CN118149803B - Inertial measurement method, apparatus, device, computer-readable storage medium, and product - Google Patents
Inertial measurement method, apparatus, device, computer-readable storage medium, and product Download PDFInfo
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- CN118149803B CN118149803B CN202410573849.1A CN202410573849A CN118149803B CN 118149803 B CN118149803 B CN 118149803B CN 202410573849 A CN202410573849 A CN 202410573849A CN 118149803 B CN118149803 B CN 118149803B
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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
- 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
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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
- G01C21/20—Instruments for performing navigational calculations
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Abstract
The application discloses an inertial measurement method, an inertial measurement device, an apparatus, a computer readable storage medium and a product, and relates to the technical field of inertial measurement, wherein the method comprises the following steps: acquiring auxiliary measurement data of the motion carrier, wherein the auxiliary measurement data at least comprises sound velocity meter data and wheel speed meter data; determining the application type of a platform of the motion carrier according to the sound velocity meter data and the wheel speed data; and constructing a target scene measurement model of the moving carrier according to the platform application type and a preset inertial measurement model, and determining navigation positioning data according to the target scene measurement model and the inertial measurement data of the moving carrier. The application aims to construct an inertial measurement model suitable for different application scenes so as to improve the accuracy of inertial measurement.
Description
Technical Field
The present application relates to the field of inertial measurement technology, and in particular, to an inertial measurement method, apparatus, device, computer readable storage medium, and product.
Background
Along with the continuous development of inertial measurement technology, inertial navigation systems are widely applied to various motion carriers, and provide important navigation positioning information for the motion carriers. Therefore, users have placed higher demands on the accuracy of inertial measurements of inertial navigation systems.
The existing inertial measurement mode usually adopts a unified inertial measurement model to conduct inertial calculation on motion carriers in different application scenes. However, although the use of a unified inertial measurement model simplifies the inertial measurement process to some extent, the differences between different application scenarios and motion vectors are ignored. Taking a vehicle-mounted platform and a ship-mounted platform as examples, although the vehicle-mounted platform and the ship-mounted platform are required to be subjected to navigation positioning by depending on an inertial navigation system, the high-precision navigation requirements under different application scenes are hardly met by using a unified inertial measurement model due to the fact that the use environments and the motion characteristics of the vehicle-mounted platform and the ship-mounted platform are obviously different, and the accuracy of inertial measurement is seriously affected.
In summary, how to construct an inertial measurement model suitable for different application scenarios to improve the accuracy of inertial measurement is a technical problem that needs to be solved at present.
Disclosure of Invention
The application mainly aims to provide an inertial measurement method, an inertial measurement device, a computer-readable storage medium and an inertial measurement product, and aims to construct inertial measurement models applicable to different application scenes so as to improve the accuracy of inertial measurement.
To achieve the above object, the present application provides an inertial measurement method including:
acquiring auxiliary measurement data of a motion carrier, wherein the auxiliary measurement data at least comprise sound velocity meter data and wheel speed meter data;
determining a platform application type of the motion carrier according to the sound velocity meter data and the wheel speed meter data;
And constructing a target scene measurement model of the motion carrier according to the platform application type and a preset inertial measurement model, and determining navigation positioning data according to the target scene measurement model and the inertial measurement data of the motion carrier.
In one embodiment, the step of determining the platform application type of the moving carrier from the sonic meter data and the wheel speed meter data comprises:
determining an electrical sound speed signal of the sound speed meter data and an electrical wheel speed signal of the wheel speed meter data;
when the sound velocity electric signal is at a high level and the wheel speed electric signal is at a low level, determining that the platform application type of the motion carrier is a shipboard application platform;
When the sound velocity electric signal is at a low level and the wheel speed electric signal is at a high level, determining that the platform application type of the motion carrier is a vehicle-mounted application platform;
And when the sound velocity electric signal and the wheel speed electric signal are both at low levels, determining that the platform application type of the motion carrier is a universal platform.
In an embodiment, the step of constructing the target scene measurement model of the motion carrier according to the platform application type and a preset inertial measurement model includes:
judging whether the platform application type is the universal platform or not;
if the platform application type is the universal platform, taking a preset inertial measurement model as a target scene measurement model of the motion carrier;
and if the platform application type is not the universal platform, updating the inertial measurement model according to the platform application type to obtain the target scene measurement model.
In one embodiment, the step of updating the inertial measurement model according to the platform application type to obtain the target scene measurement model includes:
Acquiring initial error parameters and measurement error parameters corresponding to the platform application type from the inertial measurement model, and determining an initial variance matrix and a measurement variance matrix designated by the inertial measurement model;
Updating the initial variance value of the initial error parameter mapping in the initial variance matrix and the measurement variance value of the measurement error parameter mapping in the measurement variance matrix according to the platform application type to obtain an updated initial variance matrix and an updated measurement variance matrix;
and constructing the target scene measurement model according to the updated initial variance matrix and the updated measurement variance matrix.
In one embodiment, the step of determining navigational positioning data based on the target scenario measurement model and inertial measurement data of the moving carrier comprises:
determining inertial measurement data of the motion carrier, and obtaining a pose initial value of the motion carrier according to the inertial measurement data;
And carrying out Kalman filtering calculation on the pose initial value according to the target scene measurement model to obtain a pose compensation value, and overlapping the pose compensation value on the pose initial value to obtain navigation positioning data.
In addition, in order to achieve the above object, the present application also provides an inertial measurement device including:
the acquisition module is used for acquiring auxiliary measurement data of the motion carrier, wherein the auxiliary measurement data at least comprise sound velocity meter data and wheel speed meter data;
The type determining module is used for determining the platform application type of the motion carrier according to the sound velocity meter data and the wheel speed meter data;
The construction module is used for constructing a target scene measurement model of the motion carrier according to the platform application type and a preset inertial measurement model, and determining navigation positioning data according to the target scene measurement model and the inertial measurement data of the motion carrier.
The individual functional modules of the inertial measurement unit according to the application, when in operation, carry out the steps of the inertial measurement method according to the application as described above.
In addition, in order to achieve the above object, the present application also provides an inertial measurement device including a memory, a processor, and an inertial measurement program stored on the memory and executable on the processor, the inertial measurement program implementing the steps of the inertial measurement method described above when executed by the processor.
In addition, in order to achieve the above object, the present application also provides a computer-readable storage medium having stored thereon an inertial measurement program which, when executed by a processor, implements the steps of the inertial measurement method described above.
Furthermore, to achieve the above object, the present application provides a computer program product comprising an inertial measurement program which, when executed by a processor, implements the steps of the inertial measurement method described above.
The application provides an optimized inertial measurement method, device and equipment and a computer readable storage medium aiming at the limitations of the existing inertial measurement mode. Specifically, the method and the device can acquire auxiliary measurement data of the motion carrier in time, wherein the auxiliary measurement data at least comprise sound velocity meter data and wheel speed meter data, so that multi-source data support is provided for judging the application type of a subsequent platform. Then, the platform application type of the motion carrier can be accurately and reliably obtained according to the sound velocity meter data and the wheel speed meter data, so that the target scene measurement model can be constructed according to the platform application type and the preset inertia measurement model, the high-precision navigation requirement of the inertia measurement model in different application scenes is met, the navigation positioning data can be accurately obtained according to the target scene measurement model and the inertia measurement data of the motion carrier, the problem that the measurement accuracy is poor due to the fact that the unified inertia measurement model cannot be adapted to the application scene change is avoided, and the accuracy of inertia measurement is remarkably improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic flow chart of a first embodiment of an inertial measurement method of the present application;
FIG. 2 is a flow chart of a second embodiment of the inertial measurement method of the present application;
FIG. 3 is an application scenario diagram of the inertial measurement method of the present application;
FIG. 4 is a schematic view of an inertial measurement unit according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an inertial measurement device according to an embodiment of the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
An embodiment of the present application provides an inertial measurement method, and referring to fig. 1, fig. 1 is a schematic flow chart of a first embodiment of the inertial measurement method of the present application.
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application.
The inertial measurement technology is a key technology for navigation of a moving carrier, and an inertial navigation system can work all day time without depending on external information and is widely applied to various moving carriers such as vehicles, airplanes, ships, underwater submarines and the like. Due to the existence of inertial measurement errors, inertial estimation is performed by using observables with errors, which can lead to gradual divergence of the position, speed and posture of the moving carrier. Therefore, the traditional inertial measurement mode often adopts a unified inertial measurement model, and the model simplifies the measurement process to a certain extent, but ignores the differences between different application scenes and motion carriers, so that the requirement of high-precision navigation is often difficult to achieve in practical application. Particularly, when facing complex and changeable application scenes, the unified measurement model often cannot accurately reflect the actual motion state and environmental characteristics of the motion carrier, so that the accuracy of inertial measurement is seriously affected.
To solve the above-mentioned drawbacks, the present application provides an inertial measurement method, apparatus, device, computer-readable storage medium, and product.
The inertial measurement method provided by the application can be executed by the terminal equipment for carrying out inertial measurement on the moving carrier, and particularly the control center in the terminal equipment is used for executing the inertial measurement method. In the following embodiments, the execution body of the present application will not be described in detail.
The inertia measurement method of the application can comprise the steps S10 to S30:
Step S10: auxiliary measurement data of the moving carrier are acquired, wherein the auxiliary measurement data at least comprise sound velocity meter data and wheel speed meter data.
In this embodiment, according to the interface board in the terminal device, which is in communication connection with each path of sensor of the motion carrier, auxiliary measurement data collected by each path of sensor can be accurately received in real time, so that the phenomenon that the auxiliary measurement data is lost or damaged in the transmission process is avoided, the accuracy and the integrity of the data are ensured, and multi-source data support is provided for judging the application type of the subsequent platform.
It should be noted that the auxiliary measurement data at least includes sound velocity meter data, wheel speed meter data and GNSS (Global Navigation SATELLITE SYSTEM ) data, wherein the sound velocity meter data is collected by a sound velocity meter sensor, the wheel speed meter data is collected by a wheel speed meter sensor, and the GNSS data is collected by a satellite navigation system. In addition, the application type of the platform of the wheel speed meter sensor applied to the moving carrier is on-vehicle application platform, and the application type of the platform of the sound speed meter sensor applied to the moving carrier is on-board application platform.
Step S20: and determining the platform application type of the moving carrier according to the sound velocity meter data and the wheel speed meter data.
In the embodiment, the data format conversion is performed on the sound velocity meter data and the wheel speed meter data according to the preset binary format, and the sound velocity binary number of the sound velocity meter data and the wheel speed binary number of the wheel speed meter data can be accurately obtained, so that the data with different sources and different formats can be ensured to be uniformly and efficiently processed and analyzed by the system, and the accuracy and the efficiency of data processing are effectively improved. Then, the platform application type of the motion carrier can be rapidly and accurately obtained according to the sound speed binary number and the wheel speed binary number, so that an accurate and specific application scene is provided for the construction of a subsequent target scene measurement model, and the accuracy of inertial measurement is further effectively improved.
It should be noted that the platform application type of the motion carrier may be a shipborne application platform, a vehicle-mounted application platform or a general platform; further, the on-board application platform is associated with speed of sound data, and the on-board application platform is associated with wheel speed data.
In a specific embodiment, detecting whether the sound velocity meter data exceeds a preset sound velocity data threshold value, and detecting whether the wheel speed meter data exceeds a preset wheel speed data threshold value; if the sound speed data exceeds a preset sound speed data threshold value or the wheel speed data exceeds a preset wheel speed data threshold value, the binary value 1 representing the valid sound speed data or the binary value 1 representing the valid wheel speed data is displayed; if the sound velocity meter data does not exceed the preset sound velocity data threshold value or the wheel speed meter data does not exceed the preset wheel speed data threshold value, the effective binary position 0 of the sound velocity meter data is represented, or the effective binary position 0 of the wheel speed meter data is represented, so that data format conversion is realized, and the accuracy and the efficiency of data processing are effectively improved.
When the binary number is 1, it is understood that the level signal corresponding to each of the sound velocity meter data and the wheel speed count data at this time is at the high level; when the binary number is 0, it can be understood that the level signal corresponding to each of the sonic meter data and the wheel speed data at this time is low level. The level signal corresponding to the sound velocity meter data is a sound velocity electric signal, and the level signal corresponding to the wheel speed meter data is a wheel speed electric signal.
Step S30: and constructing a target scene measurement model of the motion carrier according to the platform application type and a preset inertial measurement model, and determining navigation positioning data according to the target scene measurement model and the inertial measurement data of the motion carrier.
In this embodiment, the target scene measurement model of the motion carrier can be accurately constructed according to the platform application type and the preset inertial measurement model, so as to adapt to the high-precision inertial measurement requirements of the model in different application scenes. Then, the navigation positioning data of the motion carrier can be accurately obtained according to the target scene measurement model and the inertia measurement data of the motion carrier, so that the accuracy and reliability of the navigation positioning data are effectively improved, and the accuracy of inertia measurement is remarkably improved.
In summary, the present application proposes an optimized inertial measurement method, apparatus, device and computer readable storage medium for solving the limitations of the existing inertial measurement method. Specifically, the method and the device can acquire auxiliary measurement data of the motion carrier in time, wherein the auxiliary measurement data at least comprise sound velocity meter data and wheel speed meter data, so that multi-source data support is provided for judging the application type of a subsequent platform. Then, the platform application type of the motion carrier can be accurately and reliably obtained according to the sound velocity meter data and the wheel speed meter data, so that the target scene measurement model can be constructed according to the platform application type and the preset inertia measurement model, the high-precision navigation requirement of the inertia measurement model in different application scenes is met, the navigation positioning data can be accurately obtained according to the target scene measurement model and the inertia measurement data of the motion carrier, the problem that the measurement accuracy is poor due to the fact that the unified inertia measurement model cannot be adapted to the application scene change is avoided, and the accuracy of inertia measurement is remarkably improved.
Further, based on the first embodiment of the inertial measurement method of the present application, a second embodiment of the inertial measurement method of the present application is proposed, and referring to fig. 2, fig. 2 is a schematic flow chart of the second embodiment of the inertial measurement method of the present application.
Further, in some possible embodiments, step S20 described above: determining the platform application type of the motion carrier according to the sound velocity meter data and the wheel speed meter data, and further comprising the following implementation steps S201-S204:
Step S201: determining an electrical sound speed signal of the sound speed meter data and an electrical wheel speed signal of the wheel speed meter data;
step S202: when the sound velocity electric signal is at a high level and the wheel speed electric signal is at a low level, determining that the platform application type of the motion carrier is a shipboard application platform;
Step S203: when the sound velocity electric signal is at a low level and the wheel speed electric signal is at a high level, determining that the platform application type of the motion carrier is a vehicle-mounted application platform;
Step S204: and when the sound velocity electric signal and the wheel speed electric signal are both at low levels, determining that the platform application type of the motion carrier is a universal platform.
In this embodiment, after determining the sound velocity electric signal of the sound velocity meter data and the wheel speed electric signal of the wheel speed meter data, it is possible to rapidly determine whether the platform application type of the moving carrier is a ship-borne application platform, a vehicle-mounted application platform or a general-purpose platform by directly comparing the sound velocity electric signal and the level state of the wheel speed electric signal. Specifically, when the sound velocity electric signal is at a high level and the wheel speed electric signal is at a low level, determining that the application type of the platform of the motion carrier is a shipborne application platform; when the sound velocity electric signal is at a low level and the wheel speed electric signal is at a high level, determining the application type of the platform of the motion carrier as a vehicle-mounted application platform; when the sound velocity electric signal and the wheel speed electric signal are both low levels, the application type of the platform of the motion carrier is determined to be a universal platform. The application can rapidly and accurately identify the application type of the platform of the motion carrier according to the level states of the sound velocity electric signal and the wheel speed electric signal, effectively reduces the calculation time and the resource consumption, and improves the accuracy and the efficiency of data processing.
It should be noted that the on-board application platform may be understood as an on-board/underwater vehicle platform.
Further, in other possible embodiments, step S30 described above: the method comprises the steps of constructing a target scene measurement model of the motion carrier according to the platform application type and a preset inertial measurement model, and further comprises the following implementation steps S301-S303:
step S301: judging whether the platform application type is the universal platform or not;
step S302: if the platform application type is the universal platform, taking a preset inertial measurement model as a target scene measurement model of the motion carrier;
Step S303: and if the platform application type is not the universal platform, updating the inertial measurement model according to the platform application type to obtain the target scene measurement model.
In this embodiment, the system can flexibly select the applicable inertial measurement model by judging whether the platform application type is a universal platform. Specifically, when the platform application type is a universal platform, the preset inertial measurement model is directly used as a target scene measurement model of the motion carrier, and the terminal equipment does not need to perform additional model updating calculation due to the adoption of the preset inertial measurement model, so that the calculation load and response time are reduced. When the platform application type is not a universal platform, the inertial measurement model is updated in a targeted manner according to the platform application type, so that the obtained target scene measurement model can be better adapted to the motion characteristics of different platforms, the motion characteristics of different platforms under specific environments can be reflected more accurately, and the accuracy and the reliability of inertial measurement are improved remarkably.
It should be noted that the preset inertial measurement model expression is as follows:
wherein, To differentiate the error state of the moving carrier,In order to state the one-step transition matrix,A matrix is assigned to the system state noise,AndWhite noise is measured for gyro angular rate and accelerometer specific force respectively, X is a systematic error state vector (i.e. initial error parameter), the application sets upThe initial mean square error matrix of (a) is an initial variance matrix P 0, V is a preset model noise vector (i.e. a system measurement noise vector), Z is a measurement vector (i.e. a measurement error parameter), the application sets the measurement mean square error matrix of Z as a measurement variance matrix R 0, H is a preset inertial measurement model,Is the transposition of the error angle of the motion carrier platform,The method is a transposition of the speed error of the moving carrier; Is a transpose of the position error of the moving carrier, Is the transposition of random constant drift values of gyroscopes in a motion carrier,Is the transposition of the random constant bias value of the accelerometer,、AndThe eastern direction, the north direction and the sky direction are respectively the position measuring vectors,、AndThe eastbound, northbound and heaven velocity measurement vectors, respectively.
When the platform application type of the motion carrier is a universal platform,AndThe initial variance values of the respective mappings are all 0, i.e. byThe initial variance matrix formed by the initial variance values of the respective maps is 0.
When the platform application type of the motion carrier is a vehicle-mounted application platform, the motion carrier is provided withAndIs combined intoI.e.The scale coefficient error of the wheel speed meter sensor; mounting errors for pitch angles of wheel speed meter sensors; and mounting errors for course angles of wheel speed meter sensors.
When the type of platform application of the moving carrier is an on-board application platform,AndThe error of the forward scale factor and the error of the lateral scale factor of the sound velocity meter are respectively; The pitch angle installation error of the sensor of the sound velocity meter; Is the heading angle installation error of the sonic meter sensor.
In a specific embodiment, the number and type of multisource observables are determined by detecting the valid status of the observables (i.e., sonic meter data, wheel speed meter data, and GNSS data), and if the sonic meter data is detected valid, then the method is setWhen the initial variance matrix P 0 of the sonic meter is used, the error of the lateral scale factor of the sonic meter is calculatedInitial variance value of mappingInitializing to a non-0 valid value; when the measurement variance matrix R 0 of the filter is set, the eastern position measurement vector is calculatedNorth position measurement vectorVector of measurement of the position of the skyVector of measurement of the tangential velocityRespectively corresponding measurement variance valuesMeasuring variance valueMeasuring variance valueAnd measuring variance valuesAnd initializing to an infinite value, and constructing a mathematical model of the submersible scene fused with the measurement information of the sound velocity meter.
If the wheel speed meter data is detected to be valid, the method is setWhen the initial variance matrix P 0 of the wheel speed meter sensor is used, the scale coefficient error of the wheel speed meter sensor is calculatedInitial variance value adjustment of mappingIs 0; when the measurement variance matrix R 0 of the filter is set, the eastern direction speed measurement vector is calculatedNorth velocity measurement vectorVector of measurement of the tangential velocityCorresponding to、And (d) sumThe vehicle-mounted scene mathematical model construction of fusing the wheel speed meter measurement information can be achieved when the vehicle-mounted scene mathematical model construction is initialized to an infinite value;
If the GNSS data is detected to be valid, setting When the initial variance matrix P 0 of (2) is set, the error state is set、、AndCorresponding to、、AndAnd when the initialization is 0, the vehicle-mounted scene mathematical model construction fusing the GNSS measurement information can be achieved.
Further, in some possible embodiments, step S303 is described above: updating the inertial measurement model according to the platform application type to obtain the target scene measurement model, and further comprising the following implementation steps S3031-S3033:
step S3031: and acquiring initial error parameters and measurement error parameters corresponding to the platform application type from the inertial measurement model, and determining an initial variance matrix and a measurement variance matrix designated by the inertial measurement model.
In this embodiment, an initial error parameter and a measurement error parameter corresponding to a platform application type are obtained in a preset inertial measurement model, and, illustratively, when the platform application type is a vehicle-mounted application platform, the initial error parameter and the measurement error parameter of a motion carrier corresponding to a wheel speed meter sensor are quickly searched from the preset inertial measurement model; when the application type of the platform is a shipborne application platform, the initial error parameters corresponding to the sound velocity meter sensor and the measurement error parameters of the motion carrier are quickly searched from a preset inertial measurement model, so that the platform error characteristics of different application scenes can be quickly and accurately distinguished, then an initial variance matrix and a measurement variance matrix designated by the inertial measurement model are determined, and the construction efficiency of the target scene measurement model can be improved.
When the application type of the platform is a vehicle-mounted application platform, the initial error parameter corresponding to the wheel speed meter sensor is the scale coefficient error of the wheel speed meter sensorThe measurement error parameter of the moving carrier is position measurement errorError in measurement of the tangential velocity; When the platform application type is the shipboard application platform, the initial error parameter corresponding to the acoustic velocity meter sensor is the lateral scale factor error of the acoustic velocity meterThe measurement error parameter of the motion carrier is the measurement error of the tangential velocity。
Step S3032: and updating the initial variance value of the initial error parameter mapping in the initial variance matrix and the measurement variance value of the measurement error parameter mapping in the measurement variance matrix according to the platform application type respectively to obtain an updated initial variance matrix and an updated measurement variance matrix.
In this embodiment, the initial variance value of the initial error parameter map in the initial variance matrix and the measurement variance value of the measurement error parameter map in the measurement variance matrix are updated according to the platform application type, so that the updated initial variance matrix and the updated measurement variance matrix can be quickly and accurately obtained.
In a specific embodiment, when the platform application type is the vehicle-mounted application platform, the scale coefficient error in the initial variance matrix is calculatedThe initial variance value of the mapping is adjusted to be a non-0 effective value, and the position measurement error in the measurement variance matrix is determined(I.eAnd) Mapped measurement variance values and measurement errors of the tangential velocityThe measurement variance values of the mapping are all adjusted to infinity values, so that the initialization processing of the initial variance matrix and the measurement variance matrix is completed, the updating of the initial variance matrix and the measurement variance matrix under the vehicle-mounted application platform is realized, and accurate and reliable data support is provided for the subsequent model construction applied to the vehicle-mounted application platform.
When the application type of the platform is the shipboard application platform, the error of the lateral scale factors in the initial variance matrix is reducedThe initial variance value of the mapping is adjusted to 0, and the velocity measurement error in the measurement variance matrix is adjusted(I.e、And) The mapped measurement variance value is adjusted to an infinite value, so that accurate and reliable data support is provided for the subsequent model construction applied to the vehicle-mounted application platform.
Step S3033: and constructing the target scene measurement model according to the updated initial variance matrix and the updated measurement variance matrix.
In this embodiment, the target scene measurement model constructed according to the updated initial variance matrix and the updated measurement variance matrix can perform customized error processing for each platform application type, thereby remarkably improving the accuracy and reliability of inertial measurement.
Further, in some possible embodiments, step S30 described above: determining navigation positioning data according to the target scene measurement model and the inertial measurement data of the moving carrier, and implementing the following steps B10-B20:
Step B10: determining inertial measurement data of the motion carrier, and obtaining a pose initial value of the motion carrier according to the inertial measurement data;
in this embodiment, the present application performs initial alignment according to the inertial measurement data of the motion carrier, so as to obtain the initial pose value output by the inertial measurement module in the motion carrier.
The initial pose values include a pose measurement value, an azimuth measurement value, a speed measurement value, and a position measurement value.
The inertial measurement data at least comprise attitude angle and heading data of the motion carrier in a static state, and whether the motion carrier is parallel to the large ground or not is judged according to the absolute value of the attitude angle; after the motion carrier is determined to be parallel to the large ground, the carrier azimuth of the motion carrier is adjusted to be consistent with the azimuth of the north pole of the large ground according to the heading data, and the initial pose value of the motion carrier is obtained through the inertial measurement unit, so that the accuracy of the initial pose value is effectively improved.
Step B20: and carrying out Kalman filtering calculation on the pose initial value according to the target scene measurement model to obtain a pose compensation value, and overlapping the pose compensation value on the pose initial value to obtain navigation positioning data.
In this embodiment, the pose compensation value can be accurately obtained by performing kalman filtering calculation on the pose initial value according to the target scene measurement model, and the pose compensation value is superimposed on the pose initial value, so that the navigation positioning data can be accurately obtained, the problem of poor measurement accuracy caused by the fact that the unified inertial measurement model cannot adapt to the application scene change is avoided, and the accuracy of inertial measurement is remarkably improved.
The pose compensation value includes a pose error compensation value, an azimuth error compensation value, a speed error compensation value, and a position error compensation value.
The navigational positioning data comprises an actual pose, an actual position, an actual velocity and an actual position of the moving carrier.
In yet another embodiment, referring to fig. 3, fig. 3 is an application scenario diagram related to the inertial measurement method of the present application. (1) multisource observation data reception and preprocessing: the method comprises the steps of receiving measurement data input by each sensor through an interface board, preprocessing the data into a specified format, setting the validity of the type of measurement data to be 1 if certain sensor data are received, otherwise setting the type of measurement data to be 0, and measuring the data types to include: GNSS measurement data, wheel speed meter measurement data and sound velocity meter measurement data;
(2) Judging the platform type and the scene: the navigation board judges a motion platform where the inertial navigation system is located by judging the validity of each type of measurement data, if the wheel speed meter measurement data are valid, the motion platform is judged to be on-board, if the sound speed meter measurement data are valid, the motion platform is judged to be on-board/underwater vehicle platform, and if the wheel speed meter and the sound speed meter measurement data are invalid, the motion platform is judged to be on general platform;
(3) Initial alignment: the navigation board performs initial alignment by using inertial measurement data to obtain initial pose values of the inertial measurement module, wherein the initial pose values comprise pose measurement values, azimuth measurement values, speed measurement values and position measurement values;
(4) Constructing a mathematical model: if the model is a ship-borne or underwater vehicle platform, automatically constructing an inertial and sound velocity meter combined filtering mathematical model, if the model is a vehicle-mounted platform, automatically constructing an inertial and wheel velocity meter combined filtering mathematical model, and if the model is a general platform, automatically constructing an inertial and satellite combined filtering mathematical model;
(5) Error estimation and compensation: performing combined filtering calculation by using the constructed combined filtering mathematical model, and estimating and compensating an error state in real time;
(6) And (3) outputting a navigation result: and outputting navigation resolving results (namely navigation positioning data) comprising the actual gesture, the actual azimuth, the actual speed and the actual position of the motion carrier.
In summary, the application provides a method capable of automatically identifying a motion carrier and a use scene according to the input multisource observables and automatically constructing a corresponding mathematical model to perform systematic error estimation and compensation, so as to improve the scene adaptability of the system and reduce the after-sales maintenance cost.
In addition, the application also provides an inertial measurement device, please refer to fig. 4, fig. 4 is a schematic structural diagram of the inertial measurement device according to an embodiment of the application.
The inertial measurement unit of the application includes:
The acquisition module H01 is used for acquiring auxiliary measurement data of the motion carrier, wherein the auxiliary measurement data at least comprise sound velocity meter data and wheel speed meter data;
the type determining module H02 is used for determining the platform application type of the moving carrier according to the sound velocity meter data and the wheel speed meter data;
The construction module H03 is used for constructing a target scene measurement model of the motion carrier according to the platform application type and a preset inertial measurement model, and determining navigation positioning data according to the target scene measurement model and the inertial measurement data of the motion carrier.
Alternatively, the type determining module H02 may be further configured to determine an electrical sound speed signal of the sound speed meter data and an electrical wheel speed signal of the wheel speed meter data; when the sound velocity electric signal is at a high level and the wheel speed electric signal is at a low level, determining that the platform application type of the motion carrier is a shipboard application platform; when the sound velocity electric signal is at a low level and the wheel speed electric signal is at a high level, determining that the platform application type of the motion carrier is a vehicle-mounted application platform; when the sound velocity electric signal and the wheel speed electric signal are both at low levels, determining that the platform application type of the motion carrier is a universal platform;
Optionally, the building module H03 may be further configured to determine whether the platform application type is the generic platform; if the platform application type is the universal platform, taking a preset inertial measurement model as a target scene measurement model of the motion carrier; and if the platform application type is not the universal platform, updating the inertial measurement model according to the platform application type to obtain the target scene measurement model.
Optionally, the building module H03 may be further configured to obtain an initial error parameter and a measurement error parameter corresponding to the platform application type in the inertial measurement model, and determine an initial variance matrix and a measurement variance matrix specified by the inertial measurement model; updating the initial variance value of the initial error parameter mapping in the initial variance matrix and the measurement variance value of the measurement error parameter mapping in the measurement variance matrix according to the platform application type to obtain an updated initial variance matrix and an updated measurement variance matrix; and constructing the target scene measurement model according to the updated initial variance matrix and the updated measurement variance matrix.
Optionally, the construction module H03 may be further configured to determine inertial measurement data of the moving carrier, and obtain an initial pose value of the moving carrier according to the inertial measurement data; and carrying out Kalman filtering calculation on the pose initial value according to the target scene measurement model to obtain a pose compensation value, and overlapping the pose compensation value on the pose initial value to obtain navigation positioning data.
The individual functional modules of the inertial measurement unit according to the application, when in operation, carry out the steps of the inertial measurement method according to the application as described above.
Furthermore, the present application provides a storage medium that is a computer-readable storage medium. The computer readable storage medium stores an inertial measurement program which, when executed by a processor, performs the steps of the inertial measurement method described above.
In addition, the application also provides inertial measurement equipment. Referring to fig. 5, fig. 5 is a schematic structural diagram of an inertial measurement device according to an embodiment of the application. The inertial measurement device of the embodiment of the application can be particularly a device for locally running an inertial measurement method.
As shown in fig. 5, an inertial measurement device according to an embodiment of the present application may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., wi-Fi interface).
A memory 1005 is provided on the inertial measurement apparatus main body, and a program is stored on the memory 1005, which when executed by the processor 1001, realizes a corresponding operation. The memory 1005 is also used to store parameters for use by the inertial measurement device. The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
Those skilled in the art will appreciate that the inertial measurement device structure shown in FIG. 5 is not limiting of the inertial measurement device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 5, an operating system, a network communication module, a user interface module, and an inertial measurement program of the inertial measurement device may be included in a memory 1005 as one type of storage medium.
In the inertial measurement device shown in fig. 5, a processor 1001 may be used to invoke the inertial measurement program of the inertial measurement device stored in a memory 1005 and perform the steps of any of the inertial measurement methods described above.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a computer readable storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing an inertial measurement device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present application.
The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the application, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (9)
1. An inertial measurement method, the inertial measurement method comprising:
acquiring auxiliary measurement data of a motion carrier, wherein the auxiliary measurement data at least comprise sound velocity meter data and wheel speed meter data;
determining a platform application type of the motion carrier according to the sound velocity meter data and the wheel speed meter data;
Constructing a target scene measurement model of the motion carrier according to the platform application type and a preset inertial measurement model, and determining navigation positioning data according to the target scene measurement model and the inertial measurement data of the motion carrier; wherein the expression of the inertial measurement model is as follows:
wherein, Differentiating the error state of the moving carrier,In order to state the one-step transition matrix,A matrix is assigned to the system state noise,Is thatAndIs a matrix of the (c) in the matrix,AndWhite noise is measured for the gyro angular rate and the accelerometer specific force, respectively, X is the systematic error state vector,Is the transposition of the error angle of the motion carrier platform,The method is a transposition of the speed error of the moving carrier; Is a transpose of the position error of the moving carrier, Is the transposition of random constant drift values of gyroscopes in a motion carrier,Is the transposition of the random constant bias value of the accelerometer,Is the course angle installation error of the sound velocity meter sensor or the course angle installation error of the wheel speed meter sensor,Is the pitch angle installation error of the sound velocity meter sensor or the pitch angle installation error of the wheel speed meter sensor,AndRespectively a forward scale factor error and a lateral scale factor error of the sound velocity meter, Z is a measurement vector, H is a preset inertial measurement model, V is a preset model noise vector,、AndThe eastern direction, the north direction and the sky direction are respectively the position measuring vectors,、AndThe vector is respectively measured for the east, north and sky speed;
the step of determining the platform application type of the moving carrier according to the sound velocity meter data and the wheel speed meter data comprises the following steps:
Detecting whether the sound velocity meter data exceeds a preset sound velocity data threshold value or not, and detecting whether the wheel speed meter data exceeds a preset wheel speed data threshold value or not;
If the sound speed data exceeds the sound speed data threshold value and the wheel speed data does not exceed the wheel speed data threshold value, determining sound speed binary position 1 of the sound speed data and wheel speed binary position 0 of the wheel speed data, and determining that the platform application type of the motion carrier is a shipborne application platform according to sound speed high level and wheel speed low level obtained by the sound speed binary position 1 and the wheel speed binary position 0;
if the sound velocity meter data does not exceed the sound velocity data threshold value and the wheel speed meter data exceeds the wheel speed data threshold value, determining sound velocity binary position 0 of the sound velocity meter data and wheel speed binary position 1 of the wheel speed meter data, and determining the application type of the platform of the motion carrier as a vehicle-mounted application platform according to sound velocity low level and wheel speed high level obtained by the sound velocity binary position 0 and the wheel speed binary position 1;
if the sound velocity meter data does not exceed the sound velocity data threshold value and the wheel speed meter data does not exceed the wheel speed data threshold value, determining sound velocity binary position 0 of the sound velocity meter data and wheel speed binary position 0 of the wheel speed meter data, and determining the platform application type of the motion carrier as a universal platform according to sound velocity low level and wheel speed low level obtained by the sound velocity binary position 0 and the wheel speed binary position 0.
2. The inertial measurement method of claim 1, wherein the step of determining the platform application type of the moving carrier from the sonic meter data and the wheel speed meter data comprises:
determining an electrical sound speed signal of the sound speed meter data and an electrical wheel speed signal of the wheel speed meter data;
when the sound velocity electric signal is at a high level and the wheel speed electric signal is at a low level, determining that the platform application type of the motion carrier is a shipboard application platform;
When the sound velocity electric signal is at a low level and the wheel speed electric signal is at a high level, determining that the platform application type of the motion carrier is a vehicle-mounted application platform;
And when the sound velocity electric signal and the wheel speed electric signal are both at low levels, determining that the platform application type of the motion carrier is a universal platform.
3. The inertial measurement method of claim 2, wherein the step of constructing a target scene measurement model of the moving carrier according to the platform application type and a preset inertial measurement model comprises:
judging whether the platform application type is the universal platform or not;
if the platform application type is the universal platform, taking a preset inertial measurement model as a target scene measurement model of the motion carrier;
and if the platform application type is not the universal platform, updating the inertial measurement model according to the platform application type to obtain the target scene measurement model.
4. The inertial measurement method of claim 3, wherein updating the inertial measurement model according to the platform application type to obtain the target scene measurement model comprises:
Acquiring initial error parameters and measurement error parameters corresponding to the platform application type from the inertial measurement model, and determining an initial variance matrix and a measurement variance matrix designated by the inertial measurement model;
Updating the initial variance value of the initial error parameter mapping in the initial variance matrix and the measurement variance value of the measurement error parameter mapping in the measurement variance matrix according to the platform application type to obtain an updated initial variance matrix and an updated measurement variance matrix;
and constructing the target scene measurement model according to the updated initial variance matrix and the updated measurement variance matrix.
5. The inertial measurement method of claim 1, wherein determining navigational positioning data from inertial measurement data of the target scene measurement model and the moving carrier comprises:
determining inertial measurement data of the motion carrier, and obtaining a pose initial value of the motion carrier according to the inertial measurement data;
And carrying out Kalman filtering calculation on the pose initial value according to the target scene measurement model to obtain a pose compensation value, and overlapping the pose compensation value on the pose initial value to obtain navigation positioning data.
6. An inertial measurement device, the inertial measurement device comprising:
the acquisition module is used for acquiring auxiliary measurement data of the motion carrier, wherein the auxiliary measurement data at least comprise sound velocity meter data and wheel speed meter data;
The type determining module is used for determining the platform application type of the moving carrier according to the sound velocity meter data and the wheel speed meter data;
the construction module is used for constructing a target scene measurement model of the motion carrier according to the platform application type and a preset inertial measurement model, and determining navigation positioning data according to the target scene measurement model and the inertial measurement data of the motion carrier; wherein the expression of the inertial measurement model is as follows:
wherein, Differentiating the error state of the moving carrier,In order to state the one-step transition matrix,A matrix is assigned to the system state noise,Is thatAndIs a matrix of the (c) in the matrix,AndWhite noise is measured for the gyro angular rate and the accelerometer specific force, respectively, X is the systematic error state vector,Is the transposition of the error angle of the motion carrier platform,The method is a transposition of the speed error of the moving carrier; Is a transpose of the position error of the moving carrier, Is the transposition of random constant drift values of gyroscopes in a motion carrier,Is the transposition of the random constant bias value of the accelerometer,Is the course angle installation error of the sound velocity meter sensor or the course angle installation error of the wheel speed meter sensor,Is the pitch angle installation error of the sound velocity meter sensor or the pitch angle installation error of the wheel speed meter sensor,AndRespectively a forward scale factor error and a lateral scale factor error of the sound velocity meter, Z is a measurement vector, H is a preset inertial measurement model, V is a preset model noise vector,、AndThe eastern direction, the north direction and the sky direction are respectively the position measuring vectors,、AndThe vector is respectively measured for the east, north and sky speed;
The type determining module is further used for detecting whether the sound velocity meter data exceeds a preset sound velocity data threshold value and detecting whether the wheel speed meter data exceeds a preset wheel speed data threshold value; if the sound speed data exceeds the sound speed data threshold value and the wheel speed data does not exceed the wheel speed data threshold value, determining sound speed binary position 1 of the sound speed data and wheel speed binary position 0 of the wheel speed data, and determining that the platform application type of the motion carrier is a shipborne application platform according to sound speed high level and wheel speed low level obtained by the sound speed binary position 1 and the wheel speed binary position 0; if the sound velocity meter data does not exceed the sound velocity data threshold value and the wheel speed meter data exceeds the wheel speed data threshold value, determining sound velocity binary position 0 of the sound velocity meter data and wheel speed binary position 1 of the wheel speed meter data, and determining the application type of the platform of the motion carrier as a vehicle-mounted application platform according to sound velocity low level and wheel speed high level obtained by the sound velocity binary position 0 and the wheel speed binary position 1; if the sound velocity meter data does not exceed the sound velocity data threshold value and the wheel speed meter data does not exceed the wheel speed data threshold value, determining sound velocity binary position 0 of the sound velocity meter data and wheel speed binary position 0 of the wheel speed meter data, and determining the platform application type of the motion carrier as a universal platform according to sound velocity low level and wheel speed low level obtained by the sound velocity binary position 0 and the wheel speed binary position 0.
7. An inertial measurement device comprising a memory, a processor and an inertial measurement program stored on the memory and executable on the processor, the processor implementing the steps of the inertial measurement method of any one of claims 1 to 5 when the inertial measurement program is executed.
8. A computer-readable storage medium, on which an inertial measurement program is stored, which when executed by a processor implements the steps of the inertial measurement method according to any one of claims 1 to 5.
9. A computer program product, characterized in that the computer program product comprises an inertial measurement program which, when executed by a processor, implements the steps of the inertial measurement method according to any one of claims 1 to 5.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107907900A (en) * | 2017-11-07 | 2018-04-13 | 长光卫星技术有限公司 | A kind of multi-sensor combined navigation system and method for GNSS double antennas auxiliary |
| CN111982106A (en) * | 2020-08-28 | 2020-11-24 | 北京信息科技大学 | Navigation method, navigation device, storage medium and electronic device |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FR2878954B1 (en) * | 2004-12-07 | 2007-03-30 | Sagem | HYBRID INERTIAL NAVIGATION SYSTEM BASED ON A CINEMATIC MODEL |
| CN109764870B (en) * | 2019-01-17 | 2023-04-25 | 上海华测导航技术股份有限公司 | Carrier Initial Heading Estimation Method Based on Transformation Estimator Modeling Scheme |
| CN110174105B (en) * | 2019-06-14 | 2022-02-11 | 西南科技大学 | Intelligent agent autonomous navigation algorithm and system in complex environment |
| DE102020202627A1 (en) * | 2020-03-02 | 2021-09-02 | Robert Bosch Gesellschaft mit beschränkter Haftung | Adapting a parameterization of algorithms for a sensor data fusion |
| CN111412912A (en) * | 2020-04-14 | 2020-07-14 | 上海华测导航技术股份有限公司 | Navigation board, multi-source data fusion method for navigation board and carrier |
| CN113465628B (en) * | 2021-06-17 | 2024-07-09 | 杭州鸿泉物联网技术股份有限公司 | Inertial measurement unit data compensation method and system |
| CN215678780U (en) * | 2021-08-10 | 2022-01-28 | 长沙海格北斗信息技术有限公司 | Vehicle-mounted and shipborne compatible Beidou third-number communication positioning terminal |
| CN115265527A (en) * | 2022-05-20 | 2022-11-01 | 广州南方卫星导航仪器有限公司 | Method for processing GNSS/INS combined data and combined navigation system |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107907900A (en) * | 2017-11-07 | 2018-04-13 | 长光卫星技术有限公司 | A kind of multi-sensor combined navigation system and method for GNSS double antennas auxiliary |
| CN111982106A (en) * | 2020-08-28 | 2020-11-24 | 北京信息科技大学 | Navigation method, navigation device, storage medium and electronic device |
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