CN113405549B - Vehicle positioning method, assembly, electronic device and storage medium - Google Patents
Vehicle positioning method, assembly, electronic device and storage medium Download PDFInfo
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Classifications
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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
- G01C21/10—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
- G01C21/183—Compensation of inertial measurements, e.g. for temperature effects
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
- G01S19/49—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an inertial position system, e.g. loosely-coupled
Abstract
The application provides a vehicle positioning method, a vehicle positioning component, electronic equipment and a storage medium, wherein the method comprises the following steps: judging whether the GPS signal state acquired by the vehicle-mounted positioning system is valid or not; if the GPS signal state is invalid, determining the type of the environment state of the vehicle in an electronic map of the vehicle-mounted positioning system according to a strapdown inertial navigation calculation result in the vehicle-mounted positioning system; determining corresponding filtering data and filtering parameters according to the environmental state type; correcting the strapdown inertial navigation calculation result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model; and determining a vehicle positioning result according to the correction result of the strapdown inertial navigation calculation. And determining the filtering data and the filtering parameters which are most matched with the environmental state type by utilizing the environmental state type of the vehicle in the electronic map, and further correcting the strapdown inertial navigation calculation result according to the most matched filtering data and the filtering parameters to obtain an accurate correction result and a vehicle positioning result.
Description
Technical Field
The embodiment of the application relates to the technical field of positioning, in particular to a vehicle positioning method, a vehicle positioning component, an electronic device and a storage medium.
Background
With the improvement of living standard, driving trip becomes a daily choice of people. In the driving process of a vehicle, in order to provide navigation signals or route guidance for people, positioning the vehicle becomes an indispensable link.
In the prior art, a global positioning system (Global Positioning System, abbreviated as GPS) is generally used for positioning a vehicle, but when the vehicle is located in a special environment of a satellite signal blind area, a signal lock losing problem occurs under the condition that an object is blocked above a GPS receiver, and at this time, the transmission of positioning signals of the GPS is limited. At this time, the accuracy of the vehicle positioning will not be ensured.
Disclosure of Invention
In view of the above, the present application provides a vehicle positioning method, a vehicle positioning assembly, an electronic device, and a storage medium.
In a first aspect, the present application provides a vehicle positioning method, including:
judging whether the GPS signal state acquired by the vehicle-mounted positioning system is valid or not;
if the GPS signal state is invalid, determining the type of the environment state of the vehicle in an electronic map of the vehicle-mounted positioning system according to a strapdown inertial navigation calculation result in the vehicle-mounted positioning system;
determining corresponding filtering data and filtering parameters according to the environmental state type;
Correcting the strapdown inertial navigation calculation result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model;
and determining a vehicle positioning result according to the correction result of the strapdown inertial navigation calculation.
In a second aspect, the present application provides a vehicle positioning device comprising:
the judging module is used for judging whether the GPS signal state acquired by the vehicle-mounted positioning system is valid or not;
the first determining module is used for determining the type of the environment state of the vehicle in the electronic map of the vehicle positioning system according to the strapdown inertial navigation calculation result in the vehicle positioning system if the GPS signal state is determined to be invalid;
the second determining module is used for determining corresponding filtering data and filtering parameters according to the environmental state type;
the correction module is used for correcting the strapdown inertial navigation calculation result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model;
and the third determining module is used for determining a vehicle positioning result according to the corrected result of the strapdown inertial navigation calculation.
In a third aspect, the present application provides an in-vehicle positioning assembly comprising:
a vehicle positioning system and a vehicle positioning controller;
the vehicle-mounted positioning system comprises a GPS receiver, a strapdown inertial navigation positioning module, an electronic map module and a filtering module;
The vehicle positioning controller is configured to control the vehicle positioning system to perform vehicle positioning by using the method of any one of the first aspects.
In a fourth aspect, the present application provides an electronic device, comprising: at least one processor and memory;
the memory stores computer-executable instructions;
at least one processor executes computer-executable instructions stored in a memory such that the at least one processor performs the method of any of the preceding claims.
In a fifth aspect, the present application provides a computer readable storage medium having stored therein computer executable instructions which, when executed by a processor, implement a method as in any preceding claim.
In a sixth aspect, the application provides a computer program product comprising a computer program which, when executed by a processor, implements a method according to any of the preceding claims.
According to the vehicle positioning method, the components, the electronic equipment and the storage medium, whether the GPS signal state acquired by the vehicle-mounted positioning system is effective or not is judged; if the GPS signal state is invalid, determining the type of the environment state of the vehicle in an electronic map of the vehicle-mounted positioning system according to a strapdown inertial navigation calculation result in the vehicle-mounted positioning system; determining corresponding filtering data and filtering parameters according to the environmental state type; correcting the strapdown inertial navigation calculation result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model; and determining a vehicle positioning result according to the correction result of the strapdown inertial navigation calculation. According to the vehicle positioning method provided by the application, under the condition that the GPS signal is invalid, the filtering data and the filtering parameters which are most matched with the environmental state type are determined by utilizing the environmental state type of the vehicle in the electronic map, and further, the strapdown inertial navigation calculation result is corrected by adopting the adaptive Kalman filtering model according to the most matched filtering data and the filtering parameters, so that an accurate correction result can be obtained, and further, an accurate vehicle positioning result can be obtained.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions of the prior art, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it will be obvious that the drawings in the following description are some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a schematic diagram of a network architecture on which the present application is based;
fig. 2 is a schematic flow chart of a vehicle positioning method according to an embodiment of the present application;
FIG. 3 is a flowchart of another vehicle positioning method according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a vehicle positioning device according to the present application;
FIG. 5 is a schematic diagram of a high-precision positioning system according to the present application;
fig. 6 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
With the improvement of living standard, driving trip becomes a daily choice of people. In the driving process of a vehicle, in order to provide navigation signals or route guidance for people, positioning the vehicle becomes an indispensable link.
In the prior art, a global positioning system (Global Positioning System, abbreviated as GPS) is generally used for positioning a vehicle, but when the vehicle is located in a special environment, such as a dense urban building area, a tunnel culvert, a road with dense trees and other satellite signal blind areas, a signal lock losing problem occurs under the condition that an object is blocked above a GPS receiver, and at the moment, the transmission of positioning signals of the GPS is limited. At this time, the accuracy of the vehicle positioning will not be ensured.
Aiming at the problems, the application provides a vehicle positioning method based on an electronic map, which solves the problem that the existing vehicle-mounted positioning system cannot accurately position in a satellite signal blind area on the premise of not increasing hardware cost on the basis of GPS, IMU, OD multi-sensor fusion, and realizes the full-road-section positioning of a vehicle-mounted navigation system.
Specifically, the application provides a vehicle positioning method, a vehicle positioning device, a vehicle positioning assembly, an electronic device and a storage medium.
Referring to fig. 1, fig. 1 is a schematic diagram of a network architecture according to the present application, and as shown in fig. 1, one network architecture according to the present application may include a vehicle positioning device 1, a vehicle positioning system 2, and a vehicle 3.
Wherein the vehicle positioning device 1 and the vehicle positioning system 2 are both mounted on the vehicle 3. The vehicle-mounted positioning system 2 is operable to perform vehicle positioning under control of the vehicle positioning device 1, and acquire a vehicle positioning result of the vehicle position.
The vehicle positioning system 2 comprises various positioning devices including, but not limited to, a GPS receiver, a strapdown inertial navigation positioning module, an electronic map module and a filtering module. The GPS receiver is used for receiving GPS signals, comprises two standard messages of $GPRMC and $GPGGA, and can acquire information such as position, speed, course angle and the like; the electronic map module is used for storing the related data of the electronic map.
The vehicle positioning device 1 may be hardware or software for controlling the in-vehicle positioning system 2 to perform operation, and when it is software, it may be installed in an electronic apparatus having an operation function, including but not limited to an in-vehicle computer, an in-vehicle terminal, and the like.
In a first aspect, referring to fig. 2, fig. 2 is a flow chart of a vehicle positioning method according to an embodiment of the present application. The vehicle positioning method provided by the embodiment of the application comprises the following steps:
And step 101, judging whether the GPS signal state acquired by the vehicle-mounted positioning system is valid.
Step 102, if the GPS signal state is invalid, determining the type of the environment state of the vehicle in the electronic map of the vehicle-mounted positioning system according to the strapdown inertial navigation calculation result in the vehicle-mounted positioning system.
And step 103, determining corresponding filtering data and filtering parameters according to the environmental state type.
And 104, correcting the strapdown inertial navigation calculation result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model.
And 105, determining a vehicle positioning result according to the corrected result of the strapdown inertial navigation calculation.
The execution main body of the vehicle positioning method provided by the embodiment of the application is the vehicle positioning device.
The vehicle positioning method provided by the application can be suitable for vehicle positioning of vehicles in various environments, and the environments of the vehicle positioning method can be particularly provided with areas with road information, including but not limited to satellite signal dead zones, and the vehicle positioning method is particularly suitable for high-speed/trunk transportation with bad satellite signals.
It should be noted that, the vehicle positioning method can be used together with the existing GPS positioning technology, for example, when the vehicle executes an autopilot task or performs a navigation task, the GPS technology and the vehicle positioning method provided by the present application can be synchronously utilized to provide positioning services for the autopilot task or the navigation task, so as to supplement the vehicle positioning based on the GPS technology. In addition, the vehicle positioning method can also independently provide positioning service for the vehicle in an automatic driving task or a navigation task, and particularly has better universality and better positioning effect in the scene that GPS signals cannot be well received, such as high-speed/trunk transportation including satellite signal faults.
Before executing step 101, the vehicle positioning method provided by the application optionally performs an initialization process on the vehicle-mounted positioning system when the vehicle is started, so as to initialize each parameter in the vehicle-mounted positioning system.
Specifically, the initialization of the GPS receiver can be automatically completed by powering on and placing the GPS receiver in the open area for a few seconds. For the strapdown inertial navigation positioning module, the initialization of the strapdown inertial navigation positioning module needs to meet two conditions that the vehicle speed exceeds a threshold value and the GPS receiver is initialized, wherein the vehicle speed can be acquired through a vehicle speed sensor, and the vehicle speed threshold value can be 10km/h.
And then, the vehicle-mounted positioning device assigns an effective GPS signal acquired by the GPS receiver to the initial pose of the strapdown inertial navigation positioning module so as to finish the initialization of the strapdown inertial navigation positioning module.
Under the condition that an effective GPS signal obtained by a GPS receiver is effective, initial filtering parameters of self-adaptive Kalman filtering in a filtering module in a vehicle-mounted positioning system are set, so that system initialization is completed.
After the initialization of the vehicle-mounted positioning system is completed, the vehicle positioning device performs strapdown inertial navigation calculation on the vehicle-mounted positioning system to obtain a strapdown inertial navigation calculation result. The strapdown inertial navigation positioning module in the vehicle-mounted positioning system can perform error compensation on a moving vehicle, namely, the heading, the gesture, the speed and the position of the vehicle are calculated according to each piece of measurement information in the vehicle-mounted positioning system.
In order to reduce the influence of output noise of the strapdown gyroscope and the accelerometer on the system calculation accuracy in an actual system and fully utilize output information, the outputs of the gyroscope and the accelerometer are all in an increment form, namely the accelerometer output is a speed increment, the gyroscope output is an angle increment (the output of the liquid-floated gyroscope or the flexible gyroscope and the accelerometer is converted into pulse output by adopting I-F or V-F, and the laser gyroscope is the pulse output). In this case, the gesture and navigation solutions can only be accomplished by solving the differential equations, and when there is linear and angular vibration of the vehicle, or maneuver movement of the vehicle, there will be a cone error in the gesture solution, a pitch error in the velocity solution, and a scroll error in the position solution. Among these errors, the cone error has the most serious influence on the strapdown inertial navigation accuracy, the pitch error is secondary, the scroll error is the lightest, and strict compensation is required in the corresponding algorithm.
Specifically, in this embodiment, the vehicle positioning device performs strapdown inertial navigation calculation processing on the vehicle positioning system, completes the whole strapdown inertial navigation calculation based on IMU calculation, and periodically adopts effective GPS information and default adaptive kalman filter parameters to correct the IMU calculation result in a traditional loose coupling manner. This part is prior art and is not described in detail.
Unlike the prior art, the vehicle positioning method provided by the application can realize accurate positioning of the vehicle under the condition that the GPS signal is invalid. The application further comprises the step of judging whether the GPS signal state acquired by the vehicle-mounted positioning system is valid.
In other embodiments, the determination of whether the GPS signal state is valid is accomplished as follows:
if the number of GPS signals in the received GPS signals is greater than or equal to a number threshold value and the number of effective GPS signals is greater than a signal threshold value, the GPS signal state is effective; if the number of GPS signals in the received GPS signals is smaller than the number threshold or the number of effective GPS signals is smaller than or equal to the signal threshold, the GPS signal state is invalid.
Specifically, table 1 provides a way to determine the state of the GPS signal.
TABLE 1
In table 1, the number threshold is 6 and the signal threshold is 5. The number threshold is greater than or equal to the signal threshold, and it is understood that the number threshold and the signal threshold in table 1 are only exemplary, and may be other values satisfying the condition.
That is, the GPS signals acquired by the vehicle positioning system are transmitted from a plurality of satellites, and by using the determination strategy of table 1, the GPS signal status is valid only when the number of GPS signals and the number of valid GPS signals satisfy the corresponding number requirements. And when the number of the GPS signals does not meet the corresponding number requirement and/or the effective GPS signals do not meet the corresponding number requirement, the GPS signal states are invalid.
The manner of determining whether the GPS signal is a valid CPS signal is a conventional manner, and will not be described in detail herein.
It should be noted that, when the vehicle is in a special environment including a dense urban building area, tunnel culverts, a dense tree road and other satellite signal blind areas, the GPS signal state is often in an invalid state. This will also lead to corrections to the strapdown inertial navigation solution achieved based on the GPS signals, the accuracy of which will be problematic. Based on the situation, in the application, the type of the environment state of the vehicle in the electronic map of the vehicle-mounted positioning system is determined according to the strapdown inertial navigation calculation result in the vehicle-mounted positioning system, corresponding filtering data and filtering parameters are determined, and the strapdown inertial navigation calculation result is corrected by adopting the adaptive Kalman filtering model so as to obtain the positioning result of the vehicle.
That is, when determining that the GPS signal state acquired by the vehicle-mounted positioning system is invalid, the device calls an electronic map of the vehicle-mounted positioning system, determines pose information of the vehicle in the electronic map by using pose information in a strapdown inertial navigation solution result, further determines an environment state type of the vehicle in the electronic map, determines filtering data and filtering parameters for self-adaptive Kalman filtering according to the environment state type, and corrects the strapdown inertial navigation solution result based on the obtained filtering data and the filtering parameters; and finally, determining a vehicle positioning result according to the correction result of the strapdown inertial navigation calculation.
Optionally, when determining the vehicle positioning result according to the correction result of the strapdown inertial navigation solution, if the GPS signal is determined to be valid at this time, the error between the correction result of the strapdown inertial navigation solution and the GPS positioning result needs to be compared, and when the absolute value of the positioning error between the correction result of the strapdown inertial navigation solution and the GPS positioning result is smaller than a preset first positioning error threshold and the absolute value of the orientation error between the correction result of the strapdown inertial navigation solution and the GPS positioning result is smaller than the preset first orientation error threshold, the correction result based on the strapdown inertial navigation solution can be used as the positioning result, otherwise, the GPS positioning result is used as the positioning result, so that the influence on the positioning result caused by the positioning error due to non-convergence of the adaptive kalman filter can be reduced.
The first positioning error threshold value can be determined according to the Euclidean distance difference between the IMU and the GPS position point when the vehicle-mounted positioning system is started or after the strapdown inertial navigation solution reset is completed; the first orientation error can be determined according to the course angle difference between the IMU and the GPS when the vehicle-mounted positioning system is started or after the strapdown inertial navigation solution is reset.
According to the vehicle positioning method provided by the embodiment, whether the GPS signal state acquired by the vehicle-mounted positioning system is effective or not is judged; if the GPS signal state is invalid, determining the type of the environment state of the vehicle in an electronic map of the vehicle-mounted positioning system according to a strapdown inertial navigation calculation result in the vehicle-mounted positioning system; determining corresponding filtering data and filtering parameters according to the environmental state type; correcting the strapdown inertial navigation calculation result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model; and determining a vehicle positioning result according to the correction result of the strapdown inertial navigation calculation. Under the condition that GPS signals are invalid, the type of the environment state of the vehicle in the electronic map is utilized to determine the filtering data and the filtering parameters which are most matched with the type of the environment state, and further, according to the most matched filtering data and the most matched filtering parameters, the adaptive Kalman filtering model is adopted to correct the strapdown inertial navigation calculation result, then, an accurate correction result can be obtained, and further, an accurate vehicle positioning result can be obtained.
In other optional embodiments, when it is determined that the GPS signal state acquired by the vehicle positioning system is valid, similarly to the prior art, the device corrects the strapdown inertial navigation solution result acquired by the vehicle positioning system by adopting the adaptive filtering algorithm according to the valid GPS signal acquired by the vehicle positioning system and the adaptive kalman filter parameter obtained by initializing the vehicle positioning system, and then inputs the corrected strapdown inertial navigation solution result into the electronic map, and determines the vehicle positioning result of the vehicle in the electronic map according to the strapdown inertial navigation solution result.
In the vehicle positioning method, in order to enable the positioning effect to be better, the application provides different positioning modes for the condition that different GPS signals fail. The environment state type is mainly divided into two types, namely a signal blind area (such as a tunnel, a culvert and the like) where the vehicle is in a long-term signal lock losing state and a signal blind area state (such as an urban canyon area, a road with high and dense trees and the like) where the vehicle is in a short-term signal lock losing state. The application also provides another vehicle positioning method facing different environment state types, so as to ensure that a processing mode which is more consistent with the environment state types is adopted under different types of environments, and the positioning of the vehicle is realized.
Fig. 3 is a flow chart of another vehicle positioning method provided by the present application, as shown in fig. 3, the vehicle positioning method includes:
step 201, initializing a vehicle-mounted positioning system.
Step 202, carrying out strapdown inertial navigation calculation on the vehicle-mounted positioning system to obtain a strapdown inertial navigation calculation result.
And 203, judging whether the GPS signal state acquired by the vehicle-mounted positioning system is valid.
If so, go to step 204; if not, step 205 is performed.
And 204, correcting a strapdown inertial navigation calculation result obtained by the vehicle-mounted positioning system according to the effective GPS signals obtained by the vehicle-mounted positioning system and the obtained self-adaptive Kalman filtering parameters for initializing the vehicle-mounted positioning system.
After correcting the strapdown inertial navigation calculation result, inputting the corrected strapdown inertial navigation calculation result into the electronic map, and determining a vehicle positioning result of the vehicle in the electronic map according to the strapdown inertial navigation calculation result.
Step 205, determining the type of the environment state of the vehicle in the electronic map of the vehicle-mounted positioning system according to the strapdown inertial navigation solution result in the vehicle-mounted positioning system, and determining corresponding filtering data and filtering parameters according to the type of the environment state.
Optionally, in step 205, determining the type of the environmental state of the vehicle in the electronic map of the vehicle positioning system according to the strapdown inertial navigation solution result in the vehicle positioning system specifically includes:
step 205a, determining the environmental characteristics of the vehicle in the electronic map of the vehicle-mounted positioning system according to the strapdown inertial navigation solution result in the vehicle-mounted positioning system.
And step 205b, if the environmental characteristic is determined to be the closed environmental characteristic, determining that the environmental state type is a signal blind area state of the vehicle in long-term signal lock loss.
And 205c, if the environmental characteristic is determined to be an open environmental characteristic, determining that the environmental state type is a signal blind area state of the vehicle in short-term signal lock loss.
Specifically, the position information of the vehicle is included in the strapdown inertial navigation calculation result, position information closest to the position information and on the road of the electronic map can be determined in the electronic map according to the position information of the vehicle, and the position information closest to the position information and on the road of the electronic map is used as the position information of the vehicle in the electronic map. And then determining the environmental characteristics of the vehicle in the electronic map according to the pose information of the vehicle in the electronic map.
If the environmental features of the vehicle in the electronic map include the environmental features of tunnels, culverts, underground channels and the like which obviously cannot receive GPS signals, the environmental features are determined to be closed environmental features, and the environmental state type is a signal blind area state of long-term signal unlocking. If the environmental features of the vehicle in the electronic map include surface roads, namely no closed environmental features, the environmental features are determined to be open environmental features, and the environmental state type is determined to be a signal blind area state of short-term signal lock loss.
If the environmental state type is determined to be the signal blind area state of the vehicle in the long-term signal lock loss state, executing step 206;
if it is determined that the current environmental status type of the vehicle is a signal blind area status in which the vehicle is out of lock for a short period of time, step 207 is performed.
Step 206, calculating a first difference value between pose information in the electronic map and pose information in the strapdown inertial navigation calculation result, determining the first difference value as filtering data, and determining preset filtering parameters corresponding to tunnels and culverts as filtering parameters.
In this embodiment, when the environmental state type is a signal blind area state in which the vehicle is in a long-term signal lock loss state, pose information of the vehicle in the electronic map can be calculated. And calculating the filtering data by using the pose information in the electronic map and the pose information in the strapdown inertial navigation calculation result. Specifically, a difference value between pose information in the electronic map and pose information in a strapdown inertial navigation calculation result is calculated, the difference value is a first difference value, and the first difference value is determined as filtering data.
Optionally, when the pose information of the vehicle in the electronic map is calculated, determining the pose information of the vehicle in the electronic map according to the strapdown inertial navigation calculation result.
Specifically, pose information closest to pose information in the strapdown inertial navigation calculation result is determined in the electronic map according to the pose information in the strapdown inertial navigation calculation result, and the closest pose information is located on a road of the electronic map; and determining the closest pose information as pose information of the vehicle in the electronic map.
More specifically, mapping pose information in a strapdown inertial navigation calculation result to an electronic map to obtain a vehicle mapping pose, and matching the vehicle mapping pose with the electronic map by adopting a preset matching algorithm to obtain most likely vehicle pose information, wherein the most likely vehicle pose information is pose information of a vehicle in the electronic map. The most likely vehicle pose is located on the road of the electronic map and is the pose information closest to the vehicle pose information in the strapdown inertial navigation solution.
The preset matching algorithm is not limited in this embodiment.
In this embodiment, filtering parameters under different environmental status types are preset. And acquiring preset filtering parameters under the state of the signal blind area of the long-term signal loss lock of the vehicle, namely acquiring preset filtering parameters corresponding to the tunnel and the culvert, and determining the filtering parameters as the filtering parameters of the self-adaptive Kalman filtering when the vehicle is in the state of the signal blind area of the long-term signal loss lock.
After step 206 is performed, step 208 is performed.
Step 207, calculating a second difference value between the speedometer speed data of the vehicle-mounted positioning system and the speed data in the strapdown inertial navigation calculation result, and determining the second difference value as filtering data; and determining the filtering parameters of the preset signal shielding area as the filtering parameters.
In this embodiment, when the environmental state type is that the vehicle is in a signal blind area state of short-term signal lock loss, the odometer speed data can be obtained. The filtered data is calculated using the odometer speed data and the speed data in the strapdown inertial navigation solution. Specifically, a difference between the odometer speed data and the speed data in the strapdown inertial navigation solution is calculated, the difference being a second difference, and the second difference being determined as the filtered data.
In this embodiment, a preset filtering parameter is obtained when the vehicle is in a signal blind area state of short-term signal loss lock, that is, a filtering parameter corresponding to a preset signal shielding area is obtained, and the filtering parameter is determined to be a filtering parameter of adaptive kalman filtering when the vehicle is in a signal blind area state of short-term signal loss lock.
And step 208, correcting the strapdown inertial navigation calculation result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model.
Optionally, in this embodiment, step 208 includes the steps of:
step 2081, the filtered data and the filtered parameters are input into the adaptive Kalman filtering model.
And step 2082, calculating a correction error corresponding to the strapdown inertial navigation calculation result by adopting the adaptive Kalman filtering model.
And step 2083, correcting the strapdown inertial navigation calculation result according to the correction error.
The adaptive Kalman filtering model is a system model which is pushed out by strapdown inertial navigation in Kalman filtering, and can be expressed as a formula I and a formula II:
δx k ＝Φ k/k-1 δx k-1 +W k-1 i is a kind of
Z k ＝H k δx k +V k II (II)
Wherein δx k And the system state variable is also the correction error corresponding to the strapdown inertial navigation calculation result in the kth iterative calculation. Phi k/k-1 For the system state transition matrix, W k-1 Is the system noise vector, H k For the system measurement matrix, V k To measure the noise vector. Z is Z k Represented as filtered data.
Wherein the system state variable may be represented by formula III:
the 15 variables in the formula III are respectively east, north and sky misalignment angle correction errors, east, north and sky speed correction errors, latitude, longitude and altitude correction errors. Gyro zero offset drift and accelerometer zero offset values in x, y and z directions. The zero offset drift of the gyroscope and the zero offset value of the accelerometer in the x, y and z directions are parameters of strapdown inertial navigation calculation.
Corresponding to the system state variables, the system noise vector is:
wherein phi is k/k-1 After the system state variables of the matrix are determined, the matrix can be deduced along with a strapdown inertial navigation calculation algorithm, and the description is omitted here; h k After the observed quantity is determined, it can be expressed as formula V:
H＝[0 7×2 I 7×7 0 7×6 ]v (V)
Correspondingly, measure the noise vector V k Can be represented by formula VI:
the variables in formula VI correspond to the measured noise of course angle, east direction, north direction, sky direction, latitude and longitude elevation respectively.
Specifically, in this embodiment, the filtering data and the filtering parameters are input into the adaptive kalman filter model, the adaptive kalman filter model is solved in an iterative manner, and the calculation process shown in formula VII is performed in one iteration process:
in the formula VII, the five formulas are respectively represented as a dynamic system prediction matrix, a state covariance prediction matrix, a filtering gain matrix, a state update matrix, and a state covariance update matrix.
In formula VII, δx k-1 P is the corrected error after the kth iteration k-1 、Q k-1 R is R k Are all filtering parameters, Z k For filtering the data.
It should be noted that the adaptive predictor α and the adaptive noise modifier β may be added to the formula VII. The positions of α and β are not limited, and α may be added to the second formula of formula VII and β may be added to the third formula of formula VII.
In the first iterative calculation δx 0 Has a value of 0, P 0 、Q 0 R is R 1 The value of the filter parameter is the value of the filter parameter under the corresponding environment state type. Z is Z 1 Is the filtered data for the calculated environmental state type. After the first iteration is calculated, P in the second iteration is obtained 1 、δx 1 . According to δx 1 Correcting the strapdown inertial navigation settlement result to obtain a corrected strapdown inertial navigation settlement result, and calculating filtering data Z in the second iteration according to the corrected strapdown inertial navigation settlement result 2 。Q 0 R is R 1 The value of the filter parameter is unchanged. And P is taken up 1 、δx 1 、Q 0 R is R 1 Carry-inA third iterative calculation is performed into VII, and so on, until a convergence condition is reached. The convergence condition may be that the correction error of the kth time is approximately equal to the correction error of the k+1th time, or the iteration number reaches the preset iteration number.
It should be noted that, among the above filtering parameters corresponding to different environmental states, when the GPS signal validity and the road scene are switched, the above filtering parameters are reset.
Step 209, determining a vehicle positioning result according to the corrected result of the strapdown inertial navigation solution.
In addition, on the basis of the above embodiment, if the current environmental state type of the vehicle is that the vehicle is in a signal blind area state of short-term signal loss lock, after step 209, the method further includes:
Re-acquiring the GPS signals and determining a GPS positioning result according to the re-acquired GPS signals when the signal state of the re-acquired GPS signals is determined to be effective; and determining whether to re-execute the initialization processing of the vehicle-mounted positioning system according to the GPS positioning result and the positioning error and the direction error between the positioning results of the vehicle.
Specifically, when the GPS signal is invalid and the vehicle is in a tunnel culvert scene, comparing a strapdown inertial navigation settlement result with a GPS positioning result when the GPS is valid again, and when the absolute value of positioning errors of the GPS signal and the GPS positioning result is smaller than a second positioning error threshold value and the orientation error of the GPS signal and the GPS positioning result is smaller than a second orientation error threshold value, indicating that the corrected strapdown inertial navigation settlement result is accurate; otherwise, the device needs to reset the vehicle-mounted positioning system and the corresponding adaptive Kalman filtering parameters, and then continues to execute the process of initializing the vehicle-mounted positioning system again. The second positioning error threshold is determined by the Euclidean distance difference between the IMU and the GPS position point when the vehicle exits the tunnel; the second orientation error threshold is determined by a heading angle difference between the IMU and the GPS when the vehicle exits the tunnel.
According to the vehicle positioning method provided by the application, the vehicle-mounted positioning system is initialized; carrying out strapdown inertial navigation calculation on the vehicle-mounted positioning system to obtain a strapdown inertial navigation calculation result; judging whether the GPS signal state acquired by the vehicle-mounted positioning system is effective or not, if not, determining the type of the environment state of the vehicle in an electronic map of the vehicle-mounted positioning system according to the strapdown inertial navigation calculation result in the vehicle-mounted positioning system, and determining corresponding filtering data and filtering parameters according to the type of the environment state; correcting the strapdown inertial navigation calculation result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model; and determining a vehicle positioning result according to the correction result of the strapdown inertial navigation calculation. The vehicle full-road section accurate positioning method is used for realizing the vehicle full-road section accurate positioning under special environments such as satellite signal blind areas including urban building dense areas, tunnel culverts, high and dense trees and the like.
In a second aspect, fig. 4 is a schematic structural diagram of a vehicle positioning device according to the present application, as shown in fig. 4, where the vehicle positioning device includes:
the judging module 10 is configured to judge whether the GPS signal state acquired by the vehicle positioning system is valid.
The first determining module 20 is configured to determine, if the GPS signal status is determined to be invalid, a type of an environmental status of the vehicle in an electronic map of the vehicle positioning system according to a strapdown inertial navigation solution result in the vehicle positioning system;
the second determining module 30 is configured to determine the corresponding filtering data and the filtering parameters according to the environmental status type.
And the correction module 40 is used for correcting the strapdown inertial navigation calculation result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model.
The third determining module 50 is configured to determine a vehicle positioning result according to the corrected result of the strapdown inertial navigation solution.
Optionally, the first determining module 20 is specifically configured to determine, according to a strapdown inertial navigation solution result in the vehicle-mounted positioning system, an environmental feature of the vehicle in an electronic map of the vehicle-mounted positioning system; if the environmental characteristics are determined to be the closed environmental characteristics, determining that the environmental state type is a signal blind area state of long-term signal lock losing; and if the environmental characteristics are determined to be open environmental characteristics, determining that the environmental state type is a signal blind area state of short-term signal unlocking.
Optionally, if the environment state type is determined to be a signal blind area state of the vehicle in which the vehicle is out of lock for a long time, the first determining module 20 is further configured to determine pose information of the vehicle in the electronic map according to a strapdown inertial navigation solution result after determining that the GPS signal state is invalid.
Optionally, the first determining module 20 is specifically configured to, when determining pose information of the vehicle in the electronic map according to the strapdown inertial navigation solution result: determining pose information closest to pose information in the strapdown inertial navigation calculation result in the electronic map according to the pose information in the strapdown inertial navigation calculation result, wherein the closest pose information is positioned on a road of the electronic map; and determining the closest pose information as pose information of the vehicle in the electronic map.
Optionally, the second determining module 30 is specifically configured to calculate a first difference between pose information in the electronic map and pose information in the strapdown inertial navigation solution result if the environmental state type is determined to be a signal blind area state where the vehicle is in a long-term signal loss lock, determine the first difference as filtering data, and determine filtering parameters corresponding to a preset tunnel and culvert as filtering parameters; if the current environment state type of the vehicle is determined to be a signal blind area state of short-term signal lock losing of the vehicle, calculating a second difference value between the speedometer speed data of the vehicle-mounted positioning system and the speed data in the strapdown inertial navigation solution result, and determining the second difference value as filtering data; and determining the filtering parameters of the preset signal shielding area as the filtering parameters.
Optionally, the correction module 40 is specifically configured to input the filtering data and the filtering parameters into the adaptive kalman filtering model; calculating a correction error corresponding to the strapdown inertial navigation calculation result by adopting a self-adaptive Kalman filtering model; and correcting the strapdown inertial navigation calculation result according to the correction error.
Optionally, the vehicle positioning device further includes: the fourth determining module is used for re-acquiring the GPS signal and determining a GPS positioning result according to the re-acquired GPS signal when determining that the signal state of the re-acquired GPS signal is effective if the current environment state type of the vehicle is a signal blind area state of short-term signal lock losing of the vehicle; and determining whether to execute initialization processing on the vehicle-mounted positioning system according to the pose error between the GPS positioning result and the vehicle positioning result.
Optionally, the vehicle positioning device further includes: the device comprises an acquisition module and a calculation module.
The acquisition module is used for acquiring GPS positioning information corresponding to the effective GPS signals, a strapdown inertial navigation resolving result and filtering parameters obtained by initializing the vehicle-mounted positioning system if the GPS signal state is determined to be effective. And the calculation module is used for calculating a third difference value between the vehicle positioning result corresponding to the effective GPS signal and the strapdown inertial navigation calculation result. And the correction module is also used for correcting the strapdown inertial navigation calculation result according to the third difference value, the filtering parameter obtained by initializing the vehicle-mounted positioning system and the adaptive Kalman filtering model.
Optionally, the GPS signals acquired by the in-vehicle positioning system are transmitted by a plurality of satellites.
Correspondingly, the judging module 10 is specifically configured to, if the number of GPS signals in the received GPS signals is greater than or equal to the number threshold and the number of valid GPS signals is greater than the signal threshold, enable the GPS signal status; if the number of GPS signals in the received GPS signals is smaller than the number threshold or the number of effective GPS signals is smaller than or equal to the signal threshold, the GPS signal state is invalid.
The vehicle positioning device provided by the application can execute the technical scheme of the method embodiment shown in fig. 2 and 3, and the implementation principle and the technical effect are similar to those of the method embodiment shown in fig. 2 and 3, and are not repeated here.
In the next aspect, fig. 5 is a schematic structural diagram of a vehicle positioning assembly provided by the present application, where the vehicle positioning assembly provided in this embodiment includes: a vehicle positioning system and a vehicle positioning controller; the vehicle-mounted positioning system comprises a GPS receiver, a strapdown inertial navigation positioning module, an electronic map module and a filtering module; the vehicle positioning controller is used for controlling the vehicle positioning system to perform vehicle positioning by adopting the method of any one of the above steps. This embodiment will not be described in detail.
In the next aspect, the present embodiment further provides an electronic device, which may be configured to execute the technical solution of the foregoing method embodiment, and the implementation principle and the technical effect are similar, and this embodiment is not repeated herein.
Referring to fig. 6, there is shown a schematic structural diagram of an electronic device 900 suitable for implementing an embodiment of the present application, where the electronic device 900 may be a terminal device or a server. The terminal device may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a personal digital assistant (Personal Digital Assistant, PDA for short), a tablet (Portable Android Device, PAD for short), a portable multimedia player (Portable Media Player, PMP for short), an in-vehicle terminal (e.g., an in-vehicle navigation terminal), and the like, and a fixed terminal such as a digital TV, a desktop computer, and the like. The electronic device shown in fig. 6 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments of the application.
As shown in fig. 6, the electronic apparatus 900 may include a positioning device (e.g., a central processing unit, a graphics processor, etc.) 901 that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 902 or a program loaded from a storage device 908 into a random access Memory (Random Access Memory, RAM) 903. In the RAM 903, various programs and data necessary for the operation of the electronic device 900 are also stored. The positioning device 901, the ROM 902, and the RAM 903 are connected to each other by a bus 904. An input/output (I/O) interface 905 is also connected to the bus 904.
In general, the following devices may be connected to the I/O interface 905: input devices 906 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, and the like; an output device 907 including, for example, a liquid crystal display (Liquid Crystal Display, LCD for short), a speaker, a vibrator, and the like; storage 908 including, for example, magnetic tape, hard disk, etc.; and a communication device 909. The communication means 909 may allow the electronic device 900 to communicate wirelessly or by wire with other devices to exchange data. While fig. 6 shows an electronic device 900 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead.
In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via the communication device 909, or installed from the storage device 908, or installed from the ROM 902. When the computer program is executed by the positioning device 901, the above-described functions defined in the method of the embodiment of the present application are performed.
The computer readable medium of the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.
The computer-readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to perform the methods shown in the above-described embodiments.
Computer program code for carrying out operations of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a local area network (Local Area Network, LAN for short) or a wide area network (Wide Area Network, WAN for short), or it may be connected to an external computer (e.g., connected via the internet using an internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented in software or in hardware. The name of the unit does not in any way constitute a limitation of the unit itself, for example the first acquisition unit may also be described as "unit acquiring at least two internet protocol addresses".
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.
In the context of the present application, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Claims (11)
1. A vehicle positioning method, characterized by comprising:
judging whether the GPS signal state acquired by the vehicle-mounted positioning system is valid or not;
if the GPS signal state is invalid, determining the type of the environment state of the vehicle in an electronic map of the vehicle-mounted positioning system according to a strapdown inertial navigation calculation result in the vehicle-mounted positioning system;
determining corresponding filtering data and filtering parameters according to the environmental state type;
correcting the strapdown inertial navigation calculation result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model;
determining a vehicle positioning result according to the correction result of strapdown inertial navigation calculation;
according to the environment state type, determining corresponding filtering data and filtering parameters comprises the following steps:
if the environment state type is determined to be a signal blind area state of the vehicle in long-term signal lock losing, calculating a first difference value between pose information in the electronic map and pose information in a strapdown inertial navigation resolving result, determining the first difference value as filtering data, determining preset filtering parameters corresponding to tunnels and culverts as filtering parameters, wherein the signal blind area state of the vehicle in long-term signal lock losing is used for indicating that the environment characteristics of the vehicle in the electronic map, including the tunnels, the culverts and underground channels, obviously cannot receive GPS signals;
If the current environment state type of the vehicle is determined to be a signal blind area state of short-term signal lock losing of the vehicle, calculating a second difference value between the speedometer speed data of the vehicle-mounted positioning system and the speed data in the strapdown inertial navigation solution result, and determining the second difference value as filtering data; and determining a filtering parameter of a preset signal shielding area as the filtering parameter, wherein the state that the vehicle is in a signal blind area state of short-term signal unlocking is used for indicating that the vehicle comprises an earth surface road in the environmental characteristics of the electronic map.
2. The vehicle positioning method according to claim 1, wherein the type of the environmental state of the vehicle in the electronic map of the vehicle positioning system is determined according to the strapdown inertial navigation solution in the vehicle positioning system;
determining the environmental characteristics of the vehicle in an electronic map of the vehicle-mounted positioning system according to the strapdown inertial navigation calculation result in the vehicle-mounted positioning system;
if the environmental characteristics are determined to be the closed environmental characteristics, determining that the environmental state type is a signal blind area state of the vehicle in long-term signal lock losing;
and if the environmental characteristics are determined to be open environmental characteristics, determining that the environmental state type is a signal blind area state of the vehicle in short-term signal unlocking.
3. The vehicle positioning method according to claim 2, characterized in that, if it is determined that the environmental state type is a signal blind state in which the vehicle is out of lock for a long period of time, after it is determined that the GPS signal state is invalid, further comprising:
and determining pose information of the vehicle in the electronic map according to the strapdown inertial navigation calculation result.
4. The vehicle positioning method according to claim 3, wherein determining pose information of the vehicle in the electronic map based on the strapdown inertial navigation solution result includes:
determining pose information closest to pose information in the strapdown inertial navigation calculation result in the electronic map according to the pose information in the strapdown inertial navigation calculation result, wherein the closest pose information is positioned on a road of the electronic map;
and determining the closest pose information as pose information of the vehicle in the electronic map.
5. The vehicle positioning method according to claim 1, wherein correcting the strapdown inertial navigation solution according to the filter data, the filter parameters, and the adaptive kalman filter model includes:
inputting the filtering data and the filtering parameters into an adaptive Kalman filtering model;
calculating a correction error corresponding to the strapdown inertial navigation calculation result by adopting a self-adaptive Kalman filtering model;
And correcting the strapdown inertial navigation calculation result according to the correction error.
6. The vehicle positioning method according to claim 5, wherein if the current environmental state type of the vehicle is a signal blind area state of short-term signal loss lock, correcting the strapdown inertial navigation solution result according to the filtering data, the filtering parameters and the adaptive kalman filter model further comprises:
re-acquiring the GPS signals and determining a GPS positioning result according to the re-acquired GPS signals when the signal state of the re-acquired GPS signals is determined to be effective;
and determining whether to execute initialization processing on the vehicle-mounted positioning system according to the pose error between the GPS positioning result and the vehicle positioning result.
7. The vehicle positioning method according to claim 1, characterized by further comprising, if it is determined that the GPS signal state is valid:
acquiring GPS positioning information corresponding to an effective GPS signal, a strapdown inertial navigation resolving result and filtering parameters obtained by initializing a vehicle-mounted positioning system;
calculating a third difference value between a vehicle positioning result corresponding to the effective GPS signal and a strapdown inertial navigation calculation result;
and correcting the strapdown inertial navigation calculation result according to the third difference value, the filtering parameter obtained by initializing the vehicle-mounted positioning system and the adaptive Kalman filtering model.
8. The vehicle positioning method according to any one of claims 1 to 7, characterized in that GPS signals acquired by an on-board positioning system are transmitted by a plurality of satellites;
correspondingly, judging whether the GPS signal state acquired by the vehicle-mounted positioning system is valid or not comprises the following steps:
if the number of GPS signals in the received GPS signals is greater than or equal to a number threshold value and the number of effective GPS signals is greater than a signal threshold value, the GPS signal state is effective;
if the number of GPS signals in the received GPS signals is smaller than the number threshold or the number of effective GPS signals is smaller than or equal to the signal threshold, the GPS signal state is invalid.
9. A vehicle locating assembly, comprising: a vehicle positioning system and a vehicle positioning controller;
the vehicle-mounted positioning system comprises a GPS receiver, a strapdown inertial navigation positioning module, an electronic map module and a filtering module;
a vehicle positioning controller for controlling the vehicle positioning system to perform vehicle positioning using the method of any one of claims 1-8.
10. An electronic device, comprising: at least one processor and memory;
the memory stores computer-executable instructions;
at least one processor executing computer-executable instructions stored in memory causes the at least one processor to perform the method of any one of claims 1-8.
11. A computer readable storage medium, characterized in that computer executable instructions are stored in the computer readable storage medium, which when executed by a processor, implement the method according to any of claims 1-8.
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