CN106871893A - Distributed INS/UWB tight integrations navigation system and method - Google Patents

Distributed INS/UWB tight integrations navigation system and method Download PDF

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Publication number
CN106871893A
CN106871893A CN201710123870.1A CN201710123870A CN106871893A CN 106871893 A CN106871893 A CN 106871893A CN 201710123870 A CN201710123870 A CN 201710123870A CN 106871893 A CN106871893 A CN 106871893A
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uwb
inertial navigation
navigation device
information
data
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徐元
程金
赵钦君
王滨
部丽丽
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University of Jinan
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University of Jinan
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12Navigation; 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
    • G01C21/16Navigation; 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
    • G01C21/165Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments

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  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Automation & Control Theory (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Navigation (AREA)

Abstract

The invention discloses a kind of distributed INS/UWB tight integrations navigation system and method, system includes inertial navigation device, pseudorange detection unit, wireless system for transmitting data and data handling system;Inertial navigation device, the navigation information for measuring pedestrian, navigation information includes position, speed and attitude information;Pseudorange detection unit, for obtaining pseudo-range information:Wireless system for transmitting data, it is connected with inertial navigation device and pseudorange detection unit, data for inertial navigation device and pseudorange detection unit to be gathered are delivered in data handling system by being wirelessly transferred, and the control command that data handling system sends is delivered in the inertial navigation device;The data handling system:Using Distributed Database cluster estimation unit, for carrying out data fusion estimation to the data for collecting, and control command is sent to inertial navigation device, the present invention can reduce influence of the indoor complexity navigational environment to integrated navigation precision, obtain the optimal predictor of target pedestrian's navigation information.

Description

Distributed INS/UWB tight integrations navigation system and method
Technical field
The present invention relates to combine field of locating technology, more particularly to a kind of distributed INS/UWB tight integrations under complex environment Navigation system and method.
Background technology
In recent years, pedestrian navigation (Pedestrian Navigation, PN) is used as the emerging field of airmanship application, Just increasingly paid attention to by scholars, and be increasingly becoming the study hotspot in the field.But tunnel, bulk storage plant, The factor such as under the indoor environments such as lower parking lot, extraneous radio signal is faint, electromagnetic interference is strong all can be to target pedestrian navigation The accuracy of acquisition of information, real-time and robustness have a significant impact.How the limited information that will be obtained under indoor environment is carried out Effective fusion influence with complex environment in decontamination chamber, it is ensured that pedestrian navigation precision it is continual and steady, with important section's scientific principle By meaning and actual application value.
In existing positioning method, GPS (Global Navigation Satellite System, GNSS) it is a kind of the most commonly used mode.Although GNSS can by the continual and steady positional information of precision, It is easily limited its range of application by electromagnetic interference, the shortcoming external environment such as blocked and influenceed, particularly indoors, underground passage Deng the scene that some closed, environment are complicated, GNSS signal is seriously blocked, it is impossible to effectively worked.In recent years, UWB (Ultra Wideband) is shown very the characteristics of positioning precision is high under complex environment with it in short distance local positioning field Big potentiality.Scholars propose the pedestrian navigation being applied to the target following based on UWB under GNSS failure environment.This mode Although indoor positioning can be realized, because indoor environment is complicated and changeable, UWB signal is very easily interfered and causes to determine Position precise decreasing even losing lock;At the same time, because the communication technology that UWB is used is usually short-distance wireless communication technology, because If this wants to complete large-scale indoor objects track and localization, it is necessary to substantial amounts of network node is completed jointly, this will introduce network A series of problems, such as organizational structure optimization design, many cluster network cooperatings of multinode communicate.Therefore at this stage based on UWB target with Navigation field still faces many challenges to track indoors.
In terms of navigation model, what pedestrian's integrated navigation field application indoors was more at present is pine combination navigation model. The model has the advantages that easily realization, it should be noted however that the realization of the model needs to participate in the various of integrated navigation Technology can singly complete navigator fix.For example, it is desired to UWB equipment can provide the navigation information of pedestrian, this requires mesh Environment residing for mark pedestrian allows for obtaining at least 3 reference mode information, and this greatly reduces integrated navigation model Range of application, at the same time, participates in the sub- technology complete independently positioning of navigation, have also been introduced new error, is unfavorable for that combination is led The raising of boat technology acuracy.In order to overcome this problem, scholars propose for tight integration model to be applied to indoor pedestrian navigation neck The original sensor data for participating in the sub- technology of integrated navigation is directly applied to last navigation information by domain, tight integration model Resolve, reduce sub- technology and voluntarily resolve the risk for introducing new error, improve the precision of integrated navigation, however it is necessary that point out It is that existing tight integration navigation model uses Centralized Mode, and this mode Fault Tolerance is poor, and is unfavorable for increasingly accurate Complicated integrated navigation model.
Patent document《A kind of IMU/WSN Combinated navigation methods towards indoor mobile robot》In, its method is in WSN Pseudorange estimates part and has used local filter, effectively raises the estimate accuracy of pseudorange, but in follow-up data fusion portion Point still use Centralized Mode, and Centralized Mode to cause that this centralized Integrated navigation mode can not still improve its fault-tolerant Ability, therefore, it is necessary to the relevant issues to how to improve navigation system fault-tolerant ability are studied.
The content of the invention
In order to solve the deficiencies in the prior art, the invention provides a kind of distributed INS/UWB tight integrations navigation system, can Influence of the indoor complexity navigational environment to integrated navigation precision is reduced, the optimal predictor of target pedestrian's navigation information is obtained.
The technical solution adopted by the present invention is:
A kind of distributed INS/UWB tight integrations navigation system, it is characterised in that detected including inertial navigation device, pseudorange Unit, wireless system for transmitting data and data handling system;
The inertial navigation device, the navigation information for measuring pedestrian, the navigation information includes position, speed and appearance State information;
The pseudorange detection unit, for obtaining pseudo-range information:
The wireless system for transmitting data, is connected with inertial navigation device and pseudorange detection unit, for by inertial navigation The data that device and pseudorange detection unit are gathered are delivered in data handling system by being wirelessly transferred, and by data processing system The control command for sending of uniting is delivered in the inertial navigation device;
The data handling system:Using Distributed Database cluster estimation unit, for entering line number to the data for collecting Estimate according to fusion, and control command is sent to inertial navigation device.
Further, setting subdata is melted during the Distributed Database cluster estimation unit is included in each radio communication channel Close unit, the result of subdata integrated unit retransmited to master data integrated unit, the result according to master data integrated unit and The result of inertial navigation device measurement obtains the optimal positional information of target pedestrian at current time.
Further, the data fusion unit uses extended Kalman filter, by the EKF The navigation information of the target pedestrian that device is obtained to inertial navigation device, and existed by the pseudo-range information that UWB positions label acquisition Data fusion estimation is carried out in radio communication channel.
Further, the pseudorange detection unit includes that UWB positions label and UWB reference modes;The UWB reference modes The position of setting is previously positioned at, inertial navigation device and UWB positioning labels are separately fixed at pedestrian;By measuring UWB The distance between positioning label and UWB reference modes, obtain pseudo-range information.
Further, the UWB reference modes also can be placed in optional position.
Further, the extended Kalman filter carries out data and melts by the iteration to observational equation and state equation Close and estimate.
The invention allows for a kind of distributed INS/UWB tight integrations air navigation aid, using following steps:
(1) positional information using the error vector of inertial navigation device and each UWB reference modes is used as quantity of state, with inertia The positional information and pseudo-range information of the target pedestrian of navigational material collection are measured as systematic perspective, are built INS/UWB tight integrations and are led Model plane type;
(2) according to the INS/UWB tight integrations navigation model, by the navigation of target pedestrian in each radio communication channel Information and pseudo-range information carry out data fusion estimation, obtain Current wireless communication channel, the navigation of the target pedestrian at current time Information optimal estimation;
(3) optimal estimation for obtaining in each radio communication channel is carried out into data fusion estimation again, obtains target pedestrian The error of optimal location information is estimated, and the target pedestrian positional information that inertial navigation device is collected is with the target pedestrian most The error of excellent positional information is estimated and subtracted each other, and obtains the optimal positional information of the target pedestrian at current time.
Further, the data fusion is estimated to use expanded Kalman filtration algorithm.
Further, the quantity of state includes the error vector of inertial navigation device and east orientation, the north of each UWB reference modes To positional information.
Further, the systematic perspective is measured as the east orientation of target pedestrian and the quadratic sum of north orientation positional information with pseudorange letter The difference of breath square.
Further, the error vector of the inertial navigation device and the east orientation with each UWB reference modes, north orientation position letter Breath has initial value, and initial value is self-defining value.
Further, the expanded Kalman filtration algorithm carries out data using the iteration to observational equation and state equation Fusion is estimated.
Further, the state equation of extended Kalman filter is in i-th radio communication channel:
Wherein,The navigation that respectively k moment and k+1 moment INS measurements obtain is sat Two velocity errors in direction of east orientation and north orientation of the lower target pedestrian of mark system; During respectively k Carve two site errors in direction of east orientation and north orientation with target pedestrian under k+1 moment navigational coordinate systems;ωkFor state is made an uproar Sound, its covariance matrix is Qith;T is the sampling period.
Further, the observational equation of extended Kalman filter is in i-th radio communication channel:
Wherein,The east orientation resolved for k moment inertial navigation devices IMU and north orientation position;It is k moment IMU The unknown node that obtains of measurement is to the pseudorange between i-th reference mode;For the unknown node that k moment UWB measurements are obtained is arrived Pseudorange between i-th reference mode;It is i-th coordinate of reference mode,It is observation noise, its covariance Battle array is Qith
Further, in the radio communication channel in extended Kalman filter spreading kalman algorithm iterative equation For:
Wherein,
Further, the iterative equation of the master data fusion estimation unit is:
Compared with prior art, the beneficial effects of the invention are as follows:
(1) present invention uses commonwealth filter technique, and pseudorange (the i.e. anchor accessed by positioning label is built in the wireless channel The distance between node and target pedestrian) sensor raw data such as target pedestrian's navigation information for resolving of information, inertia device Model between the pedestrian navigation information and navigational environment information that are obtained with final needs, to reduce indoor complexity navigational environment pair The influence of integrated navigation precision, is that local filter is completed to estimate the high accuracy of navigation information and laid the first stone.Each communication channel The navigation information estimated carries out data fusion by senior filter, to complete the optimal predictor to target pedestrian's navigation information.
(2) Combinated navigation method uses improved INS/UWB tight integrations model, the model to be resolved with INS and obtain target line The pseudorange that the east orientation of people and the quadratic sum of north orientation positional information and UWB positioning label measurements are obtained square difference as systematic perspective Measurement;On this basis, filtered by EKF carries out data fusion by the navigation information that INS and UWB is obtained, and finally gives current Moment optimal navigation information and reference mode positional information is estimated.Improve the precision and robust of Data Fusion Filtering device Property.
(3) by building distributed integrated navigation system, compared to patent document《It is a kind of towards indoor mobile robot IMU/WSN Combinated navigation methods》, the present invention uses distributed junction filter in the part that data fusion is estimated, by data Fused filtering device is applied in UWB radio communication channels, increased system survivability.
(4) high accuracy positioning in the pedestrian that can be used under indoor environment.
Brief description of the drawings
The Figure of description for constituting the part of the application is used for providing further understanding of the present application, and the application's shows Meaning property embodiment and its illustrated for explaining the application, does not constitute the improper restriction to the application.
Fig. 1 is a kind of distributed INS/UWB tight integrations navigation system schematic diagram;
Fig. 2 is a kind of schematic diagram of distributed INS/UWB tight integrations air navigation aid.
Specific embodiment
It is noted that described further below is all exemplary, it is intended to provide further instruction to the application.Unless another Indicate, all technologies used herein and scientific terminology are with usual with the application person of an ordinary skill in the technical field The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singulative Be also intended to include plural form, additionally, it should be understood that, when in this manual use term "comprising" and/or " bag Include " when, it indicates existing characteristics, step, operation, device, component and/or combinations thereof.
EKF:Extended Kalman filter;
IMU:Inertial navigation device;
INS:Inertial navigation system.
Embodiment 1:As shown in figure 1, a kind of distributed INS/UWB tight integrations navigation system, including inertial navigation device, puppet Away from detection unit, wireless system for transmitting data and data handling system;
Inertial navigation device, the navigation information for measuring pedestrian, navigation information includes position, speed and attitude information; Pseudorange detection unit, for obtaining pseudo-range information:Wireless system for transmitting data, with inertial navigation device and pseudorange detection unit phase Even, it is delivered to data handling system by being wirelessly transferred for the data for being gathered inertial navigation device and pseudorange detection unit In, and the control command that data handling system sends is delivered in the inertial navigation device;Data handling system:Using point Cloth data fusion estimation unit, for the data for collecting to be carried out with data fusion estimation, and sends to inertial navigation device Control command.
Pseudorange detection unit includes that UWB positions label and UWB reference modes;UWB reference modes are previously positioned at setting Position, inertial navigation device and UWB positioning labels are separately fixed at pedestrian;Label is positioned with UWB references by measuring UWB The distance between node, obtains pseudo-range information.
UWB reference modes also can be placed in optional position.
Distributed Database cluster estimation unit sets subdata integrated unit, subdata in being included in each radio communication channel The result of integrated unit is retransmited to master data integrated unit, and the result and inertial navigation device according to master data integrated unit are surveyed The result of amount obtains the optimal positional information of target pedestrian at current time.
Data fusion unit uses extended Kalman filter, by the extended Kalman filter to inertial navigation device Part obtain target pedestrian navigation information, and by UWB position label obtain pseudo-range information in radio communication channel Carry out data fusion estimation.
Extended Kalman filter carries out data fusion estimation by the iteration to observational equation and state equation.
Embodiment 2:As shown in Fig. 2 a kind of distributed INS/UWB tight integrations air navigation aid, using following steps:
(1) positional information using the error vector of inertial navigation device and each UWB reference modes is used as quantity of state, with inertia The positional information and pseudo-range information of the target pedestrian of navigational material collection are measured as systematic perspective, are built INS/UWB tight integrations and are led Model plane type;
(2) according to the INS/UWB tight integrations navigation model, by the navigation of target pedestrian in each radio communication channel Information and pseudo-range information carry out data fusion estimation, obtain Current wireless communication channel, the navigation of the target pedestrian at current time Information optimal estimation;
(3) optimal estimation for obtaining in each radio communication channel is carried out into data fusion estimation again, obtains target pedestrian The error of optimal location information is estimated, and the target pedestrian positional information that inertial navigation device is collected is with the target pedestrian most The error of excellent positional information is estimated and subtracted each other, and obtains the optimal positional information of the target pedestrian at current time.
Data fusion is estimated to use expanded Kalman filtration algorithm.The error vector of quantity of state including inertial navigation device and The east orientation of each UWB reference modes, north orientation positional information.Systematic perspective is measured as the east orientation of target pedestrian and putting down for north orientation positional information Side and and pseudo-range information square difference.
The error vector of inertial navigation device and the east orientation with each UWB reference modes, north orientation positional information have initial value, Initial value is self-defining value.Expanded Kalman filtration algorithm carries out data fusion using the iteration to observational equation and state equation Estimate.
Embodiment 3:A kind of distributed INS/UWB tight integrations navigation, including:Inertial navigation device IMU, UWB positioning label, UWB reference modes and data handling system;
Inertial navigation device INS and UWB positioning label are separately positioned on the cap of pedestrian, and UWB reference modes are arranged on Optional position, inertial navigation device INS and UWB positioning label is connected with data handling system respectively.
Wherein, inertial navigation device INS:The navigation information such as position, speed and attitude for measuring pedestrian;
UWB positions label:For measuring the distance between UWB positioning labels and reference mode information, i.e. pseudo-range information;
UWB reference modes:Known position is previously positioned at, is easy to measurement and is positioned the distance between label;
Data handling system:For carrying out data fusion to the sensing data for collecting.
Data handling system includes EKF wave filters, by the EKF to inertial navigation device INS in local relative coordinate The pseudo-range information that navigation information and UWB the positioning label of the target pedestrian obtained in system are obtained in local relative coordinate system enters Row data fusion.
Embodiment 4:A kind of distributed INS/UWB tight integrations air navigation aid, including:
(1) using the error vector of inertial navigation device INS as quantity of state, obtained with inertial navigation device INS measurements The pseudorange that the east orientation of target pedestrian and the quadratic sum of north orientation positional information and UWB positioning label measurements are obtained square difference conduct Systematic perspective is measured, and distribution INS/UWB tight integration models are built in communication channel;
(2) inertial navigation device INS and UWB are positioned into label by EKF wave filters to be obtained in local relative coordinate system The navigation information of target pedestrian carry out data fusion;The output of EKF wave filters is to obtain current time to be obtained based on wireless channel The optimal estimation of the target pedestrian that takes optimal navigation information and reference mode position.
The state equation of EKF wave filters is in i-th radio communication channel:
Wherein,The navigation that respectively k moment and k+1 moment INS measurements obtain is sat Two velocity errors in direction of east orientation and north orientation of the lower target pedestrian of mark system; During respectively k Carve two site errors in direction of east orientation and north orientation with target pedestrian under k+1 moment navigational coordinate systems;ωkFor state is made an uproar Sound, its covariance matrix is Qith;T is the sampling period.
The observational equation of EKF wave filters is in i-th radio communication channel:
Wherein,The east orientation resolved for k moment inertia devices IMU and north orientation position;For k moment IMU is measured The unknown node for obtaining is to the pseudorange between i-th reference mode;The unknown node obtained for k moment UWB measurements is to i-th Pseudorange between individual reference mode;It is i-th coordinate of reference mode,It is observation noise, its covariance matrix It is Qith
The iterative equation of EKF algorithms is in EKF wave filters in the radio communication channel:
Wherein,
The iterative equation of the senior filter is:
The preferred embodiment of the application is the foregoing is only, the application is not limited to, for the skill of this area For art personnel, the application can have various modifications and variations.It is all within spirit herein and principle, made any repair Change, equivalent, improvement etc., should be included within the protection domain of the application.

Claims (10)

1. a kind of distributed INS/UWB tight integrations navigation system, it is characterised in that single including inertial navigation device, pseudorange detection Unit, wireless system for transmitting data and data handling system;
The inertial navigation device, the navigation information for measuring pedestrian, the navigation information includes position, speed and attitude letter Breath;
The pseudorange detection unit, for obtaining pseudo-range information:
The wireless system for transmitting data, is connected with inertial navigation device and pseudorange detection unit, for by inertial navigation device The data gathered with pseudorange detection unit are delivered in data handling system by being wirelessly transferred, and data handling system is sent out The control command sent is delivered in the inertial navigation device;
The data handling system:Using Distributed Database cluster estimation unit, melt for carrying out data to the data for collecting Close and estimate, and control command is sent to inertial navigation device.
2. system according to claim 1, it is characterised in that:The pseudorange detection unit includes that UWB positions label and UWB Reference mode;The UWB reference modes are previously positioned at the position of setting, and inertial navigation device and UWB positioning labels are solid respectively It is scheduled on pedestrian;The distance between label and UWB reference modes are positioned by measuring UWB, pseudo-range information is obtained.
3. system according to claim 2, it is characterised in that:The UWB reference modes also can be placed in optional position.
4. system according to claim 1, it is characterised in that:The Distributed Database cluster estimation unit is included in each nothing Subdata integrated unit is set in line communication channel, and the result of subdata integrated unit is retransmited to master data integrated unit, root The result measured according to the result and inertial navigation device of master data integrated unit obtains the optimal position of target pedestrian at current time Confidence ceases.
5. system according to claim 1, it is characterised in that:The data fusion unit uses EKF Device, the navigation information of the target pedestrian obtained to inertial navigation device by the extended Kalman filter, and by UWB The pseudo-range information that positioning label is obtained carries out data fusion estimation in radio communication channel.
6. a kind of distributed INS/UWB tight integrations air navigation aid, it is characterised in that use following steps:
(1)Positional information using the error vector of inertial navigation device and each UWB reference modes as quantity of state, with inertial navigation The positional information and pseudo-range information of the target pedestrian of device collection are measured as systematic perspective, build INS/UWB tight integrations navigation mould Type;
(2)According to the INS/UWB tight integrations navigation model, by the navigation information of target pedestrian in each radio communication channel Data fusion estimation is carried out with pseudo-range information, Current wireless communication channel, the navigation information of the target pedestrian at current time is obtained Optimal estimation;
(3)The optimal estimation for obtaining in each radio communication channel is carried out into data fusion estimation again, target pedestrian is obtained optimal The error of positional information is estimated, the target pedestrian positional information that inertial navigation device is collected and the optimal position of target pedestrian The error of confidence breath is estimated and subtracted each other, and obtains the optimal positional information of the target pedestrian at current time.
7. method according to claim 4, it is characterised in that the data fusion is estimated to be calculated using EKF Method.
8. method according to claim 4, it is characterised in that quantity of state includes the error vector of inertial navigation device and each The east orientation of UWB reference modes, north orientation positional information.
9. method according to claim 5, it is characterised in that the error vector of the inertial navigation device and each UWB join Examining the east orientation of node, north orientation positional information has initial value, and initial value is self-defining value.
10. method according to claim 4, it is characterised in that the systematic perspective is measured as east orientation and the north of target pedestrian To the quadratic sum and the difference of pseudo-range information square of positional information.
CN201710123870.1A 2017-03-03 2017-03-03 Distributed INS/UWB tight integrations navigation system and method Pending CN106871893A (en)

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CN107402375B (en) * 2017-08-08 2020-05-05 济南大学 Indoor pedestrian positioning EFIR data fusion system with observation time lag and method
CN107631727A (en) * 2017-09-12 2018-01-26 杭州电子科技大学 A kind of indoor CSS/INS integrated navigation systems
CN107631727B (en) * 2017-09-12 2020-09-01 杭州电子科技大学 Indoor CSS/INS integrated navigation system
CN108680167B (en) * 2018-05-16 2020-10-16 深迪半导体(上海)有限公司 Indoor dead reckoning positioning method and system based on UWB and laser ranging
CN108680167A (en) * 2018-05-16 2018-10-19 深迪半导体(上海)有限公司 Indoor dead reckoning localization method and system based on UWB and laser ranging
CN109000654A (en) * 2018-06-07 2018-12-14 全图通位置网络有限公司 Localization method, device, equipment and storage medium
CN109000654B (en) * 2018-06-07 2022-04-01 全图通位置网络有限公司 Positioning method, device, equipment and storage medium
CN109655060A (en) * 2019-02-19 2019-04-19 济南大学 Based on the KF/FIR and LS-SVM INS/UWB Integrated Navigation Algorithm merged and system
CN109884586A (en) * 2019-03-07 2019-06-14 广东工业大学 Unmanned plane localization method, device, system and storage medium based on ultra-wide band
CN110315540A (en) * 2019-07-15 2019-10-11 南京航空航天大学 One kind being based on the tightly coupled robot localization method and system of UWB and binocular VO
CN111678513A (en) * 2020-06-18 2020-09-18 山东建筑大学 Ultra-wideband/inertial navigation tight coupling indoor positioning device and system
CN112325880A (en) * 2021-01-04 2021-02-05 中国人民解放军国防科技大学 Distributed platform relative positioning method and device, computer equipment and storage medium
CN112325880B (en) * 2021-01-04 2021-03-26 中国人民解放军国防科技大学 Distributed platform relative positioning method and device, computer equipment and storage medium
CN113900061A (en) * 2021-05-31 2022-01-07 深圳市易艾得尔智慧科技有限公司 Navigation positioning system and method based on UWB wireless positioning and IMU fusion

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Application publication date: 20170620