WO2022135070A1 - Procédé et dispositif de navigation par inertie - Google Patents

Procédé et dispositif de navigation par inertie Download PDF

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Publication number
WO2022135070A1
WO2022135070A1 PCT/CN2021/133976 CN2021133976W WO2022135070A1 WO 2022135070 A1 WO2022135070 A1 WO 2022135070A1 CN 2021133976 W CN2021133976 W CN 2021133976W WO 2022135070 A1 WO2022135070 A1 WO 2022135070A1
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WIPO (PCT)
Prior art keywords
acceleration data
kalman filter
data
mobile terminal
inertial navigation
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PCT/CN2021/133976
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English (en)
Chinese (zh)
Inventor
郭为
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北京紫光展锐通信技术有限公司
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Publication of WO2022135070A1 publication Critical patent/WO2022135070A1/fr

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    • 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

Definitions

  • the embodiments of the present application relate to the technical field of inertial navigation, and in particular, to an inertial navigation method and device.
  • the Inertial Navigation System takes Newton's laws of mechanics as its working principle, uses the inertial measurement element installed on the carrier to measure the acceleration information of the carrier, and obtains the navigation parameters such as the displacement and velocity of the carrier through integral operation.
  • Inertial navigation has complete autonomy and anti-interference, and has high accuracy in a short period of time.
  • some errors will inevitably be introduced in the entire integration process, and the error will change with time. Accumulated, resulting in poor accuracy for long-term navigation work.
  • the embodiments of the present application provide an inertial navigation method and device, which can effectively reduce the integral error in the inertial navigation and improve the precision of the inertial navigation.
  • an embodiment of the present application provides an inertial navigation method, which is applied to a mobile terminal, and the method includes:
  • the acceleration data is processed based on the first Kalman filter to obtain error data corresponding to the acceleration data, and the first Kalman filter is a zero-order Kalman filter;
  • the target acceleration data is processed based on the second Kalman filter to obtain motion data of the mobile terminal.
  • the acceleration data is processed based on the error data to obtain processed target acceleration data, including:
  • a difference between the acceleration data and the error data is calculated, and the difference is determined as the target acceleration data.
  • the target acceleration data is processed based on the second Kalman filter to obtain the motion data of the mobile terminal, including:
  • the second Kalman filter is a second-order Kalman filter.
  • an inertial navigation device which is applied to a mobile terminal, and the device includes:
  • a measurement module configured to obtain acceleration data of the mobile terminal by measuring the acceleration measurement device of the mobile terminal
  • the first processing module is configured to process the acceleration data based on the first Kalman filter, obtain error data corresponding to the acceleration data, and process the acceleration data based on the error data to obtain the processed acceleration data.
  • target acceleration data the first Kalman filter is a zero-order Kalman filter;
  • the second processing module is configured to process the target acceleration data based on the second Kalman filter to obtain motion data of the mobile terminal.
  • the first processing module is used for:
  • a difference between the acceleration data and the error data is calculated, and the difference is determined as the target acceleration data.
  • the second processing module is used for:
  • the second Kalman filter is a second-order Kalman filter.
  • an embodiment of the present application provides a mobile terminal, including at least one processor and a memory;
  • the memory stores computer-executable instructions
  • the at least one processor executes computer-implemented instructions stored in the memory, causing the at least one processor to perform the inertial navigation method as provided by the first aspect.
  • an embodiment of the present application provides a computer-readable storage medium, where computer-executable instructions are stored in the computer-readable storage medium, and when a processor executes the computer-executable instructions, the inertial navigation provided in the first aspect is implemented method.
  • an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the inertial navigation method provided in the first aspect.
  • the acceleration data of the mobile terminal is obtained by measuring the acceleration measurement device of the mobile terminal
  • the acceleration data is processed based on the first Kalman filter to obtain the corresponding acceleration data.
  • error data and use the error data to process the acceleration data to obtain the processed target acceleration data, and then process the above-mentioned target acceleration data based on the second Kalman filter to obtain the velocity data and displacement data of the mobile terminal
  • the first Kalman filter is a zero-order Kalman filter.
  • the first Kalman filter is used to process the acceleration data, so that the error of the acceleration data can be eliminated in real time, and then the second Kalman filter is used to process the acceleration data.
  • the controller calculates the motion data of the mobile terminal, so that the integration error can be eliminated in real time during the inertial navigation process, and the accuracy of the inertial navigation can be improved.
  • FIG. 1 is a schematic structural diagram of an inertial navigation processing system provided in an embodiment of the application.
  • FIG. 2 is a schematic flowchart of an inertial navigation method provided in an embodiment of the present application.
  • FIG. 3 is a schematic diagram of a curve of acceleration data obtained by measurement in an embodiment of the application and error data processed by the first Kalman filter;
  • FIG. 4 is a schematic diagram of the comparison of the speed data curve obtained after being processed by the first Kalman filter and the second Kalman filter simultaneously and the speed data curve obtained without being processed by the first Kalman filter in the embodiment of the application;
  • Fig. 5 is the comparative schematic diagram of the displacement data curve obtained after the first Kalman filter and the second Kalman filter are processed simultaneously in the embodiment of the application and the displacement data curve obtained without being processed by the first Kalman filter;
  • FIG. 6 is a schematic diagram of a program module of an inertial navigation device provided in an embodiment of the application.
  • FIG. 7 is a schematic diagram of a hardware structure of a mobile terminal provided in an embodiment of the present application.
  • Inertial Navigation System also known as inertial reference system
  • inertial reference system is an autonomous navigation system that does not rely on external information and does not radiate energy to the outside (such as radio navigation). Its working environment includes not only the air, the ground, but also underwater.
  • the basic working principle of inertial navigation is based on Newton's laws of mechanics. By measuring the acceleration of the mobile terminal in the inertial reference frame, integrating it with time, and transforming it into the navigation coordinate system, the mobile terminal can be obtained. Information such as velocity, yaw angle, and displacement in the navigation coordinate system.
  • an embodiment of the present application provides an inertial navigation method. After the acceleration data of the mobile terminal is measured, the zero-order Kalman filter is used to eliminate the error of the acceleration data, and then the second Kalman filter is used. The controller calculates the motion data of the mobile terminal, so that the integration error can be eliminated in real time during the inertial navigation process, and the accuracy of the inertial navigation can be improved.
  • FIG. 1 is a schematic structural diagram of an inertial navigation processing system provided in the embodiments of the present application.
  • the first Kalman filter is used to process the acceleration data to obtain error data corresponding to the acceleration data, and then the above-mentioned acceleration data are processed based on the obtained error data.
  • the processed target acceleration data is processed by the second Kalman filter, and the velocity data and displacement data of the mobile terminal can be obtained.
  • the second Kalman filter is a schematic structural diagram of an inertial navigation processing system provided in the embodiments of the present application.
  • FIG. 2 is a schematic flowchart of an inertial navigation method provided by an embodiment of the present application, which can be applied to a mobile terminal.
  • the above inertial navigation method includes:
  • the above-mentioned mobile terminal may be a mobile phone, a vehicle-mounted terminal, a POS machine, or the like.
  • the above acceleration measurement device may use an acceleration sensor.
  • an acceleration sensor composed of a mass block, a damper, an elastic element, a sensitive element and an adaptive circuit can be obtained by using Newton's second law by measuring the inertial force on the mass block during the acceleration process of the mobile terminal. acceleration value.
  • the types of acceleration sensors that can be used include capacitive acceleration sensors, inductive acceleration sensors, strain-type acceleration sensors, piezoresistive acceleration sensors, piezoelectric acceleration sensors, and the like.
  • S202 Process the acceleration data based on the first Kalman filter to obtain error data corresponding to the acceleration data.
  • the calculation of the Kalman filter is based on the state equation, so the state equation of the inertial navigation system needs to be determined first.
  • the state equation is set as:
  • X(k) is the current state
  • X(k+1) is the state at the next moment
  • ⁇ is the transition matrix
  • B is the control matrix
  • u is the control quantity
  • ⁇ is the noise matrix
  • W is the system noise
  • Y is the output quantity
  • H is the output matrix
  • V is the observation noise. That is, the observed output at this moment and the state at the next moment can be obtained from the known state, control quantity and system noise at the current moment.
  • the above-mentioned first Kalman filter adopts the zero-order Kalman filter, namely:
  • FIG. 3 Schematic diagram of the curve of the error data after Kalman filter processing.
  • the difference between the acceleration data and the error data may be calculated, and the difference may be determined as the target acceleration data.
  • X(k) is the current state
  • X(k+1) is the state at the next moment
  • ⁇ is the transition matrix
  • B is the control matrix
  • u is the control quantity
  • ⁇ is the noise matrix
  • W is the system noise
  • Y is the output quantity
  • H is the output matrix
  • V is the observation noise. That is, the observable output at this moment and the state at the next moment can be obtained from the known state, control quantity and system noise at the current moment.
  • the above state includes the acceleration, velocity and displacement of the mobile terminal, that is, X(k) includes a vector of acceleration, velocity and displacement:
  • the state transition matrix ⁇ is a matrix that expresses the relationship between the state at the next moment and the state at this moment. Assuming that the sampling period T is relatively short, it can be approximated that the acceleration a is almost constant, then:
  • integral operation can be performed on the above target acceleration data to obtain velocity data and displacement data of the mobile terminal.
  • FIG. 4 and FIG. 5 are the first Kalman filter in the embodiment of the application.
  • the first Kalman filter is used to process the acceleration data, so that the error of the acceleration data can be eliminated in real time, and then the second Kalman filter is used to process the acceleration data.
  • the Kalman filter calculates the speed data and displacement data of the mobile terminal, so that the integration error can be eliminated in real time during the inertial navigation process, and the accuracy of the inertial navigation can be improved.
  • FIG. 6 is a schematic diagram of a program module of an inertial navigation device provided in an embodiment of the application, and the inertial navigation device 60 includes:
  • the measurement module 601 is configured to obtain acceleration data of the mobile terminal by measuring the acceleration measurement device of the mobile terminal.
  • the first processing module 602 is configured to process the acceleration data based on the first Kalman filter to obtain error data corresponding to the acceleration data, and process the acceleration data based on the error data to obtain processed target acceleration data , the above-mentioned first Kalman filter is a zero-order Kalman filter.
  • the second processing module 603 is configured to process the above-mentioned target acceleration data based on the second Kalman filter to obtain motion data of the mobile terminal.
  • the first Kalman filter is used to process the acceleration data, which can eliminate the error of the acceleration data in real time, and then use the first Kalman filter to process the acceleration data.
  • the second Kalman filter calculates the motion data of the mobile terminal, so that the integration error can be eliminated in real time during the inertial navigation process, and the accuracy of the inertial navigation can be improved.
  • the above-mentioned first processing module is used for:
  • a difference between the acceleration data and the error data is calculated, and the difference is determined as the target acceleration data.
  • the above-mentioned second processing module is used for:
  • the above-mentioned second Kalman filter is a second-order Kalman filter.
  • an embodiment of the present application further provides a mobile terminal, the mobile terminal includes at least one processor and a memory; wherein, the memory stores computer execution instructions; the above-mentioned at least one processor The computer-executed instructions stored in the memory are executed to implement each step in the inertial navigation method described in the above embodiments, which will not be repeated here.
  • FIG. 7 is a schematic diagram of a hardware structure of a mobile terminal according to an embodiment of the present application.
  • the mobile terminal 70 in this embodiment includes: a processor 701 and a memory 702; wherein:
  • a memory 702 for storing computer-executed instructions
  • the processor 701 is configured to execute the computer-executed instructions stored in the memory, so as to implement each step in the inertial navigation method described in the foregoing embodiments, which will not be repeated here.
  • the memory 702 may be independent or integrated with the processor 701 .
  • the device further includes a bus 703 for connecting the memory 702 and the processor 701 .
  • the embodiments of the present application further provide a computer-readable storage medium, where computer-executable instructions are stored in the computer-readable storage medium, and when the processor executes the computer-executable instructions In order to implement each step in the inertial navigation method as described in the above embodiment, the details are not repeated here.
  • the embodiments of the present application further provide a computer program product, including a computer program, which, when executed by a processor, implements the inertial navigation described in the foregoing embodiments Each step in the method will not be repeated here.
  • the disclosed apparatus and method may be implemented in other manners.
  • the device embodiments described above are only illustrative.
  • the division of the modules is only a logical function division. In actual implementation, there may be other division methods.
  • multiple modules may be combined or integrated. to another system, or some features can be ignored, or not implemented.
  • the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or modules, and may be in electrical, mechanical or other forms.
  • modules described as separate components may or may not be physically separated, and components shown as modules may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment.
  • each functional module in each embodiment of the present application may be integrated in one processing unit, or each module may exist physically alone, or two or more modules may be integrated in one unit.
  • the units formed by the above modules can be implemented in the form of hardware, or can be implemented in the form of hardware plus software functional units.
  • the above-mentioned integrated modules implemented in the form of software functional modules may be stored in a computer-readable storage medium.
  • the above-mentioned software function modules are stored in a storage medium, and include several instructions to enable a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (English: processor) to execute the various embodiments of the present application. part of the method.
  • processor may be a central processing unit (English: Central Processing Unit, referred to as: CPU), or other general-purpose processors, digital signal processors (English: Digital Signal Processor, referred to as: DSP), application-specific integrated circuits (English: Application Specific Integrated Circuit, referred to as: ASIC) and so on.
  • a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in conjunction with the application can be directly embodied as executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.
  • the memory may include high-speed RAM memory, and may also include non-volatile storage NVM, such as at least one magnetic disk memory, and may also be a U disk, a removable hard disk, a read-only memory, a magnetic disk or an optical disk, and the like.
  • NVM non-volatile storage
  • the bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, or the like.
  • ISA Industry Standard Architecture
  • PCI Peripheral Component
  • EISA Extended Industry Standard Architecture
  • the bus can be divided into address bus, data bus, control bus and so on.
  • the buses in the drawings of the present application are not limited to only one bus or one type of bus.
  • the above-mentioned storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable Except programmable read only memory (EPROM), programmable read only memory (PROM), read only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.
  • SRAM static random access memory
  • EEPROM electrically erasable programmable read only memory
  • EPROM erasable except programmable read only memory
  • PROM programmable read only memory
  • ROM read only memory
  • magnetic memory flash memory
  • flash memory magnetic disk or optical disk.
  • a storage medium can be any available medium that can be accessed by a general purpose or special purpose computer.
  • An exemplary storage medium is coupled to the processor, such that the processor can read information from, and write information to, the storage medium.
  • the storage medium can also be an integral part of the processor.
  • the processor and the storage medium may be located in application specific integrated circuits (Application Specific Integrated Circuits, ASIC for short).
  • ASIC Application Specific Integrated Circuits
  • the processor and the storage medium may also exist in the electronic device or the host device as discrete components.
  • the aforementioned program can be stored in a computer-readable storage medium.
  • the steps including the above method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

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

La présente invention concerne un procédé et un appareil de navigation par inertie, un terminal mobile, un support de stockage lisible par ordinateur et un produit de programme informatique. Ledit procédé comprend les étapes consistant à : utiliser un dispositif de mesure d'accélération d'un terminal mobile pour obtenir des données d'accélération du terminal mobile (S201) ; traiter les données d'accélération sur la base d'un premier filtre de Kalman pour obtenir des données d'erreur correspondant aux données d'accélération, le premier filtre de Kalman étant un filtre de Kalman d'ordre zéro (S202) ; traiter les données d'accélération sur la base des données d'erreur, pour obtenir des données d'accélération cible traitées (S203) ; et traiter les données d'accélération cible sur la base d'un second filtre de Kalman pour obtenir des données de déplacement du terminal mobile (S204). Dans ledit procédé, une fois que les données d'accélération du terminal mobile sont mesurées, l'erreur des données d'accélération est éliminée d'abord au moyen du premier filtre de Kalman, puis les données de déplacement du terminal mobile sont calculées au moyen du second filtre de Kalman, de telle sorte qu'une élimination en temps réel d'une erreur d'intégration peut être effectuée pendant un procédé de navigation par inertie, ce qui permet d'améliorer la précision de la navigation par inertie.
PCT/CN2021/133976 2020-12-24 2021-11-29 Procédé et dispositif de navigation par inertie WO2022135070A1 (fr)

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