CN117935543A - Accident lane positioning system based on Beidou positioning and Internet of things - Google Patents
Accident lane positioning system based on Beidou positioning and Internet of things Download PDFInfo
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- 239000005436 troposphere Substances 0.000 claims abstract description 42
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- 239000005433 ionosphere Substances 0.000 claims abstract description 18
- 238000004458 analytical method Methods 0.000 claims abstract description 4
- 230000008054 signal transmission Effects 0.000 claims abstract description 4
- 230000008569 process Effects 0.000 claims description 20
- 230000008859 change Effects 0.000 claims description 17
- DMBHHRLKUKUOEG-UHFFFAOYSA-N diphenylamine Chemical compound C=1C=CC=CC=1NC1=CC=CC=C1 DMBHHRLKUKUOEG-UHFFFAOYSA-N 0.000 claims description 2
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Abstract
The invention relates to the technical field of accident lane positioning, and particularly discloses an accident lane positioning system based on Beidou positioning and Internet of things, which comprises the following steps: and a signal transmission module: the method comprises the steps of transmitting and receiving a double-frequency satellite signal, and recording the transmitting time and the receiving time; and a signal processing module: acquiring the duration between the sending time and the receiving time, and recording the duration as the actual propagation time; acquiring the position coordinates of an accident vehicle, and acquiring the average density of a troposphere of the position coordinates of the current day; obtaining the refractive index of the troposphere corresponding to the position coordinate according to the relation between the troposphere density and the refractive index; obtaining the delay amount of the satellite signals in ionosphere propagation according to the frequencies of two satellite signals in the double-frequency satellite signals; obtaining a propagation time of the satellite signal; and a signal analysis module: and setting a propagation time difference threshold range, comparing the propagation time with a standard propagation time length, and determining whether the accident vehicle is in an overhead road section or not according to a comparison result and the propagation time difference threshold range.
Description
Technical Field
The invention relates to the technical field of accident lane positioning, in particular to an accident lane positioning system based on Beidou positioning and the Internet of things.
Background
Accident lane positioning refers to determining the specific position and lane of an accident when a traffic accident occurs. The system is beneficial to rescue workers to arrive at the scene quickly, the accidents are handled in time, and further casualties and property loss are reduced. In addition, with the development of technology, modern lane navigation technologies have been able to provide drivers with more accurate and safe services.
An accident lane positioning system based on Beidou positioning and the Internet of things is an innovative solution combining a high-precision positioning technology of a Beidou satellite navigation system with an Internet of things technology. The system not only utilizes the front edge technologies such as the Internet of things, the Beidou high-precision positioning technology, the artificial intelligence technology, the blockchain technology, the visual identification, the big data calculation and the like to collect multi-dimensional information, but also combines the Internet and the artificial intelligence technology to provide higher information transmission efficiency and precision.
In the prior art, the accident lane is usually positioned by positioning the position of the accident vehicle, so that the accident lane is positioned, and the situation of positioning overlapping can occur on an overhead road by the method, so that whether the accident lane is positioned on an overhead road section or not cannot be accurately positioned.
Disclosure of Invention
The invention aims to provide an accident lane positioning system based on Beidou positioning and the Internet of things, which solves the technical problems.
The aim of the invention can be achieved by the following technical scheme:
accident lane positioning system based on big dipper location and thing networking, including following module:
and a signal transmission module:
The device comprises a transmitting end and a receiving end; the method comprises the steps of transmitting and receiving a double-frequency satellite signal, and recording the transmitting time and the receiving time; the double-frequency satellite signal consists of two satellite signals with frequencies f 1 and f 2 respectively;
and a signal processing module:
Acquiring the duration between the sending time and the receiving time, and marking the duration as the actual propagation time T 0; acquiring the position coordinates of an accident vehicle, and acquiring the average density of a troposphere of the position coordinates of the current day; obtaining the refractive index n of the troposphere corresponding to the position coordinate according to the relation between the troposphere density and the refractive index;
Obtaining the delay T 1 of the satellite signal in ionosphere propagation according to the frequencies of two satellite signals in the double-frequency satellite signal, wherein
Wherein, P 1 is the carrier phase observation of the satellite signal with frequency f 1, and P 2 is the carrier phase observation of the satellite signal with frequency f 2;
Acquiring the propagation velocity v of the satellite signal in a vacuum state, and obtaining the propagation velocity of the satellite signal at the troposphere at the moment according to the refractive index n as follows Obtaining the propagation time T of the satellite signal, wherein
Wherein L represents the distance from the transmitting end to the top end of the troposphere;
And a signal analysis module:
Acquiring vacuum propagation time required by satellite signals to propagate from the ground to the satellite, and recording the vacuum propagation time as standard propagation time;
Setting a propagation time difference threshold range, comparing the propagation time with a standard propagation time length, and determining whether the accident vehicle is in an overhead road section or not according to a comparison result and the propagation time difference threshold range; and acquiring the position of the accident lane, generating a navigation route, and sending the navigation route to the rescue department.
As a further scheme of the invention: the working frequency of the satellite signal is selected to be (1000 MHz,2 GHz).
As a further scheme of the invention: the tropospheric average density acquisition process comprises:
Acquiring initial air pressure at the current day position coordinates, acquiring air pressure at each height node according to an air pressure change relation, and obtaining average air pressure p in the convection layer;
Acquiring the temperature of the current day position coordinate as an initial temperature, and acquiring the average temperature t at each altitude node according to a temperature change relation;
Deriving a tropospheric average density ρ, wherein Where R is the gas constant, r= 8.314J/(mol·k).
As a further scheme of the invention: the obtaining process of the air pressure change relation and the temperature change relation comprises the following steps:
Taking the air pressure and the temperature on the ground as initial air pressure and initial temperature;
And selecting a plurality of height nodes at the same position, acquiring air pressure variation and temperature variation of each height node compared with the initial air pressure and the initial temperature, and respectively acquiring an air pressure variation relation expression representing air pressure variation along with the height and a temperature variation relation expression representing temperature variation along with the height after fitting.
As a further scheme of the invention: the process for obtaining the relation between the tropospheric density and the refractive index comprises the following steps:
and selecting a plurality of density nodes, simulating the refractive index of satellite signals in the troposphere under each density node in a CFD model, and fitting to obtain a relational expression of the troposphere density and the refractive index.
As a further scheme of the invention: the setting process of the propagation time difference threshold range comprises the following steps:
obtaining the average height h of an overhead road section in a city from the ground, and obtaining the propagation speed v of a satellite signal in a vacuum state to obtain the vacuum propagation time T' of the satellite signal from the overhead road section to the ground, wherein
An error threshold range (-epsilon, epsilon) is set, wherein epsilon > 0, and the propagation time difference threshold range is (2T '-epsilon, 2T' +epsilon).
As a further scheme of the invention: the process according to the comparison result and the propagation time difference threshold range comprises the following steps:
the propagation time is differenced with the standard propagation time length, and the absolute value of the difference value is obtained;
When the absolute value of the difference value belongs to the error threshold value range, the accident vehicle is not positioned on the overhead road section;
When the absolute value of the difference value belongs to the propagation time difference threshold value range, the accident vehicle is in an overhead road section.
As a further scheme of the invention: the process of transmitting and receiving the dual-frequency satellite signal further comprises:
if the transmitting end has an included angle theta with the ground vertical line, the distance from the transmitting end to the top end of the troposphere at the moment
The invention has the beneficial effects that:
The system compares the propagation time with the standard propagation time by acquiring the propagation time of the satellite signal between the accident vehicle and the satellite, and determines whether the accident vehicle is in an overhead road section according to the comparison result and the propagation time difference threshold range; the method solves the problem that positioning overlap occurs when the accident vehicle is positioned on an overhead road section, so that the accident lane positioning is more accurate.
In addition, the system eliminates the influence of air pressure and temperature in the process of judging the vehicle position through the satellite signal propagation time length; it is understood that satellite signals are affected by refraction of the troposphere and the ionosphere during the propagation of satellite signals in the atmosphere, resulting in delays in the satellite signals; for the convection layer, the average density in the convection layer is different due to the difference of air pressure and temperature in the convection layer, and the refractive index is different; obtaining the refractive index of the troposphere at the position coordinate of the accident day by determining the average density of the troposphere at the position coordinate of the accident day; for the ionosphere, obtaining the delay amount of the ionosphere to the generation of satellite signals through the double-frequency observation value; further, according to the refractive index of the troposphere and the delay amount of the ionosphere, the propagation duration of the satellite signal in vacuum is obtained; the method eliminates errors possibly occurring in the troposphere and the ionosphere when the satellite signals in the atmosphere are transmitted, so that the judgment result is more accurate.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic flow diagram of an information processing module in an accident lane positioning system based on Beidou positioning and internet of things.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention discloses an accident lane positioning system based on Beidou positioning and the internet of things, which comprises the following modules:
and a signal transmission module:
The device comprises a transmitting end and a receiving end; the method comprises the steps of transmitting and receiving a double-frequency satellite signal, and recording the transmitting time and the receiving time; the double-frequency satellite signal consists of two satellite signals with frequencies f 1 and f 2 respectively;
The working frequency of the satellite signal is selected in the range of (1000 MHz,2 GHz);
It should be further noted that the signal frequency selection of the global positioning system is determined according to specific requirements and conditions; first, the frequency cannot exceed 2GHZ, since a signal above this frequency requires a beam antenna to receive, which can cause the antenna to become large in size and may be obscured by rain, fog, leaves, etc.; second, the ionosphere has a significant impact on the frequency range below 1,000mhz and frequencies above 10GH, and therefore these two ranges are not ideal choices; determining that the selected range of the working frequency of the satellite signal is (1000 MHz,2 GHz);
and a signal processing module:
Acquiring the duration between the sending time and the receiving time, and marking the duration as the actual propagation time T 0; acquiring the position coordinates of an accident vehicle, and acquiring the average density of a troposphere of the position coordinates of the current day; obtaining the refractive index n of the troposphere corresponding to the position coordinate according to the relation between the troposphere density and the refractive index;
The process for obtaining the relation between the tropospheric density and the refractive index comprises the following steps:
Selecting a plurality of density nodes, simulating the refractive index of satellite signals in a troposphere under each density node in a CFD model, and fitting to obtain a relational expression of the troposphere density and the refractive index;
It should be further noted that the density of the simulated troposphere may use computational fluid dynamics models, i.e., CFD models, which simulate forced and natural convection, as well as internal or external flow; when the model is used, firstly, basic parameters of the model, such as a Transient model is selected, and gravity is opened; then the physical properties of the material can be modified, and the density is set to be ideal incompressible gas; afterwards, the accuracy of the solution can be verified by adjusting the refinement degree of the grid; if the solution does not change within an acceptable range, then the simulation is considered to be convergent; in CFD models, the change in density can be simulated by a transient model;
the tropospheric average density acquisition process comprises:
Acquiring initial air pressure at the current day position coordinates, acquiring air pressure at each height node according to an air pressure change relation, and obtaining average air pressure p in the convection layer;
Acquiring the temperature of the current day position coordinate as an initial temperature, and acquiring the average temperature t at each altitude node according to a temperature change relation;
the obtaining process of the air pressure change relation and the temperature change relation comprises the following steps:
Taking the air pressure and the temperature on the ground as initial air pressure and initial temperature;
Selecting a plurality of height nodes at the same position, acquiring air pressure variation and temperature variation of each height node compared with initial air pressure and initial temperature, and respectively acquiring an air pressure variation relation expression representing air pressure variation along with height variation and a temperature variation relation expression representing temperature variation along with height variation after fitting;
Deriving a tropospheric average density ρ, wherein Wherein R is a gas constant, r= 8.314J/(mol·k);
it will be appreciated that the density of the troposphere is indeed affected by the air pressure and temperature; as the height increases, the atmospheric pressure will gradually decrease and the temperature will also change; in the vicinity of the earth's surface, the atmospheric temperature is generally relatively high due to solar radiation and the heating action of the earth's surface; however, as the height increases, the temperature gradually decreases; so in the troposphere, the air temperature decreases with increasing altitude; and then the average air pressure and average temperature in the troposphere are obtained according to the air pressure change relation and the temperature change relation, and the air density calculation formula is used Obtaining the average density of the troposphere;
Obtaining the delay T 1 of the satellite signal in ionosphere propagation according to the frequencies of two satellite signals in the double-frequency satellite signal, wherein
Wherein, P 1 is the carrier phase observation of the satellite signal with frequency f 1, and P 2 is the carrier phase observation of the satellite signal with frequency f 2;
It should be further noted that, the formula of eliminating ionospheric delay by using the dual-frequency observation value is a formula for reducing satellite signal propagation delay caused by the ionosphere; the formula is based on a double-frequency observation value, calculates ionosphere delay amount by utilizing the phase difference of two different frequencies of an observation signal, and subtracts the ionosphere delay amount from a received signal, so that a more accurate satellite positioning result is obtained; furthermore, in the calculation of ionospheric delay amount by a dual-frequency observation value, carrier-phase observations are known; specifically, the dual-frequency observation value utilizes the combination of observation values with different frequencies to correct the ionospheric delay, the satellite transmits two frequencies, the electromagnetic waves with the two frequencies can be considered to propagate on the same path, and if the time difference of the signals with the two frequencies reaching a receiver is accurately determined, the ionospheric delay received by the two signals can be reversely deduced; so in this process, the carrier phase observations are involved as known data;
Acquiring the propagation velocity v of the satellite signal in a vacuum state, and obtaining the propagation velocity of the satellite signal at the troposphere at the moment according to the refractive index n as follows Obtaining the propagation time T of the satellite signal, wherein
Wherein L represents the distance from the transmitting end to the top end of the troposphere;
It is understood that satellite signals are affected by refraction of the troposphere and the ionosphere during the propagation of satellite signals in the atmosphere, resulting in delays in the satellite signals; for the convection layer, the average density in the convection layer is different due to the difference of air pressure and temperature in the convection layer, and the refractive index is different; obtaining the refractive index of the troposphere at the position coordinate of the accident day by determining the average density of the troposphere at the position coordinate of the accident day; for the ionosphere, obtaining the delay amount of the ionosphere to the generation of satellite signals through the double-frequency observation value; further, according to the refractive index of the troposphere and the delay amount of the ionosphere, the propagation duration of the satellite signal in vacuum is obtained; the method eliminates errors possibly occurring in the troposphere and the ionosphere when the satellite signals in the atmosphere are transmitted, so that the judgment result is more accurate;
the process of transmitting and receiving the dual-frequency satellite signal further comprises:
if the transmitting end has an included angle theta with the ground vertical line, the distance from the transmitting end to the top end of the troposphere at the moment
And a signal analysis module:
Acquiring vacuum propagation time required by satellite signals to propagate from the ground to the satellite, and recording the vacuum propagation time as standard propagation time;
Setting a propagation time difference threshold range, comparing the propagation time with a standard propagation time length, and determining whether the accident vehicle is in an overhead road section or not according to a comparison result and the propagation time difference threshold range; acquiring the position of an accident lane, generating a navigation route, and sending the navigation route to a rescue department;
the setting process of the propagation time difference threshold range comprises the following steps:
obtaining the average height h of an overhead road section in a city from the ground, and obtaining the propagation speed v of a satellite signal in a vacuum state to obtain the vacuum propagation time T' of the satellite signal from the overhead road section to the ground, wherein
Setting an error threshold range (-epsilon, epsilon), wherein epsilon > 0, and the propagation time difference threshold range is (2T '-epsilon, 2T' +epsilon);
the process according to the comparison result and the propagation time difference threshold range comprises the following steps:
the propagation time is differenced with the standard propagation time length, and the absolute value of the difference value is obtained;
When the absolute value of the difference value belongs to the error threshold value range, the accident vehicle is not positioned on the overhead road section;
When the absolute value of the difference value belongs to the propagation time difference threshold value range, the accident vehicle is positioned on an overhead road section;
It can be understood that by acquiring the propagation time length of the satellite signal between the accident vehicle and the satellite, comparing the propagation time with the standard propagation time length, and determining whether the accident vehicle is on an overhead road section according to the comparison result and the propagation time difference threshold range; the method solves the problem that positioning overlap occurs when the accident vehicle is positioned on an overhead road section, so that the accident lane positioning is more accurate.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (8)
1. Accident lane positioning system based on big dipper location and thing networking, its characterized in that includes following module:
and a signal transmission module:
The device comprises a transmitting end and a receiving end; the method comprises the steps of transmitting and receiving a double-frequency satellite signal, and recording the transmitting time and the receiving time; the double-frequency satellite signal consists of two satellite signals with the frequencies of f1 and f1 respectively;
and a signal processing module:
Acquiring the duration between the sending time and the receiving time, and marking the duration as the actual propagation time T 0; acquiring the position coordinates of an accident vehicle, and acquiring the average density of a troposphere of the position coordinates of the current day; obtaining the refractive index n of the troposphere corresponding to the position coordinate according to the relation between the troposphere density and the refractive index;
Obtaining the delay T 1 of the satellite signal in ionosphere propagation according to the frequencies of two satellite signals in the double-frequency satellite signal, wherein
Wherein, P 1 is the carrier phase observation of the satellite signal with frequency f 1, and P 2 is the carrier phase observation of the satellite signal with frequency f 2;
Acquiring the propagation velocity v of the satellite signal in a vacuum state, and obtaining the propagation velocity of the satellite signal at the troposphere at the moment according to the refractive index n as follows Obtaining the propagation time T of the satellite signal, wherein
Wherein L represents the distance from the transmitting end to the top end of the troposphere;
And a signal analysis module:
Acquiring vacuum propagation time required by satellite signals to propagate from the ground to the satellite, and recording the vacuum propagation time as standard propagation time;
Setting a propagation time difference threshold range, comparing the propagation time with a standard propagation time length, and determining whether the accident vehicle is in an overhead road section or not according to a comparison result and the propagation time difference threshold range; and acquiring the position of the accident lane, generating a navigation route, and sending the navigation route to the rescue department.
2. The accident lane positioning system based on Beidou positioning and Internet of things according to claim 1, wherein the working frequency of the satellite signals is selected in the range of (1000 MHz,2 GHz).
3. The accident lane positioning system based on Beidou positioning and internet of things according to claim 1, wherein the tropospheric average density acquisition process comprises:
Acquiring initial air pressure at the current day position coordinates, acquiring air pressure at each height node according to an air pressure change relation, and obtaining average air pressure p in the convection layer;
Acquiring the temperature of the current day position coordinate as an initial temperature, and acquiring the average temperature t at each altitude node according to a temperature change relation;
Deriving a tropospheric average density p, wherein Where R is the gas constant, r= 8.314J/(mol·k).
4. The accident lane positioning system based on Beidou positioning and internet of things according to claim 3, wherein the obtaining process of the air pressure change relation and the temperature change relation comprises:
Taking the air pressure and the temperature on the ground as initial air pressure and initial temperature;
And selecting a plurality of height nodes at the same position, acquiring air pressure variation and temperature variation of each height node compared with the initial air pressure and the initial temperature, and respectively acquiring an air pressure variation relation expression representing air pressure variation along with the height and a temperature variation relation expression representing temperature variation along with the height after fitting.
5. The accident lane positioning system based on Beidou positioning and internet of things according to claim 1, wherein the process for obtaining the relational expression of the tropospheric density and the refractive index comprises:
and selecting a plurality of density nodes, simulating the refractive index of satellite signals in the troposphere under each density node in a CFD model, and fitting to obtain a relational expression of the troposphere density and the refractive index.
6. The accident lane positioning system based on Beidou positioning and internet of things according to claim 1, wherein the setting process of the propagation time difference threshold range comprises:
obtaining the average height h of an overhead road section in a city from the ground, and obtaining the propagation speed v of a satellite signal in a vacuum state to obtain the vacuum propagation time T' of the satellite signal from the overhead road section to the ground, wherein
An error threshold range (-epsilon, epsilon) is set, wherein epsilon > 0, and the propagation time difference threshold range is (2T '-epsilon, 2T' +epsilon).
7. The accident lane positioning system based on Beidou positioning and internet of things according to claim 6, wherein the process according to the comparison result and the propagation time difference threshold range comprises:
the propagation time is differenced with the standard propagation time length, and the absolute value of the difference value is obtained;
When the absolute value of the difference value belongs to the error threshold value range, the accident vehicle is not positioned on the overhead road section;
When the absolute value of the difference value belongs to the propagation time difference threshold value range, the accident vehicle is in an overhead road section.
8. The accident lane positioning system based on Beidou positioning and internet of things according to claim 1, wherein the process of transmitting and receiving the dual-frequency satellite signals further comprises:
if the transmitting end and the ground vertical line form an included angle, the distance from the transmitting end to the top end of the troposphere at the moment
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