CN113109775A - Millimeter wave radar target visibility judgment method considering target surface coverage characteristics - Google Patents

Millimeter wave radar target visibility judgment method considering target surface coverage characteristics Download PDF

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CN113109775A
CN113109775A CN202110403866.7A CN202110403866A CN113109775A CN 113109775 A CN113109775 A CN 113109775A CN 202110403866 A CN202110403866 A CN 202110403866A CN 113109775 A CN113109775 A CN 113109775A
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snow
target
coverage
vehicle
reflection intensity
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CN113109775B (en
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詹军
杨凯
祝怀男
姜勐
曹子坤
仲昭辉
王战古
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Jilin University
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    • 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
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Abstract

The invention discloses a millimeter wave radar target visibility judgment method considering target surface coverage characteristics, which respectively establishes a target vehicle outer surface accumulated water, accumulated snow and other sundry coverage model; calculating the shielding relation between vehicles in the detection range of the millimeter wave radar by using a ray matrix method, and outputting the ratio of the actual visible area of each reflecting surface on the outer surface of the vehicle to the area of the reflecting surface; calculating the RCS value of each reflecting surface on the outer surface of the vehicle by using a physical optical approximation algorithm, and outputting the RCS value when each reflecting surface of the vehicle is not shielded; applying a model for covering accumulated water, accumulated snow and sundries on the outer surface of the target vehicle to RCS calculation of each reflecting surface of the target vehicle, and calculating influence coefficients of reflecting surfaces of target objects made of different materials on the reflection intensity of the millimeter wave radar; and calculating the actual reflection intensity value of each reflection surface of the target object, and comparing the actual reflection intensity value with a preset visibility threshold value to obtain the visibility of the target object.

Description

Millimeter wave radar target visibility judgment method considering target surface coverage characteristics
Technical Field
The invention belongs to the field of simulation test verification of intelligent automobiles, and particularly relates to a method for judging the visibility of a target object by a millimeter wave radar considering the coverage characteristics of the surface of the target, aiming at the modeling requirement of a high-precision millimeter wave radar.
Background
Virtual sensor modeling is an important part of intelligent automobile test evaluation. The millimeter wave radar virtual model is a vehicle-mounted sensor model widely used for virtual test and evaluation of intelligent vehicles, and is very important for modeling research of millimeter wave radars. In the research process, the physical characteristics of the target object surface covering are found to have great influence on the reflection of the millimeter wave radar. In consideration of special weather, such as rainy and snowy weather, a part of impurities such as rainwater, ice and snow or mud can be accumulated on the outer surface of the vehicle, and the electromagnetic wave intensity returned when the electromagnetic wave emitted by the millimeter wave radar irradiates a reflecting surface covered by objects such as a water film or ice and snow is greatly weakened due to the absorption effect of the water and the ice on the electromagnetic wave, so that the coverage rate of the impurities such as the water film and the ice and snow on the outer surface of the vehicle in the special weather is needed to be modeled, and the influence of the coverage rate of the rain and snow is considered when the millimeter wave radar model calculates the reflection intensity (RCS) of a target object, so that the calculation of the reflection intensity is closer to the real situation. The method can simulate the characteristics of the vehicle outer surface covering under the special weather condition of the simulation scene more truly, and greatly improve the accuracy of the millimeter wave radar model in identifying the target under the special weather condition.
At present, the research on the millimeter wave radar model aiming at special weather mainly focuses on the propagation process of the electromagnetic waves emitted by the millimeter wave radar. In the literature, the research on millimeter wave rainfall and near-field target scattering characteristics analyzes the electromagnetic scattering characteristics of raindrops and the multiple scattering effect of electromagnetic waves transmitted in a random discrete medium, calculates the attenuation value of the rainfall by using a Monte Carlo method, and analyzes the influence of the backscattering enhancement on the detection performance of the millimeter wave radar. The method for evaluating the automobile driving environment danger of the laser radar modeling and rain accumulation laser radar researches a parameter calibration process of a simplified model on the premise of ensuring the precision of a physical model, models different weather, and simulates the influence of rain particle noise points on the attenuation of the laser radar under different weather, particularly rainy days. The literature-Influences of weather phenomena on automatic laser radar systems outlines various physical principles causing interference of laser radar optical signals and theoretical research of influence degree and applies a signal transmission model to a new laser radar signal simulator. The influence of a thin water layer on a vehicle-mounted 77GHz automatic radar signals is researched by The document of The flame of The water-converted two electric radomes on 77GHz, and a measurement error existing in The water film is simulated based on a layered medium wave propagation theoretical model and a numerical model considering The near-field propagation effect of CST simulation. The document-Indicators for the Signal degradation and Optimization of automatic Radar surface conditioner analyses the images of water film and rainwater on the transmission of millimeter waves, researches and evaluates the physical parameters of wave interaction with the water film and rainwater, establishes a method for measuring the indexes of the water film and the rainwater in a Radar system at low cost and introduces some technologies to optimize the detection performance of the Radar.
The current automatic driving virtual scene simulation software only considers the influence of special weather such as rain, snow, fog and the like on the vision, vehicle dynamics, sound and the like of a driver, and does not consider the influence of the change of the reflection intensity of the surface of a target object caused by the special weather on the detection of the target object by a sensor. In areas with strong snowfall and rainfall, the coverage of snow and rain on the surface of the target object is not negligible. The covering of sundries such as snow, water and mud can cause the material of the outer surface of the vehicle to change, and the reflection intensity of the reflection surface of different materials to the electromagnetic wave of the millimeter wave radar is different, so that the recognition of the automatic driving vehicle to the target object can be influenced. The invention improves the simulation precision of the millimeter wave radar model under the special weather conditions of rain, snow and the like, accurately describes the visibility judgment of the millimeter wave radar on the target object under the condition that the surface of the target object is covered in the rain and snow weather, and provides a foundation for expanding the virtual simulation verification working condition of the intelligent automobile.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a millimeter wave radar target visibility judgment method considering target surface coverage characteristics, a physical characteristic model of a target object surface covering under a special weather condition is added into a millimeter wave radar model, the change rule of the target object surface area snow-water coverage rate along with time, snowfall and rainfall intensity and temperature is obtained, the influence of the target object surface reflection surface with the covering on the millimeter wave radar reflection intensity is considered on the basis of calculating the radar wave reflection intensity value by a physical optical algorithm, the RCS value of the target object can be obtained more accurately, and the visibility judgment of the target object is closer to the real millimeter wave radar detection result.
The purpose of the invention is realized by the following technical scheme:
a millimeter wave radar target visibility judgment method considering target surface coverage characteristics comprises the following steps:
step one, modeling the rain and snow coverage rate of the outer surface of a vehicle: respectively establishing a water model of the outer surface area of the target vehicle and an accumulated snow model of the outer surface of the target vehicle according to the water film and accumulated snow covering conditions on the reflecting surface of the target vehicle on the basis of considering the change relation of the covering conditions along with the intensity of rainfall and snowfall, time and temperature;
step two, acquiring the state information and the 3D information of the target object: generating target object state information through scene information acquisition, and storing the target object state information and the target object 3D information in corresponding linked lists;
step three, occlusion calculation: according to the state information and the 3D information of the target object, calculating the shielding relation between the vehicles in the detection range of the millimeter wave radar by using a ray matrix method, outputting the ratio of the actual visible area of each reflecting surface on the outer surface of the vehicle to the area of the reflecting surface and the area coefficient alpha, and further classifying the target object into a partially visible target and a completely invisible target;
step four, calculating the reflection intensity: for a part of visible targets, calculating the RCS value of each reflecting surface on the outer surface of the vehicle by using a physical optical approximation algorithm, and outputting the RCS value of each reflecting surface of the vehicle which is not shielded;
step five, calculating a reflection intensity correction coefficient: and applying the water model of the outer surface area of the target vehicle and the snow model of the outer surface of the target vehicle to each reflecting surface of the target vehicle to obtain the percentage coverage value of rain and snow of each reflecting surface, and calculating and outputting a reflection intensity calculation coefficient according to the influence coefficients of objects made of different materials such as rain, snow and the like on electromagnetic waves.
Step six: and (3) judging the visibility of the target object: and calculating the actual reflection intensity value of each reflecting surface of the target object according to the calculated reflection intensity of each reflecting surface of the target object, the reflection coefficient of the water drops, the water films and the accumulated snow on the millimeter wave radar and the visible area coefficient obtained by shielding the calculated visible area, and comparing the actual reflection intensity value with a preset visibility threshold value to obtain the visibility of the target object.
Further, the step of modeling the rain and snow coverage of the outer surface of the vehicle specifically comprises:
1.1) water model of external surface area of target vehicle:
the rain and snow intensity is normalized to a random step function between 0 and 1, and the rain coverage of the vehicle external surface area is expressed by the following formula with the time:
Figure BDA0003021458230000031
in the formula, FRdIs the coverage of the water droplets; fRmIs the coverage of the water film; qRIs the intensity of rainfall; t is time in min; considering the influence of environmental factors on the coverage rate of the accumulated water and the water film, adding a correction coefficient to correct the difference of the factors, namely muRdA correction factor for water drop coverage; mu.sRmIs a correction factor for water film coverage;
1.2) snow accumulation model of the outer surface of the target vehicle:
snow coverage rate F of outer surface of static vehicleSSIntensity Q following snowfallSThe relationship with the time temperature T can be represented by the following equation:
Figure BDA0003021458230000032
snow cover ratio F of outer surface of moving vehicleSMIntensity Q following snowfallSThe relationship with time T, temperature T can be represented by the following equation:
Figure BDA0003021458230000033
considering the influence of environmental factors on the coverage rate of accumulated snow, a correction coefficient is added to correct the difference of the factors, and muSSAnd muSMCorrection coefficients of snow coverage of the static vehicle and the dynamic vehicle respectively;
FRd、FRm、FSMand FSSAll values are [0,1 ]]When the value reaches 1, the change is not caused;
when the snow cover reaches one hundred percent, the newly covered snow will increase the snow cover thickness gamma, and the relation expression of the snow cover thickness and the snow intensity and time is as follows:
γ＝μγ·QS·t
in the formula, muγThe snow cover thickness correction factor;
1.3) a model of the surface sundry coverage rate of the target vehicle:
by FZ＝rand[0,1]Indicating the debris coverage of the target vehicle surface.
Further, the calculating of the reflection intensity correction coefficient in the fifth step specifically includes:
for a particular reflecting surface, when the surface has a covering and the coverage ratio is F, the reflection intensity coefficient calculation formula is as follows:
a) calculation of the reflective surface covered with water droplets:
Figure BDA0003021458230000041
in the formula, epsilonRdCalculating coefficient of reflection intensity covered by surface water drops; fRdIs the reflective surface water drop coverage;
Figure BDA0003021458230000042
the influence coefficient of water drop coverage on the reflection intensity of the millimeter wave radar is shown;
b) calculation of the reflective surface covered with a water film:
Figure BDA0003021458230000043
in the formula, epsilonRmCalculating coefficient of reflection intensity covered by surface water film; fRmIs the water film coverage of the reflecting surface; siIs the area of the corresponding reflecting surface;
Figure BDA0003021458230000044
the influence coefficient of the water film coverage on the reflection intensity of the millimeter wave radar is shown;
c) calculation of the reflection surface covered with snow:
Figure BDA0003021458230000045
in the formula, epsilonSCalculating coefficients for the snow cover reflection intensities; fSThe snow coverage rate;
Figure BDA0003021458230000046
the influence coefficient of accumulated snow on the reflection intensity of the millimeter wave radar is shown; gamma is the thickness of accumulated snow; gamma ray0Identifying the critical snow thickness for the signal when the snow thickness exceeds gamma0In time, the millimeter wave radar cannot identify the target object;
d) calculation of the reflecting surface covered with impurities:
Figure BDA0003021458230000047
in the formula, epsilonZCalculating coefficients for the reflection intensity with the sundries covered; fZRepresenting a debris coverage of a surface of the target vehicle;
Figure BDA0003021458230000048
and the attenuation coefficient of the millimeter wave radar electromagnetic wave by the sundries is represented.
Further, in the sixth target object visibility judgment, the calculation formula of the reflection intensity value is as follows:
Figure BDA0003021458230000049
in the formula (I), the compound is shown in the specification,
Figure BDA00030214582300000410
is the final reflection intensity value of the ith reflection surface of the target object;
Figure BDA00030214582300000411
the reflection intensity value is the reflection intensity value when the ith reflection surface of the target object is not shielded and the coverage rate is 0; ε is the reflection intensity correction coefficient of the reflection surface; α is a visible area coefficient of the reflecting surface after being blocked.
Drawings
FIG. 1 is an overall flow chart of the present invention.
Detailed Description
The technical scheme of the invention is further described in the following by combining the attached drawings.
As shown in fig. 1, a millimeter wave radar target visibility judgment method considering target surface coverage characteristics includes the following steps:
step one, modeling the rain and snow coverage rate of the outer surface of a vehicle: and respectively establishing a water model of the outer surface area of the target vehicle and an accumulated snow model of the outer surface of the target vehicle on the basis of considering the change relation of the coverage condition along with the intensity of rainfall and snowfall, time and temperature.
In special weather such as rainy days and snowy days, the parking at two sides of the road is often covered with water films, snow, mud stains and the like. As the time duration of the rain and snow weather changes, the areas of the outer surface of the vehicle covered with water films, snow and mud also vary. And establishing the change rate of the water film or the snow cover covered on the outer surface of the vehicle according to the intensity of rainfall and snowfall and the time relation. Generally, the worse the weather, the longer the duration the vehicle is covered with a film of water and snow. However, the particles of rainfall and snowfall have different physical properties and water has a flow property, so that the coverage rates of the particles of rainfall and snowfall are different from each other. Rainfall covers two kinds of water films and water drops on the outer surface of the vehicle, the water films cover when the rainfall degree is large, and the water drops cover when the rainfall intensity is small. The rate of rain covering the exterior surface of the vehicle is significantly faster than the rate of snow covering the exterior surface of the vehicle. And when the temperature of the environment is different, the snowfall on the outer surface of the vehicle can be quickly converted into water drops, and the covering rate on the outer surface of the vehicle can be accelerated. For snowfall, the coverage rate of a stationary object is much higher than that of a moving object.
In order to meet the requirement of real-time performance of simulation calculation, the invention simplifies the water accumulation model and the snow accumulation model and reserves certain time rule and physical characteristics.
1.1) water model of external surface area of target vehicle:
the rain and snow intensity is normalized to a random step function between 0 and 1, and the rain coverage of the vehicle external surface area is expressed by the following formula with the time:
Figure BDA0003021458230000051
in the formula, FRdIs the coverage of the water droplets, FRmIs the coverage of the water film, QRIs the intensity of rainfall, t is the time, here in minutes (min); considering the influence of environmental factors on the coverage rate of the accumulated water and the water film, adding a correction coefficient to correct the difference of the factors, namely muRdCorrection factor for water droplet coverage, μRmIs the correction factor of the water film coverage, muRdAnd muRmObtained through experiments or experiences, and the method is different according to factors such as geographical positions, environmental conditions and the like.
1.2) snow accumulation model of the outer surface of the target vehicle:
snow coverage rate F of outer surface of static vehicleSSIntensity Q following snowfallSThe relationship with the time temperature T can be represented by the following equation:
Figure BDA0003021458230000052
snow cover ratio F of outer surface of moving vehicleSMIntensity Q following snowfallSThe relationship with time T, temperature T can be represented by the following equation:
Figure BDA0003021458230000061
considering the influence of environmental factors on the snow cover rate, a correction coefficient is added to correct the difference of the factors, and muSSAnd muSMThe correction coefficients of the snow coverage of the static vehicle and the dynamic vehicle are obtained through experiments or experiences and are different according to different factors such as geographical positions, environmental conditions and the like.
FRd、FRm、FSMAnd FSSAll values are [0,1 ]]When the value reaches 1, it is not changed.
When the snow cover reaches one hundred percent, the newly covered snow will increase the thickness gamma of the snow cover. Assuming that the snow cover thickness is linearly related to the snow intensity and time, the relational expression is as follows:
γ＝μγ·QS·t
in the formula ofγThe snow cover thickness correction coefficient.
1.3) a model of the surface sundry coverage rate of the target vehicle:
the road surface becomes wet and slippery due to rain and snow weatherWhen the vehicle runs on such a road surface, the rotation of the tires and the splashing of muddy water can cover a large amount of mud or other impurities on the surface of the target vehicle, so that the detection of the target object by the millimeter wave radar is influenced. Because the appearance of the sundries has no fixed relation with time, in order to more generally solve the influence of sundry coverage on the surface of the target vehicle on the detection of the millimeter wave radar, F is usedZ＝rand[0,1]Indicating the debris coverage of the target vehicle surface,
Figure BDA0003021458230000062
and the attenuation coefficient of the millimeter wave radar electromagnetic wave by the sundries is represented.
Step two, acquiring the state information and the 3D information of the target object: and generating target object state information by acquiring scene information, and storing the target object state information and the target object 3D information in corresponding linked lists. The state information comprises the current position, speed, acceleration and driving direction of the target vehicle, and the 3D information of the target object comprises the shape size, the shape of the reflecting surface and the angle of the target object.
Step three, occlusion calculation: calculating the shielding relation between vehicles in the detection range of the millimeter wave radar by using a ray matrix method according to the state information and the 3D information of the target object, and outputting the ratio of the actual visible area of each reflecting surface on the outer surface of the vehicle to the area of the reflecting surface and the visible area coefficient alpha; the target object is classified into a partially visible target and a completely invisible target.
Step four, calculating the reflection intensity: and for a part of visible targets, calculating the RCS value of each reflecting surface on the outer surface of the vehicle by using a physical optical approximation algorithm, and outputting the RCS value of each reflecting surface of the vehicle which is not shielded.
Step five, calculating a reflection intensity correction coefficient: and applying the water model of the outer surface area of the target vehicle and the snow model of the outer surface of the target vehicle to each reflecting surface of the target vehicle to obtain the percentage coverage value of rain and snow of each reflecting surface, and calculating and outputting a reflection intensity calculation coefficient according to the influence coefficients of different materials (rain and snow) on electromagnetic waves.
The basic principle of the reflection intensity calculation coefficient is that the influence coefficient of objects (water, snow, mud, and the like) made of different materials on the reflection intensity and the influence of the coverage rate on the reflection intensity of the millimeter wave radar are obtained through experiments or empirical data. The influence of the water film on the millimeter wave radar is mainly to reduce or increase the reflection intensity value of the target object, the attenuation of the accumulated snow cover on the millimeter wave radar signal is very obvious, and when the accumulated snow cover reaches a certain thickness, the millimeter wave radar cannot identify the target object.
For a particular reflecting surface, when the surface has a covering and the coverage ratio is F, the reflection intensity coefficient calculation formula is as follows:
a) calculation of reflective surfaces covered by water droplets
Figure BDA0003021458230000071
In the formula ofRdIs the coefficient of reflection intensity calculation for surface water drop coverage, FRdIs the water drop coverage of the reflective surface,
Figure BDA0003021458230000072
is the influence coefficient of water drop coverage on the reflection intensity of the millimeter wave radar.
b) Calculation of reflective surfaces covered with Water film
Figure BDA0003021458230000073
In the formula ofRmIs the coefficient of reflection intensity calculation for surface water film coverage, FRmIs the water film coverage rate of the surface of the reflecting surface,
Figure BDA0003021458230000074
the influence coefficient of the water film coverage on the reflection intensity of the millimeter wave radar is shown.
c) Calculation of a reflecting surface covered with snow
The snow cover of a static vehicle mainly covers front and rear windshields, an engine compartment cover, a rear tail box cover and a roof of the vehicle, the snow cover of a moving vehicle is mainly concentrated on the engine compartment and the rear tail box cover because a driver can manually remove the snow cover on the windshields by using a windshield wiper, the snow cover is difficult to form because the engine compartment cover is high in temperature when the vehicle runs, and therefore the snow cover coverage rate of the running vehicle is calculated by excluding the reflection surfaces of the windshields and the engine compartment cover. When the snow cover thickness on the surface of the target object reaches the signal identification critical value thickness, the millimeter wave radar cannot identify the part of the target object covered by the snow.
The calculation coefficient of the reflection intensity when the surface of the target object is covered by snow is as follows:
Figure BDA0003021458230000075
in the formula ofSCalculating coefficients for the intensity of the snow cover reflection, FSThe coverage rate of the accumulated snow is shown as,
Figure BDA0003021458230000076
the influence coefficient of accumulated snow on the reflection intensity of the millimeter wave radar is gamma, the thickness of the accumulated snow is gamma0Identifying the critical snow thickness for the signal when the snow thickness exceeds gamma0At this time, the millimeter wave radar cannot recognize the target object. When calculating, it is necessary to first judge whether the vehicle is stationary or moving, and then select corresponding F according to the situationSThe value of (a).
d) Calculation of reflecting surfaces covered by impurities
Figure BDA0003021458230000077
In the formula ofZCalculating the coefficient for the intensity of the reflection with the inclusion cover, FZIndicating the debris coverage of the target vehicle surface,
Figure BDA0003021458230000078
representing the attenuation of the millimeter wave radar electromagnetic wave by the sundriesAnd (4) the coefficient.
Step six: and (3) judging the visibility of the target object: and calculating the actual reflection intensity value of each reflecting surface of the target object according to the calculated reflection intensity of each reflecting surface of the target object, the reflection coefficient of the water drops, the water films and the accumulated snow on the millimeter wave radar and the calculated area coefficient for shielding, and comparing the actual reflection intensity value with a preset visibility threshold value to obtain the visibility of the target object.
Figure BDA0003021458230000081
In the formula
Figure BDA0003021458230000082
Is the final reflection intensity value of the ith reflection surface of the target object,
Figure BDA0003021458230000083
the reflection intensity value is the reflection intensity value when the ith reflection surface of the target object is not blocked and the surface impurity coverage rate is 0, epsilon is the reflection intensity correction coefficient of the reflection surface, and alpha is the visible area coefficient of the reflection surface after being blocked.
And calculating to obtain the final reflection intensity of each reflecting surface of the target, and comparing the final reflection intensity with an RCS visible threshold value preset in the model to obtain the final visibility of each reflecting surface. And if at least one of the actual visible reflecting surfaces of the target object is visible, and if all the reflecting surface reflection intensity values do not reach the preset RCS threshold value, the target object is invisible.

Claims (4)

1. A millimeter wave radar target visibility judgment method considering target surface coverage characteristics is characterized by comprising the following steps:
step one, modeling the rain and snow coverage rate of the outer surface of a vehicle: respectively establishing a water model of the outer surface area of the target vehicle and an accumulated snow model of the outer surface of the target vehicle according to the water film and accumulated snow covering conditions on the reflecting surface of the target vehicle on the basis of considering the change relation of the covering conditions along with the intensity of rainfall and snowfall, time and temperature;
step two, acquiring the state information and the 3D information of the target object: generating target object state information through scene information acquisition, and storing the target object state information and the target object 3D information in corresponding linked lists;
step three, occlusion calculation: according to the state information and the 3D information of the target object, calculating the shielding relation between the vehicles in the detection range of the millimeter wave radar by using a ray matrix method, outputting the ratio of the actual visible area of each reflecting surface on the outer surface of the vehicle to the area of the reflecting surface and the visible area coefficient alpha, and further classifying the target object into a partially visible target and a completely invisible target;
step four, calculating the reflection intensity: for a part of visible targets, calculating the RCS value of each reflecting surface on the outer surface of the vehicle by using a physical optical algorithm, and outputting the RCS value of each reflecting surface of the vehicle which is not shielded;
step five, calculating a reflection intensity correction coefficient: applying a target vehicle outer surface area water model and a target vehicle outer surface snow accumulation model to each reflecting surface of a target vehicle to obtain a rain and snow coverage percentage value of each reflecting surface, and calculating and outputting a reflection intensity calculation coefficient according to influence coefficients of objects made of different materials on electromagnetic waves;
step six: and (3) judging the visibility of the target object: and calculating the actual reflection intensity value of each reflecting surface of the target object according to the calculated reflection intensity of each reflecting surface of the target object, the reflection coefficient of the water drops, the water films and the accumulated snow on the millimeter wave radar and the visible area coefficient obtained by shielding the calculated visible area, and comparing the actual reflection intensity value with a preset visibility threshold value to obtain the visibility of the target object.
2. The millimeter wave radar target visibility determination method taking into account target surface coverage characteristics according to claim 1, wherein the step of modeling the rain and snow coverage of the outer surface of the vehicle specifically comprises:
1.1) water model of external surface area of target vehicle:
the rain and snow intensity is normalized to a random step function between 0 and 1, and the rain coverage of the vehicle external surface area is expressed by the following formula with the time:
Figure FDA0003021458220000011
in the formula, FRdIs the coverage of the water droplets; fRmIs the coverage of the water film; qRIs the intensity of rainfall; t is time in min; considering the influence of environmental factors on the coverage rate of the accumulated water and the water film, adding a correction coefficient to correct the difference of the factors, namely muRdA correction factor for water drop coverage; mu.sRmIs a correction factor for water film coverage;
1.2) snow accumulation model of the outer surface of the target vehicle:
snow coverage rate F of outer surface of static vehicleSSIntensity Q following snowfallSThe relationship with the time temperature T can be represented by the following equation:
Figure FDA0003021458220000021
snow cover ratio F of outer surface of moving vehicleSMIntensity Q following snowfallSThe relationship with time T, temperature T can be represented by the following equation:
Figure FDA0003021458220000022
considering the influence of environmental factors on the coverage rate of accumulated snow, a correction coefficient is added to correct the difference of the factors, and muSSAnd muSMCorrection coefficients of snow coverage of the static vehicle and the dynamic vehicle respectively;
FRd、FRm、FSMand FSSAll values are [0,1 ]]When the value reaches 1, the change is not caused;
when the snow cover reaches one hundred percent, the newly covered snow will increase the snow cover thickness gamma, and the relation expression of the snow cover thickness and the snow intensity and time is as follows:
γ＝μγ·QS·t
in the formula, muγThe snow cover thickness correction factor;
1.3) a model of the surface sundry coverage rate of the target vehicle:
by FZ＝rand[0,1]Indicating the debris coverage of the target vehicle surface.
3. The millimeter wave radar target visibility judgment method taking target surface coverage characteristics into consideration as set forth in claim 1, wherein the step five reflection intensity correction coefficient calculation specifically includes:
for a particular reflecting surface, when the surface has a covering and the coverage ratio is F, the reflection intensity coefficient calculation formula is as follows:
a) calculation of the reflective surface covered with water droplets:
Figure FDA0003021458220000023
in the formula, epsilonRdCalculating coefficient of reflection intensity covered by surface water drops; fRdIs the reflective surface water drop coverage;
Figure FDA0003021458220000024
the influence coefficient of water drop coverage on the reflection intensity of the millimeter wave radar is shown;
b) calculation of the reflective surface covered with a water film:
Figure FDA0003021458220000025
in the formula, epsilonRmCalculating coefficient of reflection intensity covered by surface water film; fRmIs the water film coverage of the reflecting surface;
Figure FDA0003021458220000026
the influence coefficient of the water film coverage on the reflection intensity of the millimeter wave radar is shown;
c) calculation of the reflection surface covered with snow:
Figure FDA0003021458220000027
in the formula, epsilonSCalculating coefficients for the snow cover reflection intensities; fSThe snow coverage rate;
Figure FDA0003021458220000028
the attenuation coefficient of the accumulated snow to the reflection intensity of the millimeter wave radar is obtained; gamma is the thickness of accumulated snow; gamma ray0Identifying the critical snow thickness for the signal when the snow thickness exceeds gamma0In time, the millimeter wave radar cannot identify the target object;
d) calculation of the reflecting surface covered with impurities:
Figure FDA0003021458220000031
in the formula, epsilonZCalculating coefficients for the reflection intensity with the sundries covered; fZRepresenting a debris coverage of a surface of the target vehicle;
Figure FDA0003021458220000032
and the attenuation coefficient of the millimeter wave radar electromagnetic wave by the sundries is represented.
4. The millimeter wave radar target visibility judgment method taking into account target surface coverage characteristics according to claim 1, wherein in the six-step target object visibility judgment, the calculation formula of the reflection intensity value is as follows:
Figure FDA0003021458220000033
in the formula (I), the compound is shown in the specification,
Figure FDA0003021458220000034
is the final reflection intensity value of the ith reflection surface of the target object;
Figure FDA0003021458220000035
the reflection intensity value is the reflection intensity value when the ith reflection surface of the target object is not shielded and the coverage rate is 0; ε is the reflection intensity correction coefficient of the reflection surface; α is a visible area coefficient of the reflecting surface after being blocked.
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