Positioning data processing method and device, electronic equipment and storage medium

Abstract

The invention relates to the field of data processing, in particular to a positioning data processing method and device, electronic equipment and a storage medium. According to the embodiment of the invention, a plurality of positioning points and longitude and latitude parameters in the current acquisition period are firstly obtained, and the data volume is increased. The error influence of a single positioning point caused by instantaneous factors such as satellite signal quality fluctuation and a multipath effect can be reduced. Secondly, the positioning points are constructed into a positioning point sequence in a time sequence, the positioning point sequence is input into a sliding window, and continuous analysis can be carried out on positioning data in a period of time; furthermore, the first target positioning point is updated by acquiring the target positioning point and the target longitude and latitude parameters in the sliding window, and the whole positioning point sequence is updated in sequence, so that a data smoothing effect is realized. According to the updating mode, information of surrounding positioning points which are close in time is utilized, and the positioning points which may drift are corrected.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a method, device, electronic device and storage medium for processing positioning data. Background Art

[0002] GPS is a global navigation satellite system, which is widely used in traffic navigation, geographic information system and military fields. Its positioning accuracy can usually reach meter level or even centimeter level, but high accuracy depends on many factors such as satellite signal quality and receiver performance.

[0003] The accuracy of GPS positioning will be affected by atmospheric delay, multipath effect, building obstruction, satellite clock error and satellite orbit error, for example: Atmospheric delay: When the signal passes through the atmosphere, it will be affected by the ionosphere and troposphere, causing the signal propagation speed to change, thus affecting the positioning accuracy. Multipath effect: During the propagation process, GPS signals may pass through reflectors such as buildings and water surfaces, generating multiple paths of signals to reach the receiver, causing deviations in the positioning results. Building obstruction: When the GPS receiver is blocked by objects such as buildings, the received satellite signal will be weakened or blocked, resulting in a decrease in positioning accuracy. Satellite clock error: There is a certain error in the clock on the satellite, which will affect the accuracy of positioning. Satellite orbit error: There is a deviation between the actual orbit of the satellite and the theoretical orbit, which will also affect the positioning accuracy.

[0004] Based on this, it can be determined that the above-mentioned factors such as atmospheric delay, multipath effect, building obstruction, satellite clock error and satellite orbit error cause some positioning data to be distorted, resulting in trajectory drift. Summary of the invention

[0005] In view of this, the embodiments of the present invention provide a method, device, electronic device and storage medium for processing positioning data to solve the problem that the GPS positioning accuracy may be affected by various factors and cause trajectory drift.

[0006] In a first aspect, an embodiment of the present invention provides a method for processing positioning data, the method comprising:

[0007] Acquire multiple positioning points collected in the current collection cycle and the latitude and longitude parameters corresponding to the positioning points;

[0008] Construct a positioning point sequence from the positioning points in chronological order, and enter the positioning point sequence into a preset sliding window;

[0009] Acquire the target positioning point of the positioning point sequence that falls within the sliding window, and acquire the target longitude and latitude parameters corresponding to the target positioning point;

[0010] The target longitude and latitude parameters are used to update the longitude and latitude parameters of the first target positioning point in the sliding window, and the sliding window is slid to update the longitude and latitude parameters of each positioning point in the positioning point sequence in turn.

[0011] Furthermore, the acquiring of the plurality of positioning points collected in the current collection period and the latitude and longitude parameters corresponding to the positioning points includes:

[0012] The application scenarios for obtaining positioning data and the environmental conditions of the collection equipment;

[0013] Analyze the application scenario and the environmental conditions to determine a collection frequency, and use the collection frequency to determine a current collection period;

[0014] In the current collection cycle, the collection device is called to collect positioning data to obtain multiple positioning points.

[0015] Further, the entering the positioning point sequence into a preset sliding window includes:

[0016] Obtaining changes between positioning points in the current acquisition cycle;

[0017] Determine a window length using the change, and construct the sliding window using the window length;

[0018] The positioning point sequence is recorded into the sliding window.

[0019] Further, the updating of the longitude and latitude parameters of the first target positioning point in the sliding window by using the target longitude and latitude parameters includes:

[0020] Extracting a target longitude parameter and a target latitude parameter from the target longitude and latitude parameters;

[0021] Calculating an average longitude parameter using the target longitude parameters of each of the target positioning points and the number of target positioning points corresponding to the target positioning points;

[0022] Calculating an average latitude parameter using the target latitude parameters of each of the target positioning points and the number of target positioning points corresponding to the target positioning points;

[0023] The longitude and latitude parameters of the first target positioning point in the sliding window are updated using the average longitude parameter and the average latitude parameter.

[0024] Furthermore, after updating the longitude and latitude parameters of the first target positioning point in the sliding window using the target longitude and latitude parameters, the method further includes:

[0025] Analyze the target longitude and latitude parameters of each target positioning point in the sliding window respectively to obtain the change trend of the target longitude and latitude parameters in time series;

[0026] The acquisition frequency is adjusted using the change trend, wherein the acquisition frequency is used to determine the acquisition period.

[0027] Further, adjusting the acquisition frequency by utilizing the change trend includes:

[0028] If the change trend shows that the positioning point will enter an area where the signal strength is lower than the preset strength or the environment is complex, the acquisition frequency is increased; or if the change trend shows that the positioning point is in a stable state, the acquisition frequency is reduced.

[0029] Furthermore, after updating the longitude and latitude parameters of the first target positioning point in the sliding window using the target longitude and latitude parameters, the method further includes:

[0030] Detecting a target state corresponding to the positioning point, and acquiring a display style corresponding to the target state;

[0031] The positioning point is displayed on a map according to the display style.

[0032] In a second aspect, an embodiment of the present invention provides a device for processing positioning data, the device comprising:

[0033] A collection module, used to obtain multiple positioning points collected in the current collection period and the latitude and longitude parameters corresponding to the positioning points;

[0034] A processing module, used to construct a positioning point sequence from the positioning points in chronological order, and enter the positioning point sequence into a preset sliding window;

[0035] A screening module, used to obtain the target positioning point whose positioning point sequence falls within the sliding window, and obtain the target longitude and latitude parameters corresponding to the target positioning point;

[0036] The updating module is used to update the longitude and latitude parameters of the first target positioning point in the sliding window using the target longitude and latitude parameters, and to update the longitude and latitude parameters of each positioning point in the positioning point sequence in turn by sliding the sliding window.

[0037] In a third aspect, an embodiment of the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0038] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method of the first aspect or any corresponding embodiment thereof.

[0039] The embodiment of the present application first obtains multiple positioning points and longitude and latitude parameters within the current acquisition cycle, thereby increasing the amount of data. The error impact of a single positioning point caused by instantaneous factors such as fluctuations in satellite signal quality and multipath effects can be reduced. Secondly, the positioning points are constructed as a positioning point sequence in chronological order and entered into a sliding window, so that the positioning data within a period of time can be continuously analyzed. Furthermore, by obtaining the target positioning point and the target longitude and latitude parameters within the sliding window to update the first target positioning point, and updating the entire positioning point sequence in sequence, a data smoothing effect is achieved. This updating method utilizes the information of the surrounding positioning points that are close in time to correct the positioning points that may drift. For example, when a certain positioning point is affected by factors such as building obstruction or satellite clock error and produces a large deviation, by combining the longitude and latitude parameters with the surrounding positioning points, the impact of this deviation on the trajectory can be reduced, making the trajectory more stable and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 is a flowchart of a method for processing positioning data according to some embodiments of the present invention;

[0042] Figure 2 is a schematic diagram of a sliding window according to some embodiments of the present invention;

[0043] Figure 3 is a flowchart of a method for processing positioning data according to some embodiments of the present invention;

[0044] Figure 4 is a structural block diagram of a device for processing positioning data according to an embodiment of the present invention;

[0045] Figure 5 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0047] According to an embodiment of the present invention, a method, apparatus, electronic device and storage medium for processing positioning data are provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0048] In this embodiment, a method for processing positioning data is provided. Figure 1 is a flow chart of a method for processing positioning data according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0049] Step S101, obtaining multiple positioning points collected in the current collection cycle and the longitude and latitude parameters corresponding to the positioning points.

[0050] In an embodiment of the present application, obtaining multiple positioning points collected in the current collection period and the latitude and longitude parameters corresponding to the positioning points includes the following steps A1-A3:

[0051] Step A1, obtaining the application scenario of the positioning data and the environmental conditions of the acquisition device.

[0052] Specifically, first determine the application scenario: if it is a traffic navigation application, it is necessary to consider factors such as the vehicle's driving speed and road conditions. You can interact with the traffic navigation software to obtain the current vehicle's driving status information, or use sensors to detect parameters such as the vehicle's acceleration and steering to infer the driving status.

[0053] For geographic information system applications, the characteristics of the application scenario need to be determined based on the scale of the map, data update requirements, etc. For example, when making high-precision maps, more frequent positioning data collection is required; while when conducting macro applications such as regional planning, a lower collection frequency may be sufficient.

[0054] At the same time, determine the environmental conditions: Detect the surrounding physical environment, including whether there are obstacles such as tall buildings and mountains that may block the satellite signal. You can use sensors to detect the height and distance of surrounding buildings, or obtain terrain information through map data. Consider the impact of weather conditions on satellite signals, such as cloud thickness, rainfall, etc. You can obtain weather information for the current area by connecting to a meteorological data service. Evaluate the electromagnetic environment to determine whether there are other electronic devices that may interfere with the GPS signal. You can use a spectrum analyzer to detect the strength and frequency distribution of surrounding electromagnetic signals.

[0055] Step A2: Analyze application scenarios and environmental conditions to determine the acquisition frequency, and use the acquisition frequency to determine the current acquisition period.

[0056] Specifically, if the application scenario is traffic navigation with high-speed vehicles and there is no obvious signal obstruction in the environment, in order to track the vehicle position in a timely and accurate manner, a higher acquisition frequency can be set, such as once per second. This is because the vehicle is moving at a high speed and more frequent positioning updates are required to ensure the accuracy of navigation. For pedestrian navigation applications in environments with many high-rise buildings such as urban canyons, since the signal may be unstable, the acquisition frequency can be appropriately reduced, such as once every 2 seconds. This can reduce errors caused by unstable signals while ensuring a certain positioning accuracy. In a geographic information system, if a large-scale terrain survey is being conducted and the environment is relatively open, the acquisition frequency can be lower, such as once every 10 seconds or longer. For urban planning applications that require high precision, the acquisition frequency can be appropriately increased.

[0057] Once the acquisition frequency is determined, the current acquisition period can be calculated from the time. For example, if the acquisition frequency is once per second, the current acquisition period is a 1-second period starting from the current time. You can use the system clock to record time and determine the start and end time of each acquisition period based on the acquisition frequency.

[0058] Step A3: In the current collection cycle, the collection device is called to collect positioning data to obtain multiple positioning points.

[0059] Specifically, for devices with built-in GPS modules, such as smartphones and tablets, the GPS function can be called through the API provided by the operating system. For example, in the Android system, the LocationManager class can be used to obtain positioning information. Developers need to set appropriate permissions in the code and register location update listeners to receive positioning data during the collection cycle. During the collection process, some parameters need to be set according to the characteristics of the device, such as positioning mode (such as high-precision mode, power saving mode, etc.), data output format, etc.

[0060] During the acquisition cycle, the device will continuously receive satellite signals and calculate positioning points. These positioning points can be expressed in the form of longitude and latitude coordinates. The acquisition device will store these positioning points in the internal buffer or send them to the connected device. The connected device (such as a computer, mobile device, etc.) needs to continuously read the positioning data sent by the acquisition device, or obtain positioning points from the internal buffer. You can use a loop or event-driven method to continuously obtain positioning data to ensure that multiple positioning points are obtained during the acquisition cycle. For each positioning point, in addition to the longitude and latitude coordinates, other relevant information can also be obtained, such as positioning time, signal strength, number of satellites, etc. This information can be used for subsequent data processing and analysis.

[0061] Step S102: construct a positioning point sequence from the positioning points in chronological order, and enter the positioning point sequence into a preset sliding window.

[0062] In the embodiment of the present application, first, after acquiring multiple positioning points, these positioning points are arranged in chronological order according to the timestamp information corresponding to each positioning point, so as to construct a positioning point sequence, wherein the position of each positioning point in the sequence reflects the chronological order of its acquisition.

[0063] Next, a sliding window is pre-set. This window has a specific size and can accommodate a certain number of positioning points. The constructed positioning point sequence is recorded one by one into this sliding window. Starting from the earliest positioning point, it is placed in the first position of the window in turn. As new positioning points are continuously added, the positioning points in the window are continuously updated. If the window is full, the new positioning point will replace the earliest positioning point in the window, so that the window always contains the latest number of positioning points. In this way, by recording the positioning point sequence into the sliding window, the positioning data within a period of time can be easily analyzed and processed.

[0064] In an embodiment of the present application, recording the positioning point sequence into a pre-set sliding window includes: obtaining changes between positioning points in the current acquisition cycle; determining the window length using the changes, and constructing a sliding window using the window length; recording the positioning point sequence into the sliding window.

[0065] First, multiple positioning points have been acquired in the current collection cycle. In order to determine the changes between the positioning points, it is necessary to compare the longitude and latitude parameters and timestamps of adjacent positioning points. For two adjacent positioning points, calculate the longitude and latitude differences between them. For example, the longitude and latitude of positioning point A are (Pa1, Pb1), and the longitude and latitude of positioning point B are (Pa2, Pb2), then the longitude difference is Pa2-Pa1, and the latitude difference is Pb2-Pb1. Based on the longitude and latitude difference, the actual distance between the two points can be calculated. The spherical distance calculation formula can be used to accurately calculate the actual distance between the two points by considering the curvature of the earth. In addition to distance changes, direction changes can also be analyzed. By calculating the angle between the line connecting the two positioning points and the true north direction, the change in the moving direction can be determined.

[0066] Record the acquisition time of each positioning point and calculate the time interval between adjacent positioning points. For example, if the acquisition time of positioning point A is Ta1 and the acquisition time of positioning point B is Ta2, then the time interval is Ta2-Ta1.

[0067] The window length is determined based on the distance change and time change between the positioning points. If the positioning points move quickly and the distance change is large, the window length can be appropriately increased to ensure that enough positioning points are covered to accurately analyze the movement trend. Conversely, if the movement speed is slow, the window length can be reduced to increase the sensitivity to local changes.

[0068] For example, you can set a threshold value. When the distance between two consecutive positioning points exceeds a certain value, the window length is increased; when the distance is less than a certain value, the window length is reduced. At the same time, the window length can also be adjusted according to the time interval. If the time interval is long, it means that the frequency of positioning point collection is low. The window length can be increased to ensure that there is enough data for analysis.

[0069] In addition, the appropriate window length for different application scenarios can be determined through experiments or experience. For example, in traffic navigation, the window length can be determined based on the average speed of the vehicle and the frequency of collecting positioning data; in pedestrian navigation, the window length can be determined based on the walking speed of pedestrians and the positioning accuracy requirements.

[0070] Once the window length is determined, a sliding window can be constructed. A sliding window can be represented by a data structure, such as an array or a linked list. The size of the window is fixed to the determined window length, and each position can store information about a location point, including latitude and longitude coordinates, acquisition time, etc. Some properties can be set for the sliding window, such as the start and end position pointers of the current window, which are used to indicate the range of locations contained in the window.

[0071] Before starting to record the sequence of anchor points, initialize the sliding window. Set the window's start and end position pointers to initial values, usually pointing to the first position of the window. If the window is empty, you can assign an initial value to each position or mark it as unused.

[0072] The sequence of anchor points is recorded into the sliding window one by one in chronological order. Starting from the earliest anchor point, it is placed in the first position of the window. As new anchor points are added, the anchor points in the window are continuously updated. If the window is full, the new anchor point will replace the earliest anchor point in the window, so that the window always contains a certain number of the latest anchor points. During the recording process, the start and end position pointers of the window need to be updated to correctly indicate the range of anchor points contained in the window.

[0073] Step S103, obtaining the target positioning point of the positioning point sequence falling within the sliding window, and obtaining the target longitude and latitude parameters corresponding to the target positioning point.

[0074] In the embodiment of the present application, first, after the positioning point sequence is entered into the preset sliding window, it is necessary to determine the target positioning point that falls within the sliding window. Each positioning point in the positioning point sequence is checked one by one to determine whether its timestamp is within the time range covered by the sliding window. If the timestamp of a positioning point is between the start time and the end time of the sliding window, then this positioning point is determined as the target positioning point.

[0075] Once the target positioning point is determined, its corresponding target longitude and latitude parameters can be obtained. Each positioning point usually contains longitude and latitude information. For the target positioning point, its stored longitude value can be directly extracted as the target longitude parameter, and its stored latitude value can be extracted as the target latitude parameter. These target longitude and latitude parameters will be used for subsequent calculations and analysis, such as updating the longitude and latitude parameters of the first target positioning point in the sliding window.

[0076] Step S104, using the target longitude and latitude parameters to update the longitude and latitude parameters of the first target positioning point in the sliding window, and sliding the sliding window to update the longitude and latitude parameters of each positioning point in the positioning point sequence in turn.

[0077] First, the target longitude parameter and target latitude parameter are extracted from the target longitude and latitude parameters. Then, the average longitude parameter is calculated using the target longitude parameters of each target positioning point and the number of target positioning points, and the average latitude parameter is calculated in the same way. Then, the longitude and latitude parameters of the first target positioning point in the sliding window are updated using the average longitude parameter and the average latitude parameter, that is, the longitude value of the first target positioning point is replaced by the average longitude parameter, and the latitude value is replaced by the average latitude parameter.

[0078] After completing the update of the first target positioning point, slide the sliding window. This means moving the window forward one position so that the second positioning point in the original window becomes the first positioning point in the new window. Then repeat the above process of extracting the target longitude and latitude parameters, calculating the average longitude and latitude parameters, and updating the longitude and latitude parameters of the positioning points, and update the longitude and latitude parameters of each positioning point in the positioning point sequence in turn. By continuously sliding the window and updating the positioning points, the longitude and latitude parameters in the entire positioning point sequence can be made more accurate and stable, reflecting a more realistic trend of location information changes.

[0079] In the embodiment of the present application, the longitude and latitude parameters of the first target positioning point in the sliding window are updated using the target longitude and latitude parameters, including the following steps B1-B4:

[0080] Step B1, extracting a target longitude parameter and a target latitude parameter from the target longitude and latitude parameters.

[0081] Specifically, for each target positioning point, the latitude and longitude parameters contained therein can be stored in the form of a data structure (such as a structure or an object). In this data structure, there are fields representing longitude and latitude respectively. By accessing the data structure of the target positioning point, the target longitude parameter and the target latitude parameter can be directly extracted.

[0082] Step B2, calculating an average longitude parameter using the target longitude parameters of each target positioning point and the number of target positioning points.

[0083] Specifically, first, initialize a variable to store the total longitude, such as "totalLongitude", and set its initial value to 0. Then, traverse all target positioning points. For each target positioning point, add its target longitude parameter to "totalLongitude". Finally, calculate the average longitude parameter. The average longitude parameter is equal to "totalLongitude" divided by the number of target positioning points. This can be implemented using the division operation in the programming language. For example, if there are "n" target positioning points, the average longitude parameter is "totalLongitude / n".

[0084] Step B3, calculating an average latitude parameter using the target latitude parameters of each target positioning point and the number of target positioning points.

[0085] Specifically, initialize a variable to store the total latitude, such as "totalLatitude", with an initial value of 0. Traverse the target positioning points and add the target latitude parameter of each target positioning point to "totalLatitude". Calculate the average latitude parameter, that is, "totalLatitude / n", where "n" is the number of target positioning points.

[0086] Step B4: Update the longitude and latitude parameters of the first target positioning point in the sliding window using the average longitude parameter and the average latitude parameter.

[0087] Specifically, find the first target positioning point in the sliding window. The first target positioning point can be quickly located through the index or pointer in the data structure of the sliding window. Assign the calculated average longitude parameter to the longitude field of the first target positioning point. For example, if the data structure of the first target positioning point is an object, it can be updated using the method of "firstTargetPoint.longitude=averageLongitude". Similarly, assign the calculated average latitude parameter to the latitude field of the first target positioning point, such as "firstTargetPoint.latitude=averageLatitude". This completes the update of the longitude and latitude parameters of the first target positioning point in the sliding window.

[0088] As an example, Figure 2 As shown, assuming that there is a series of collected data points, we set every 10 data points as a window and set the number n for each window. For example, the data points in window Wn are numbered from Pn to Pn+10. The 10 collected data points from Pn to Pn+10 are entered into the sliding window Wn. For the data points in window Wn, we process their longitude and latitude respectively. Add the longitude values ​​of these 10 data points in sequence, that is, add Pna, Pn+1a, Pn+2a...Pn+9a, Pn+10a, and then divide by the total number of data points 10 to obtain the corrected longitude average Pa. Similarly, add the latitude values ​​of these 10 data points Pnb, Pn+1b, Pn+2b...Pn+9b, Pn+10b and divide by 10 to obtain the corrected latitude average Pb. After such calculation, Pa and Pb become the corrected longitude and latitude of point Pn. By taking the average value in this way, the impact of deviations in individual data points on the overall positioning can be reduced, making the point a more effective positioning data point.

[0089] The embodiment of the present application first obtains multiple positioning points and longitude and latitude parameters within the current acquisition cycle, thereby increasing the amount of data. The error impact of a single positioning point caused by instantaneous factors such as fluctuations in satellite signal quality and multipath effects can be reduced. Secondly, the positioning points are constructed as a positioning point sequence in chronological order and entered into a sliding window, so that the positioning data within a period of time can be continuously analyzed. Furthermore, by obtaining the target positioning point and the target longitude and latitude parameters within the sliding window to update the first target positioning point, and updating the entire positioning point sequence in sequence, a data smoothing effect is achieved. This updating method utilizes the information of the surrounding positioning points that are close in time to correct the positioning points that may drift. For example, when a certain positioning point is affected by factors such as building obstruction or satellite clock error and produces a large deviation, by combining the longitude and latitude parameters with the surrounding positioning points, the impact of this deviation on the trajectory can be reduced, making the trajectory more stable and accurate.

[0090] In the embodiment of the present application, after the longitude and latitude parameters of the first target positioning point in the sliding window are updated using the target longitude and latitude parameters, as shown in FIG. Figure 3 As shown, the method also includes:

[0091] Step S201, analyzing the target longitude and latitude parameters of each target positioning point in the sliding window respectively, and obtaining the change trend of the target longitude and latitude parameters in time series.

[0092] In an embodiment of the present application, first, each target positioning point in the sliding window and its corresponding target longitude and latitude parameters are obtained. These parameters can be arranged in chronological order to construct a time series. For the longitude parameter, its change in the time series can be observed. The longitude difference between adjacent time points is calculated, and the size and direction of these differences are analyzed. If the difference shows a trend of gradually increasing over a period of time, it means that the positioning point may be moving eastward; if the difference gradually decreases, it may be moving westward. Similarly, the same analysis is performed on the latitude parameter to determine the movement trend of the positioning point in the north-south direction.

[0093] The change rate of longitude and latitude parameters can also be calculated, that is, the ratio of the difference to the time interval. A larger change rate indicates that the positioning point moves faster, while a smaller change rate indicates that the moving speed is slower or in a stable state. Through a comprehensive analysis of these changes, the change trend of the target longitude and latitude parameters in the time series can be obtained, such as fast movement to the east, slow movement to the north, and being in a relatively stable state.

[0094] Step S202: adjusting the acquisition frequency using the change trend, wherein the acquisition frequency is used to determine the acquisition period.

[0095] In an embodiment of the present application, the acquisition frequency is adjusted using the change trend, including: if the change trend shows that the positioning point will enter an area where the signal strength is lower than the preset strength or the environment is complex, then the acquisition frequency is increased; or, if the change trend shows that the positioning point is in a stable state, then the acquisition frequency is reduced.

[0096] Specifically, the trend of changes in the latitude and longitude parameters of the target positioning point is continuously monitored. If the trend shows that the positioning point will enter an area where the signal strength is lower than the preset strength or the environment is complex, the following methods can be used to increase the acquisition frequency: On the one hand, historical data or geographic information can be analyzed to determine which areas may have signal strength lower than the preset strength or complex environment. For example, urban areas with dense high-rise buildings, mountainous areas, tunnels, etc. usually have poor signals. When the trend of changes in the target latitude and longitude parameters indicates that the positioning point is approaching these areas, the acquisition frequency can be increased.

[0097] On the other hand, the signal strength and other indicators around the positioning point can be monitored in real time. If the signal strength begins to drop, or there is a large signal fluctuation, it can also be judged that the positioning point may be about to enter an area where the signal strength is lower than the preset strength, thereby increasing the collection frequency. Increasing the collection frequency can be achieved by adjusting the settings of the positioning device or calling related APIs, such as shortening the time interval for positioning data collection.

[0098] If the trend shows that the positioning point is in a stable state, reduce the acquisition frequency. The stable state can be judged in the following way: when the target longitude and latitude parameters change very little over a period of time, such as the difference between the longitude and latitude of several adjacent time points is almost zero, or the rate of change is very low, the positioning point can be considered to be in a stable state.

[0099] Lowering the acquisition frequency in a stable state can save device power and resources, while reducing the pressure of data transmission and processing. Lowering the acquisition frequency can also be achieved by adjusting device settings or APIs, such as extending the time interval for positioning data collection. Adjusting the acquisition frequency will directly affect the acquisition period, which is inversely proportional to the acquisition frequency, that is, the higher the acquisition frequency, the shorter the acquisition period; the lower the acquisition frequency, the longer the acquisition period.

[0100] In an embodiment of the present application, after updating the longitude and latitude parameters of the first target positioning point in the sliding window using the target longitude and latitude parameters, the method also includes: detecting the target state corresponding to the positioning point and obtaining the display style corresponding to the target state; and displaying the positioning point on the map according to the display style.

[0101] In an embodiment of the present application, first, a state detection is performed on each positioning point. This can be done by analyzing the latitude and longitude parameters, moving speed, signal strength and other factors of the positioning point to determine its target state. For example, if the moving speed of the positioning point is zero and the signal strength is stable, it can be judged as a stationary state; if the moving speed is fast and the signal strength fluctuates greatly, it may be a moving state. Or different states are divided according to other specific rules and algorithms, such as normal state, abnormal state, etc. Once the target state of the positioning point is determined, the display style corresponding to the state is obtained. The display style may include different icons, colors, sizes and other features. For example, a positioning point in a stationary state can be represented by a green circular icon, a positioning point in a moving state can be represented by a blue arrow icon, and a positioning point in an abnormal state can be represented by a red exclamation mark icon.

[0102] Then, the positioning point is displayed on the map according to its corresponding display style. This can be achieved by calling the map API or related map display tools. The latitude and longitude coordinates of the positioning point are converted to the specific location on the map, and the corresponding icon, color and other attributes are set according to the display style. In this way, when viewing the map, the user can intuitively understand the status of each positioning point, so as to better understand the situation reflected by the positioning data.

[0103] In this embodiment, a processing device for positioning data is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0104] This embodiment provides a positioning data processing device, such as Figure 4 As shown, including:

[0105] The acquisition module 401 is used to acquire multiple positioning points acquired in the current acquisition cycle and the latitude and longitude parameters corresponding to the positioning points;

[0106] Processing module 402, used to construct a positioning point sequence according to the time sequence of the positioning points, and enter the positioning point sequence into a preset sliding window;

[0107] The screening module 403 is used to obtain the target positioning point whose positioning point sequence falls into the sliding window, and obtain the target longitude and latitude parameters corresponding to the target positioning point;

[0108] The updating module 404 is used to update the longitude and latitude parameters of the first target positioning point in the sliding window using the target longitude and latitude parameters, and to update the longitude and latitude parameters of each positioning point in the positioning point sequence in sequence by sliding the sliding window.

[0109] In an embodiment of the present application, the acquisition module 401 is used to obtain the application scenario of the positioning data and the environmental conditions in which the acquisition device is located; analyze the application scenario and the environmental conditions to determine the acquisition frequency, and use the acquisition frequency to determine the current acquisition cycle; within the current acquisition cycle, call the acquisition device to collect positioning data to obtain multiple positioning points.

[0110] In the embodiment of the present application, the processing module 402 is used to obtain the changes between the positioning points in the current acquisition cycle; determine the window length using the changes, and construct a sliding window using the window length; and enter the positioning point sequence into the sliding window.

[0111] In an embodiment of the present application, the update module 404 is used to extract the target longitude parameter and the target latitude parameter from the target longitude and latitude parameters; calculate the average longitude parameter using the target longitude parameters of each target positioning point and the number corresponding to the target positioning point; calculate the average latitude parameter using the target latitude parameters of each target positioning point and the number corresponding to the target positioning point; and update the longitude and latitude parameters of the first target positioning point in the sliding window using the average longitude parameter and the average latitude parameter.

[0112] In an embodiment of the present application, the device also includes: an analysis module, which is used to analyze the target longitude and latitude parameters of each target positioning point in the sliding window respectively to obtain the change trend of the target longitude and latitude parameters in the time series; and adjust the collection frequency using the change trend, wherein the collection frequency is used to determine the collection period.

[0113] In an embodiment of the present application, the analysis module is used to increase the acquisition frequency if the change trend shows that the positioning point will enter an area with a signal strength lower than a preset strength or a complex environment; or, if the change trend shows that the positioning point is in a stable state, reduce the acquisition frequency.

[0114] In an embodiment of the present application, the device also includes: a display module, which is used to detect the target state corresponding to the positioning point and obtain the display style corresponding to the target state; and display the positioning point on the map according to the display style.

[0115] See also Figure 5 , Figure 5 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 5As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system).

[0116] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0117] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0118] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the use of a computer device based on the presentation of a small program landing page, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0119] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0120] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0121] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0122] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for processing positioning data, characterized in that: The method comprises: Acquire multiple positioning points collected in the current collection cycle and the latitude and longitude parameters corresponding to the positioning points; Construct a positioning point sequence from the positioning points in chronological order, and enter the positioning point sequence into a preset sliding window; Acquire the target positioning point of the positioning point sequence that falls within the sliding window, and acquire the target longitude and latitude parameters corresponding to the target positioning point; The target longitude and latitude parameters are used to update the longitude and latitude parameters of the first target positioning point in the sliding window, and the sliding window is slid to update the longitude and latitude parameters of each positioning point in the positioning point sequence in turn.

2. The method according to claim 1, characterized in that The acquiring of multiple positioning points collected in the current collection cycle and the latitude and longitude parameters corresponding to the positioning points includes: The application scenarios for obtaining positioning data and the environmental conditions of the collection equipment; Analyze the application scenario and the environmental conditions to determine a collection frequency, and use the collection frequency to determine a current collection period; In the current collection cycle, the collection device is called to collect positioning data to obtain multiple positioning points.

3. The method according to claim 1, characterized in that The step of entering the positioning point sequence into a preset sliding window comprises: Obtaining changes between positioning points in the current acquisition cycle; Determine a window length using the change, and construct the sliding window using the window length; The positioning point sequence is recorded into the sliding window.

4. The method according to claim 1, characterized in that: The updating of the longitude and latitude parameters of the first target positioning point in the sliding window by using the target longitude and latitude parameters includes: Extracting a target longitude parameter and a target latitude parameter from the target longitude and latitude parameters; Calculating an average longitude parameter using the target longitude parameters of each of the target positioning points and the number of target positioning points corresponding to the target positioning points; Calculating an average latitude parameter using the target latitude parameters of each of the target positioning points and the number of target positioning points corresponding to the target positioning points; The longitude and latitude parameters of the first target positioning point in the sliding window are updated using the average longitude parameter and the average latitude parameter.

5. The method according to claim 1, characterized in that: After updating the longitude and latitude parameters of the first target positioning point in the sliding window using the target longitude and latitude parameters, the method further includes: Analyze the target longitude and latitude parameters of each target positioning point in the sliding window respectively to obtain the change trend of the target longitude and latitude parameters in time series; The acquisition frequency is adjusted using the change trend, wherein the acquisition frequency is used to determine the acquisition period.

6. The method according to claim 5, characterized in that The adjusting the acquisition frequency by utilizing the change trend includes: If the change trend shows that the positioning point will enter an area where the signal strength is lower than the preset strength or the environment is complex, the acquisition frequency is increased; or if the change trend shows that the positioning point is in a stable state, the acquisition frequency is reduced.

7. The method according to claim 1, characterized in that After updating the longitude and latitude parameters of the first target positioning point in the sliding window using the target longitude and latitude parameters, the method further includes: Detecting a target state corresponding to the positioning point, and acquiring a display style corresponding to the target state; The positioning point is displayed on a map according to the display style.

8. A positioning data processing device, characterized in that: The device comprises: The acquisition module is used to acquire multiple positioning points acquired in the current acquisition cycle and the latitude and longitude parameters corresponding to the positioning points; A processing module, used to construct a positioning point sequence from the positioning points in chronological order, and enter the positioning point sequence into a preset sliding window; A screening module, used to obtain the target positioning point whose positioning point sequence falls within the sliding window, and obtain the target longitude and latitude parameters corresponding to the target positioning point; The updating module is used to update the longitude and latitude parameters of the first target positioning point in the sliding window using the target longitude and latitude parameters, and to update the longitude and latitude parameters of each positioning point in the positioning point sequence in turn by sliding the sliding window.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

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