CN111880156B - Road dough fog detection method, system and radar - Google Patents
Road dough fog detection method, system and radar Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/411—Identification of targets based on measurements of radar reflectivity
- G01S7/412—Identification of targets based on measurements of radar reflectivity based on a comparison between measured values and known or stored values
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/95—Radar or analogous systems specially adapted for specific applications for meteorological use
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Abstract
The embodiment of the application provides a detection method and a system for road surface mist and a radar, wherein the detection method for the road surface mist comprises the following steps: irradiating a radar target by emitting electromagnetic waves; receiving an echo signal reflected by the radar target; and determining whether the signal-to-noise ratio value of the echo signal is in a first preset signal-to-noise ratio value range, and if the signal-to-noise ratio value of the echo signal is in the first preset signal-to-noise ratio value range, determining that the road surface has the fog. The method provided by the embodiment can accurately and effectively detect whether the fog exists on the road surface, and then the fog early warning can be timely carried out.
Description
Technical Field
The embodiment of the application relates to the technical field of radars, in particular to a detection method and system for road surface mist and a radar.
Background
The influence of the heavy fog weather on transportation is large, and how to better cope with the heavy fog weather is a key and difficult problem which needs to be faced in transportation construction and development. The mist is formed by cooling air close to a road surface by radiation cooling of the ground, and often appears in a local range from tens of meters to hundreds of meters in the large mist, and has the characteristics of more dense mist, lower visibility, stronger burst property and the like. Then how to monitor the mist in a large scale to make the driving safety induction device fully play a role is a problem to be solved.
For monitoring the mist, at present, instruments and equipment such as an atmosphere transmission instrument and a visibility meter exist, and the equipment has the defect of short monitoring distance, so that only the visibility condition of a monitoring point can be obtained. In addition, a camera and a point type visibility meter are generally adopted, wherein the camera can only observe a next video picture under a certain view field, and the position of the fog clusters cannot be known. The point type visibility meter can only measure the visibility of a certain point, so that the point is approximate, and the fog cannot be measured. Especially in case of uneven fog, local rain or snow storm, the readings of the camera and the point visibility meter are very prone to deviation and misleading.
Therefore, the prior art cannot accurately and effectively detect whether the fog exists on the road surface, so that the fog early warning cannot be timely carried out.
Disclosure of Invention
The embodiment of the application provides a detection method, a detection system and a radar for road surface fog, which are used for solving the problem that the prior art cannot accurately and effectively detect whether the fog exists on the road surface, so that the fog early warning cannot be timely carried out.
In a first aspect, an embodiment of the present application provides a method for detecting a road surface mist, including:
irradiating a radar target by emitting electromagnetic waves;
Receiving an echo signal reflected by the radar target;
and determining whether the signal-to-noise ratio value of the echo signal is in a first preset signal-to-noise ratio value range, and if the signal-to-noise ratio value of the echo signal is in the first preset signal-to-noise ratio value range, determining that the road surface has the fog.
In one possible design, the maximum value in the first predetermined signal-to-noise ratio value range is lower than or equal to a predetermined normal signal-to-noise ratio value;
before said determining whether the signal-to-noise ratio value of the echo signal is within a first predetermined signal-to-noise ratio value range, the method further comprises:
When the pavement is dry, averaging the signal-to-noise ratio value in the second echo signal sample received after the radar target is scanned to obtain a preset normal signal-to-noise ratio value;
in a preset group fog scene, determining a first preset signal-to-noise ratio value range from a first echo signal sample received after the radar target is scanned and a preset normal signal-to-noise ratio value;
The preset group fog scene is used for representing a scene that the radar and the radar target have group fog on a preset field.
In one possible design, the determining the first preset signal-to-noise ratio value range from the first echo signal sample received after scanning the radar target and the preset normal signal-to-noise ratio value includes:
searching a maximum value lower than the preset normal signal-to-noise value from the signal-to-noise value extracted from the first echo signal sample;
Taking the maximum value lower than the preset normal signal-to-noise value in the signal-to-noise values extracted from the first echo signal sample as a maximum limit value;
and forming the first preset signal-to-noise ratio value range according to the minimum value and the maximum limit value of the extracted signal-to-noise ratio value.
In one possible design, the receiving the echo signal reflected by the radar target includes:
And receiving a plurality of echo signals reflected by the radar target in a preset time period.
In one possible design, the determining whether the signal-to-noise ratio value of the echo signal is within a first preset signal-to-noise ratio value range, and if the signal-to-noise ratio value of the echo signal is within the first preset signal-to-noise ratio value range, determining that the road surface has the fog cluster includes:
determining a first proportion of the signal-to-noise ratio value of each echo signal in a first preset signal-to-noise ratio value range, and if the first proportion is larger than the preset proportion, determining that the road surface has the fog.
In one possible design, after the receiving the echo signal reflected by the radar target, the method further includes:
Determining whether the signal-to-noise ratio value of the echo signal is in a second preset signal-to-noise ratio value range, a third preset signal-to-noise ratio value range or a fourth preset signal-to-noise ratio value range;
If the signal-to-noise ratio value of the echo signal is in a second preset signal-to-noise ratio value range, determining that the road surface is in a preset small rain state;
if the signal-to-noise ratio value of the echo signal is in a third preset signal-to-noise ratio value range, determining that the road surface is in a preset middle rain state;
if the signal-to-noise ratio value of the echo signal is in a fourth preset signal-to-noise ratio value range, determining that the road surface is in a preset heavy rain state;
The maximum value of the signal-to-noise ratio value in the second preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the first preset signal-to-noise ratio value range, and the maximum value of the signal-to-noise ratio value in the third preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the second preset signal-to-noise ratio value range; and the maximum value of the signal-to-noise ratio value in the fourth preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the third preset signal-to-noise ratio value range.
In one possible design, the second preset signal-to-noise value range is determined from a third echo signal sample received after scanning the radar target in a preset rain-light scene, the preset rain-light scene being used for representing a scene in a preset rain-light state on a preset field;
The third preset signal-to-noise ratio value range is determined from a fourth echo signal sample received after the radar target is scanned in a preset rainy scene, wherein the preset rainy scene is used for representing a scene in a middle preset rainy state on a preset field;
the fourth preset signal-to-noise ratio value range is determined from a fifth echo signal sample received after the radar target is scanned in a preset heavy rain scene, and the preset heavy rain scene is used for representing a scene in a preset heavy rain state on a preset field.
In one possible design, the radar target is a corner reflector.
In a second aspect, embodiments of the present application provide a radar for performing the method as described in the first aspect and the various possible designs of the first aspect.
In a third aspect, an embodiment of the present application provides a detection system for road surface fog, including the radar and the radar target according to the second aspect; the radar and the radar target are respectively arranged at two sides of the road surface and are higher than the position of the preset distance of the road surface, and the radar target are oppositely arranged.
According to the method, the system and the radar for detecting the road surface fog, firstly, the radar target is irradiated by the emitted electromagnetic wave, so that the radar target reflects or refracts the electromagnetic wave to generate the echo signal with strong signals, and as the concentration of the fog is larger, the signal-to-noise ratio of the echo signal of the radar is smaller, whether the fog exists on the road surface or the road section can be determined by judging whether the signal-to-noise ratio in the echo signal is in the first preset signal-to-noise ratio range, if the signal-to-noise ratio of the echo signal is in the first preset signal-to-noise ratio range, the existence of the fog on the road surface or the road section is indicated, and therefore whether the fog exists on the road section or not is judged according to the range of the signal-to-noise ratio of the echo signal of the radar, the problem that whether the fog exists on the road surface cannot be accurately and effectively detected in the prior art is solved, and then the early warning of the fog can be timely carried out.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions of the prior art, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it will be obvious that the drawings in the following description are some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a schematic diagram of a system for detecting road surface mist according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a method for detecting road surface mist according to an embodiment of the present application;
FIG. 3 is a flow chart of a method for detecting road surface mist according to another embodiment of the present application;
fig. 4 is a flow chart of a method for detecting road surface mist according to another embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented, for example, in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In the prior art, for monitoring of the fog clusters, at present, instruments and equipment such as an atmosphere transmission instrument and a visibility meter exist, and the equipment has the defect of short monitoring distance, and only the visibility condition of a monitoring point can be obtained, so that whether the fog clusters exist on a road surface cannot be accurately and effectively detected in the prior art, and the fog clusters cannot be early warned in time.
In order to solve the problems, the technical idea of the application is as follows: due to the fact that attenuation coefficients of electromagnetic waves of the radar, which propagate in the atmosphere, are different under the influence of different weather, the intensity of echo signals of the electromagnetic waves can be changed correspondingly, and weather conditions of a current road section, such as dryness or non-dryness, can be distinguished. The method comprises the steps of detecting whether the road section has the cluster fog or not, and judging whether the road section has the cluster fog or not according to the cluster fog, wherein the occurrence of the cluster fog can increase the attenuation coefficient of electromagnetic waves, the angle anti-return wave signal of a radar is obviously weakened compared with the dry weather, and the larger the cluster fog concentration is, the smaller the signal-to-noise value of the radar return wave signal is, so that the existence of the cluster fog on the road section can be accurately and effectively detected, and further, the cluster fog early warning can be timely carried out.
The technical scheme of the application is described in detail below by specific examples. The following embodiments may be combined with each other, and some embodiments may not be repeated for the same or similar concepts or processes.
Fig. 1 is a schematic structural diagram of a system for detecting road surface mist according to an embodiment of the present application. Referring to fig. 1, the detection system for the road surface mist comprises: radar 10 and radar target 20; the radar is provided with a road surface fog detection function, the radar target can be a corner reflector or a radar reflector, after the radar electromagnetic wave scans corner reflection, the electromagnetic wave can generate refraction amplification on a metal corner, a strong echo signal is generated, and the strong echo target appears on a screen of the radar.
The radar and the radar target are respectively arranged at two sides of the road surface and are higher than the position of the preset distance of the road surface, and the radar target are oppositely arranged. In practical applications, a radar is generally required to face a radar target (such as a corner reflector), and the radar and the corner reflector are installed at both sides of a road surface at a position higher than the ground by a predetermined distance (such as a height of 7-10 meters). In the process of detecting the fog, the radar irradiates the corner reflector by emitting electromagnetic waves, and the corner reflector reflects the electromagnetic waves to generate echo signals. Specifically, the radar transmitter directs electromagnetic wave energy through an antenna in a direction in space, where an object (i.e., a radar target such as a corner reflector) reflects the impinging electromagnetic wave, and the radar antenna receives the reflected wave and then processes it. The treatment process comprises the following steps: and the radar receives and analyzes the echo signal reflected by the radar target, judges whether the signal-to-noise ratio value of the echo signal is in a first preset signal-to-noise ratio value range, and determines that the road surface has the fog cluster if the signal-to-noise ratio value of the echo signal is in the first preset signal-to-noise ratio value range. Therefore, by the radar function, that is, the group fog detection function provided in the radar, it is possible to accurately detect whether or not the current road section is dry or a group fog exists.
Specifically, referring to fig. 2 for how to implement road-dough fog detection, fig. 2 is a schematic flow chart of a road-dough fog detection method according to an embodiment of the present application. The detection method of the road surface mist can comprise the following steps:
s201, irradiating a radar target by emitting electromagnetic waves.
In this embodiment, the execution subject of the method may be a radar. The transmitter of the radar emits electromagnetic waves through an antenna onto a radar target, which may be a corner reflector. Since the detection of the mist by the radar is applied in the air of a height of about 10m, there is no target in the vicinity, and the radar must have a target, a corner reflector is provided so as to reflect a signal of an electromagnetic wave as a target of the radar.
S202, receiving echo signals reflected by the radar target.
In this embodiment, the electromagnetic wave may generate refraction amplification on the metal angle in the corner reflector, generate a strong echo signal, and may generate a strong echo target on the screen of the radar. After the antenna of the radar receives the echo signals, the intensity of electromagnetic echo changes correspondingly based on different attenuation coefficients of electromagnetic wave propagation in the atmosphere under the influence of different weather, so that the principle of distinguishing the weather conditions of the current road section is utilized to analyze the echo signals.
S203, determining whether the signal-to-noise ratio value of the echo signal is in a first preset signal-to-noise ratio value range, and if the signal-to-noise ratio value of the echo signal is in the first preset signal-to-noise ratio value range, determining that the road surface has the fog. In practical application, due to the occurrence of the cluster fog, the attenuation coefficient of electromagnetic waves can be increased, echo signals reflected by a corner reflector of the radar are obviously weakened compared with the dry weather, the larger the cluster fog concentration is, the smaller the signal-to-noise ratio value of the radar echo is, and therefore whether the cluster fog exists on the road surface can be judged through the signal-to-noise ratio value of the echo signals.
Specifically, in the state of the cluster mist, the signal-to-noise ratio of the echo signal is lower than that of the echo signal in the normal dry state, so that the range of the signal-to-noise ratio in the state of the cluster mist can be determined through experiments. The first preset signal-to-noise ratio value range is a range where the signal-to-noise ratio value in the cluster fog state is located, so that if the signal-to-noise ratio value of the echo signal is lower than a preset normal signal-to-noise ratio value, the possibility of the cluster fog exists, and if the signal-to-noise ratio value of the echo signal is in the first preset signal-to-noise ratio value range, the existence of the cluster fog on the road surface is determined.
According to the road surface fog detection method, the radar target is irradiated by the emitted electromagnetic waves, so that the radar target reflects or refracts the electromagnetic waves to generate the echo signals with strong signals, and as the concentration of the fog is larger, the signal-to-noise ratio value of the echo signals of the radar is smaller, whether the fog exists on the road surface or the road section can be determined by judging whether the signal-to-noise ratio value in the echo signals is in the first preset signal-to-noise ratio value range, if the signal-to-noise ratio value of the echo signals is in the first preset signal-to-noise ratio value range, the existence of the fog exists on the road surface or the road section is indicated, and therefore whether the fog exists on the road section is judged through the range of the signal-to-noise ratio value of the echo signals of the radar, the problem that whether the fog exists on the road surface cannot be accurately and effectively detected in the prior art is solved, and the fog early warning can be timely carried out.
In one possible design, referring to fig. 3, fig. 3 is a flow chart of a method for detecting a road surface according to another embodiment of the present application. The present embodiment describes in detail how to determine the first preset signal-to-noise ratio value range based on the above embodiment, for example, the embodiment described in fig. 2. Wherein, the maximum value in the first preset signal-to-noise ratio value range is lower than a preset normal signal-to-noise ratio value; before said determining whether the signal-to-noise ratio value of the echo signal is within a first predetermined signal-to-noise ratio value range, the method may further comprise the steps of:
And S301, when the road surface is dry, averaging the signal-to-noise ratio value in the second echo signal sample received after the radar target is scanned, and obtaining a preset normal signal-to-noise ratio value.
S302, in a preset group fog scene, a first preset signal-to-noise ratio value range is determined from a first echo signal sample received after the radar target is scanned and a preset normal signal-to-noise ratio value.
The preset group fog scene is used for representing a scene that the radar and the radar target have group fog on a preset field.
In practical application, a road dough fog detection system is built on an open ground, namely, a radar and a corner reflector are arranged on two opposite sides, the height is between 7 meters and 10 meters, under the condition of dry weather, a plurality of echo signals of electromagnetic waves of the radar reflected by the corner reflector are continuously or indirectly collected, a signal-to-noise ratio value is extracted from each echo signal, then an average value is taken, and the average value is taken as a preset normal signal-to-noise ratio value. And then, continuously or indirectly collecting a plurality of echo signals of the electromagnetic wave of the radar reflected by the corner reflector through artificial manufacturing of the cluster fog, extracting a signal-to-noise ratio value from each echo signal, and determining a first preset signal-to-noise ratio value range in a preset cluster fog scene according to each signal-to-noise ratio value and a preset normal signal-to-noise ratio value. The preset group fog scene here is a scene where the radar and the radar target have group fog on a preset field.
In one possible design, how to determine the first preset signal-to-noise ratio range from the first echo signal sample received after scanning the radar target and the preset normal signal-to-noise ratio value may be shown in fig. 4, fig. 4 is a schematic flow chart of a method for detecting a road surface mist according to another embodiment of the present application, and the embodiment is described in detail in S302 on the basis of the foregoing embodiment. The determining a first preset signal-to-noise ratio value range from a first echo signal sample received after scanning the radar target and a preset normal signal-to-noise ratio value may include:
s401, extracting the minimum value of the signal-to-noise value from a first echo signal sample received after the radar target is scanned.
S402, searching a maximum value lower than the preset normal signal-to-noise value from the signal-to-noise value extracted from the first echo signal sample.
S403, taking the maximum value lower than the preset normal signal-to-noise value in the signal-to-noise value extracted from the first echo signal sample as the maximum limit value.
S404, forming the first preset signal-to-noise ratio value range according to the minimum value and the maximum limit value of the extracted signal-to-noise ratio value.
In this embodiment, the minimum value of the signal-to-noise ratio value and the maximum value lower than the preset normal signal-to-noise ratio value are extracted from the first echo signal sample received after the radar target is scanned, and the maximum value lower than the preset normal signal-to-noise ratio value is taken as the maximum limit value, that is, the maximum limit value is taken as the right end point of the first preset signal-to-noise ratio value range, and the first preset signal-to-noise ratio value range does not include or does not include the right end point. And simultaneously, taking the minimum value of the extracted signal-to-noise ratio value as the left end point of the first preset signal-to-noise ratio value range, wherein the left end is opened or closed without limitation. For example, the minimum value of the extracted snr value is a, and the maximum limit value is b, then the first predetermined snr value range is (a, b) or [ a, b ] or (a, b) or [ a, b ].
In one possible design, this embodiment describes in detail how to determine that there is a fog of road surfaces based on the above embodiments. The method comprises the following specific steps:
And a1, receiving a plurality of echo signals reflected by the radar target in a preset time period.
Step a2, determining a first proportion of the signal-to-noise ratio value of each echo signal in a first preset signal-to-noise ratio value range, and if the first proportion is larger than the preset proportion, determining that the road surface has the fog.
In this embodiment, in order to accurately measure the fog, echo signals within a period of time may be detected, specifically, in a preset period of time, electromagnetic waves are emitted by a radar, a plurality of echo signals reflected by a corner reflector within the preset period of time are received, then whether the signal-to-noise ratio value of each echo signal is within a first preset signal-to-noise ratio value range is determined, the proportion of the signal-to-noise ratio values of all echo signals within the first preset signal-to-noise ratio value range, that is, a first proportion, is counted, and if the first proportion is greater than the preset proportion, it is indicated that the fog exists on the road surface, and accurate and effective measurement of the fog state is achieved.
In one possible design, the method for detecting the road surface mist can also detect the state of light rain, medium rain or heavy rain, and the method for detecting the road surface mist is described in detail on the basis of the embodiment. After the receiving the echo signal reflected by the radar target, the method may further include the steps of:
and b1, determining whether the signal-to-noise ratio value of the echo signal is in a second preset signal-to-noise ratio value range, a third preset signal-to-noise ratio value range or a fourth preset signal-to-noise ratio value range.
And b2, if the signal-to-noise ratio value of the echo signal is in a second preset signal-to-noise ratio value range, determining that the road surface is in a preset small rain state.
And b3, if the signal-to-noise ratio value of the echo signal is in a third preset signal-to-noise ratio value range, determining that the road surface is in a preset middle rain state.
And b4, if the signal-to-noise ratio value of the echo signal is in a fourth preset signal-to-noise ratio value range, determining that the road surface is in a preset heavy rain state.
Wherein the maximum value of the signal-to-noise ratio value in the second preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the first preset signal-to-noise ratio value range, and the maximum value of the signal-to-noise ratio value in the third preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the second preset signal-to-noise ratio value range; and the maximum value of the signal-to-noise ratio value in the fourth preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the third preset signal-to-noise ratio value range.
In practical application, the fog, the light rain, the medium rain and the heavy rain are all noise, the noise can be sequentially increased, and the corresponding signal-to-noise value (the ratio of effective signals to noise) is sequentially decreased. The scene of detecting the group fog can be set to detect whether the road surface is in a light rain state, a medium rain state or a heavy rain state or not.
The preset small rain scene is a scene in a preset small rain state on a preset field, the preset medium rain scene is a scene in a medium preset rain state on the preset field, and the preset big rain scene is a scene in a preset big rain state on the preset field.
Specifically, it is determined that, in a preset small rain scene, when the radar target is in a preset small rain state, the signal-to-noise ratio value range of the echo signal is a second preset signal-to-noise ratio value range, and the second preset signal-to-noise ratio value range is determined from a third echo signal sample received after the radar target is scanned in the preset small rain scene. And determining that the signal-to-noise ratio value range of the echo signal is a third preset signal-to-noise ratio value range when the radar target is in a preset rainy scene, wherein the third preset signal-to-noise ratio value range is determined from a fourth echo signal sample received after the radar target is scanned in the preset rainy scene. And determining that the signal-to-noise ratio value range of the echo signal is a fourth preset signal-to-noise ratio value range when the radar target is in a preset heavy rain scene and is in a preset heavy rain state, wherein the fourth preset signal-to-noise ratio value range is determined from a fifth echo signal sample received after the radar target is scanned in the preset heavy rain scene. Specifically, how to determine the respective corresponding preset signal-to-noise ratio value ranges from the third echo signal sample, the fourth echo signal sample, and the fifth echo signal sample may be similar to the above determination manner of the value range lower than the preset signal-to-noise ratio value range, which is not described herein again.
Therefore, if the signal-to-noise ratio value of the echo signal is within a second preset signal-to-noise ratio value range, determining that the road surface is in a preset small rain state; if the signal-to-noise ratio value of the echo signal is in a third preset signal-to-noise ratio value range, determining that the road surface is in a preset middle rain state; and if the signal-to-noise ratio value of the echo signal is in a fourth preset signal-to-noise ratio value range, determining that the road surface is in a preset heavy rain state.
Because the signal-to-noise ratio values corresponding to the fog, the light rain, the medium rain and the heavy rain become smaller in sequence, the maximum value of the signal-to-noise ratio value in the second preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the first preset signal-to-noise ratio value range, and the maximum value of the signal-to-noise ratio value in the third preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the second preset signal-to-noise ratio value range; and the maximum value of the signal-to-noise ratio value in the fourth preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the third preset signal-to-noise ratio value range.
In one possible design, in order to enable timely early warning, the present embodiment describes the method for detecting the road dough mist in detail based on the above embodiment, for example, the embodiment described in fig. 2. After the determining that the road surface is in the presence of the fog, the method may further include:
And sending information for indicating that the road surface has the fog to a preset terminal so that the preset terminal sends out an early warning signal.
In this embodiment, after detecting that the road surface has the fog, the radar sends information for indicating that the road surface has the fog to related departments, such as highway departments, and the highway departments send the fog warning to ensure the travel safety of pedestrians. Or the information for indicating the state of light rain, medium rain or heavy rain on the road surface can be sent to related departments, and the related departments send out early warning of light rain, medium rain or heavy rain.
According to the application, whether the road section has the cluster fog is judged by the range of the signal-to-noise ratio value of the echo signal of the radar, so that the problem that whether the cluster fog exists on the road surface cannot be accurately and effectively detected in the prior art is solved, and then cluster fog early warning, light rain early warning, medium rain early warning or heavy rain early warning and the like can be timely carried out, and the travel safety of pedestrians is further ensured.
In order to realize the detection method of the road surface fog, the embodiment provides a radar. See radar 10 described in fig. 1. The radar is used for executing the road-dough fog detection method according to the embodiment.
Specifically, the radar is used for irradiating a radar target by transmitting electromagnetic waves, receiving an echo signal reflected by the radar target, determining whether the signal-to-noise ratio value of the echo signal is in a first preset signal-to-noise ratio value range or not through a mass fog detection function, and if the signal-to-noise ratio value of the echo signal is in the first preset signal-to-noise ratio value range, determining that mass fog exists on the road surface.
In this embodiment, the radar irradiates the radar target by emitting electromagnetic waves, so that the radar target reflects or refracts the electromagnetic waves to generate an echo signal with a strong signal, and as the concentration of the cluster fog is larger, the signal-to-noise ratio value of the echo signal of the radar is smaller, whether the cluster fog exists on the road surface or the road section can be determined by judging whether the signal-to-noise ratio value in the echo signal is within a first preset signal-to-noise ratio value range, if the signal-to-noise ratio value of the echo signal is within the first preset signal-to-noise ratio value range, the existence of the cluster fog on the road surface or the road section is indicated, so that the application judges whether the cluster fog exists on the road section through the range of the signal-to-noise ratio value of the echo signal of the radar, solves the problem that whether the cluster fog exists on the road surface cannot be accurately and effectively detected in the prior art, and further can perform cluster fog early warning in time.
The radar provided in this embodiment may be used to implement the technical solution of the foregoing method embodiment, and its implementation principle and technical effects are similar, and this embodiment will not be described here again.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and when a processor executes the computer execution instructions, the detection method of the road surface fog is realized.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, for example, multiple modules may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms. In addition, each functional module in the embodiments of the present application may be integrated in one processing unit, or each module may exist alone physically, or two or more modules may be integrated in one unit. The units formed by the modules can be realized in a form of hardware or a form of hardware and software functional units.
The integrated modules, which are implemented in the form of software functional modules, may be stored in a computer readable storage medium. The software functional module is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (english: processor) to perform some of the steps of the methods according to the embodiments of the application. It should be understood that the above Processor may be a central processing unit (english: central Processing Unit, abbreviated as CPU), or may be other general purpose processors, a digital signal Processor (english: DIGITAL SIGNAL Processor, abbreviated as DSP), an Application-specific integrated Circuit (english: application SPECIFIC INTEGRATED Circuit, abbreviated as ASIC), or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present application may be embodied directly in a hardware processor for execution, or in a combination of hardware and software modules in a processor for execution.
The memory may comprise a high-speed RAM memory, and may further comprise a non-volatile memory NVM, such as at least one magnetic disk memory, and may also be a U-disk, a removable hard disk, a read-only memory, a magnetic disk or optical disk, etc. The bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (PERIPHERAL COMPONENT, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, the buses in the drawings of the present application are not limited to only one bus or to one type of bus. The storage medium may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an Application SPECIFIC INTEGRATED Circuits (ASIC). It is also possible that the processor and the storage medium reside as discrete components in an electronic device or a master device.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application.
Claims (9)
1. A method for detecting a road surface fog, comprising:
irradiating a radar target by emitting electromagnetic waves;
Receiving an echo signal reflected by the radar target;
Determining whether the signal-to-noise ratio value of the echo signal is in a first preset signal-to-noise ratio value range, and if the signal-to-noise ratio value of the echo signal is in the first preset signal-to-noise ratio value range, determining that the road surface has the fog;
the maximum value in the first preset signal-to-noise ratio value range is lower than a preset normal signal-to-noise ratio value;
before said determining whether the signal-to-noise ratio value of the echo signal is within a first predetermined signal-to-noise ratio value range, the method further comprises:
When the pavement is dry, averaging the signal-to-noise ratio value in the second echo signal sample received after the radar target is scanned to obtain a preset normal signal-to-noise ratio value;
in a preset group fog scene, determining a first preset signal-to-noise ratio value range from a first echo signal sample received after the radar target is scanned and a preset normal signal-to-noise ratio value;
The preset group fog scene is used for representing a scene that the radar and the radar target have group fog on a preset field.
2. The method of claim 1, wherein the determining a first predetermined signal-to-noise ratio value range from the first echo signal samples received after scanning the radar target and a predetermined normal signal-to-noise ratio value comprises:
extracting a minimum value of a signal-to-noise value from a first echo signal sample received after the radar target is scanned;
searching a maximum value lower than the preset normal signal-to-noise value from the signal-to-noise value extracted from the first echo signal sample;
Taking the maximum value lower than the preset normal signal-to-noise value in the signal-to-noise values extracted from the first echo signal sample as a maximum limit value;
and forming the first preset signal-to-noise ratio value range according to the minimum value and the maximum limit value of the extracted signal-to-noise ratio value.
3. The method according to claim 1 or 2, wherein said receiving echo signals reflected by said radar target comprises:
And receiving a plurality of echo signals reflected by the radar target in a preset time period.
4. A method according to claim 3, wherein said determining whether the signal-to-noise ratio value of the echo signal is within a first predetermined signal-to-noise ratio value range, and if the signal-to-noise ratio value of the echo signal is within the first predetermined signal-to-noise ratio value range, determining that the road surface is in a fog cluster comprises:
determining a first proportion of the signal-to-noise ratio value of each echo signal in a first preset signal-to-noise ratio value range, and if the first proportion is larger than the preset proportion, determining that the road surface has the fog.
5. The method of claim 1, wherein after said receiving the echo signal reflected by the radar target, the method further comprises:
Determining whether the signal-to-noise ratio value of the echo signal is in a second preset signal-to-noise ratio value range, a third preset signal-to-noise ratio value range or a fourth preset signal-to-noise ratio value range;
If the signal-to-noise ratio value of the echo signal is in a second preset signal-to-noise ratio value range, determining that the road surface is in a preset small rain state;
if the signal-to-noise ratio value of the echo signal is in a third preset signal-to-noise ratio value range, determining that the road surface is in a preset middle rain state;
if the signal-to-noise ratio value of the echo signal is in a fourth preset signal-to-noise ratio value range, determining that the road surface is in a preset heavy rain state;
The maximum value of the signal-to-noise ratio value in the second preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the first preset signal-to-noise ratio value range, and the maximum value of the signal-to-noise ratio value in the third preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the second preset signal-to-noise ratio value range; and the maximum value of the signal-to-noise ratio value in the fourth preset signal-to-noise ratio value range is smaller than the minimum value of the signal-to-noise ratio value in the third preset signal-to-noise ratio value range.
6. The method of claim 5, wherein the second predetermined signal-to-noise ratio value range is determined from third echo signal samples received after scanning the radar target in a predetermined rain-light scene, the predetermined rain-light scene being indicative of a scene in a predetermined rain-light state on a predetermined scene;
The third preset signal-to-noise ratio value range is determined from a fourth echo signal sample received after the radar target is scanned in a preset rainy scene, wherein the preset rainy scene is used for representing a scene in a middle preset rainy state on a preset field;
the fourth preset signal-to-noise ratio value range is determined from a fifth echo signal sample received after the radar target is scanned in a preset heavy rain scene, and the preset heavy rain scene is used for representing a scene in a preset heavy rain state on a preset field.
7. The method of claim 1, wherein the radar target is a corner reflector;
after said determining that said pavement surface is in the presence of a fog, said method further comprising:
And sending information for indicating that the road surface has the fog to a preset terminal so that the preset terminal sends out an early warning signal.
8. A radar, characterized in that it is adapted to perform the method according to any of claims 1-7.
9. A system for detecting a fog of a road surface, comprising: the radar and radar target of claim 8;
the radar and the radar target are respectively arranged at two sides of the road surface and are higher than the position of the preset distance of the road surface, and the radar target are oppositely arranged.
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