CN109470253B - Real-time positioning processing method and device - Google Patents
Real-time positioning processing method and device Download PDFInfo
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- CN109470253B CN109470253B CN201811204144.3A CN201811204144A CN109470253B CN 109470253 B CN109470253 B CN 109470253B CN 201811204144 A CN201811204144 A CN 201811204144A CN 109470253 B CN109470253 B CN 109470253B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention provides a real-time positioning processing method and a real-time positioning processing device, wherein the receiving method comprises the following steps: acquiring n coordinate points reported by user equipment before a coordinate point to be detected; determining the n coordinate points as a prediction window; judging whether the coordinate point to be detected is a noisy point or not according to the average speed of the n coordinate points in the prediction window, the speed standard deviation of the n coordinate points and the speed of the coordinate point to be detected; and the user equipment is positioned in real time according to the judgment result, so that the problem that the positioning is not accurate enough due to the fact that the misjudgment rate of the coordinate point is high because the noise point is filtered according to the coordinate precision in the related technology can be solved, the speeds of the coordinate point to be detected and the previous n coordinate points are compared, the noise point is filtered, and the accuracy of noise point filtering is improved.
Description
Technical Field
The invention relates to the field of communication, in particular to a real-time positioning processing method and device.
Background
In the process of dispatching the order for the driver, the scheduling and the calculation are required according to the real-time position of the driver, so that the resources are timely and accurately distributed. However, because GPS positioning is affected by clock error, ephemeris error, delay error, etc., a certain offset may be generated, and positioning of the base station/WIFI positioning may also be changed due to signal density, geographical location, etc., which may cause a noise point with an excessive offset, thereby affecting the use experience of the system.
At present, the filtering noise point is only filtered according to the coordinate precision, so that the misjudgment probability of the coordinate point is very high, the positioning is not accurate enough, and the experience of a driver and a user is influenced.
Aiming at the problem that in the related art, noise points are filtered according to coordinate precision, so that the misjudgment rate of coordinate points is high, and the positioning is not accurate enough, a solution is not provided.
Disclosure of Invention
The embodiment of the invention provides a real-time positioning processing method and a real-time positioning processing device, which are used for at least solving the problem that in the related technology, the erroneous judgment rate of a coordinate point is large to cause inaccurate positioning due to the fact that noisy points are filtered according to the coordinate precision.
According to an embodiment of the present invention, there is provided a real-time positioning processing method, including:
acquiring n coordinate points reported by user equipment before a coordinate point to be detected, wherein n is a natural number greater than 1;
determining the n coordinate points as a prediction window;
judging whether the coordinate point to be detected is a noise point or not according to the average speed of the n coordinate points in the prediction window, the speed standard deviation of the n coordinate points and the speed of the coordinate point to be detected;
and positioning the user equipment in real time according to the judgment result.
Optionally, the performing real-time positioning according to the judgment result includes:
filtering the coordinate point to be detected under the condition that the coordinate point to be detected is a noise point as a result of the judgment, and determining a coordinate point which is previous to the coordinate point to be detected as the real-time position of the user equipment;
and determining the coordinate point to be detected as the real-time position of the user equipment under the condition that the judgment result is that the coordinate point to be detected is a non-noise point.
Optionally, the method further comprises:
and adding the coordinate point to be detected into the prediction window under the condition that the judgment result is that the coordinate point to be detected is a non-noise point.
Optionally, the determining whether the coordinate point to be measured is a noise point according to the average speed of the n coordinate points in the prediction window and the speed of the coordinate point to be measured includes:
determining a speed prediction range according to the average speed of the n coordinate points in the prediction window;
determining adjacent coordinate points of the coordinate points to be measured in the speed prediction range;
judging whether the number of the adjacent coordinate points is greater than a preset threshold value or not;
under the condition that the judgment result is negative, determining the coordinate point to be detected as a noise point;
if the judgment result is yes, determining the coordinate point to be detected as a suspected noise point; calculating the speed standard deviation of the n coordinate points in the prediction window and the speed of the coordinate point to be measured; judging whether the speed of the coordinate point to be detected is within the speed standard deviation range of the n coordinate points; and determining whether the coordinate point to be detected is a noise point according to the judgment result.
Optionally, determining neighboring coordinate points of the coordinate point to be measured within the speed prediction range includes:
and determining the coordinate point with the average speed within the speed prediction range in the n coordinate points as the adjacent coordinate point of the coordinate point to be detected.
Optionally, the n coordinate points are non-noisy points, a time interval between a 1 st coordinate point and an nth coordinate point in the n coordinate points is within a predetermined time interval threshold, and a distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within a predetermined distance threshold.
Optionally, the method further comprises:
if the time interval between the 1 st coordinate point and the nth coordinate point in the n coordinate points is not within the preset time interval threshold and/or the distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is not within the preset distance threshold, moving the prediction window forwards, and adding the to-be-detected coordinate point into the moved prediction window until the time interval between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within the preset time interval threshold, wherein the distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within the preset distance threshold.
Optionally, before acquiring the n coordinate points reported before the coordinate point to be measured, the method further includes:
and determining that the average speed, the acceleration, the angle and the distance of the coordinate point to be measured relative to the previous coordinate point are within a preset range.
According to another embodiment of the present invention, there is also provided a real-time positioning processing apparatus including:
the acquisition module is used for acquiring n coordinate points reported by user equipment before the coordinate point to be detected, wherein n is a natural number greater than 1;
a determining module, configured to determine the n coordinate points as a prediction window;
the judging module is used for judging whether the coordinate point to be detected is a noise point according to the average speed of the n coordinate points in the prediction window, the speed standard deviation of the n coordinate points and the speed of the coordinate point to be detected;
and the positioning module is used for positioning the user equipment in real time according to the judgment result.
Optionally, the positioning module comprises:
the first determining unit is used for filtering the coordinate point to be detected and determining the previous coordinate point of the coordinate point to be detected as the real-time position of the user equipment under the condition that the judgment result is that the coordinate point to be detected is a noise point;
and the second determining unit is used for determining the coordinate point to be detected as the real-time position of the user equipment under the condition that the judgment result is that the coordinate point to be detected is the non-noise point.
Optionally, the apparatus further comprises:
and the adding unit is used for adding the coordinate point to be detected into the prediction window under the condition that the judgment result is that the coordinate point to be detected is a non-noise point.
Optionally, the determining module includes:
a third determining unit, configured to determine a speed prediction range according to the average speed of the n coordinate points within the prediction window;
a fourth determination unit configured to determine an adjacent coordinate point of the coordinate point to be measured within the speed prediction range;
a judging unit configured to judge whether the number of the adjacent coordinate points is greater than a predetermined threshold;
a fifth determining unit, configured to determine that the coordinate point to be measured is a noise point if the determination result is negative;
a sixth determining unit, configured to determine that the coordinate point to be detected is a suspected noise point if the determination result is yes; calculating the speed standard deviation of the n coordinate points in the prediction window and the speed of the coordinate point to be measured; judging whether the speed of the coordinate point to be detected is within the speed standard deviation range of the n coordinate points; and determining whether the coordinate point to be detected is a noise point according to the judgment result.
Optionally, the fourth determining unit is further configured to
And determining the coordinate point with the average speed within the speed prediction range in the n coordinate points as the adjacent coordinate point of the coordinate point to be detected.
Optionally, the n coordinate points are non-noisy points, a time interval between a 1 st coordinate point and an nth coordinate point in the n coordinate points is within a predetermined time interval threshold, and a distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within a predetermined distance threshold.
Optionally, the apparatus further comprises:
a forward moving module, configured to move the prediction window forward if a time interval between a 1 st coordinate point and an nth coordinate point in the n coordinate points is not within a predetermined time interval threshold and/or a distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is not within a predetermined distance threshold, and add the to-be-detected coordinate point into the forward-moved prediction window until the time interval between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within the predetermined time interval threshold, where the distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within the predetermined distance threshold.
Optionally, before acquiring the n coordinate points reported before the coordinate point to be measured, the apparatus further includes:
and determining that the average speed, the acceleration, the angle and the distance of the coordinate point to be measured relative to the previous coordinate point are within a preset range.
According to a further embodiment of the present invention, there is also provided a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
According to yet another embodiment of the present invention, there is also provided an electronic device, including a memory in which a computer program is stored and a processor configured to execute the computer program to perform the steps in any of the above method embodiments.
According to the invention, n coordinate points reported by user equipment before the coordinate point to be detected are obtained; determining the n coordinate points as a prediction window; judging whether the coordinate point to be detected is a noise point or not according to the average speed of the n coordinate points in the prediction window, the speed standard deviation of the n coordinate points and the speed of the coordinate point to be detected; and the user equipment is positioned in real time according to the judgment result, so that the problem that the positioning is not accurate enough due to the fact that the misjudgment rate of the coordinate point is high because the noise point is filtered according to the coordinate precision in the related technology can be solved, the speeds of the coordinate point to be detected and the previous n coordinate points are compared, the noise point is filtered, and the accuracy of noise point filtering is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a block diagram of a hardware structure of a mobile terminal of a real-time positioning processing method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method of real-time location processing according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating noise filtering of a coordinate point to be measured according to an embodiment of the present invention;
fig. 4 is a block diagram of a real-time positioning processing apparatus according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Example 1
The method provided by the first embodiment of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking a mobile terminal as an example, fig. 1 is a hardware structure block diagram of a mobile terminal of a real-time positioning processing method according to an embodiment of the present invention, as shown in fig. 1, a mobile terminal 10 may include one or more processors 102 (only one is shown in fig. 1) (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA, etc.), and a memory 104 for storing data, and optionally, the mobile terminal may further include a transmission device 106 for communication function and an input/output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration, and does not limit the structure of the mobile terminal. For example, the mobile terminal 10 may include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store a computer program, for example, a software program of application software and a module, such as a computer program corresponding to the message receiving method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, so as to implement the method described above. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the mobile terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used to receive or transmit data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal 10. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In this embodiment, a real-time positioning processing method operating in the mobile terminal or the network architecture is provided, and fig. 2 is a flowchart of a real-time positioning processing method according to an embodiment of the present invention, as shown in fig. 2, the flowchart includes the following steps:
step S202, acquiring n coordinate points reported by user equipment before a coordinate point to be detected, wherein n is a natural number greater than 1;
step S204, determining the n coordinate points as a prediction window;
step S206, judging whether the coordinate point to be detected is a noise point according to the average speed of the n coordinate points in the prediction window, the speed standard deviation of the n coordinate points and the speed of the coordinate point to be detected;
and S208, positioning the user equipment in real time according to the judgment result.
Through the steps, n coordinate points reported by the user equipment before the coordinate point to be detected are obtained; determining the n coordinate points as a prediction window; judging whether the coordinate point to be detected is a noise point or not according to the average speed of the n coordinate points in the prediction window, the speed standard deviation of the n coordinate points and the speed of the coordinate point to be detected; the user equipment is positioned in real time according to the judgment result, so that the problem that in the related technology, the positioning is not accurate enough due to the fact that the misjudgment rate of the coordinate point is large due to the fact that the noise point is filtered according to the coordinate precision can be solved, the speed of the coordinate point to be detected and the speed of the n coordinate points before the coordinate point to be detected are compared, the noise point is filtered, and the accuracy of noise point filtering is improved.
In the embodiment of the present invention, the performing real-time positioning according to the judgment result specifically may include: filtering the coordinate point to be detected under the condition that the coordinate point to be detected is a noise point as a result of the judgment, and determining a previous coordinate point of the coordinate point to be detected as a real-time position of the user equipment, namely, considering that the user equipment has no position change compared with a position reported last time; and determining the coordinate point to be detected as the real-time position of the user equipment under the condition that the coordinate point to be detected is a non-noise point as a judgment result, namely determining the current position of the user equipment as the position of the coordinate point to be detected.
In the embodiment of the invention, under the condition that the coordinate point to be detected is a non-noise point as a result of the judgment, the coordinate point to be detected is added into the prediction window for judging whether the coordinate point to be detected is a noise point, so that the noise point filtering of the coordinate point to be detected collected in real time is realized.
In this embodiment of the present invention, the determining whether the coordinate point to be measured is a noise point according to the average speed of the n coordinate points in the prediction window and the speed of the coordinate point to be measured specifically includes: determining a speed prediction range according to the average speed of the n coordinate points in the prediction window; determining adjacent coordinate points of the coordinate points to be measured in the speed prediction range; judging whether the number of the adjacent coordinate points is greater than a preset threshold value or not; under the condition that the judgment result is negative, determining the coordinate point to be detected as a noise point; if the judgment result is yes, determining the coordinate point to be detected as a suspected noise point; calculating the speed standard deviation of the n coordinate points in the prediction window and the speed of the coordinate point to be measured; judging whether the speed of the coordinate point to be detected is within the speed standard deviation range of the n coordinate points; and determining whether the coordinate point to be detected is a noise point according to the judgment result, determining that the coordinate point to be detected is a non-noise point if the judgment result is yes, and determining that the coordinate point to be detected is a noise point if the judgment result is no.
In an optional embodiment, determining the coordinate points adjacent to the coordinate point to be measured in the speed prediction range may specifically include: and determining the coordinate point with the average speed within the speed prediction range in the n coordinate points as the adjacent coordinate point of the coordinate point to be detected.
In the embodiment of the present invention, the n coordinate points are non-noise points, a time interval between a 1 st coordinate point and an nth coordinate point in the n coordinate points is within a predetermined time interval threshold, and a distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within a predetermined distance threshold; or if the time interval between the 1 st coordinate point and the nth coordinate point in the n coordinate points is not within the preset time interval threshold and/or the distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is not within the preset distance threshold, moving the prediction window forwards, and adding the coordinate point to be detected into the moved prediction window till the time interval between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within the preset time interval threshold, wherein the distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within the preset distance threshold.
In the embodiment of the invention, the vehicle motion track has a theoretical boundary, and the noise point is directly defined when the vehicle motion track exceeds the boundary. The boundary rules include a high-speed filtering rule, an acceleration filtering rule, an angle filtering rule and a distance filtering rule. Specifically, before the n coordinate points reported before the coordinate point to be measured are obtained, it is determined that the average speed, the acceleration, the angle and the distance of the coordinate point to be measured relative to the previous coordinate point are within a preset range, that is, the noise point is filtered by the boundary principle, so that the efficiency and the accuracy of noise point filtering are improved.
The embodiment of the invention predicts the speed and other information of the next coordinate point in the dynamic time window, compares the speed and other information with the actual value, and judges whether the coordinate point is a noise point by combining the number of the neighbor coordinate points of the coordinate point in a certain threshold range. Fig. 3 is a flowchart of filtering noise of a coordinate point to be measured according to an embodiment of the present invention, as shown in fig. 3, including:
step S301, judging whether the obtained coordinate point P to be detected is the same as the last noise point, if so, executing step S302, and if not, executing step S303;
step S302, determining a coordinate point P to be measured as a noise point;
step S303, acquiring the first n coordinate points of the point p to be measured as a prediction window;
a step S304 of determining whether or not the prediction window satisfies a threshold value such as a time interval and a movement distance, and if the determination result is yes, executing a step S306, and if the determination result is no, executing a step S305;
s305, the prediction window moves forward, the point to be measured is added into the prediction window, and the step S304 is returned;
step S306, calculating a range according to the predicted window speed, and calculating the number of neighbor points in the range of the point p to be measured;
step S307, judging whether the number of the neighbor points is greater than a density threshold value, if so, executing step S308, and if not, executing step S309;
step S308, determining the coordinate point P to be measured as a non-noise point;
step S309, adding the coordinate point P to be detected into a suspected noise point;
step S310, calculating the average speed and standard deviation of a prediction window and the average speed of a point p to be measured;
step S311, judging whether the speed of the point to be measured is within the standard deviation range of the prediction window, if so, executing step S313, and if not, executing step S312;
step S312, determining the coordinate point P to be measured as a non-noise point.
Step 313, determining the coordinate point P to be measured as a non-noise point.
And if the point to be measured is judged to be a non-noise point, adding the point into the prediction window, moving the window forward, and continuing 1.
The embodiment of the invention judges the noise point by combining the density clustering, the dynamic window and the boundary principle, thereby fundamentally changing the defect of filtering according to the coordinate precision.
Whether the neighbor point included in the real-time position in a certain range meets a threshold value is judged by calculating whether the neighbor point meets the threshold value, if the neighbor point does not meet the threshold value, the neighbor point is judged as a noise point, and if the neighbor point meets the threshold value, the neighbor point is judged again by combining an edge rule.
And adding the data which is judged to be the non-noise point into the window, moving the window forwards, predicting the speed of the next position through a coordinate point in the window, and calculating the density clustering range according to the predicted speed value and the time interval.
Since the motion trail of the vehicle has a theoretical boundary, exceeding the boundary is directly defined as noise. The boundary principle comprises a high-speed filtering principle, an acceleration filtering principle, an angle filtering principle and a distance filtering principle.
In an optional embodiment, the parameters of noise filtering of the coordinate point to be measured may be optimized, and the accuracy, precision, and recall rate are introduced to quantify the algorithm optimization result, specifically, after a predetermined time, the coordinate point reported in a period of time is obtained, the obtained coordinate point is filtered for noise, and the algorithm optimization result is quantified by comparing the noise filtering condition with the data performed in real time before.
TP: determining that the noise is actually also a quantity of noise
FP: the number of noise points actually determined to be non-noise points
TN: determining that the non-noise is actually a quantity of non-noise
FN: number of noise points determined to be non-noise points but actually noise points
The accuracy is as follows: (TP + TN)/ALL
The precision rate is: TP/(TP + FP)
The recall ratio is: TP/(TP + FN)
Through optimization, the accuracy rate is improved to 99.95% from 85%, the accuracy rate is improved to 90% from 10%, and the recall rate is improved to 95% from 80%.
Example 2
In this embodiment, an information relevance processing apparatus is further provided, and the apparatus is used to implement the foregoing embodiments and preferred embodiments, and the description already made is omitted for brevity. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 4 is a block diagram of a real-time positioning processing apparatus according to an embodiment of the present invention, as shown in fig. 4, including:
an obtaining module 42, configured to obtain n coordinate points reported by the user equipment before the coordinate point to be detected;
a determining module 44, configured to determine the n coordinate points as a prediction window;
a determining module 46, configured to determine whether the coordinate point to be detected is a noise point according to the average speed of the n coordinate points in the prediction window, the speed standard deviation of the n coordinate points, and the speed of the coordinate point to be detected;
and the positioning module 48 is configured to perform real-time positioning on the user equipment according to the judgment result.
Optionally, the positioning module comprises:
the first determining unit is used for filtering the coordinate point to be detected and determining the previous coordinate point of the coordinate point to be detected as the real-time position of the user equipment under the condition that the judgment result is that the coordinate point to be detected is a noise point;
and the second determining unit is used for determining the coordinate point to be detected as the real-time position of the user equipment under the condition that the judgment result is that the coordinate point to be detected is the non-noise point.
Optionally, the apparatus further comprises:
and the adding unit is used for adding the coordinate point to be detected into the prediction window under the condition that the judgment result is that the coordinate point to be detected is a non-noise point.
Optionally, the determining module includes:
a third determining unit, configured to determine a speed prediction range according to the average speed of the n coordinate points within the prediction window;
a fourth determination unit configured to determine an adjacent coordinate point of the coordinate point to be measured within the speed prediction range;
a judging unit configured to judge whether the number of the adjacent coordinate points is greater than a predetermined threshold;
a fifth determining unit, configured to determine that the coordinate point to be measured is a noise point if the determination result is negative;
a sixth determining unit, configured to determine that the coordinate point to be detected is a suspected noise point if the determination result is yes; calculating the speed standard deviation of the n coordinate points in the prediction window and the speed of the coordinate point to be measured; judging whether the speed of the coordinate point to be detected is within the speed standard deviation range of the n coordinate points; and determining whether the coordinate point to be detected is a noise point according to the judgment result.
Optionally, the fourth determining unit is further configured to
And determining the coordinate point with the average speed within the speed prediction range in the n coordinate points as the adjacent coordinate point of the coordinate point to be detected.
Optionally, the n coordinate points are non-noisy points, a time interval between a 1 st coordinate point and an nth coordinate point in the n coordinate points is within a predetermined time interval threshold, and a distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within a predetermined distance threshold.
Optionally, the apparatus further comprises:
a forward moving module, configured to move the prediction window forward if a time interval between a 1 st coordinate point and an nth coordinate point in the n coordinate points is not within a predetermined time interval threshold and/or a distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is not within a predetermined distance threshold, and add the to-be-detected coordinate point into the forward-moved prediction window until the time interval between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within the predetermined time interval threshold, where the distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within the predetermined distance threshold.
Optionally, before acquiring the n coordinate points reported before the coordinate point to be measured, the apparatus further includes:
and determining that the average speed, the acceleration, the angle and the distance of the coordinate point to be measured relative to the previous coordinate point are within a preset range.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
Example 3
Embodiments of the present invention also provide a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:
s1, acquiring n coordinate points reported by the user equipment before the coordinate point to be detected;
s2, determining the n coordinate points as a prediction window;
s3, judging whether the coordinate point to be detected is a noise point according to the average speed of the n coordinate points in the prediction window, the speed standard deviation of the n coordinate points and the speed of the coordinate point to be detected;
and S4, positioning the user equipment in real time according to the judgment result.
Optionally, in this embodiment, the storage medium may include but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Example 4
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, acquiring n coordinate points reported by the user equipment before the coordinate point to be detected;
s2, determining the n coordinate points as a prediction window;
s3, judging whether the coordinate point to be detected is a noise point according to the average speed of the n coordinate points in the prediction window, the speed standard deviation of the n coordinate points and the speed of the coordinate point to be detected;
and S4, positioning the user equipment in real time according to the judgment result.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A real-time location processing method, comprising:
acquiring n coordinate points reported by user equipment before a coordinate point to be detected, wherein n is a natural number greater than 1;
determining the n coordinate points as a prediction window;
judging whether the coordinate point to be detected is a noise point according to the average speed of the n coordinate points in the prediction window, the speed standard deviation of the n coordinate points and the speed of the coordinate point to be detected, and the method comprises the following steps: determining a speed prediction range according to the average speed of the n coordinate points in the prediction window; determining adjacent coordinate points of the coordinate points to be measured in the speed prediction range; judging whether the number of the adjacent coordinate points is greater than a preset threshold value or not; under the condition that the judgment result is negative, determining the coordinate point to be detected as a noise point; if the judgment result is yes, determining the coordinate point to be detected as a suspected noise point; calculating the speed standard deviation of the n coordinate points in the prediction window and the speed of the coordinate point to be measured; judging whether the speed of the coordinate point to be detected is within the speed standard deviation range of the n coordinate points; determining whether the coordinate point to be detected is a noise point according to the judgment result;
and positioning the user equipment in real time according to the judgment result.
2. The method of claim 1, wherein the performing real-time positioning according to the determination result comprises:
filtering the coordinate point to be detected under the condition that the coordinate point to be detected is a noise point as a result of the judgment, and determining a coordinate point which is previous to the coordinate point to be detected as the real-time position of the user equipment;
and determining the coordinate point to be detected as the real-time position of the user equipment under the condition that the judgment result is that the coordinate point to be detected is a non-noise point.
3. The method of claim 2, further comprising:
and adding the coordinate point to be detected into the prediction window under the condition that the judgment result is that the coordinate point to be detected is a non-noise point.
4. The method of claim 1, wherein determining neighboring coordinate points of the coordinate point to be measured within the speed prediction range comprises:
and determining the coordinate point with the average speed within the speed prediction range in the n coordinate points as the adjacent coordinate point of the coordinate point to be detected.
5. The method according to any one of claims 1 to 4,
the n coordinate points are non-noise points, the time interval between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within a preset time interval threshold, and the distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within a preset distance threshold.
6. The method according to any one of claims 1 to 4, further comprising:
if the time interval between the 1 st coordinate point and the nth coordinate point in the n coordinate points is not within the preset time interval threshold and/or the distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is not within the preset distance threshold, moving the prediction window forwards, and adding the to-be-detected coordinate point into the moved prediction window until the time interval between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within the preset time interval threshold, wherein the distance between the 1 st coordinate point and the nth coordinate point in the n coordinate points is within the preset distance threshold.
7. The method according to any one of claims 1 to 4, wherein before the n coordinate points reported before the coordinate point to be measured is obtained, the method further comprises:
and determining that the average speed, the acceleration, the angle and the distance of the coordinate point to be measured relative to the previous coordinate point are within a preset range.
8. A real-time location processing apparatus, comprising:
the acquisition module is used for acquiring n coordinate points reported by user equipment before the coordinate point to be detected, wherein n is a natural number greater than 1;
a determining module, configured to determine the n coordinate points as a prediction window;
a determining module, configured to determine whether the coordinate point to be detected is a noise point according to the average speed of the n coordinate points in the prediction window, the speed standard deviation of the n coordinate points, and the speed of the coordinate point to be detected, including: determining a speed prediction range according to the average speed of the n coordinate points in the prediction window; determining adjacent coordinate points of the coordinate points to be measured in the speed prediction range; judging whether the number of the adjacent coordinate points is greater than a preset threshold value or not; under the condition that the judgment result is negative, determining the coordinate point to be detected as a noise point; if the judgment result is yes, determining the coordinate point to be detected as a suspected noise point; calculating the speed standard deviation of the n coordinate points in the prediction window and the speed of the coordinate point to be measured; judging whether the speed of the coordinate point to be detected is within the speed standard deviation range of the n coordinate points; determining whether the coordinate point to be detected is a noise point according to the judgment result;
and the positioning module is used for positioning the user equipment in real time according to the judgment result.
9. A storage medium, in which a computer program is stored, wherein the computer program is arranged to perform the method of any of claims 1 to 7 when executed.
10. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is arranged to execute the computer program to perform the method of any of claims 1 to 7.
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