CN107132542B - A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar - Google Patents

A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar Download PDF

Info

Publication number
CN107132542B
CN107132542B CN201710300242.6A CN201710300242A CN107132542B CN 107132542 B CN107132542 B CN 107132542B CN 201710300242 A CN201710300242 A CN 201710300242A CN 107132542 B CN107132542 B CN 107132542B
Authority
CN
China
Prior art keywords
small feature
feature loss
landing
doppler radar
formula
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201710300242.6A
Other languages
Chinese (zh)
Other versions
CN107132542A (en
Inventor
崔平远
贾贺
朱圣英
于正湜
戴娟
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing University of Technology
Original Assignee
Beijing University of Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing University of Technology filed Critical Beijing University of Technology
Priority to CN201710300242.6A priority Critical patent/CN107132542B/en
Publication of CN107132542A publication Critical patent/CN107132542A/en
Application granted granted Critical
Publication of CN107132542B publication Critical patent/CN107132542B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • 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
    • G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Electromagnetism (AREA)
  • Multimedia (AREA)
  • Automation & Control Theory (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

The present invention discloses a kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar, belongs to deep-space detection field.Implementation method of the present invention are as follows: the kinetic model for establishing small feature loss soft lander probe establishes the standard Gravitation Field Model of small feature loss and carries out linearization process to kinetic model；Establish independent navigation measurement model, on the basis of autonomous optical navigation method, introduce Doppler radar ranging and range rate information, emit radar beam by Doppler radar, instrumentation radar beam direction to small feature loss surface relative distance and relative velocity, to obtain detector real time position and velocity information；According to small feature loss landing kinetic model and measurement model, detector real-time navigation status information is resolved based on nonlinear system filtering algorithm.The present invention can be improved the estimated accuracy of small feature loss soft landing autonomic air navigation aid, filtering convergence rate, realizes the quick accurate estimation of detector's status, provides support for the accurate soft landing task navigation of small feature loss.

Description

A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar
Technical field
The present invention relates to a kind of small feature loss soft landing autonomic air navigation aids, belong to field of deep space exploration.
Background technique
It is that the mankind understand the formation and evolution in universe and the solar system, explore the main way of origin of life that small feature loss, which lands and detects, Diameter, and detector is in the warm that complex region precision landing of the small feature loss surface with high scientific value is deep space exploration technical research Point problem.Since small feature loss is remote apart from the earth, take the conventional navigation mode of earth station's telemetry communication that there is biggish communication Time delay, it is difficult to meet the requirement of small feature loss landing task, therefore, autonomous navigation technology becomes mainly leading for small feature loss landing detection Boat mode.Since small feature loss gravitational field is weak, distribution is irregular and ground surface environment is complicated, and small feature loss soft landing needs realization double Zero (i.e. Landing on Small Bodies surface (distance zero) Shi Yaoqiu speed is zero) attachment, therefore soft on small feature loss surface to detector Land causes very big difficulty.Basis of the position and speed information that autonomous navigation system provides as Guidance and control, navigation Precision directly influences small feature loss landing precision, is also related to the success or failure of entire detection mission.Therefore, small feature loss soft landing autonomic The research of air navigation aid is significant, and it is preset with section to be directly related to the arrival whether lander can be safe and accurate Learn the target area of value.
Optical guidance has had wide by the advantages that independence is strong, precision is high in terms of spacecraft landing independent navigation General application.In small feature loss landing detection mission, the general autonomous navigation scheme using optical navigation camera tracking target landing point, The detection of the gray level image, the completion of spaceborne image processing software in scheduled landing region to characteristic point is obtained by optical navigation camera And tracking.But this method needs to obtain the accurate position coordinates of small feature loss surface characteristics point in advance, and to be obtained in actual task It is very difficult for obtaining accurate characteristic point position coordinate, therefore is easy to appear the error hiding of characteristic point, to influence from leading The estimated accuracy of boat system.
Summary of the invention
For estimated accuracy existing for small feature loss soft landing autonomic optical guidance in the prior art it is low with filtering convergence rate A kind of slow problem, small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar disclosed by the invention, will solve The technical issues of be improve small feature loss soft landing autonomic air navigation aid estimated accuracy, filtering convergence rate, realize detector shape The quick accurate estimation of state provides technical support for the accurate soft landing task navigation conceptual design of small feature loss.
The purpose of the present invention is what is be achieved through the following technical solutions.
A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar disclosed by the invention, is established small The kinetic model of celestial body soft lander probe is established the standard Gravitation Field Model of small feature loss and is carried out to kinetic model linear Change processing.Independent navigation measurement model is established, on the basis of autonomous optical navigation method, the ranging for introducing Doppler radar is surveyed Fast information emits radar beam by Doppler radar, then to the relative distance in radar beam direction to small feature loss surface and Relative velocity measures, to obtain the real-time position and speed information of detector.According to small feature loss landing dynamics Model and measurement model resolve detector real-time navigation status information based on nonlinear system filtering algorithm.
In conjunction with measurement accuracy demand and cost effectiveness, the Doppler radar preferably six light beam Doppler radars.
A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar disclosed by the invention, including such as Lower step:
Step 1: establishing the kinetic model of small feature loss soft lander probe.
The kinetic model of small feature loss soft landing is established in the case where J2000 landing point is connected coordinate system.State vector includes small The position and speed vector of celestial body landing seeker, shown in the kinetic model of foundation such as formula (1):
Figure BDA0001284034200000021
Wherein r represents Relative position vector, and v indicates that relative velocity vector, F indicate that control acceleration, U indicate that small feature loss draws Power acceleration, ω are small feature loss spin angle velocity.
Choose detector position vector r and velocity vector v as state variable, then
Figure BDA0001284034200000023
Figure BDA0001284034200000024
Figure BDA0001284034200000031
The standard gravitational field of small feature loss uses spherical harmonic coefficient expansion model, and statement is as shown in formula (6):
Figure BDA0001284034200000032
In formula, λ, φ are respectively longitude and latitude of the check point away from small feature loss mass center；R is check point away from small feature loss mass center Distance；
Figure BDA0001284034200000033
For spherical harmonic coefficient；N, m is order and number；G is universal gravitational constant；M is small feature loss quality；R0For The Brillouin radius of a ball；For Legnedre polynomial of associating.
The matrix form of the formula (6) preferably quadravalence spherical harmonic coefficient model.
Step 2: establishing soft landing small feature loss independent navigation measurement model.
The independent navigation measurement model includes that optical camera sight information measurement model and Doppler radar ranging are surveyed Fast measurement model.
The process of camera imaging uses the model of pinhole imaging system, a certain characteristic point f on small feature loss surface1In camera coordinates Position coordinates under system are rp=[xc yc zc]T, then it is in camera as shown in the picture original pixel coordinate such as formula (7) in plane:
Figure BDA0001284034200000035
Wherein: f is camera focus, zcIt is target point along camera reference line to the distance of camera imaging plane.
Define xc,ycThe attitude misalignment in direction is respectively θ1,θ2, then the Random-Rotation during camera measurement will be to feature The position measurement of point has an impact, therefore in the case of little deviation shown in actual position coordinates such as formula (8):
Figure BDA0001284034200000036
Detector attitude error increases with the increase of detector flying distance, ignores and is directed toward angle multiplication to denominator part Influence, then formula (8) can simplify are as follows:
Figure BDA0001284034200000037
Meanwhile in conjunction with Doppler radar measurement along the relative distance ρ in radar beam direction to celestial surfacejAnd relative velocity
Figure BDA0001284034200000038
Relative distance ρj, relative velocity
Figure BDA0001284034200000039
Respectively as shown in formula (10), (11):
Figure BDA0001284034200000041
Wherein: ρjIt is beam direction at a distance from ground,
Figure BDA0001284034200000042
Line-of-sight velocity is represented, B is modulation bandwidth, and c is the light velocity, and T is The period of waveform, λ are wavelength, fRIt is intermediate frequency, fdIt is Doppler frequency shift, Doppler radar measurement radar beam quantity is n.
Therefore, shown in the measurement vector such as formula (11) of Doppler radar:
Figure BDA0001284034200000043
The unit vector for being defined on each beam direction that landing point is connected under coordinate system is λj(j=1 ..., n), such as Shown in formula (12):
Figure BDA0001284034200000044
Figure BDA0001284034200000045
It is the transformation matrix to landing coordinate system from detector body system, shown in matrix such as formula (13):
Figure BDA0001284034200000046
In formula,
Figure BDA0001284034200000047
θ, ψ are respectively the rotation angle of three axis of x, y, z, in addition, detector's status and Doppler radar measurement Shown in relationship such as formula (14), (15) between value:
ρj=z/ (λj·[001]T) (j=1 ..., n) (14)
Wherein z is spacecraft height, vx,vy,vzIt is the component of the spacecraft velocity vector in rectangular coordinate system,
Figure BDA0001284034200000049
ForInverse matrix, represent from landing point be connected coordinate system to this system transition matrix.
In conjunction with measurement accuracy demand and cost effectiveness, the Doppler radar preferably six light beam Doppler radars.
Step 3: according to small feature loss landing kinetic model and measurement model, being resolved and visited based on nonlinear system filtering algorithm Survey device real-time navigation status information.
The measurement model that the small feature loss landing kinetic model that is obtained according to step 1, step 2 obtain, passes through Navigation The state of detector is estimated in calculating.Due to state model and measurement model present it is non-linear, therefore select nonlinear filtering Wave device, preferred development Kalman filtering (EKF) improve Navigation precision and convergence rate.The state of final output detector is believed Breath.
The utility model has the advantages that
1, in the prior art only with the air navigation aid of optical camera measurement characteristic point sight information, due to the position of characteristic point Setting coordinate has certain matching error, leads to the problem that navigation accuracy is lower, filtering convergence rate is slower occur.The present invention discloses A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar, pass through introduce Doppler radar ranging Test the speed information, can be realized the quick estimation to detector position and speed, optical camera Feature Points Matching error is effectively reduced To the adverse effect of independent navigation performance, the estimated accuracy and filtering convergence rate of navigation algorithm are improved, the following small feature loss is met The accuracy requirement of soft landing autonomic navigation.
2, a kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar disclosed by the invention uses Nonlinear filter improves the precision and filtering convergence rate of Autonomous Navigation Algorithm.
Detailed description of the invention
Fig. 1 is the flow chart of the small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar；
When Fig. 2 is the autonomous navigation method in specific embodiment only with optical camera, detector is connected in landing point and sits Navigation error curve under mark system.
(Fig. 2 a is the direction detector x position navigation error curve, Fig. 2 b be the direction detector y position navigation error curve, Fig. 2 c is the direction detector z position navigation error curve, Fig. 2 d is the direction detector x speed navigation error curve, Fig. 2 e is spy Survey the direction device y speed navigation error curve, Fig. 2 f be the direction detector z speed navigation error curve)
Fig. 3 is that the small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar is used in specific embodiment When, navigation error curve of the detector in the case where landing point is connected coordinate system.
(Fig. 3 a is the direction detector x position navigation error curve, Fig. 3 b be the direction detector y position navigation error curve, Fig. 3 c is the direction detector z position navigation error curve, Fig. 3 d is the direction detector x speed navigation error curve, Fig. 3 e is spy Survey the direction device y speed navigation error curve, Fig. 3 f be the direction detector z speed navigation error curve)
Specific embodiment
Objects and advantages in order to better illustrate the present invention with reference to the accompanying drawing do further summary of the invention with example Explanation.
Embodiment 1:
This example is directed to small feature loss soft landing, carries out simulating, verifying by target small feature loss of Eros433.Detector is in small day The initial position that body landing point is connected under coordinate system is [500m, 300m, 2000m]T, initial velocity is [- 0.5m/s, -0.3m/ s,-0.5m/s]T, small feature loss superficial objects landing point position is [0m, 0m, 0m]T.By the sight letter for combining optical camera measurement The opposite ranging and range rate information of breath and Doppler lidar, using extended Kalman filter (EKF), to the position of detector It sets, speed state carries out Combined estimator, independent navigation when realizing high-precision real.
A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar disclosed in this example, including such as Lower step:
Step 1: establishing the kinetic model of small feature loss soft lander probe.
The kinetic model of small feature loss soft landing is established in the case where J2000 landing point is connected coordinate system.State vector includes small The position and speed vector of celestial body landing seeker, shown in the kinetic model of foundation such as formula (1):
Figure BDA0001284034200000061
Wherein r represents Relative position vector, and v indicates that relative velocity vector, F indicate that control acceleration, U indicate that small feature loss draws Power acceleration, ω are small feature loss spin angle velocity.
Choose detector position vector r and velocity vector v as state variable, then
Figure BDA0001284034200000062
Figure BDA0001284034200000063
The standard gravitational field of small feature loss uses spherical harmonic coefficient expansion model, and statement is as shown in formula (6):
Figure BDA0001284034200000072
In formula, λ, φ are respectively longitude and latitude of the check point away from small feature loss mass center；R is check point away from small feature loss mass center Distance；For spherical harmonic coefficient；N, m is order and number；G is universal gravitational constant；M is small feature loss quality；R0For The Brillouin radius of a ball；
Figure BDA0001284034200000074
For Legnedre polynomial of associating.
The matrix form of the formula (6) preferably quadravalence spherical harmonic coefficient model.
Step 2: establishing soft landing small feature loss independent navigation measurement model.
The independent navigation measurement model includes that optical camera sight information measurement model and Doppler radar ranging are surveyed Fast measurement model.
The process of camera imaging uses the model of pinhole imaging system, a certain characteristic point f on small feature loss surface1In camera coordinates Position coordinates under system are rp=[xc yc zc]T, then it is in camera as shown in the picture original pixel coordinate such as formula (7) in plane:
Figure BDA0001284034200000075
Wherein: f is camera focus, zcIt is target point along camera reference line to the distance of camera imaging plane.
Define xc,ycThe attitude misalignment in direction is respectively θ1,θ2, then the Random-Rotation during camera measurement will be to feature Actual position coordinates such as formula (8) is shown under the position measurement of point has an impact, therefore little deviation is assumed:
Figure BDA0001284034200000076
Detector attitude error increases with the increase of detector flying distance, ignores and is directed toward angle multiplication to denominator part Influence, then formula (8) can simplify are as follows:
Figure BDA0001284034200000077
Meanwhile in conjunction with Doppler radar measurement along the relative distance ρ in radar beam direction to celestial surfacejAnd relative velocity
Figure BDA0001284034200000078
Relative distance ρj, relative velocity
Figure BDA0001284034200000079
Respectively as shown in formula (10), (11):
Figure BDA0001284034200000081
Wherein: ρjIt is beam direction at a distance from ground,
Figure BDA0001284034200000082
Line-of-sight velocity is represented, B is modulation bandwidth, and c is the light velocity, and T is The period of waveform, λ are wavelength, fRIt is intermediate frequency, fdIt is Doppler frequency shift.
In conjunction with measurement accuracy demand and cost effectiveness, the Doppler radar preferably six light beam Doppler radars, six light beams are more It is general strangle radar light beam be directed toward is defined as: Doppler radar wherein beam of laser wave beam along spacecraft vertical axis be directed toward minimum point, Wherein three beams diagonal beam and vertical axis are at equally distributed azimuth angle alpha, and in addition two beams are per a branch of downwards with each rotary shaft at β Angle, the advance axis direction with lander is at the angle γ.
Therefore, shown in the measurement vector such as formula (11) of Doppler radar:
Figure BDA0001284034200000083
The unit vector for being defined on each beam direction that landing point is connected under coordinate system is λj(j=1 ..., 6), such as Shown in formula (12):
It is the transformation matrix to landing coordinate system from detector body system, shown in matrix such as formula (13):
Figure BDA0001284034200000086
In formula,θ, ψ are respectively the rotation angle of three axis of x, y, z, in addition, detector's status and Doppler radar measurement Shown in relationship such as formula (14), (15) between value:
ρj=z/ (dj·[001]T) (j=1 ..., n) (14)
Figure BDA0001284034200000088
Wherein z is spacecraft height, vx,vy,vzIt is the component of the spacecraft velocity vector in rectangular coordinate system,
Figure BDA0001284034200000089
For
Figure BDA00012840342000000810
Inverse matrix, represent from landing point be connected coordinate system to this system transition matrix.
Step 3: according to small feature loss landing kinetic model and measurement model, being resolved and visited based on nonlinear system filtering algorithm Survey device real-time navigation status information.
The measurement model that the small feature loss landing kinetic model that is obtained according to step 1, step 2 obtain, passes through Navigation The state of detector is estimated in calculating.Due to state model and measurement model present it is non-linear, therefore select nonlinear filtering Wave device, preferred development Kalman filtering (EKF) improve Navigation precision and convergence rate.The state of final output detector is believed Breath.
Simulating, verifying is carried out to the air navigation aid of the present embodiment, the simulation parameter of landing seeker is as shown in table 1.
1 simulation parameter of table
Figure BDA0001284034200000091
Only with the autonomous navigation method of optical camera and the small feature loss based on optics and Doppler radar of the present embodiment Soft landing autonomic air navigation aid Numerical Simulation Results difference it is as shown in Figure 2 and Figure 3, be set forth in figure detector position and The navigation estimation error curve of speed.From simulation result as can be seen that compared to the air navigation aid using optical camera, it is based on light It learns and the navigation accuracy of the small feature loss soft landing autonomic air navigation aid of Doppler radar is significantly improved with filtering convergence rate, energy It is enough that real-time estimation is carried out to the position of detector and speed, it can finally obtain high-precision state estimation information.
The scope of the present invention is not only limited to embodiment, and embodiment is used to explain the present invention, it is all with of the invention identical Change or modification under the conditions of principle and design is within protection scope disclosed by the invention.

Claims (5)

1. a kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar, it is characterised in that: including as follows Step,
Step 1: establishing the kinetic model of small feature loss soft lander probe；
The kinetic model of small feature loss soft landing is established in the case where J2000 landing point is connected coordinate system；State vector includes small feature loss The position and speed vector of landing seeker, shown in the kinetic model of foundation such as formula (1):
Figure FDA0002125253390000011
Wherein r represents Relative position vector, and v indicates that relative velocity vector, F indicate that control acceleration, U indicate that small feature loss gravitation adds Speed, ω are small feature loss spin angle velocity；
Choose detector position vector r and velocity vector v as state variable, then
Figure FDA0002125253390000012
Figure FDA0002125253390000013
Figure FDA0002125253390000014
Figure FDA0002125253390000015
The standard gravitational field of small feature loss uses spherical harmonic coefficient expansion model, and statement is as shown in formula (6):
Figure FDA0002125253390000016
In formula, γ, φ are respectively longitude and latitude of the check point away from small feature loss mass center；R is check point away from small feature loss mass center away from From；
Figure FDA0002125253390000017
For spherical harmonic coefficient；N, m is order and number；G is universal gravitational constant；M is small feature loss quality；R0For The Brillouin radius of a ball；
Figure FDA0002125253390000018
For Legnedre polynomial of associating；
Step 2: establishing soft landing small feature loss independent navigation measurement model；
The independent navigation measurement model includes that optical camera sight information measurement model and Doppler radar ranging and range rate are surveyed Measure model；
The process of camera imaging uses the model of pinhole imaging system, a certain characteristic point f on small feature loss surface1Under camera coordinates system Position coordinates be rp=[xc yc zc]T, then in camera as shown in the pixel pixel coordinate such as formula (7) in plane:
Wherein: f is camera focus, zcIt is target point along camera reference line to the distance of camera imaging plane；
Define xc,ycThe attitude misalignment in direction is respectively θ1,θ2, then the Random-Rotation during camera measurement is by the position to characteristic point Measurement is set to have an impact, therefore in the case of little deviation shown in actual position coordinates such as formula (8):
Figure FDA0002125253390000022
Detector attitude error increases with the increase of detector flying distance, ignores and is directed toward the shadow that angle is multiplied to denominator part It rings, then formula (8) simplifies are as follows:
Figure FDA0002125253390000023
Meanwhile in conjunction with Doppler radar measurement along the relative distance ρ in radar beam direction to celestial surfacejAnd relative velocity
Figure FDA0002125253390000024
Relative distance ρj, relative velocity
Figure FDA0002125253390000025
Respectively as shown in formula (10), (11):
Figure FDA0002125253390000026
Wherein: ρjIt is beam direction at a distance from ground,
Figure FDA0002125253390000027
Line-of-sight velocity is represented, B is modulation bandwidth, and c is the light velocity, and T is waveform Period, λ is wavelength, fRIt is intermediate frequency, fdIt is Doppler frequency shift, Doppler radar measurement radar beam quantity is n；
Therefore, shown in the measurement vector such as formula (11) of Doppler radar:
The unit vector for being defined on each beam direction that landing point is connected under coordinate system is λj(j=1 ..., n), such as formula (12) shown in:
Figure FDA0002125253390000029
It is the transformation matrix to landing coordinate system from detector body system, shown in matrix such as formula (13):
Figure FDA0002125253390000031
In formula,
Figure FDA0002125253390000032
θ, ψ are respectively the rotation angle of three axis of x, y, z, in addition, detector's status and Doppler radar measurement value it Between relationship such as formula (14), shown in (15):
ρj=z/ (λj·[0 0 1]T) (j=1 ..., n) (14)
Figure FDA0002125253390000033
Wherein z is spacecraft height, vx,vy,vzIt is the component of the spacecraft velocity vector in rectangular coordinate system,For
Figure FDA0002125253390000035
Inverse matrix, represent from landing point be connected coordinate system to this system transition matrix；
Step 3: according to small feature loss landing kinetic model and measurement model, detector being resolved based on nonlinear system filtering algorithm Real-time navigation status information；
The measurement model that the small feature loss landing kinetic model that is obtained according to step 1, step 2 obtain, is calculated by Navigation The state of detector is estimated, the status information of final output detector.
2. a kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar as described in claim 1, Be characterized in that: the formula (6) selects the matrix form of quadravalence spherical harmonic coefficient model.
3. a kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar as described in claim 1, Be characterized in that: in conjunction with measurement accuracy demand and cost effectiveness, the Doppler radar selects six light beam Doppler radars.
4. a kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar as described in claim 1, Be characterized in that: Navigation described in step 3, which calculates, selects nonlinear filter.
5. a kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar as claimed in claim 4, Be characterized in that: the nonlinear filter selects Extended Kalman filter (EKF) to improve Navigation precision and convergence rate.
CN201710300242.6A 2017-05-02 2017-05-02 A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar Active CN107132542B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710300242.6A CN107132542B (en) 2017-05-02 2017-05-02 A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710300242.6A CN107132542B (en) 2017-05-02 2017-05-02 A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar

Publications (2)

Publication Number Publication Date
CN107132542A CN107132542A (en) 2017-09-05
CN107132542B true CN107132542B (en) 2019-10-15

Family

ID=59715173

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710300242.6A Active CN107132542B (en) 2017-05-02 2017-05-02 A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar

Country Status (1)

Country Link
CN (1) CN107132542B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110889219A (en) * 2019-11-22 2020-03-17 北京理工大学 Small celestial body gravitational field inversion correction method based on inter-device ranging

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107655485B (en) * 2017-09-25 2020-06-16 北京理工大学 Cruise section autonomous navigation position deviation correction method
CN109212976B (en) * 2018-11-20 2020-07-07 北京理工大学 Input-limited small celestial body soft landing robust trajectory tracking control method
CN109269512B (en) * 2018-12-06 2021-05-04 北京理工大学 Relative navigation method for fusing planet landing image and distance measurement
CN110307840B (en) * 2019-05-21 2021-09-07 北京控制工程研究所 Landing stage robust fusion method based on multi-beam ranging, velocity measurement and inertia
CN112050830B (en) * 2019-06-06 2023-06-02 华为技术有限公司 Motion state estimation method and device
CN113432609B (en) * 2021-06-16 2022-11-29 北京理工大学 Flexible attachment state collaborative estimation method
CN113408623B (en) * 2021-06-21 2022-10-04 北京理工大学 Non-cooperative target flexible attachment multi-node fusion estimation method

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2083998C1 (en) * 1995-09-11 1997-07-10 Выдревич Моисей Бецалелович Doppler sensor of components of velocity vector, altitude and local vertical for helicopters and vertical landing space vehicles
CN1847791A (en) * 2006-05-12 2006-10-18 哈尔滨工业大学 Verification system for fast autonomous deep-space optical navigation control prototype
CN101762273A (en) * 2010-02-01 2010-06-30 北京理工大学 Autonomous optical navigation method for soft landing for deep space probe
CN103438890A (en) * 2013-09-05 2013-12-11 北京理工大学 Planetary power descending branch navigation method based on TDS (total descending sensor) and image measurement
CN103528587A (en) * 2013-10-15 2014-01-22 西北工业大学 Autonomous integrated navigation system
CN104567880A (en) * 2014-12-23 2015-04-29 北京理工大学 Mars ultimate approach segment autonomous navigation method based on multi-source information fusion

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2083998C1 (en) * 1995-09-11 1997-07-10 Выдревич Моисей Бецалелович Doppler sensor of components of velocity vector, altitude and local vertical for helicopters and vertical landing space vehicles
CN1847791A (en) * 2006-05-12 2006-10-18 哈尔滨工业大学 Verification system for fast autonomous deep-space optical navigation control prototype
CN101762273A (en) * 2010-02-01 2010-06-30 北京理工大学 Autonomous optical navigation method for soft landing for deep space probe
CN103438890A (en) * 2013-09-05 2013-12-11 北京理工大学 Planetary power descending branch navigation method based on TDS (total descending sensor) and image measurement
CN103528587A (en) * 2013-10-15 2014-01-22 西北工业大学 Autonomous integrated navigation system
CN104567880A (en) * 2014-12-23 2015-04-29 北京理工大学 Mars ultimate approach segment autonomous navigation method based on multi-source information fusion

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110889219A (en) * 2019-11-22 2020-03-17 北京理工大学 Small celestial body gravitational field inversion correction method based on inter-device ranging

Also Published As

Publication number Publication date
CN107132542A (en) 2017-09-05

Similar Documents

Publication Publication Date Title
CN107132542B (en) A kind of small feature loss soft landing autonomic air navigation aid based on optics and Doppler radar
CN110487301A (en) A kind of airborne strapdown inertial navigation system Initial Alignment Method of radar auxiliary
CN109613583B (en) Passive target positioning method based on single star and ground station direction finding and combined time difference
CN113311436B (en) Method for correcting wind measurement of motion attitude of laser wind measuring radar on mobile platform
CN103852082B (en) Inter-satellite measurement and gyro attitude orbit integrated smoothing estimation method
CN107806874B (en) A kind of inertial navigation polar region Initial Alignment Method of vision auxiliary
CN109633724B (en) Passive target positioning method based on single-satellite and multi-ground-station combined measurement
CN105698762A (en) Rapid target positioning method based on observation points at different time on single airplane flight path
CN109709537A (en) A kind of noncooperative target position and speed tracking based on satellites formation
CN111102981B (en) High-precision satellite relative navigation method based on UKF
CN105180728B (en) Front data based rapid air alignment method of rotary guided projectiles
CN107655485A (en) A kind of cruise section independent navigation position deviation modification method
CN108896957A (en) The positioning system and method in a kind of unmanned plane control signal source
CN110146093A (en) Binary asteroid detection independently cooperates with optical navigation method
CN105184002A (en) Simulation analysis method for pointing angle of data transmission antenna
US5463402A (en) Motion measurement system and method for airborne platform
CN108917764A (en) A kind of Double Satellite only ranging Relative Navigation
CN113409400A (en) Automatic tracking-based airborne photoelectric system target geographic positioning method
CN117455960B (en) Passive positioning filtering method for airborne photoelectric system to ground under time-varying observation noise condition
CN106996779B (en) Ultraviolet sensors systematic error on-orbit calibration method based on GNSS
CN105424060B (en) A kind of measurement method of aircraft star sensor and strapdown inertial measurement unit installation error
CN108106597B (en) Method for measuring angle of full strapdown laser seeker under condition of target linear field of view
CN106353756A (en) Descending track spotlight SAR (synthetic aperture radar) positioning method based on image matching
CN109471103A (en) A kind of missile-borne Bistatic SAR data fusion positioning error correcting method
CN114063054A (en) Method for backtracking and calculating rocket launching point parameters

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant