CN111006694A - Design method of trajectory generator for long-endurance inertial navigation system based on track planning - Google Patents

Design method of trajectory generator for long-endurance inertial navigation system based on track planning Download PDF

Info

Publication number
CN111006694A
CN111006694A CN201911385476.0A CN201911385476A CN111006694A CN 111006694 A CN111006694 A CN 111006694A CN 201911385476 A CN201911385476 A CN 201911385476A CN 111006694 A CN111006694 A CN 111006694A
Authority
CN
China
Prior art keywords
track
planning
speed
inertial navigation
navigation system
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.)
Granted
Application number
CN201911385476.0A
Other languages
Chinese (zh)
Other versions
CN111006694B (en
Inventor
邓志红
石雷
张文喆
赵生武
王博
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 Institute of Technology BIT
Original Assignee
Beijing Institute of Technology BIT
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 Institute of Technology BIT filed Critical Beijing Institute of Technology BIT
Priority to CN201911385476.0A priority Critical patent/CN111006694B/en
Publication of CN111006694A publication Critical patent/CN111006694A/en
Application granted granted Critical
Publication of CN111006694B publication Critical patent/CN111006694B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
    • G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Manufacturing & Machinery (AREA)
  • Automation & Control Theory (AREA)
  • Navigation (AREA)

Abstract

本发明公开了一种基于航迹规划的惯性导航系统轨迹发生器设计方法。使用本发明能够有效克服传统轨迹发生器设计方法人为设计运动状态的困难，减少研究测试中所耗费的时间和成本，提高重力辅助惯性导航系统的研究效率。本发明将航迹规划与陀螺仪、加速度计和导航数据的生成结合到一起形成长航时航行器轨迹发生器，方便进行理论和方法的验证，减少了实际试验的时间和成本。此外，本发明根据规划航迹将速度、角速度和航向信息转换为向心加速度、切向加速度和角速度信息用于轨迹发生器设计，状态切换过程自然连续，避免了人为设计运动状态时数据过于理想的问题，更贴近航行器运动的实际状态，提高了重力辅助惯性导航研究的有效性。

Figure 201911385476

The invention discloses a design method of an inertial navigation system track generator based on track planning. The invention can effectively overcome the difficulty of artificially designing the motion state of the traditional trajectory generator design method, reduce the time and cost in research and testing, and improve the research efficiency of the gravity-assisted inertial navigation system. The invention combines the track planning with the generation of the gyroscope, the accelerometer and the navigation data to form a long-endurance vehicle trajectory generator, which facilitates the verification of theories and methods and reduces the time and cost of the actual test. In addition, the present invention converts speed, angular velocity and heading information into centripetal acceleration, tangential acceleration and angular velocity information according to the planned track for the design of the trajectory generator, and the state switching process is natural and continuous, avoiding that the data is too ideal when the motion state is artificially designed The problem is closer to the actual state of vehicle motion, which improves the effectiveness of gravity-assisted inertial navigation research.

Figure 201911385476

Description

Design method of long-endurance inertial navigation system track generator based on track planning
Technical Field
The invention relates to the technical field of navigation, guidance and control, in particular to a design method of a long-endurance inertial navigation system track generator based on track planning.
Background
The inertial navigation system can provide navigation positioning information such as position, speed, attitude and the like for the carrier in real time, and is widely applied to various carriers such as land, sea, air and sky. For the long-endurance carriers of the underwater vehicle, the error of the inertial navigation system is dispersed along with the time, and the navigation requirement can not be met. The marine gravity measurement is passivity and stable in gravity information, and the gravity-assisted inertial navigation becomes a research hotspot of underwater autonomous navigation. With the research on the gravity-assisted inertial navigation system, a great deal of research and test work is required. The practical test has the problems of long period, high cost, incapability of separating various error sources to carry out single-item test and the like. To solve this problem, it is an effective way to design a trajectory generator to generate gyroscope and accelerometer data and corresponding navigation data. The conventional track generator adopts a mode that tracks are obtained by artificially designing motion states of all stages of an underwater vehicle, and meanwhile, the motion states of all stages in the tracks are input into the track generator to generate navigation data, and then subsequent researches such as gravity matching and the like are carried out. However, the long-endurance inertial navigation system has the characteristics of long driving time, long driving distance and complex driving track, and the problem of difficult design of manually setting different motion states in each stage of the traditional method exists, and the gravity field characteristic parameters cannot be included. In addition, in the process of the artificially designed motion state, all states are directly combined without considering transition during state switching, so that data generated by the traditional method is too ideal during motion state switching and is not in line with the situation of continuous change in the actual process.
Disclosure of Invention
In view of the above, the invention provides a method for designing a trajectory generator of a long-endurance inertial navigation system based on trajectory planning, which can effectively overcome the difficulty of artificially designing a motion state in a traditional trajectory generator design method, reduce the time and cost consumed in research and test, and improve the research efficiency of a gravity-assisted inertial navigation system.
The invention relates to a design method of a long-endurance inertial navigation system track generator based on track planning, which comprises the following steps:
step 1, planning the track of an aircraft by adopting a track planning algorithm, and considering gravity field information during track planning;
step 2, marking out specific speed, angular speed and course information of the aircraft in the navigation process under the flight path planned and obtained in the step 1 by adopting a dynamic window rule;
step 3, converting the speed, the angular speed and the course information of the underwater vehicle obtained in the step 2 into centripetal acceleration, tangential acceleration and angular speed information;
and 4, generating gyroscope data, accelerometer data and navigation data according to the centripetal acceleration, the tangential acceleration and the angular velocity of the underwater vehicle obtained in the step 3, and finishing the design of the track generator.
Preferably, in the step 1, the track planning algorithm adopts classical a and its improved algorithm, genetic algorithm or artificial potential field method.
Preferably, in the step 1, when the classical a-x algorithm is adopted, the cost function F isnComprises the following steps:
Fn＝p1gn+p2cn+p3hn
wherein, gnIs the known path distance from the starting point to point n; c. CnIs a point n gravity field characteristic parameter; h isnAn estimate of the minimum distance from point n to the target point; p is a radical of1，p2，p3Are weights.
Preferably, when the dynamic window method is used for planning in step 2, the following evaluation function is used for evaluation to obtain the optimal speed and the optimal angular velocity:
G(v,ω)＝σ(α·heading(v,ω)+β·dist(v,ω)+η·velocity(v,ω))
wherein G (v, omega) is an evaluation function, v is a speed, omega is an angular speed, heading (v, omega) represents an angle difference value between the direction of the underwater vehicle when the underwater vehicle reaches the tail end of the track simulation at the current sampling speed and the direction of a connecting line between the tail end and a target point, dist (v, omega) represents the distance between the underwater vehicle and the nearest obstacle on the current track, velocity (v, omega) represents the speed of the current track, α is a weight, and sigma is a smoothing parameter for smoothing the three weights.
Has the advantages that:
(1) the invention combines the flight path planning with the generation of the gyroscope, the accelerometer and the navigation data to form the long-endurance aircraft track generator, thereby facilitating the verification of theories and methods and reducing the time and cost of actual tests.
(2) According to the invention, the speed, the angular velocity and the course information are converted into centripetal acceleration, tangential acceleration and angular velocity information according to the planned flight path and are used for designing the trajectory generator, the state switching process is natural and continuous, the problem of over-ideal data when a motion state is artificially designed is avoided, the method is closer to the actual state of the motion of an aircraft, and the effectiveness of gravity-assisted inertial navigation research is improved.
Drawings
FIG. 1 is a flow chart of a method for designing a trajectory generator of a long endurance inertial navigation system based on trajectory planning according to an embodiment of the present invention;
FIG. 2 is a trace diagram generated at various stages in accordance with an embodiment of the present invention.
Detailed Description
The invention is described in detail below by way of example with reference to the accompanying drawings.
The invention provides a method for designing a track generator of an inertial navigation system based on track planning, which is different from the traditional method for obtaining a track and corresponding data of a gyroscope and an accelerometer by designing a motion state; the method is characterized in that the method directly starts from track planning, takes gravity field information into consideration in the process of track planning, extracts specific speed, angular speed and course information of the aircraft in the process of navigation by combining condition constraints suffered by the aircraft in underwater motion, and converts the speed and course information into centripetal acceleration, tangential acceleration and angular speed so as to obtain gyroscope and accelerometer data. The flow chart of the method of the invention is shown in figure 1, and the method comprises the following steps:
step 1, planning the track of an aircraft by adopting a track planning algorithm, and considering gravity field information during track planning, wherein the conventional track planning algorithms such as classic A and an improved algorithm thereof, a genetic algorithm, an artificial potential field method and the like can be adopted, and for example, gravity field characteristic parameters can be considered in a cost function when planning the track by adopting the classic A and the improved algorithm thereof; the artificial potential field method can set the area which is not suitable for navigation in the gravity field as an obstacle to carry out track planning; the gravity field characteristic parameters and the like can be considered in the adaptive value when the genetic algorithm and the improved algorithm plan the track; other track planning algorithms can add gravity field information to the algorithm by referring to the above-mentioned idea.
The present embodiment takes the classic a algorithm as an example to illustrate: according to the characteristic of gravity matching, gravity field characteristic parameters are added into a traditional cost function in a classical A-x algorithm to represent the adaptability of the point, and the cost function of the improved point n is
Fn＝p1gn+p2cn+p3hn(1)
Wherein, gnIs the known path distance from the starting point to point n; c. CnIs the gravity field characteristic parameter of point n; h isnIs an estimate of the minimum distance from point n to the target point. p is a radical of1，p2，p3The weight is set according to the requirements of the length of the flight path, the passing position of the flight path, the running time of the algorithm and the like. In general, the Euclidean distance is used to calculate g in the cost function according to the characteristics of the underwater vehiclenAnd hnCharacteristic parameter c of gravitational fieldnAnd determining according to the intensity of the change of the gravity abnormal value in the gravity matching area. The larger the value of the gravity field characteristic parameter is, the better the gravity matching effect is. So for three weights there are
p2＜0 (2)
p1,p3＞0 (3)
The distance is considered, the adaptability of a local area is also considered, and the purpose that the planned flight path passes through an area with obvious gravity field change is achieved.
And 2, planning specific speed, angular speed and course information of the aircraft in the navigation process of the flight path planned and obtained in the step 1 by a Dynamic Window Algorithm (DWA).
A common coordinate system is first defined: the system comprises a geocentric inertial coordinate system (i system), a terrestrial coordinate system (e system), a geographic coordinate system, a carrier coordinate system (b system), a track coordinate system (t system) and a navigation coordinate system (n system). The origin of a track coordinate system (t system) is positioned at the center of gravity of the carrier and fixedly connected with the carrier, the y axis is forward along a track, the x axis is horizontally rightward, a right-hand rectangular coordinate system is formed by the z axis and the xy axis, and the roll angle is not considered in the track coordinate system. The navigation coordinate system (n system) is selected as the geographical coordinate system and the heading angle is defined as being positive when rotating counterclockwise. For underwater vehicles, only advancing and steering are generally carried out, so that the invention does not consider the movement in the direction of the sky, but only the movement in the plane formed by the x and y axes of the navigation coordinate system. Because the distance of motion is short in the adjacent moments of the vehicles, the motion between two adjacent points can be considered as a straight line. At the moment, the speed v and the angular speed omega are planned, and the track can be calculated according to the initial position, the speed and the posture. In general, the motion of an underwater vehicle is constrained by the following conditions:
(1) maximum (angular) velocity (v) of underwater vehiclemax,ωmax) With minimum (angular) velocity (v)min,ωmin) The limit of (2);
(2) limiting the acceleration and deceleration of the underwater vehicle;
(3) the underwater vehicle is limited in (angular) speed under maximum deceleration conditions.
Under the condition of meeting the constraint conditions, sampling is carried out on the velocity v and the angular velocity omega to obtain the velocity v of a sampling pointi(i ═ 1,2,3, …) and ωi(i 1,2,3, …), calculating the trace at time Δ t as
x＝x+viΔt cosψt(4)
y＝y+viΔt sinψt(5)
ψt＝ψt+ωiΔt (6)
Wherein x and y are the position of the underwater vehicle in the navigation system, and delta tFor the time length of the track simulation, psitIs the heading angle of the underwater vehicle. By evaluating the function
G(v,ω)＝σ(α·heading(v,ω)+β·dist(v,ω)+η·velocity(v,ω)) (7)
The method comprises the steps of evaluating a track, wherein the heading (v, omega) represents the angle difference between the orientation of the underwater vehicle when the underwater vehicle reaches the tail end of a track simulation at a current sampling speed and the direction of a connecting line between the tail end and a target point, dist (v, omega) represents the distance between the underwater vehicle and the nearest obstacle on the current track, if no obstacle exists, the dist is set to be a constant, velocity (v, omega) represents the speed of the current track, α represents the proportion occupied by the three evaluation indexes (the angle difference, the distance and the speed), and sigma smoothes the three proportionsoptAnd angular velocity ωopt. In each sampling period, passing through an optimum speed voptAnd angular velocity ωoptAnd (4) traveling, namely, enabling the traveling track to navigate along the track planned in the step 1.
Step 3, obtaining the optimal speed v in the step 2optAnd angular velocity ωoptThe information is converted into centripetal acceleration, tangential acceleration and angular velocity information, and the conversion relationship is as follows:
an＝voptωopt(8)
Figure BDA0002343482960000061
wherein, anFor centripetal acceleration, atIs the tangential acceleration.
Step 4, obtaining the centripetal acceleration a of the underwater vehicle in the step 3nTangential acceleration atAnd angular velocity ωoptThe gyroscope data, accelerometer data, and navigation data may be generated as inputs.
When the underwater vehicle only has forward motion and steering, the projection a of the acceleration under the carrier system at the moment is
a＝[-anat0]T(10)
An attitude angular rate omega of
ω＝[0 0 ωopt]T(11)
From the coordinate system definition, a transformation matrix between coordinate systems can be obtained as
Figure BDA0002343482960000062
Figure BDA0002343482960000063
Figure BDA0002343482960000071
Wherein
Figure BDA0002343482960000072
Is a transformation matrix of the navigation coordinate system to the carrier coordinate system,
Figure BDA0002343482960000073
is a transformation matrix from the trajectory coordinate system to the navigation coordinate system,
Figure BDA0002343482960000074
and transforming the attitude angular rate into a transformation matrix under the carrier system. Psi, theta and gamma are the heading angle, pitch angle and roll angle of the carrier.
The navigation data can be obtained as follows
Figure BDA0002343482960000075
Figure BDA0002343482960000076
Figure BDA0002343482960000077
Wherein v isx,vyAnd vzThe east, north and sky velocities of the underwater vehicle,
Figure BDA0002343482960000078
λ and h are latitude, longitude and altitude.
The gyroscope and accelerometer outputs may then be calculated as
Figure BDA0002343482960000079
Figure BDA00023434829600000710
Wherein
Figure BDA00023434829600000711
Is the projection of the angular velocity of the carrier system relative to the inertial system on the carrier system,
Figure BDA00023434829600000712
for the projection of the angular velocity of the earth rotation on the navigation system,
Figure BDA00023434829600000713
for the projection of the angular velocity of the navigation system relative to the earth system on the navigation system,
Figure BDA00023434829600000714
for the projection of specific forces on the carrier system, vn＝[vxvyvz]TVelocity of the underwater vehicle under the navigation system, gn＝[0 0 g]TAnd g is the acceleration of gravity.
Finally, proper noise is added to the output of the gyroscope and the accelerometer, so that real data can be better simulated.
The invention can effectively overcome the difficulty of artificially designing the motion state during the generation of the traditional flight path and improve the research efficiency of the gravity-assisted inertial navigation system. The invention combines the flight path planning with the generation of the gyroscope, the accelerometer and the navigation data to form the long-endurance aircraft track generator, thereby facilitating the verification of theories and methods such as subsequent gravity matching and the like, and reducing the time and cost of actual tests. In addition, the speed, the angular speed and the course information are converted into centripetal acceleration, tangential acceleration and angular speed information according to the planned flight path and are used for designing the track generator, the state switching process is natural and continuous, the problem that the data is too ideal when the motion state is artificially designed is solved, the problem is closer to the actual state of the motion of the aircraft, and the effectiveness of gravity-assisted inertial navigation research is improved.
The method comprises the steps of selecting a map with 116 multiplied by 116 (unit is a grid) and gravity field parameters, setting the starting point of the underwater vehicle to be [106,99], setting the end point to be [40,30], setting errors of a gyroscope and an accelerometer in a track generator to be 0, and obtaining a track graph of each step through the method, wherein the track graph is shown in figure 2. Wherein, the dot-dash line represents the trajectory planned by the a-x algorithm; the solid line represents the underwater vehicle trajectory generated by the DWA algorithm; the dashed lines represent traces that are resolved from gyroscope and accelerometer data generated by the trace generator. It can be seen that the track obtained by performing inertial navigation calculation on gyroscope and accelerometer data obtained by the design method provided by the invention is almost the same as the track obtained by planning the flight path.
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (4)

1. A design method of a long-endurance inertial navigation system track generator based on track planning is characterized by comprising the following steps:
step 1, planning the track of an aircraft by adopting a track planning algorithm, and considering gravity field information during track planning;
step 2, marking out specific speed, angular speed and course information of the aircraft in the navigation process under the flight path planned and obtained in the step 1 by adopting a dynamic window rule;
step 3, converting the speed, the angular speed and the course information of the underwater vehicle obtained in the step 2 into centripetal acceleration, tangential acceleration and angular speed information;
and 4, generating gyroscope data, accelerometer data and navigation data according to the centripetal acceleration, the tangential acceleration and the angular velocity of the underwater vehicle obtained in the step 3, and finishing the design of the track generator.
2. The method for designing the trajectory generator of the long endurance inertial navigation system based on the trajectory planning of claim 1, wherein in the step 1, the trajectory planning algorithm adopts classical a and its modified algorithm, genetic algorithm or artificial potential field method.
3. The method for designing a trajectory generator of a long-endurance inertial navigation system based on trajectory planning as claimed in claim 2, wherein in step 1, when the classic a-x algorithm is adopted, the cost function F isnComprises the following steps:
Fn＝p1gn+p2cn+p3hn
wherein, gnIs the known path distance from the starting point to point n; c. CnIs a point n gravity field characteristic parameter; h isnAn estimate of the minimum distance from point n to the target point; p is a radical of1，p2，p3Are weights.
4. The method for designing the trajectory generator of the long-endurance inertial navigation system based on the track planning as set forth in claim 1, wherein the evaluation is performed by using the following evaluation function during the dynamic window method planning in the step 2 to obtain the optimal speed and the optimal angular velocity:
G(v,ω)＝σ(α·heading(v,ω)+β·dist(v,ω)+η·velocity(v,ω))
wherein G (v, omega) is an evaluation function, v is a speed, omega is an angular speed, heading (v, omega) represents an angle difference value between the direction of the underwater vehicle when the underwater vehicle reaches the tail end of the track simulation at the current sampling speed and the direction of a connecting line between the tail end and a target point, dist (v, omega) represents the distance between the underwater vehicle and the nearest obstacle on the current track, velocity (v, omega) represents the speed of the current track, α is a weight, and sigma is a smoothing parameter for smoothing the three weights.
CN201911385476.0A 2019-12-29 2019-12-29 Design method of long-endurance inertial navigation system track generator based on track planning Active CN111006694B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911385476.0A CN111006694B (en) 2019-12-29 2019-12-29 Design method of long-endurance inertial navigation system track generator based on track planning

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911385476.0A CN111006694B (en) 2019-12-29 2019-12-29 Design method of long-endurance inertial navigation system track generator based on track planning

Publications (2)

Publication Number Publication Date
CN111006694A true CN111006694A (en) 2020-04-14
CN111006694B CN111006694B (en) 2022-03-18

Family

ID=70118172

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911385476.0A Active CN111006694B (en) 2019-12-29 2019-12-29 Design method of long-endurance inertial navigation system track generator based on track planning

Country Status (1)

Country Link
CN (1) CN111006694B (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114859970A (en) * 2022-04-25 2022-08-05 成都星航时空科技有限公司 Unmanned aerial vehicle risk-free collaborative track planning method in dynamic obstacle environment
CN117251684A (en) * 2023-11-14 2023-12-19 中国船舶集团有限公司第七〇七研究所 Unmanned platform gravity meter data processing method based on multisource information fusion
CN117826819A (en) * 2024-01-02 2024-04-05 中国矿业大学 A three-dimensional obstacle avoidance planning method for UUV based on adaptive dynamic window method

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101424534A (en) * 2008-12-09 2009-05-06 东南大学 Inertia/gravity combined navigation semi-physical object simulating device
CN102298152A (en) * 2010-06-23 2011-12-28 爱信艾达株式会社 Track information generating device, track information generating method, and computer-readable storage medium
CN102508954A (en) * 2011-10-21 2012-06-20 天津大学 Full-digital simulation method and device for global positioning system (GPS)/strapdown inertial navigation system (SINS) combined navigation
JP2016540211A (en) * 2013-11-27 2016-12-22 ザ トラスティーズ オブ ザ ユニバーシティー オブ ペンシルバニア Multi-sensor fusion for stable autonomous flight in indoor and outdoor environments on a rotary airfoil (MAV)
CN106885569A (en) * 2017-02-24 2017-06-23 南京理工大学 A kind of missile-borne deep combination ARCKF filtering methods under strong maneuvering condition
CN108225310A (en) * 2017-12-22 2018-06-29 中国船舶重工集团公司第七0七研究所 A kind of Gravity-aided navigation path planning method
CN109489687A (en) * 2018-11-16 2019-03-19 北京电子工程总体研究所 A kind of emulation verification method and simulation and verification platform for navigation algorithm

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101424534A (en) * 2008-12-09 2009-05-06 东南大学 Inertia/gravity combined navigation semi-physical object simulating device
CN102298152A (en) * 2010-06-23 2011-12-28 爱信艾达株式会社 Track information generating device, track information generating method, and computer-readable storage medium
CN102508954A (en) * 2011-10-21 2012-06-20 天津大学 Full-digital simulation method and device for global positioning system (GPS)/strapdown inertial navigation system (SINS) combined navigation
JP2016540211A (en) * 2013-11-27 2016-12-22 ザ トラスティーズ オブ ザ ユニバーシティー オブ ペンシルバニア Multi-sensor fusion for stable autonomous flight in indoor and outdoor environments on a rotary airfoil (MAV)
CN106885569A (en) * 2017-02-24 2017-06-23 南京理工大学 A kind of missile-borne deep combination ARCKF filtering methods under strong maneuvering condition
CN108225310A (en) * 2017-12-22 2018-06-29 中国船舶重工集团公司第七0七研究所 A kind of Gravity-aided navigation path planning method
CN109489687A (en) * 2018-11-16 2019-03-19 北京电子工程总体研究所 A kind of emulation verification method and simulation and verification platform for navigation algorithm

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
A.M. YAZDANI等: "Time and Energy Efficient Trajectory Generator for Autonomous Underwater Vehicle Docking Operations", 《OCEANS 2016 MTS/IEEE MONTEREY》 *
付梦印等: "水下惯性/重力匹配自主导航综述", 《水下无人系统学报》 *
张婷: "轨迹发生器设计与仿真", 《微计算机信息》 *
洪凯程: "长航时惯性导航模型仿真及验证技术研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 *
范欣等: "一种水下航行器轨迹发生器的设计与仿真", 《鱼雷技术》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114859970A (en) * 2022-04-25 2022-08-05 成都星航时空科技有限公司 Unmanned aerial vehicle risk-free collaborative track planning method in dynamic obstacle environment
CN117251684A (en) * 2023-11-14 2023-12-19 中国船舶集团有限公司第七〇七研究所 Unmanned platform gravity meter data processing method based on multisource information fusion
CN117251684B (en) * 2023-11-14 2024-02-02 中国船舶集团有限公司第七〇七研究所 Unmanned platform gravity meter data processing method based on multisource information fusion
CN117826819A (en) * 2024-01-02 2024-04-05 中国矿业大学 A three-dimensional obstacle avoidance planning method for UUV based on adaptive dynamic window method

Also Published As

Publication number Publication date
CN111006694B (en) 2022-03-18

Similar Documents

Publication Publication Date Title
CN110471450B (en) A method for direct planning of reentry trajectories within an altitude velocity profile
CN110413000B (en) Hypersonic aircraft reentry prediction correction fault-tolerant guidance method based on deep learning
Lugo-Cárdenas et al. Dubins path generation for a fixed wing UAV
CN108416152B (en) Unmanned ship ant colony energy consumption optimal global path planning method based on electronic chart
CN111006694B (en) Design method of long-endurance inertial navigation system track generator based on track planning
CN102393200B (en) General inertial navigation test method based on flight simulation
Evans et al. Dynamics modeling and performance evaluation of an autonomous underwater vehicle
CN108871351B (en) A dynamic path planning method for AUV submarine terrain matching
CN103991559B (en) A kind of Lorentz spacecraft Hovering control method
Jann Advanced features for autonomous parafoil guidance, navigation and control
CN107844128B (en) A kind of hypersonic aircraft cruise section method of guidance based on compositely proportional guiding
CN113310496B (en) Method and device for determining moon-earth transfer track
CN110889170B (en) Method for estimating falling angle and attack angle of large-angle attack target of aircraft
CN104215262A (en) An Online Dynamic Identification Method for Inertial Sensor Errors in Inertial Navigation System
CN104778376A (en) A jump trajectory prediction method for hypersonic glide warhead in near space
CN113900448B (en) A predictive-corrective composite guidance method for aircraft based on sliding mode disturbance observer
CN107390531A (en) The hypersonic aircraft control method of parameter learning finite time convergence control
CN110196066B (en) Virtual Polar Region Method Based on Invariant Grid Attitude and Velocity Information
CN106682361A (en) System and method for simulating flight tracks of unmanned aerial vehicles on basis of GPS (global positioning system) simulation
CN103921957B (en) The energy management method of jumping up that a kind of lunar exploration airship great-jump-forward reenters
CN103616026B (en) A kind of AUV control model based on H ∞ filtering is assisted inertial navigation Combinated navigation method
CN109445283B (en) Control method for fixed-point tracking of under-actuated aerostat on plane
Vuilmet A MIMO backstepping control with acceleration feedback for torpedo
CN115963855A (en) A prediction method of unpowered reentry vehicle landing zone based on deep learning
Zakharin et al. Concept of navigation system design of UAV

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