noise;
in step a3, moreover, a ranging model is established as follows,
wherein t and tbRespectively pulse arrival navigationThe time of the celestial and solar system centroids; n is the pulsar azimuth vector; d0Is the distance from the pulsar to the solar system centroid, b is the position vector of the solar system centroid relative to the solar system centroid, c is the speed of light, σ is the TOA measurement noise, | · | represents the modulus of the vector.
In step a4, a velocity model is established as follows,
where V is the velocity measurement value and υ is the velocity measurement noise.
The invention restrains the pulse arrival time Doppler deviation, and has the advantages of filter convergence, high positioning precision and low requirement on the sensor. Therefore, the method has important practical significance for autonomous navigation of the spacecraft.
Compared with the prior art, the invention has the advantages that:
(1) the autonomous navigation system of the spacecraft has lower requirements on the sensor. Generally, high precision navigation requires high precision sensors. The sensors (astronomical optical navigation camera, X-ray sensor and spectrometer) required by the invention are all available, and are not required to be developed or collected again, so that the cost and time are saved. In addition, the method can obtain high-precision navigation positioning information even if a low-resolution astronomical optical navigation camera, a small-area X-ray sensor and a low-precision spectrometer are adopted, and can meet the requirement of deep space exploration. Above various detectors only need one can, reduced the load.
(2) The invention can realize high-precision navigation in the capture section. The acquisition segment is a highly dynamic environment. The orbit dynamics model at this time is strongly non-linear time-varying. The pulsar signal is greatly influenced by Doppler, and the Doppler compensation method has limited effect. In addition, the navigation filter is extremely divergent. The invention utilizes the direction-finding and speed-measuring information to inhibit the Doppler effect, and fully utilizes the direction-finding, distance-measuring and speed-measuring information to realize high-precision depth autonomous navigation in a capturing section.
Drawings
Fig. 1 is a flow chart of direction-finding/distance-measuring/speed-measuring depth integrated navigation according to an embodiment of the present invention.
Detailed Description
The technical scheme of the invention can adopt a computer software mode to support the automatic operation process. The technical scheme of the invention is explained in detail in the following by combining the drawings and the embodiment. EKF, short for Extended Kalman Filter, Extended Kalman Filter.
The deep space exploration capturing section is a high dynamic environment, and the influence of Doppler effect on pulsar signals is large. In the pulsar observation period, the Doppler deviation in pulsar signals is compensated by using direction-finding and speed-measuring information, so that a depth two-character is embodied; the integrated navigation method comprises the steps of establishing an orbit dynamics model, a direction finding, distance measuring and speed measuring navigation model and filtering by using an extended Kalman filter. The invention takes a golden star detector as an embodiment.
The venus express track is first given, as shown in table 1.
TABLE 1 initial orbit parameters of jinxing express train
Embodiments may be divided into a preparation phase and a filtering phase.
In the preliminary stage of the embodiment, various models required for navigation filtering are established, specifically:
step A1: the method comprises the following steps of establishing a track dynamics model of the deep space probe, wherein the track dynamics model is a prediction model of an extended Kalman filter, and the specific implementation process is as follows:
because the state vector X of the deep space probe is:
wherein r ═ x, y, z]TAnd v ═ vx,vy,vz]TRespectively the position and velocity vector of the deep space probe, x, y, z are the components of the position of the deep space probe in three axes, respectively, vx,vy,vzThe components of the speed of the deep space probe on three axes are respectively; the orbit dynamics model of the deep space probe is then:
wherein,are respectively x, y, z, vx,vy,vzThe derivative of (a) of (b),
formula (2) may be represented as:
wherein,is the derivative of the state vector X and,at a time tf (X, t) is the state transition model of the deep space probe, [ X ]1,y1,z1]And [ x ]2,y2,z2]Respectively, the relative position vectors, mu, of the Venus and Earth with respect to the center of mass of the solar systems,μv,μeThe gravitational constants of the sun, the Venus and the Earth, respectively;
rps,rpv,rpethe distances from the deep space probe to the sun centroid, the golden star centroid and the earth centroid respectively have the calculation formulas:
the distances from the star centroid and the earth centroid to the sun centroid respectively; navigation system noise omega of deep space probe is [0,0, 0, delta F ═x,ΔFy,ΔFz]TWherein, Δ Fx,ΔFyAnd Δ FzIs a perturbation force, and omega (t) is the noise of a navigation system of the deep space probe at the moment t.
Step A2: and establishing a direction-finding model.
Wherein Z is a direction finding value, rvIs the Venus position vector and upsilon is the direction finding noise.
Step A3: and establishing a ranging model.
Wherein t and tbThe time for the pulse to reach the spacecraft and solar system centroids, respectively. n is the pulsar azimuth vector. D0Is the distance from the pulsar to the solar system centroid, and b is the position vector of the solar system centroid relative to the solar system centroid. And c is the speed of light. σ is the TOA measurement noise. Where, |, represents the modulus of the vector.
Step A4: and establishing a speed measurement model.
Where V is the velocity measurement value and υ is the velocity measurement noise.
In specific implementation, the execution sequence of the steps a2, A3 and a4 may be adjusted in sequence or executed in parallel.
In the filtering stage of the embodiment, an extended kalman filter is used for filtering, which is specifically implemented as follows:
the state transition model in the navigation filter is an orbit dynamics model. The measurement model selection method in the navigation filter is as follows:
step B1: in the current pulse observation period, when the distance measurement information of the current pulse observation period is not obtained, on one hand, a direction-finding model or a speed measurement model is selected, and in the specific implementation, the corresponding model can be used according to the specific situation, namely, when the direction-finding information is obtained, an astronomical optical navigation camera is used, the direction-finding model is used, and when the speed measurement information is obtained, a speed measurement model is used based on a spectrometer. On the other hand, the pulse signal received by the X-ray sensor is compensated by using an epoch stacking method based on Doppler compensation, which specifically comprises the following steps:
step B11: the X-ray sensor records the arrival time of a single X-ray photon.
Step B12: doppler compensation is performed on the arrival time of the X-ray photon, and the process is as follows:
(a) estimating a current velocity of a spacecraftWhen the filter in the step B4 has feedback, the value is a feedback value, that is, the ranging information of the last pulse observation period obtained in the last step B4 is used; otherwise, it is obtained by integral equation (3). Wherein formula (3) is as shown in step A1.
(b) By usingThe X-ray photon arrival time is compensated for as in equation (7).
I sub-pulse Doppler compensation quantityCan be expressed as:
wherein the ith pulse period is PiThe number of pulses in the pulsar observation period is N, and the current speed of the spacecraftI.e. the spacecraft speed, t, in the ith pulse periodiAnd the arrival time of the ith sub-pulse, n is a pulsar azimuth vector, T represents transposition, and c is the speed of light. Accordingly, the k-th pulse period is Pk，Is the spacecraft velocity vector in the kth pulse period.
Step B13: the photons are superimposed according to the predicted pulse period. I.e., accumulated by pulse period, a high snr cumulative profile can be obtained, which is compared to a standard profile to obtain the time-of-arrival (TOA) of the pulse. The pulse period duration unit is typically milliseconds.
Step B2: when the pulse signal is accumulated and the ranging information (namely the pulse TOA) is obtained, the ranging model is selected, and the high-precision ranging information can be obtained by resolving the TOA. That is, after the pulse TOA is obtained in step B13, a ranging model may be selected instead.
Step B3: and the navigation filter processes the received pulse TOA, the Venus azimuth and the Doppler velocity by using the currently selected ranging model to obtain a state vector. This value is the position and velocity vector required for navigation. Furthermore, this value may also be used in the subsequent execution of B12 to compensate for the X-ray photon arrival time. After the current pulse observation period is finished, the procedure returns to step B1 to continue the navigation of the next pulse observation period. The pulse observation period is the ranging observation period.
The design of the extended Kalman filter relates to a prediction model, a measurement model and related parameters. After the model and parameter settings, the filter may filter the measurements and the resulting state estimate includes both position and velocity information components, which are the navigation results.
The filter parameters are shown in table 2:
TABLE 2 navigation Filter parameters
Where P (0) is the initial state error matrix, Q is the state noise covariance,i.e. q1The square of the square,i.e. q2Square of (d).
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (1)
1. A deep integrated navigation method facing a deep space exploration capturing section is characterized in that deep integrated navigation is carried out based on a Venus probe, and comprises a preparation stage and a filtering stage,
the preparation phase, including the building of the various models required for navigation filtering, includes the following steps,
step A1, building an orbit dynamics model of the deep space probe, which is realized as follows,
the state vector X of the deep space probe is set as,
wherein r ═ x, y, z]TAnd v ═ vx,vy,vz]TRespectively the position and velocity vector of the deep space probe, x, y, z are the components of the position of the deep space probe in three axes, respectively, vx,vy,vzThe components of the speed of the deep space probe on three axes are respectively;
the orbit dynamics of the deep space probe is modeled as,
wherein,are respectively x, y, z, vx,vy,vzThe derivative of (a) of (b),
the formula (2) is represented by the formula,
wherein,is the derivative of the state vector X and,at a time tf (X, t) is the state transition model of the deep space probe, [ X ]1,y1,z1]And [ x ]2,y2,z2]Respectively, the relative position vectors, mu, of the Venus and Earth with respect to the center of mass of the solar systems,μv,μeThe gravitational forces of the sun, the Venus and the EarthNumber rps,rpv,rpeThe distances from the deep space probe to the sun centroid, the golden star centroid and the earth centroid are respectively; r issv,rseThe distances from the star centroid and the earth centroid to the sun centroid respectively; omega (t) is the navigation system noise of the deep space probe at the moment t;
step a2, a direction-finding model is built as follows,
wherein Z is a direction finding value, rvIs a Venus position vector, upsilon is direction finding noise;
step a3, a ranging model is established as follows,
wherein t and tbRespectively the time of arrival of the pulse at the spacecraft and solar system centroids; n is the pulsar azimuth vector; d0Is the distance from the pulsar to the solar system centroid, b is the position vector of the solar system centroid relative to the solar system centroid, c is the speed of light, σ is the TOA measurement noise, | · | represents the mode of the vector;
step a4, a velocity model is established as follows,
v is a velocity measurement value, and upsilon is velocity measurement noise;
the filtering stage utilizes an extended Kalman filter for filtering, the state transition model included in the navigation filter is an orbit dynamics model, the measurement model selection in the navigation filter comprises the following steps,
step B1, when the distance measurement information of the current pulse observation period is not obtained in the current pulse observation period, selecting a direction-finding model or a speed-measuring model, and compensating the pulse signal received by the X-ray sensor by using an epoch stacking method based on Doppler compensation, wherein the compensation is realized as follows,
step B11, the X-ray sensor records the arrival time of the single X-ray photon;
step B12, doppler compensation is performed on the X-ray photon arrival time, as follows,
(a) estimating a current velocity of a spacecraftWhen the filter has feedback, the value adopts a feedback value; otherwise, obtaining the result through an integral formula III;
(b) by usingCompensating the X-ray photon arrival time according to the formula four;
i sub-pulse Doppler compensation quantityAs shown below, the following description is given,
wherein the ith pulse period is PiThe number of pulses in the pulsar observation period is N, tiIs the arrival time of the ith sub-pulse, n is the orientation vector of the pulsar, T represents transposition, c is the speed of light, k is the pulse period Pk，Is the spacecraft velocity vector in the kth pulse period;
step B13, overlapping the photons according to the predicted pulse period to obtain a pulse TOA and obtain ranging information;
step B2, when the pulse signal is accumulated and the ranging information is obtained, selecting a ranging model;
step B3, the navigation filter processes according to the received pulse TOA, the Venus azimuth and the Doppler velocity by using a ranging model to obtain a state vector and obtain a position and a velocity vector required by navigation; after the current pulse observation period is finished, the procedure returns to step B1 to continue the navigation of the next pulse observation period.
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