Satellite positioning based scene recognition method and apparatus and receiver

Abstract

The application discloses a satellite positioning-based scene recognition method and device and a receiver. Embodiments of the application realize the differentiation of more typical outdoor scenes through at least one group of feature vectors, do not need to increase hardware facilities such as cameras, do not occupy additional hardware resources of the receiver, have small calculation amount, low power consumption, and small occupied resources, are suitable for application in the field of satellite positioning or various positioning terminals, and are completely suitable for various portable terminals with tight computing resources. Further, the application embodiments also use the discrimination result of the current scene to optimize a positioning capture strategy, realize positive feedback of the positioning strategy, improve positioning accuracy, and make the positioning result route more smooth.

Description

TECHNICAL FIELD

[0001] The present application relates to, but is not limited to, satellite navigation technology, and in particular to a satellite positioning-based scene recognition method and device and receiver. BACKGROUND

[0002] Due to the advantages of global coverage, all-weather, high precision, etc. of the global satellite navigation positioning system (GNSS), its application range has become increasingly wide, among which there are some complex and harsh scenes. Under different scenes, the GNSS positioning result will have differences and errors, therefore, if the environment (i.e. scene) where the receiver is located can be accurately and quickly recognized, and then the corresponding positioning strategy is executed, the accuracy and reliability of the positioning result can be improved.

[0003] In the related art, the scene recognition method can be mainly divided into wireless signal discrimination method and image recognition method. Among them, the image recognition method mainly judges through color, texture, edge and other information features in the video or photo. On the one hand, the image recognition method needs to consume a lot of manpower to classify and label samples, and the amount of information to be calculated in a frame of image is very large; on the other hand, the camera needs to be turned on in real time to obtain the surrounding information, thus, the hardware facilities such as camera are added, and a large amount of computing resources and electric energy are consumed. The wireless signal discrimination method mainly uses wireless signals such as Wi-Fi signal, Bluetooth signal and GNSS signal. The wireless signal discrimination method has low power consumption and small amount of calculation, but is limited by wireless signal strength and external interference. The wireless signal discrimination method using Wi-Fi signal and Bluetooth signal cannot be used for long-distance acquisition, i.e. is limited to short-distance scenes. The wireless signal discrimination method using GNSS signal is mainly used for judging simple indoor and outdoor scenes, static and dynamic scenes. SUMMARY

[0004] The present application provides a satellite positioning-based scene recognition method and device and receiver, which can distinguish more outdoor scenes and is suitable for the field of satellite positioning or various positioning terminals.

[0005] The present application provides a satellite positioning-based scene recognition method, which comprises:

[0006] Obtaining at least one group of feature vectors for distinguishing different scenes, the first group of feature vectors comprising satellite signal fluctuation coefficients, the second group of feature vectors comprising satellite blockage ratios, and the third group of feature vectors comprising satellite positioning accuracy factors DOP values and satellite positioning result standard deviation STD values;

[0007] According to the obtained feature vectors and the pre-set scene distinguishing strategy, the scene where the receiver is located is recognized.

[0008] The embodiment of the present application further provides a computer readable storage medium, which stores computer executable instructions, and the computer executable instructions are used for executing the satellite positioning based scene recognition method.

[0009] The embodiment of the present application further provides a receiver, which comprises a memory and a processor, wherein the memory stores instructions executable by the processor, and the instructions are used for executing the steps of the method for implementing the satellite positioning based scene recognition.

[0010] The embodiment of the present application further provides a satellite positioning based scene recognition device, which comprises a signal processing module and an interaction module.

[0011] The signal processing module is used for obtaining at least one set of feature vectors for distinguishing different scenes, wherein the first set of feature vectors comprises satellite signal fluctuation coefficients, the second set of feature vectors comprises satellite blockage ratios, and the third set of feature vectors comprises satellite positioning DOP values and STD values of satellite positioning results.

[0012] The interaction module is used for identifying a scene where the receiver is located according to the obtained feature vectors and a pre-set scene distinguishing strategy.

[0013] The satellite positioning based scene recognition method provided by the embodiment of the present application distinguishes more typical outdoor scenes through at least one feature vector, does not need to increase hardware facilities such as a camera, does not occupy additional hardware resources of the receiver, has small calculation amount, low power consumption, and small occupied resources, is suitable for being applied to the satellite positioning field or various positioning terminals, and is completely suitable for being applied to various portable terminals with tight computing resources.

[0014] Further, the satellite positioning based scene recognition method provided by the embodiment of the present application uses the identification result of the current scene to optimize a positioning capture strategy, realizes positive feedback of the positioning strategy, improves positioning accuracy, and makes a positioning result route more smooth.

[0015] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent from the description, or can be learned by practice of the present application. The objects and other advantages of the present application will be realized and achieved by means of the structures particularly pointed out in the description and the appended claims. BRIEF DESCRIPTION OF DRAWINGS

[0016] The accompanying drawings are included to provide a further understanding of the technical scheme of the present application, and constitute a part of the specification, and are used together with the embodiments of the present application to explain the technical scheme of the present application, and do not constitute a limitation on the technical scheme of the present application.

[0017] Figure 1A flowchart of a scene recognition method based on satellite positioning in an embodiment of the present application is shown in FIG. 1.

[0018] Figure 2 A flowchart of an embodiment of the present application for recognizing a scene in which a receiver is located is shown in FIG. 2.

[0019] Figure 3 A positioning optimization effect in the related art is shown in FIG. 3.

[0020] Figure 4 A positioning optimization effect after adding a scene recognition algorithm in an embodiment of the present application is shown in FIG. 4.

[0021] Figure 5 A flowchart of an embodiment of the scene recognition method based on satellite positioning in an embodiment of the present application is shown in FIG. 5.

[0022] Figure 6 A composition structure diagram of the scene recognition device based on satellite positioning in an embodiment of the present application is shown in FIG. 6. DETAILED DESCRIPTION

[0023] In order to make the objectives, technical solutions and advantages of the present application clearer, the embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other as long as there is no conflict.

[0024] In order to facilitate the understanding of the present application, the present application will be described more fully below with reference to the accompanying drawings. The embodiments of the present application are shown in the accompanying drawings. However, the present application can be realized in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application.

[0026] It can be understood that the terms "first", "second" used in the present application are only for the purpose of description and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise specifically limited.

[0027] It can be understood that "connection" in the following embodiments should be understood as "electrical connection", "communication connection" and the like if the circuits, modules, units and the like connected by the connection have transmission of electrical signals or data between each other.

[0028] As used herein, the singular forms "a", "an" and "the" include plural referents unless the context clearly dictates otherwise. It will be further understood that the terms "comprises", "comprising", "includes" and / or "including", or the like, when used in this specification, specify the presence of stated features, integers, steps, operations, elements, components, or combinations thereof, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

[0029] In order to be able to determine the current scene, such as: open, tree shade, shielding and the like, by using GNSS signals and their positioning results, the present inventors believe through research and analysis that: it is necessary to distinguish the feature vectors of various scenes. For example: tree shade scene, shielding scene will cause different degrees of satellite signal strength attenuation, therefore, the variance and mean of satellite signal strength attenuation can be used as one of the feature vectors; In some shielding scenes, there will also be multipath signal interference, such as urban canyons, courtyards and the like, the interference of multipath signals will cause the signal strength to fluctuate greatly in a short time, therefore, the satellite signal fluctuation coefficient can be used as one of the feature vectors; For open, tree shade, shielding three scenes, satellite signal visibility can be divided into signal full visibility, signal half visibility, signal invisibility, satellite signal visibility will affect the number of satellites and the change of satellite positioning precision factor (DOP, Dilution of Precision) value, and then affect the standard deviation (STD, Standard Deviation) value of satellite positioning result, according to the number of visible satellites, the satellite blockage ratio in different environments can be obtained, therefore, the satellite blockage ratio, DOP value and STD value of satellite positioning result can also be used as feature vectors. According to the above analysis, the present embodiment proposes a method for distinguishing three typical outdoor scenes based on a multi-dimensional feature vector such as a six-dimensional feature vector. In one embodiment, the six-dimensional feature vector can include: satellite signal strength attenuation mean, satellite signal strength attenuation variance, satellite signal fluctuation coefficient, satellite blockage ratio, satellite positioning DOP value and STD value of satellite positioning result.

[0030] Figure 1 The flowchart of the scene recognition method based on satellite positioning in the present embodiment is shown in FIG. 1, which includes: Figure 1

[0031] ​Step 100: Obtain at least one of the following sets of feature vectors for distinguishing different scenarios, the first set of feature vectors including satellite signal fluctuation coefficients, the second set of feature vectors including satellite blockage ratios, and the third set of feature vectors including satellite positioning DOP values and STD values of satellite positioning results.

[0032] In an exemplary instance, in the case of obtaining the first set of feature vectors, it can be determined according to the obtained feature vectors whether the receiver is in a tree shadow scenario; in the case of obtaining the second set of feature vectors, it can be determined according to the obtained feature vectors whether the receiver is in a sheltered scenario; in the case of obtaining the third set of feature vectors, it can be determined according to the obtained feature vectors whether the receiver is in an open scenario; in the case of obtaining the first set of feature vectors and the second set of feature vectors, it can be determined according to the obtained feature vectors whether the receiver is in a tree shadow scenario or a sheltered scenario; in the case of obtaining the first set of feature vectors and the third set of feature vectors, it can be determined according to the obtained feature vectors whether the receiver is in a tree shadow scenario or an open scenario; in the case of obtaining the second set of feature vectors and the third set of feature vectors, it can be determined according to the obtained feature vectors whether the receiver is in a sheltered scenario or an open scenario; in the case of obtaining the first set of feature vectors, the second set of feature vectors and the third set of feature vectors, it can be determined according to the obtained feature vectors whether the receiver is in a tree shadow scenario, a sheltered scenario or an open scenario. It should be noted that when the obtained feature vectors include the first set of feature vectors and the second set of feature vectors, the mean and variance of satellite signal strength attenuation only need to be obtained once.

[0033] In an exemplary instance, the satellite signal strength received by the receiver is affected by the current environment, receiver noise and antenna, etc. In order to only record the current environmental influence value, the influence of other factors needs to be excluded. The satellite signal strength attenuation value C0(t) and the environmental measured signal strength C0, the current environmental standard signal strength C std The calculation of the satellite signal strength attenuation value C0(t) is shown in formula (1):

[0034] C0(t) = C std -C0 (1)

[0035] Wherein, C0 can be obtained from the NMEA Log statement output by the receiver, and then the first set of feature vectors, i.e. the mean μ c (t) and the variance σ c (t) of satellite signal strength attenuation can be calculated as shown in formulas (2) and (3):

[0036]

[0037]

[0038] where N is the number of visible satellites in the current environment, i.e. N visiable (t).

[0039] In an exemplary instance, the satellite signal strength fluctuation coefficient λ can be expressed as the fluctuation coefficient of the satellite signal strength in one second in the current environment.

[0040] Then, the second set of feature vectors, i.e. the satellite signal strength fluctuation coefficient λ, can be calculated as shown in equation (6):

[0041]

[0042] where N is the number of visible satellites in the current environment, i.e. N where N where fs represents the frequency of the output data of the receiver, n0 and n l represent the first and last epochs of the 1-second data received at the receiver end, n0 = n l -fs + 1.

[0043] In an exemplary instance, the satellite blockage ratio is the ratio of the number of visible satellites to the total number of satellites in the current environment, and the satellite blockage ratio ξ in the third set of feature vectors can be calculated as shown in equation (7):

[0044]

[0045] In equation (7), N all (t) represents the total number of satellites, N visiable (t) represents the number of visible satellites at the current time, which can be read from the log (Log) output by the receiver. In an embodiment, the number of visible satellites can be recorded by the message statement GPGSV, for example, a GPGSV message is as follows:

[0046] $GPGSV,3,1,11,18,87,050,48,22,56,250,49,21,55,122,49,03,40,284,47*78

[0047] Therefore, according to the National Marine Electronics Association (NMEA) protocol, each field has a different meaning, except for the message header $GPGSV. The third field "11" indicates that the number of currently visible satellites is 11. After the third field, every four fields represent information of one satellite: for example, 18, 87, 050, 48, which respectively represent satellite number 18, elevation angle 87, azimuth angle 50, and C / N0 value 48, i.e., the measured signal strength C0 in the environment. According to this information, the signal strength of each satellite in the current environment can be obtained. For another example, 22, 56, 250, 49, which respectively represent satellite number 22, elevation angle 56, azimuth angle 250, and C / N0 value 49, i.e., the measured signal strength C0 in the environment.

[0048] In an exemplary example, the method for obtaining the satellite positioning DOP value and the STD value of the satellite positioning result is similar to the method for obtaining the number of currently visible satellites, and can be obtained from the NEMA Log output by the receiver. Taking the satellite positioning DOP value as an example, a GPGSA message is as follows:

[0049] $GNGSA,M,3,13,06,08,09,03,14,01,02,04,05,,,1.1,0.6,0.9

[0050] According to the NMEA protocol, the 16th-18th bits in the GPGSA data structure represent the position, horizontal, and elevation accuracy factors. According to the protocol, the values of the corresponding fields in the Log can be obtained, and thus the required satellite positioning DOP value can be obtained.

[0051] In an exemplary example, the step 100 can further include, before obtaining at least one set of feature vectors for distinguishing different scenarios:

[0052] The receiver captures and processes the intermediate frequency digital signal and ephemeris information, and executes parameter configuration instructions issued through the user interface; executes an ephemeris solving algorithm: the ephemeris information is solved to obtain satellite elevation angle and azimuth angle, DOP value, pseudo-range value, etc.; executes a positioning and speed measurement algorithm: the current position and speed are calculated according to the results obtained by solving, and the results are sent to the user interface. In this way, the feature vectors for distinguishing different scenarios can be extracted from the results of the ephemeris solving and positioning and speed measurement algorithms.

[0053] Step 101: According to the obtained feature vectors and the pre-set scenario distinguishing strategy, the scenario in which the receiver is located is identified.

[0054] In one exemplary instance, the scene differentiation strategy may include comparing the obtained feature vector with pre-set feature vector thresholds corresponding to different scenes to identify the scene in which the receiver is currently located. It should be noted that the specific settings of the scene differentiation strategy are not intended to limit the scope of protection of this application and can be flexibly set according to actual application conditions.

[0055] In one embodiment, a satellite positioning DOP threshold and a satellite positioning result STD threshold are preset. The scene differentiation strategy includes: if the obtained satellite positioning DOP value is less than the satellite positioning DOP threshold, and the obtained satellite positioning result STD value is less than the satellite positioning result STD threshold, then the scene where the receiver is located is identified as an open scene. In one embodiment, a satellite signal fluctuation coefficient threshold is preset. The scene differentiation strategy includes: if the obtained satellite signal fluctuation coefficient is greater than the satellite signal fluctuation coefficient threshold, then the scene where the receiver is located is identified as a shaded scene. In one embodiment, a satellite blocking ratio threshold is preset. The scene differentiation strategy includes: if the obtained satellite blocking ratio is less than the satellite blocking ratio threshold, then the scene where the receiver is located is identified as an obstructed scene.

[0056] In one embodiment, such as Figure 2 As shown, a pre-set DOP threshold for satellite positioning, a STD threshold for satellite positioning results, a satellite signal fluctuation coefficient threshold, and a satellite blocking ratio threshold are used. The scene differentiation strategy includes: Step 200: Determine whether the obtained satellite positioning DOP value is less than the satellite positioning DOP threshold and whether the obtained satellite positioning result STD value is less than the satellite positioning result STD threshold. If both the obtained satellite positioning DOP value and the obtained satellite positioning result STD value are less than the satellite positioning result STD threshold, then the scene where the receiver is located is identified as an open scene. Otherwise, proceed to Step 201: Determine whether the obtained satellite signal fluctuation coefficient is greater than the satellite signal fluctuation coefficient threshold. If the obtained satellite signal fluctuation coefficient is greater than the satellite signal fluctuation coefficient threshold, then the scene where the receiver is located is identified as a shaded scene. If the obtained satellite signal fluctuation coefficient is not greater than the satellite signal fluctuation coefficient threshold, proceed to Step 202: Determine whether the obtained satellite blocking ratio is less than the satellite blocking ratio threshold. If the obtained satellite blocking ratio is less than the satellite blocking ratio threshold, then the scene where the receiver is located is identified as an obstructed scene. Otherwise, end.

[0057] In an example, the first set of feature vectors further comprises a mean of satellite signal strength attenuation and a variance of satellite signal strength attenuation. The second set of feature vectors further comprises a mean of satellite signal strength attenuation and a variance of satellite signal strength attenuation. The scene distinguishing strategy can further comprise: presetting a mean of satellite signal strength attenuation threshold and a variance of satellite signal strength attenuation threshold, and in a case that the obtained satellite signal fluctuation coefficient is determined to be not greater than the satellite signal fluctuation coefficient threshold and / or the obtained satellite blockage ratio is determined to be not less than the satellite blockage ratio threshold, entering step 203: determining whether the obtained mean of satellite signal strength attenuation is less than the mean of satellite signal strength attenuation threshold and the obtained variance of satellite signal strength attenuation is less than the variance of satellite signal strength attenuation threshold, and if the obtained mean of satellite signal strength attenuation is less than the mean of satellite signal strength attenuation threshold and the obtained variance of satellite signal strength attenuation is less than the variance of satellite signal strength attenuation threshold, identifying that the scene where the receiver is located is a sheltered scene; and if the obtained mean of satellite signal strength attenuation is not less than the mean of satellite signal strength attenuation threshold or the obtained variance of satellite signal strength attenuation is not less than the variance of satellite signal strength attenuation threshold, identifying that the scene where the receiver is located is a tree shadow scene.

[0058] It should be noted that, Figure 2 The steps 200, 201 and 202 shown in the above embodiment can include one or any combination of them. Figure 2 In the above embodiment, when the step 203 is included, the step 203 can also be combined with one or any combination of the steps 200, 201 and 202 to determine the scene where the receiver is located.

[0059] The scene recognition method based on satellite positioning provided by the above embodiment can distinguish more typical outdoor scenes through at least one set of feature vectors, and does not need to increase hardware facilities such as cameras, does not occupy additional hardware resources of the receiver, has small calculation amount, low power consumption, and occupies few resources, is suitable for application in the field of satellite positioning or various positioning terminals, and is completely suitable for various portable terminals with tight computing resources.

[0060] In an example, the above embodiment can further comprise:

[0061] According to the recognition result of the scene, a positioning optimization strategy corresponding to the current scene is executed.

[0062] In an example, the positioning optimization strategy is set in advance according to different scenarios, and the specific setting of the positioning optimization strategy does not limit the protection scope of the present application, and can be flexibly set according to actual application conditions. For example, in an open scenario, the number of satellite observation values is large and the observation quality is good, and when positioning calculation is performed, the positioning convergence condition can be relaxed to reduce the number of iterations. For example, in a tree shade scenario, the receiver can frequently lose lock on the satellite frequency, and even the real-time kinematic (RTK) positioning and PVT positioning are switched, so that the current positioning result has large jumps and fly points. At this time, the RTK positioning result can be used to smooth the PVT positioning result to reduce the fly points. For example, in a shielding scenario, the number of visible satellites is small, so that the satellite data stored in the receiver cannot be updated for a long time, resulting in positioning deviation in the shielding scenario. At this time, the error information can be cleared in time or the baseband configuration is reset to reacquire the satellite. When in a city shielding scenario, multipath phenomenon occurs. At this time, the anti-multipath interference can be turned on at the acquisition end.

[0063] In an embodiment, taking the identified scenario of tree shade as an example, because the satellite signal strength fluctuates greatly in the tree shade scenario, the satellite frequency can be frequently lost. Therefore, the positioning optimization strategy corresponding to the tree shade scenario can include: smoothing the PVT positioning result with the RTK positioning result to reduce the fly point phenomenon when the RTK is switched to the PVT positioning; for the frequently lost satellite, the participation in positioning calculation can also be reduced; in order to ensure the positioning accuracy and result reliability in the tree shade scenario, the positioning threshold of the RTK can be set more strictly. In an embodiment, taking the identified scenario of the shielding scenario in the city canyon as an example, because there is multipath interference at this time, the positioning optimization strategy corresponding to the shielding scenario in the city canyon can include: the anti-multipath interference function can be turned on at the signal acquisition end. In a long-time shielding environment, multiple satellites are not visible, and the stored satellite information is not updated in time. At this time, the satellite information that is not updated for a long time can be removed or the satellite signal can be reacquired through the positioning optimization strategy.

[0064] Further, the scenario recognition method based on satellite positioning provided in the embodiments of the present application also uses the discrimination result of the current scenario to optimize the positioning acquisition strategy, realizes the positive feedback of the positioning strategy, improves the positioning accuracy, and makes the positioning result route more smooth. Figure 3 In order to improve the positioning optimization effect in the related art, Figure 4The positioning optimization effect after adding the scene recognition algorithm in the embodiments of the present application is very obvious. After adding the scene recognition based on satellite positioning in the present application, the corresponding positioning strategy is executed according to the current scene of the user, so that the positioning trajectory is smoother, and the positioning precision and accuracy are obviously improved.

[0065] The present application also provides a computer readable storage medium storing computer executable instructions for executing the scene recognition method based on satellite positioning.

[0066] The present application further provides a receiver comprising a memory and a processor, wherein the memory stores instructions executable by the processor for performing the steps of the method for implementing the scene recognition based on satellite positioning.

[0067] Figure 5 The flowchart of the embodiment of the scene recognition method based on satellite positioning in the embodiments of the present application is shown in Figure 5 as follows, comprising:

[0068] Step 500: obtaining original satellite observation.

[0069] In this step, the intermediate frequency signal can be obtained by an intermediate frequency signal collector, and the corresponding satellite is captured and tracked according to the configuration parameters input by the user through the user interface to obtain signal strength, Doppler frequency and other information to obtain the original satellite observation. At the same time, input ephemeris and other auxiliary information.

[0070] Steps 5011-5012: pre-processing the original satellite signal observation, vector pre-processing.

[0071] The ephemeris information is solved to obtain the observation required for positioning and speed determination, such as satellite elevation and azimuth, DOP value, pseudo-range value, etc. The part of the vector used for scene recognition is extracted, and the vector pre-processing is performed to judge the availability of the vector and eliminate the error value, so as to better ensure the accuracy of the subsequent scene information.

[0072] Steps 5021-5022: positioning and speed determination, reading NMEA message statement.

[0073] The observation required for positioning and speed determination is calculated to calculate the current position and speed, and the result is sent to the user interface.

[0074] Step 503: obtaining the feature vector for scene recognition.

[0075] In this step, the feature vectors for distinguishing different scenarios are extracted from the results of the ephemeris solving and positioning velocity calculation algorithm and the NMEA message statements. The specific implementation can be referred to in step 100, which will not be repeated here. In this embodiment, the feature vectors can include: satellite signal strength attenuation mean and satellite signal strength attenuation variance, satellite signal fluctuation coefficient, satellite blockage ratio, satellite positioning DOP value and STD value of the satellite positioning result.

[0076] Step 504: Obtain the scenario recognition result.

[0077] This step can be implemented according to the scenario recognition strategy set in advance according to the obtained feature vectors and the scenario in which the receiver is located, which will not be repeated here.

[0078] Step 505: Use the discrimination result of the current scenario to optimize the positioning capture strategy.

[0079] This step executes the positioning optimization strategy corresponding to the current scenario according to the recognition result of the scenario. The positioning optimization strategy is set in advance according to different scenarios.

[0080] Figure 6 The schematic diagram of the composition structure of the scenario recognition device based on satellite positioning in the embodiment of the present application is shown in FIG. 1, which can include a signal processing module and an interaction module. The signal processing module is used to obtain at least one group of feature vectors for distinguishing different scenarios, the first group of feature vectors including a satellite signal fluctuation coefficient, the second group of feature vectors including a satellite blockage ratio, and the third group of feature vectors including a satellite positioning DOP value and an STD value of a satellite positioning result. Figure 6

[0081] The interaction module is used to recognize the scenario in which the receiver is located according to the obtained feature vectors and the scenario distinguishing strategy set in advance.

[0082] In an exemplary example, it can further include a control module for capturing and processing intermediate frequency digital signals and ephemeris information, and executing parameter configuration instructions issued through a user interface to obtain information for obtaining feature vectors for distinguishing different scenarios.

[0083] In an exemplary example, the first group of feature vectors further includes a satellite signal strength attenuation mean and a satellite signal strength attenuation variance. The second group of feature vectors further includes a satellite signal strength attenuation mean and a satellite signal strength attenuation variance.

[0084] ​In an example, in the control module, the following can be included: acquiring intermediate frequency signal data by using an intermediate frequency signal collector, inputting auxiliary information such as ephemeris, executing parameter configuration information input by a user through a user interface, capturing and tracking a corresponding satellite, and obtaining signal strength, Doppler frequency information and other information used to obtain a feature vector used to distinguish different scenarios.

[0085] In an example, in the signal processing module, the following can be included: performing data preprocessing on the obtained information, and solving ephemeris information to obtain observation quantities, DOP values and pseudo-range values required for positioning and speed determination.

[0086] In an example, in the interaction module, the following can be further included: further processing the observation quantities and the positioning and speed determination results in scenario recognition, such as extracting required feature vectors and identifying a current scenario. Figure 3 As shown, outputting the positioning and speed determination results to a user, and executing a corresponding positioning strategy according to a current scenario result.

[0087] The scenario recognition device based on satellite positioning provided by the embodiments of the present application realizes the distinction of more typical outdoor scenarios by using at least one feature vector, does not need to increase hardware facilities such as a camera, does not occupy additional hardware resources of a receiver, has small calculation amount, low power consumption, and occupies few resources, is suitable for application in the field of satellite positioning or various positioning terminals, and is completely suitable for various portable terminals with tight computing resources.

[0088] In an example, the signal processing module is further configured to: execute a positioning optimization strategy corresponding to a current scenario according to a recognition result of the scenario. The scenario recognition device based on satellite positioning provided by the embodiments of the present application further uses a discrimination result of the current scenario to optimize a positioning capture strategy, realizes positive feedback of the positioning strategy, improves positioning accuracy, and makes a positioning result route more smooth.

[0089] Although the embodiments disclosed in the present application are as above, the content described above is only an embodiment adopted for the purpose of facilitating the understanding of the present application, and is not intended to limit the present application. Any person skilled in the art of the present application can make any modification and change in the form and details without departing from the spirit and scope of the present application, but the patent protection scope of the present application shall be subject to the scope defined by the appended claims.

Claims

1. A scene recognition method based on satellite positioning, characterized in that, include: Obtain at least one of the following sets of feature vectors to distinguish different scenarios: the first set of feature vectors includes the satellite signal fluctuation coefficient, the second set of feature vectors includes the satellite blocking ratio, and the third set of feature vectors includes the satellite positioning accuracy factor (DOP) and the standard deviation (STD) of the satellite positioning results. The receiver's scene is identified based on the obtained feature vectors and a pre-set scene differentiation strategy; The scene differentiation strategy includes: when the feature vector includes the first set of feature vectors, if the satellite signal fluctuation coefficient is greater than the satellite signal fluctuation coefficient threshold, the scene where the receiver is located is identified as a tree-shaded scene; wherein, the satellite signal fluctuation coefficient is the fluctuation coefficient of the satellite signal strength in the current environment within one second.

2. The scene recognition method according to claim 1, further comprising, before obtaining at least one set of feature vectors for distinguishing different scenes: The system captures and processes intermediate frequency digital signals and ephemeris information, and executes parameter configuration commands issued through the user interface to obtain information for acquiring the feature vector.

3. The scene recognition method according to claim 2, wherein, The information obtained for acquiring the feature vector includes: The ephemeris information is processed to obtain the satellite elevation angle, azimuth angle, DOP value, and pseudorange value; the current position and velocity are calculated using the results obtained from the positioning and velocity measurement algorithm.

4. The scene recognition method according to claim 1, wherein, The feature vector includes the first set of feature vectors; The satellite signal strength fluctuation coefficient The following formula is used to calculate: ， ， Where N is the number of visible satellites in the current environment; This indicates the satellite signal strength attenuation value; Where fs represents the frequency of the data output by the receiver. and This indicates the first and last epochs of the data received by the receiver in one second. t represents the current time.

5. The scene recognition method according to claim 1, wherein, The feature vector includes the second set of feature vectors; The satellite blocking ratio The following formula is used to calculate: ， in, Indicates the total number of satellites. This represents the number of visible satellites at the current moment, where t represents the current moment.

6. The scene recognition method according to any one of claims 1 to 5, wherein, The scenario differentiation strategy also includes: When the feature vector includes the second set of feature vectors, if the satellite blocking ratio is less than the satellite blocking ratio threshold, the scene in which the receiver is located is identified as an obstructed scene. When the feature vector includes the third set of feature vectors, if the satellite positioning accuracy factor DOP value is less than the satellite positioning accuracy factor DOP threshold, and the STD value of the satellite positioning result is less than the STD threshold, the scene where the receiver is located is identified as an open scene. When the feature vector includes the first set of feature vectors and the third set of feature vectors, if the satellite positioning accuracy factor DOP value is not less than the satellite positioning accuracy factor DOP threshold or the STD value of the satellite positioning result is not less than the STD threshold, and the satellite signal fluctuation coefficient is greater than the satellite signal fluctuation coefficient threshold, the scene where the receiver is located is identified as a tree-shaded scene. When the feature vector includes a first set of feature vectors and a second set of feature vectors, if the satellite positioning accuracy factor DOP value is not less than the satellite positioning accuracy factor DOP threshold or the STD value of the satellite positioning result is not less than the STD threshold, and the satellite blocking ratio is less than the satellite blocking ratio threshold, the scene where the receiver is located is identified as an obstructed scene. When the feature vector includes a first set of feature vectors, a second set of feature vectors, and a third set of feature vectors, if the satellite positioning accuracy factor DOP value is not less than the satellite positioning accuracy factor DOP threshold or the STD value of the satellite positioning result is not less than the STD threshold, the satellite signal fluctuation coefficient is not greater than the satellite signal fluctuation coefficient threshold, and the satellite blocking ratio is less than the satellite blocking ratio threshold, the scene where the receiver is located is identified as an obstructed scene.

7. The scene recognition method according to any one of claims 1 to 5, wherein the feature vector includes at least one of the first set of feature vectors and the second set of feature vectors; At least one of the first set of feature vectors and the second set of feature vectors further includes: Mean and variance of satellite signal strength attenuation.

8. The scene recognition method according to claim 7, wherein, The average attenuation of satellite signal strength and satellite signal strength attenuation variance The following formula is used to calculate: ， ， Where N is the number of visible satellites in the current environment. This represents the satellite signal strength attenuation value, and t represents the current time.

9. The scene recognition method according to claim 7, characterized in that, The scenario differentiation strategy includes: When the feature vector includes at least one of the first set of feature vectors and the second set of feature vectors, and when the satellite signal fluctuation coefficient is not greater than the satellite signal fluctuation coefficient threshold and the satellite blocking ratio is not less than the satellite blocking ratio threshold, if the average satellite signal strength attenuation is less than the average satellite signal strength attenuation threshold and the variance of satellite signal strength attenuation is less than the variance of satellite signal strength attenuation threshold, the scene where the receiver is located is identified as an obstructed scene; if the average satellite signal strength attenuation is not less than the average satellite signal strength attenuation threshold or the variance of satellite signal strength attenuation is not less than the variance of satellite signal strength attenuation threshold, the scene where the receiver is located is identified as a shaded scene. When the feature vector includes a first set of feature vectors, a second set of feature vectors, and a third set of feature vectors, if the satellite positioning accuracy factor (DOP) value is not less than the satellite positioning accuracy factor (DOP) threshold or the satellite positioning result STD value is not less than the STD threshold, the satellite signal fluctuation coefficient is not greater than the satellite signal fluctuation coefficient threshold, and the satellite blocking ratio is not less than the satellite blocking ratio threshold, and if the average satellite signal strength attenuation is less than the average satellite signal strength attenuation threshold and the satellite signal strength attenuation variance is less than the satellite signal strength attenuation variance threshold, the scene where the receiver is located is identified as an obstructed scene. If the average satellite signal strength attenuation is not less than the average satellite signal strength attenuation threshold or the satellite signal strength attenuation variance is not less than the satellite signal strength attenuation variance threshold, the scene where the receiver is located is identified as a shaded scene.

10. The scene recognition method according to claim 1 or 2, further comprising: Based on the scene recognition results, execute the localization optimization strategy corresponding to the current scene.

11. The scene recognition method according to claim 10, wherein, The positioning optimization strategy includes: When the receiver is identified as being in an open scene, the positioning convergence conditions in the positioning calculation process are relaxed. When the receiver is identified as being in a shaded scene, at least one of the following operations is performed: smoothing the PVT positioning result using the real-time dynamic differential RTK positioning result and raising the RTK positioning threshold. When the receiver is identified as being in an obstructed environment, perform at least one of the following operations: clear error messages, remove satellite information that has not been updated for a long time, reacquire satellites, or enable anti-multipath interference.

12. A computer-readable storage medium storing computer-executable instructions for performing the scene recognition method based on satellite positioning as described in any one of claims 1 to 11.

13. A receiver comprising a memory and a processor, wherein, The memory stores the following instructions that can be executed by a processor: for executing the satellite positioning-based scene recognition method according to any one of claims 1 to 11.

14. A scene recognition device based on satellite positioning, applied to the scene recognition method based on satellite positioning as described in any one of claims 1 to 11, characterized in that, include: Signal processing module, interaction module; among which, The signal processing module is used to obtain at least one of the following sets of feature vectors to distinguish different scenarios: the first set of feature vectors includes the satellite signal fluctuation coefficient, the second set of feature vectors includes the satellite blocking ratio, and the third set of feature vectors includes the satellite positioning accuracy factor (DOP) value and the STD value of the satellite positioning result. An interaction module is used to identify the scene where the receiver is located based on the obtained feature vector and a pre-set scene differentiation strategy. The scene differentiation strategy includes: when the feature vector includes a first set of feature vectors, if the satellite signal fluctuation coefficient is greater than the satellite signal fluctuation coefficient threshold, the scene where the receiver is located is identified as a tree-shaded scene. The satellite signal fluctuation coefficient is the fluctuation coefficient of the satellite signal strength in the current environment within one second.

Images