1. A vehicle positioning method, characterized by comprising:

judging whether the GPS signal state acquired by the vehicle-mounted positioning system is valid;

if the GPS signal state is determined to be invalid, determining the type of the environmental state of the vehicle in an electronic map of the vehicle-mounted positioning system according to a strapdown inertial navigation resolving result in the vehicle-mounted positioning system;

determining corresponding filtering data and filtering parameters according to the environment state type;

correcting a strapdown inertial navigation resolving 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 solution.

2. The vehicle positioning method according to claim 1, characterized in that the type of the environmental state of the vehicle in the electronic map of the vehicle-mounted positioning system is determined according to the calculation result of the strapdown inertial navigation in the vehicle-mounted 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 resolving result in the vehicle-mounted positioning system;

if the environmental characteristic is determined to be the closed environmental characteristic, determining that the environmental state type is a signal blind area state that the vehicle is in a long-term signal unlocking state;

and if the environmental characteristic is determined to be the open environmental characteristic, determining that the environmental state type is a signal blind area state that the vehicle is in short-term signal unlocking.

3. The vehicle positioning method according to claim 2, wherein if it is determined that the environmental status type is a signal blind zone status in which the vehicle is in a long-term signal loss of lock, after determining that the GPS signal status is invalid, further comprising:

and determining the pose information of the vehicle in the electronic map according to the strapdown inertial navigation resolving result.

4. The vehicle positioning method according to claim 3, wherein determining pose information of the vehicle in the electronic map according to the strapdown inertial navigation solution result comprises:

determining pose information which is closest to the pose information in the strapdown inertial navigation resolving result in the electronic map according to the pose information in the strapdown inertial navigation resolving result, wherein the closest pose information is positioned on a road of the electronic map;

and determining the closest pose information as the pose information of the vehicle in the electronic map.

5. The vehicle positioning method of claim 2, wherein determining the corresponding filter data and filter parameters according to the environmental status type comprises:

if the environment state type is determined to be a signal blind area state of the vehicle in long-term signal loss of lock, 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, and determining filtering parameters corresponding to a preset tunnel and a culvert as filtering parameters;

if the current environment state type of the vehicle is determined to be the signal blind area state that the vehicle is in short-term signal unlocking, calculating a second difference value between the odometer speed data of the vehicle-mounted positioning system and the speed data in the strapdown inertial navigation resolving result, and determining the second difference value as filtering data; and determining the preset filtering parameters of the signal shielding area as the filtering parameters.

6. The vehicle positioning method according to claim 1, wherein the correction of the strapdown inertial navigation solution result according to the filter data, the filter parameters and the adaptive Kalman filter model comprises:

inputting the filtering data and the filtering parameters into an adaptive Kalman filtering model;

calculating a correction error corresponding to a strapdown inertial navigation resolving result by adopting an adaptive Kalman filtering model;

and correcting the strapdown inertial navigation calculation result according to the correction error.

7. The vehicle positioning method according to claim 6, wherein if the current environment state type of the vehicle is a signal blind area state where the vehicle is in short-term signal lock loss, after the strapdown inertial navigation solution result is corrected according to the filtering data, the filtering parameters and the adaptive Kalman filtering model, the method further comprises:

re-acquiring the GPS signal and determining a GPS positioning result according to the re-acquired GPS signal when the signal state of the re-acquired GPS signal is determined to be effective;

and determining whether to perform initialization processing on the vehicle-mounted positioning system according to the pose error between the GPS positioning result and the vehicle positioning result.

8. The vehicle positioning method of claim 1, wherein if the GPS signal status is determined to be valid, further comprising:

acquiring GPS positioning information corresponding to an effective GPS signal, a strapdown inertial navigation resolving result and a filtering parameter 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 resolving result;

and correcting the strapdown inertial navigation resolving result according to the third difference, the filtering parameters obtained by initializing the vehicle-mounted positioning system and the adaptive Kalman filtering model.

9. The vehicle positioning method according to any one of claims 1 to 8, wherein the GPS signals acquired by the in-vehicle positioning system are transmitted by a plurality of satellites;

correspondingly, judge whether the GPS signal state that on-vehicle positioning system obtained is effective, include:

if the number of the GPS signals is larger than or equal to the number threshold value and the number of the effective GPS signals is larger than the signal threshold value in the received GPS signals, the GPS signal state is effective;

if the number of the GPS signals in the received GPS signals is less than the number threshold or the number of the effective GPS signals is less than or equal to the signal threshold, the GPS signal state is invalid.

10. A vehicle locating assembly, comprising: a vehicle-mounted 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 on-board positioning system to position a vehicle using the method of any one of claims 1-9.

11. An electronic device, comprising: at least one processor and memory;

the memory stores computer-executable instructions;

the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the method of any one of claims 1-9.

12. A computer-readable storage medium, having stored thereon computer-executable instructions, which, when executed by a processor, implement the method of any one of claims 1-9.

Background

With the improvement of living standard, driving and traveling become daily choices of people. In the process of driving the vehicle, positioning the vehicle becomes an indispensable link in order to provide navigation signals or route guidance for people.

In the prior art, a vehicle is generally located by using a Global Positioning System (GPS), but when the vehicle is located in a special environment with a blind area of satellite signals, a problem of signal lock loss occurs when a shielding object is located above a GPS receiver, and transmission of a Positioning signal of the GPS is limited. At this time, the accuracy of vehicle positioning cannot be guaranteed.

Disclosure of Invention

In view of the above problems, the present application provides a vehicle positioning method, a component, an electronic device, and a storage medium.

In a first aspect, the present application provides a vehicle positioning method, comprising:

judging whether the GPS signal state acquired by the vehicle-mounted positioning system is valid;

if the GPS signal state is determined to be invalid, determining the type of the environmental state of the vehicle in an electronic map of the vehicle-mounted positioning system according to a strapdown inertial navigation resolving result in the vehicle-mounted positioning system;

determining corresponding filtering data and filtering parameters according to the environment state type;

correcting a strapdown inertial navigation resolving 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 solution.

In a second aspect, the present application provides a vehicle locating device comprising:

the judging module is used for judging whether the GPS signal state acquired by the vehicle-mounted positioning system is effective or not;

the first determination module is used for determining the type of the environmental state of the vehicle in an electronic map of the vehicle-mounted positioning system according to a strapdown inertial navigation resolving result in the vehicle-mounted 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 environment state type;

the correction module is used for correcting the strapdown inertial navigation resolving result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model;

and the third determination module is used for determining a vehicle positioning result according to the correction result of the strapdown inertial navigation calculation.

In a third aspect, the present application provides a vehicle mounted positioning assembly, comprising:

a vehicle-mounted 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 position the vehicle by using the method of any one of the first aspect.

In a fourth aspect, the present application provides an electronic device, comprising: at least one processor and memory;

the memory stores computer-executable instructions;

the at least one processor executes computer-executable instructions stored by the memory to cause the at least one processor to perform a method as in any one of the preceding.

In a fifth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium has stored therein computer-executable instructions, which when executed by a processor, implement the method as in any one of the preceding.

In a sixth aspect, the present application provides a computer program product comprising a computer program which, when executed by a processor, implements the method of any of the preceding.

The vehicle positioning method, the vehicle positioning assembly, the electronic equipment and the storage medium provided by the application judge whether the GPS signal state acquired by the vehicle positioning system is valid; if the GPS signal state is determined to be invalid, determining the type of the environmental state of the vehicle in an electronic map of the vehicle-mounted positioning system according to a strapdown inertial navigation resolving result in the vehicle-mounted positioning system; determining corresponding filtering data and filtering parameters according to the environment state type; correcting a strapdown inertial navigation resolving 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 solution. According to the vehicle positioning method, under the condition that a GPS signal is invalid, the environment state type of the vehicle in an electronic map is utilized to determine the filtering data and the filtering parameters which are most matched with the environment state type, and then the strapdown inertial navigation resolving 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 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 in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.

FIG. 1 is a schematic diagram of a network architecture upon which the present application is based;

FIG. 2 is a schematic flow chart illustrating a vehicle positioning method according to an embodiment of the present disclosure;

FIG. 3 is a schematic flow chart illustrating another vehicle positioning method provided by the embodiment of the present application;

FIG. 4 is a schematic structural diagram of a vehicle positioning device provided herein;

FIG. 5 is a schematic structural diagram of a high precision positioning system provided in 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

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

With the improvement of living standard, driving and traveling become daily choices of people. In the process of driving the vehicle, positioning the vehicle becomes an indispensable link in order to provide navigation signals or route guidance for people.

In the prior art, a Global Positioning System (GPS for short) is generally used to locate a vehicle, but when the vehicle is located in a special environment, such as a satellite signal blind area in a dense urban building area, a tunnel culvert, a tall and dense road with trees, and the like, a problem of signal lock loss occurs under the condition that a shielding object is above a GPS receiver, and transmission of a Positioning signal of the GPS is limited at this time. At this time, the accuracy of vehicle positioning cannot be guaranteed.

Aiming at the problems, the invention 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 the fusion of a GPS sensor, an IMU sensor and an OD sensor, and realizes the whole-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 on which the present application is based, and as shown in fig. 1, a network architecture on which the present application is based may include a vehicle positioning device 1, an on-board positioning system 2, and a vehicle 3.

The vehicle positioning device 1 and the vehicle positioning system 2 are both mounted on a vehicle 3. The vehicle-mounted positioning system 2 can be used for performing vehicle positioning under the control of the vehicle positioning device 1 and acquiring a vehicle positioning result of the vehicle position.

The vehicle-mounted positioning system 2 includes 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 vehicle positioning system 2 to perform calculation, and when the vehicle positioning device is software, the vehicle positioning device may be installed in an electronic device with calculation function, wherein the electronic device includes, but is not limited to, a vehicle computer, a vehicle terminal, and the like.

In a first aspect, referring to fig. 2, fig. 2 is a schematic flowchart of a vehicle positioning method provided in 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 effective.

And 102, if the GPS signal state is determined to be invalid, determining the type of the environmental state of the vehicle in the electronic map of the vehicle-mounted positioning system according to the strapdown inertial navigation resolving result in the vehicle-mounted positioning system.

And 103, determining corresponding filtering data and filtering parameters according to the environment state type.

And 104, correcting the strapdown inertial navigation resolving 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 correction result of the strapdown inertial navigation solution.

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 can specifically have regions with road information, including but not limited to satellite signal blind areas, and is particularly suitable for high-speed/trunk transportation with poor satellite signals.

The vehicle positioning method can be used together with the existing GPS positioning technology, for example, when a vehicle performs an automatic driving 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 automatic driving 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 under the condition that the GPS signals cannot be well received in the scenes such as poor satellite signals, high-speed/trunk transportation and the like.

Before step 101 is executed, optionally, an initialization process is performed 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 only by powering it on and placing it in the open area for several seconds. For the strapdown inertial navigation positioning module, the initialization of the strapdown inertial navigation positioning module needs to simultaneously meet two conditions that the vehicle speed exceeds a threshold value and the GPS receiver completes the initialization, wherein the vehicle speed can be acquired through a vehicle speed sensor, and the vehicle speed threshold value can be 10 km/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 complete the initialization of the strapdown inertial navigation positioning module.

And under the condition that the effective GPS signal acquired by the GPS receiver is effective, setting initial filtering parameters of adaptive Kalman filtering in a filtering module in the vehicle-mounted positioning system, thereby completing system initialization.

After the initialization of the vehicle-mounted positioning system is completed, the vehicle positioning device carries out 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 course, the posture, the speed and the position of the vehicle are calculated according to all measurement information in the vehicle-mounted positioning system.

In order to reduce the influence of output noise of a strapdown gyroscope and an accelerometer on system calculation precision and fully utilize output information in an actual system, the outputs of the gyroscope and the accelerometer are all in an incremental form, namely the output of the accelerometer is velocity increment, and the output of the gyroscope is angle increment (the output of a liquid floating gyroscope or a flexible gyroscope and the output of the accelerometer are converted into pulse output by adopting I-F or V-F, and the laser gyroscope is pulse output by itself). In this case, the attitude solution and the navigation solution can be completed only by solving the differential equations, and when the vehicle has linear vibration and angular vibration, or the vehicle is in maneuvering motion, there will be a cone error in the attitude solution, a rowing error in the speed solution, and a scroll error in the position solution. Among these errors, the cone error will have the most severe effect on the strapdown inertial navigation accuracy, the second order of the sculling error, and the lightest scroll error, and needs to be strictly compensated in the corresponding algorithm.

Specifically, in this embodiment, the vehicle positioning device performs strapdown inertial navigation solution processing on the vehicle positioning system, completes the entire strapdown inertial navigation solution based on IMU calculation, periodically adopts effective GPS information and default adaptive kalman filter parameters, and corrects the IMU calculation result in a conventional loose coupling manner. This section is prior art and will not be described in detail.

Different from 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 method also comprises the step of judging whether the GPS signal state acquired by the vehicle-mounted positioning system is valid or not.

In another embodiment, the determination of whether the GPS signal status is valid is implemented as follows:

if the number of the GPS signals is larger than or equal to the number threshold value and the number of the effective GPS signals is larger than the signal threshold value in the received GPS signals, the GPS signal state is effective; if the number of the GPS signals in the received GPS signals is less than the number threshold or the number of the effective GPS signals is less 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 values of the number threshold and the signal threshold in table 1 are only exemplary illustrations, and may also be other values satisfying the condition.

That is, the GPS signals acquired by the on-board positioning system are transmitted from a plurality of satellites, and the GPS signal status is valid only when both the number of GPS signals and the number of valid GPS signals satisfy the corresponding number requirements by using the determination strategy in table 1. And when the number of the GPS signals does not meet the corresponding number requirement and/or the valid GPS signals do not meet the corresponding number requirement, the GPS signal states are all invalid states.

The method for determining whether the GPS signal is a valid CPS signal is an existing method, and will not be described in detail here.

It should be noted that when the vehicle is in a special environment including a satellite signal blind area such as a dense urban building area, a tunnel culvert, a tall and dense road with trees, and the like, the GPS signal state is often in an invalid state. This will also lead to corrections to the strapdown inertial navigation solution results based on GPS signals, the accuracy of which will be problematic. Based on the situation, in the application, according to the strapdown inertial navigation solution result in the vehicle-mounted positioning system, the type of the environment state of the vehicle in the electronic map of the vehicle-mounted positioning system is determined, corresponding filtering data and filtering parameters are determined, and the strapdown inertial navigation solution result is corrected by adopting the adaptive Kalman filtering model to obtain the positioning result of the vehicle.

That is to say, when the GPS signal state acquired by the vehicle-mounted positioning system is determined to be invalid, the device calls an electronic map of the vehicle-mounted positioning system, determines the pose information of the vehicle in the electronic map by using the pose information in the strapdown inertial navigation solution result, further determines the environment state type of the vehicle in the electronic map, determines the filtering data and the filtering parameters for performing the 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 solution.

Optionally, when the vehicle positioning result is determined according to the correction result of the strapdown inertial navigation solution, if it is determined that the GPS signal is valid at this time, an error between the correction result of the strapdown inertial navigation solution and the GPS positioning result needs to be compared, when an absolute value of the positioning error between the two is smaller than a preset first positioning error threshold and an absolute value of the positioning error between the two is smaller than a preset first positioning error threshold, the correction result based on the strapdown inertial navigation solution may be used as the positioning result, otherwise, the GPS positioning result is used as the positioning result, and such a processing manner can reduce the influence on the positioning result due to the positioning error caused by unconvergence of the adaptive kalman filter.

The first positioning error threshold value can be determined according to the Euclidean distance difference between IMU and GPS position points when the vehicle-mounted positioning system is started or after the strapdown inertial navigation resolving and resetting is completed; and 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 resolving and resetting is completed.

According to the vehicle positioning method provided by the embodiment, whether the GPS signal state acquired by the vehicle-mounted positioning system is effective is judged; if the GPS signal state is determined to be invalid, determining the type of the environmental state of the vehicle in an electronic map of the vehicle-mounted positioning system according to a strapdown inertial navigation resolving result in the vehicle-mounted positioning system; determining corresponding filtering data and filtering parameters according to the environment state type; correcting a strapdown inertial navigation resolving 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 solution. The method has the advantages that under the condition that GPS signals are invalid, the environment state type of the vehicle in the electronic map is utilized to determine the filtering data and the filtering parameters which are most matched with the environment state type, and then the strapdown inertial navigation resolving result is corrected by adopting the self-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 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-mounted positioning system is valid, similar to the prior art, the device corrects the strapdown inertial navigation solution processing result acquired by the vehicle-mounted positioning system by using the adaptive filtering algorithm according to the valid GPS signal acquired by the vehicle-mounted positioning system and the adaptive kalman filtering parameter obtained by initializing the vehicle-mounted 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, different positioning modes are provided for the condition that different GPS signals are invalid. The environmental state types are mainly divided into two types, namely signal blind areas (such as tunnels, culverts and the like) when the vehicle is in a long-term signal unlocking state and signal blind area states (such as urban canyon areas, roads with tall and dense trees and the like) when the vehicle is in a short-term signal unlocking state. In the face of different environmental state types, the application also provides another vehicle positioning method to ensure that under different types of environments, a processing mode more consistent with the environmental state types is adopted to realize the positioning of the vehicle.

Fig. 3 is a schematic flowchart of another vehicle positioning method provided in the present application, and as shown in fig. 3, the vehicle positioning method includes:

step 201, initializing the vehicle-mounted positioning system.

Step 202, performing strapdown inertial navigation calculation on the vehicle-mounted positioning system to obtain a strapdown inertial navigation calculation result.

And step 203, judging whether the GPS signal state acquired by the vehicle-mounted positioning system is effective.

If yes, go to step 204; if not, go to step 205.

And 204, correcting a strapdown inertial navigation resolving result obtained by the vehicle-mounted positioning system according to the effective GPS signal obtained by the vehicle-mounted positioning system and the obtained adaptive Kalman filtering parameter obtained by initializing the vehicle-mounted positioning system.

The method includes the steps of correcting a strapdown inertial navigation calculation result, inputting the corrected strapdown inertial navigation calculation result into an electronic map, and determining a vehicle positioning result of a vehicle in the electronic map according to the strapdown inertial navigation calculation result.

And step 205, determining the environmental state type 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 determining corresponding filtering data and filtering parameters according to the environmental state type.

Optionally, in step 205, determining the type of the environmental state of the vehicle in the electronic map of the vehicle-mounted positioning system according to the calculation result of the strapdown inertial navigation in the vehicle-mounted positioning system, specifically including:

and 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 resolving 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 the signal blind area state that the vehicle is in the long-term signal unlocking.

And step 205c, if the environmental characteristic is determined to be the open environmental characteristic, determining that the environmental state type is a signal blind area state that the vehicle is in short-term signal lock loss.

Specifically, the pose information of the vehicle is included in the strapdown inertial navigation solution, and the pose information which is closest to the pose information and is on the electronic map road can be determined in the electronic map according to the pose information of the vehicle, and the closest pose information and is on the electronic map road is taken as the pose 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 characteristics of the vehicle in the electronic map include environmental characteristics such as tunnels, culverts and underground passages which obviously cannot receive GPS signals, the environmental characteristics are determined to be closed environmental characteristics, and the environmental state type is a signal blind area state of long-term signal unlocking. And if the environmental characteristics of the vehicle in the electronic map comprise surface roads, namely no closed environmental characteristics, determining that the environmental characteristics are open environmental characteristics, and determining that the environmental state type is a signal blind area state of short-term signal unlocking.

If the environmental state type is determined to be the signal blind area state that the vehicle is in the long-term signal lock-losing, executing step 206;

if the current environment state type of the vehicle is determined to be the signal blind area state that the vehicle is in the short-term signal lock-out, step 207 is executed.

And step 206, calculating a first difference value between the pose information in the electronic map and the pose information in the strapdown inertial navigation calculation result, determining the first difference value as filtering data, and determining filtering parameters corresponding to a preset tunnel and a preset culvert as filtering parameters.

In the embodiment, when the environment state type is a signal blind area state that the vehicle is in a long-term signal lock losing state, the pose information of the vehicle in the electronic map can be calculated. Therefore, the filtering data is calculated by using the pose information in the electronic map and the pose information in the strapdown inertial navigation resolving result. Specifically, a difference value between the pose information in the electronic map and the pose information in the strapdown inertial navigation solution 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, the pose information of the vehicle in the electronic map is determined according to the strapdown inertial navigation resolving result.

Specifically, determining pose information which is closest to the pose information in the strapdown inertial navigation resolving result in the electronic map according to the pose information in the strapdown inertial navigation resolving result, wherein the closest pose information is located on a road of the electronic map; and determining the closest pose information as the pose information of the vehicle in the electronic map.

More specifically, the pose information in the strapdown inertial navigation solution is mapped to an electronic map to obtain a vehicle mapping pose, the vehicle mapping pose is matched with the electronic map by adopting a preset matching algorithm, and most possible vehicle pose information is matched, wherein the most possible vehicle pose information is the pose information of the 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 in different environmental state types are preset. Then, the preset filtering parameters are obtained when the vehicle is in the signal blind area state of the long-term signal loss lock, namely the preset filtering parameters corresponding to the tunnel and the culvert are obtained, and the filtering parameters are determined as the filtering parameters of the adaptive Kalman filtering when the vehicle is in the signal blind area state of the long-term signal loss lock.

It should be noted that step 208 is executed after step 206 is executed.

Step 207, calculating a second difference value between the odometer speed data of the vehicle-mounted positioning system and the speed data in the strapdown inertial navigation resolving result, and determining the second difference value as filtering data; and determining the preset filtering parameters of the signal shielding area as the filtering parameters.

In this embodiment, when the environmental state type is a signal blind area state where the vehicle is in a short-term signal lock-out, the odometer speed data can be acquired. Therefore, the filtering data is calculated by using the speed data of the odometer and the speed data in the calculation result of the strapdown inertial navigation. Specifically, a difference between the odometer velocity data and the velocity data in the strapdown inertial navigation solution result is calculated, the difference is a second difference, and the second difference is determined as filtered data.

In this embodiment, a filtering parameter preset when the vehicle is in a signal blind area state of short-term signal loss of lock, that is, a filtering parameter corresponding to a preset signal shielding area is obtained, and the filtering parameter is determined as the filtering parameter of the adaptive kalman filtering when the vehicle is in the signal blind area state of short-term signal loss of lock.

And 208, correcting the strapdown inertial navigation resolving result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model.

Optionally, in this embodiment, step 208 includes the following steps:

step 2081, inputting the filtering data and the filtering parameters into the adaptive Kalman filtering model.

And 2082, calculating a correction error corresponding to the strapdown inertial navigation resolving result by adopting an adaptive Kalman filtering model.

And 2083, correcting the strapdown inertial navigation calculation result according to the correction error.

The adaptive Kalman filtering model is a system model derived from strapdown inertial navigation in Kalman filtering, and can be represented by formula I and formula II:

δx_k＝Φ_k/k-1δx_k-1+W_k-1formula I

Z_k＝H_kδx_k+V_kFormula II

Wherein, δ x_kAnd the error correction value is a system state variable and is also a correction error corresponding to a strapdown inertial navigation resolving result in the k-th iterative computation. Phi_k/k-1For the system state transition matrix, W_k-1Is a systematic noise vector, H_kFor the system measurement matrix, V_kTo measure the noise vector. Z_kRepresented as filtered data.

Wherein, the system state variable can be represented as formula III:

wherein, the 15 variables in formula III are correction errors of the east, north and sky misalignment angles, correction errors of the east, north and sky speeds, and correction errors of the latitude, longitude and altitude, respectively. Gyro zero offset drift in x, y, z directions and accelerometer zero offset values. And gyro zero offset drift in the x, y and z directions and accelerometer zero offset values are parameters for strapdown inertial navigation calculation.

Corresponding to the system state variables, the system noise vector is:

wherein phi_k/k-1After the system state variable is determined, the matrix can be deduced along with a strapdown inertial navigation resolving algorithm, and details are not repeated herein; h_kAfter the observed quantity is determined, it can be expressed as shown in formula V:

H＝[0_7×2 I_7×7 0_7×6]formula V

Correspondingly, a noise vector V is measured_kCan 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.

Specifically, in this embodiment, the filtering data and the filtering parameters are input into the adaptive kalman filtering model, the adaptive kalman filtering model is solved in an iterative manner, and a calculation process shown in formula VII is performed in one iterative process:

in formula VII, the five formulas are respectively represented as a dynamic system prediction matrix, a state covariance prediction matrix, a filter gain matrix, a state update matrix, and a state covariance update matrix.

In formula VII, δ x_k-1For corrected error after the kth iteration, P_k-1、Q_k-1And R_kAre all filter parameters, Z_kIs the filtered data.

It should be noted that an adaptive prediction factor α and an adaptive noise adjustment factor β can be added to formula VII. Where the positions of α and β are not limiting, α can be added to the second formula of formula VII and β can be added to the third formula of formula VII.

In the first iteration, δ x₀Is 0, P₀、Q₀And R₁The value of (a) is the value of the filter parameter corresponding to the type of the environment state. Z₁Is the calculated filtered data under the environment state type. After the first iteration is calculated, P in the second iteration is obtained₁、δx₁. According to δ x₁Correcting the calculation result of the strapdown inertial navigation 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 result₂。Q₀And R₁The value of the filter parameter is unchanged. And P is₁、δx₁、Q₀And R₁And carrying out a third iterative calculation in VII, and so on until a convergence condition is reached. The convergence condition may be that the correction error at the k-th time is approximately equal to the correction error at the (k + 1) -th time, or the iteration number reaches a preset iteration number.

It should be noted that, in the filtering parameters corresponding to the different environmental states, when the validity of the GPS signal and the road scene are switched, the filtering parameters are all reset.

And step 209, determining a vehicle positioning result according to the correction 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 a signal blind area state in which the vehicle is in short-term signal lock-out, after step 209, the method further includes:

re-acquiring the GPS signal and determining a GPS positioning result according to the re-acquired GPS signal when the signal state of the re-acquired GPS signal is determined to be effective; and determining whether to execute the initialization processing to the vehicle-mounted positioning system again according to the positioning error between the GPS positioning result and the determined vehicle positioning result and the direction error.

Specifically, when the GPS signal is invalid and the vehicle is in a tunnel culvert scene, when the GPS is valid again, the strapdown inertial navigation settlement result and the GPS positioning result still need to be compared, and when the absolute value of the positioning errors of the strapdown inertial navigation settlement result and the GPS positioning result is smaller than a second positioning error threshold value and the positioning errors of the strapdown inertial navigation settlement result and the GPS positioning result are smaller than the second positioning error threshold value, the corrected strapdown inertial navigation settlement result is accurate; otherwise, the device needs to reset the vehicle-mounted positioning system and corresponding adaptive Kalman filtering parameters, and then continues to execute the initialization processing of 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 the heading angle difference between the IMU and the GPS as the vehicle exits the tunnel.

According to the vehicle positioning method, initialization processing is carried out on a vehicle positioning system; carrying out strapdown inertial navigation resolving on the vehicle-mounted positioning system to obtain a strapdown inertial navigation resolving result; judging whether the GPS signal state acquired by the vehicle-mounted positioning system is effective or not, if not, determining the environment state type of the vehicle in an electronic map of the vehicle-mounted positioning system according to the strapdown inertial navigation resolving result in the vehicle-mounted positioning system, and determining corresponding filtering data and filtering parameters according to the environment state type; correcting a strapdown inertial navigation resolving 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 solution. The accurate positioning of the whole vehicle section in special environments such as satellite signal blind areas including urban building dense areas, tunnel culverts, roads with tall trees and the like is realized.

In a second aspect, fig. 4 is a schematic structural diagram of a vehicle positioning device provided in the present application, and as shown in fig. 4, the vehicle positioning device includes:

and the judging module 10 is used for judging whether the state of the GPS signal acquired by the vehicle-mounted positioning system is valid.

The first determining module 20 is configured to determine the type of the environmental state of the vehicle in the electronic map of the vehicle-mounted positioning system according to a strapdown inertial navigation solution result in the vehicle-mounted positioning system if it is determined that the GPS signal state is invalid;

and a second determining module 30, configured to determine corresponding filtering data and filtering parameters according to the environment state type.

And the correction module 40 is used for correcting the strapdown inertial navigation resolving result according to the filtering data, the filtering parameters and the adaptive Kalman filtering model.

And the third determination module 50 is configured to determine a vehicle positioning result according to a correction result calculated by the strapdown inertial navigation.

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 characteristic of the vehicle in an electronic map of the vehicle-mounted positioning system; if the environmental characteristic is determined to be the closed environmental characteristic, determining that the environmental state type is the signal blind area state of the long-term signal loss lock; and if the environmental characteristic is determined to be the open environmental characteristic, determining that the environmental state type is the signal blind area state of short-term signal loss of lock.

Optionally, if it is determined that the environmental state type is a signal blind area state where the vehicle is in a long-term signal loss of lock, 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, when determining pose information of the vehicle in the electronic map according to the strapdown inertial navigation solution result, the first determining module 20 is specifically configured to: determining pose information which is closest to the pose information in the strapdown inertial navigation resolving result in the electronic map according to the pose information in the strapdown inertial navigation resolving result, wherein the closest pose information is positioned on a road of the electronic map; and determining the closest pose information as the pose information of the vehicle in the electronic map.

Optionally, the second determining module 30 is specifically configured to, if it is determined that the environmental state type is a signal blind area state where the vehicle is in a long-term signal loss of lock, calculate a first difference between pose information in the electronic map and pose information in the strapdown inertial navigation solution, determine the first difference as filtering data, and determine filtering parameters corresponding to a preset tunnel and a culvert as filtering parameters; if the current environment state type of the vehicle is determined to be the signal blind area state that the vehicle is in short-term signal unlocking, calculating a second difference value between the odometer speed data of the vehicle-mounted positioning system and the speed data in the strapdown inertial navigation resolving result, and determining the second difference value as filtering data; and determining the preset filtering parameters of the signal shielding area as the filtering parameters.

Optionally, the modification 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 a strapdown inertial navigation resolving result by adopting an adaptive Kalman filtering model; and correcting the strapdown inertial navigation calculation result according to the correction error.

Optionally, the vehicle positioning device further comprises: the fourth determining module is used for reacquiring the GPS signal and determining a GPS positioning result according to the reacquired GPS signal when the current environment state type of the vehicle is a signal blind area state that the vehicle is in short-term signal lock loss; and determining whether to perform 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 comprises: the device comprises an acquisition module and a calculation module.

And the acquisition module is used for acquiring the GPS positioning information corresponding to the effective GPS signal, the strapdown inertial navigation resolving result and the filtering parameter 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 resolving result. And the correction module is also used for correcting the strapdown inertial navigation resolving result according to the third difference value, the filtering parameter obtained by initializing the vehicle-mounted positioning system and the adaptive Kalman filtering model.

Alternatively, the GPS signals acquired by the onboard positioning system are transmitted by a plurality of satellites.

Correspondingly, the determining module 10 is specifically configured to determine that the GPS signal state is valid if the number of GPS signals is greater than or equal to the number threshold and the number of valid GPS signals is greater than the signal threshold in the received GPS signals; if the number of the GPS signals in the received GPS signals is less than the number threshold or the number of the effective GPS signals is less 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 of the vehicle positioning device are similar to those of the method embodiment shown in fig. 2 and 3, and are not described in detail herein.

Next, fig. 5 is a schematic structural diagram of a vehicle-mounted positioning assembly provided in this embodiment, where the vehicle-mounted positioning assembly provided in this embodiment includes: a vehicle-mounted 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 position the vehicle by adopting the method of any one of the preceding claims. This embodiment will not be described in detail.

On the next hand, this embodiment further provides an electronic device, which can be used to implement the technical solution of the foregoing method embodiment, and the implementation principle and technical effect of the electronic device are similar, which is not described herein again.

Referring to fig. 6, a schematic structural diagram of an electronic device 900 suitable for implementing the embodiment of the present application is shown, where the electronic device 900 may be a terminal device or a server. Among them, 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 (PDA), a tablet computer (PAD), a Portable Multimedia Player (PMP), a car terminal (e.g., car navigation terminal), etc., and a fixed terminal such as a Digital TV, a desktop computer, etc. The electronic device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.

As shown in fig. 6, the electronic device 900 may include a positioning apparatus (e.g., a central processing unit, a graphics processor, etc.) 901, which may perform various suitable actions and processes according to a program stored in a Read Only Memory (ROM) 902 or a program loaded from a storage apparatus 908 into a Random Access Memory (RAM) 903. In the RAM 903, various programs and data necessary for the operation of the electronic apparatus 900 are also stored. The pointing device 901, ROM902, and RAM 903 are connected to each other by a bus 904. An input/output (I/O) interface 905 is also connected to bus 904.

Generally, the following devices may be connected to the I/O interface 905: input devices 906 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 907 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 908 including, for example, magnetic tape, hard disk, etc.; and a communication device 909. The communication device 909 may allow the electronic apparatus 900 to perform wireless or wired communication with other apparatuses to exchange data. While fig. 6 illustrates an electronic device 900 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.

In particular, according to embodiments of the application, the processes described above with reference to the flow diagrams 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 illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication device 909, or installed from the storage device 908, or installed from the ROM 902. The computer program, when executed by the positioning apparatus 901, performs the above-described functions defined in the methods of the embodiments of the present application.

It should be noted that the computer readable medium mentioned above in the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination 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 present application, 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 this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. 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, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.

The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled 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 embodiments.

Computer program code for carrying out operations for aspects 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 + + or the like 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 type of Network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

The flowchart 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 described in the embodiments of the present application may be implemented by software or hardware. Where the name of a unit does not in some cases constitute a limitation of the unit itself, for example, the first retrieving unit may also be described as a "unit for retrieving at least two internet protocol addresses".

The functions described herein above 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: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.

In the context of this 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. A 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.