CROSS-REFERENCE TO RELATED APPLICATIONS AND CLAIM TO PRIORITY

This application is related to Patent Application No. 201910270687.3 filed Apr. 4, 2019 in China, the disclosure of which is incorporated herein by reference and to which priority is claimed.

FIELD OF THE INVENTION

The invention relates to intelligent vehicle testing and validation, and in particular to a millimeter wave radar modeling-based method for object visibility determination.

BACKGROUND AND SUMMARY OF THE INVENTION

Virtual testing is widely recognized as the most effective way to intelligent vehicle development. Virtual sensor modeling is one of the most important elements of the virtual testing of intelligent vehicles; the fidelity of the virtual sensor model determines how much a virtual testing can replace a real testing. In virtual sensor models, visibility analysis is usually through geometry culling or ray tracing, which uses only geometric and graphics algorithms, without considering the effects of millimeter-wave propagation and reflection, and thus cannot represent the physical characteristics of the millimeter wave radar. The invention provides an object visibility determination method using the reflection intensity from an object, which simulates the reflection of waves in real millimeter wave radar detection, and, because different object positions, attitudes, materials, shapes or areas lead to different reflection intensities, more accurately represents the reflection process of the millimeter wave radar, reflects the performance of a virtual radar, and greatly improves the fidelity of the millimeter wave radar model.

Currently in established millimeter-wave radar models, object visibility can be determined through two approaches. One approach includes simple geometry culling and comparing an object visible length with a threshold after culling. For example, inA Novel Method of Radar Modeling for Vehicle Intelligence, Guo Jiao proposed a millimeter wave radar model in which object extraction and visibility determination are through frustum culling: first a target vehicle is simplified into a bounding box and feature points are selected, then visibility of the target vehicle is determined by judging the positional relationship between the feature points and the frustum. In a doctoral dissertation, Zhang Sumin also mentioned an approach for identifying visible objects in a radar sensor model using geometry culling, which includes judging the spatial relationship between a geometrical shape of an object and a cone representing the working area of an on-vehicle radar sensor. Similarly, Hong Feng in his doctoral dissertation proposed a sensor model in which object visibility analysis is by geometry culling on a two-dimensional plane, determining occlusion and comparing an object visible length. The other sensor modeling-based approach for object visibility determination is ray tracing. For example, Zhao Xinjun proposed a radio frequency radar system in a publication, discussing and analyzing the principles and algorithms under a radio frequency environment and using a ray tracing approach to determine object visibility. In addition, no method using reflection intensity has been reported for object visibility determination in a sensor model.

In view of the above, the invention adopts a different approach than previous research. Considering that different object positions, angles, materials, shapes or areas lead to different reflection intensities, object reflection intensity is introduced to determine and analyze object visibility. In order to meet simulation efficiency requirements, the invention mainly includes, on the basis of geometry extraction, calculating the position of a visible section and the area of reflection of an object, to obtain a reflection intensity of the object, and determining the visibility of the object according to a reflection intensity threshold.

Accordingly, an object of the invention is to provide a new millimeter wave radar modeling-based method for object visibility determination within the visibility area of the millimeter wave radar, to solve the problem of object visibility determination based on virtual sensor modeling in intelligent vehicle simulation and testing, and improve the fidelity of sensor modeling while meeting simulation efficiency requirements.

To achieve the object above, the invention provides the following solution:

A millimeter wave radar modeling-based method for object visibility determination includes the following steps:Step 1: Target vehicle information detection to obtain target vehicle information:obtaining information of a target vehicle at a variety of positions and a variety of angles within a detection area of a host vehicle, where the target vehicle is being detected by the host vehicle, and the information includes a vehicle type, shape, size, material, position, speed, acceleration, moving direction and reflectivity of the target vehicle, according to vehicle types stored in an intelligent vehicle simulation testing model, and calibrated reflectivities of the vehicle types at a variety of positions within 360 degrees within a millimeter wave radar, and building a linked list for storage;Step 2: Target vehicle reflection intensity simulation:for each target vehicle obtained in Step 1 performing geometry culling on the target vehicle, discarding completely invisible target vehicles, and calculating visible section information for each target vehicle that has a visible section, the visible section information including a position of the visible section and a corresponding angle;in reflection intensity calculation, categorizing target vehicles into four classes according to their moving directions relative to the host vehicle: the target vehicle moves in the same direction as the host vehicle; the target vehicle moves in the opposite direction of the host vehicle; the target vehicle moves to the left relative to the host vehicle; and the target vehicle moves to the right relative to the host vehicle, and further dividing each class into a plurality of situations according to a positional relationship between the visible section and the host vehicle, and calculating a target vehicle reflection intensity according to the situation;Step 3: visibility determination:analyzing visibility of the target vehicle according to the target vehicle reflection intensity calculated from Step 2, and converting and outputting information of a visible target vehicle into an expression form of a real millimeter-wave radar sensing an object.

In Step 2 of the millimeter wave radar modeling-based method for object visibility determination, the target vehicle reflection intensity calculation includes finding a reflectivity of the target vehicle at a corresponding area from the calibrated reflectivities according to the position and angle of the current target vehicle, determining a situation in a class according to the position of the visible section, and obtaining an object reflection intensity of the target vehicle by calculating an integral on an angle interval corresponding to the visible section and multiplying a height of the target vehicle type.

In Step 2 of the millimeter wave radar modeling-based method for object visibility determination, the class where the target vehicle moves in the same direction as the host vehicle includes three situations: flrcornerfeature, frrcornerfeature and frearsidefeature:the flrcornerfeature indicates that the target vehicle visible section starts from the center of the rear end of the vehicle and runs the contour of the vehicle to the top left corner;the frrcornerfeature indicates that the target vehicle visible section starts from the center of the rear end of the vehicle and runs the contour of the vehicle to the top right corner;the frearsidefeature indicates that the target vehicle visible section starts from the left side to the right side of the rear end of the vehicle.

In Step 2 of the millimeter wave radar modeling-based method for object visibility determination, the class where the target vehicle moves in the opposite direction of the host includes three situations: frfcornerfeature, flfcornerfeature, and ffrontsidefeature:the frfcornerfeature indicates that the target vehicle visible section starts from the center of the front end of the vehicle and runs the contour of the vehicle to the top right corner;the flfcornerfeature indicates that the target vehicle visible section starts from the center of the front end of the vehicle and runs the contour of the vehicle to the top left corner;the ffrontsidefeature indicates that the target vehicle visible section starts from the left side to the right side of the front end of the vehicle.

In Step 2 of the millimeter wave radar modeling-based method for object visibility determination, the class where the target vehicle moves to the left relative to the host vehicle includes three situations: fflcornerfeature, frlcornerfeature, and fleftsidefeature:the fflcornerfeature indicates that the target vehicle visible section starts from the center of the left side of the vehicle and runs the contour of the vehicle to the top corner at the front end;the frlcornerfeature indicates that the target vehicle visible section starts from the center of the left side of the vehicle and runs the contour of the vehicle to the top corner at the rear end;the fleftsidefeature indicates that the target vehicle visible section starts from the front to the end of the left side of the vehicle.

In Step 2 of the millimeter wave radar modeling-based method for object visibility determination, the class where the class where the target vehicle moves to the right of the host vehicle includes three situations: frrcornerfeature, frfcornerfeature, and frightsidefeature:the frrcornerfeature indicates that the target vehicle visible section starts from the center of the right side of the vehicle and runs the contour of the vehicle to the top corner at the rear end;the frfcornerfeature indicates that the target vehicle visible section starts from the center of the right side of the vehicle and runs the contour of the vehicle to the top corner at the front end;the frightsidefeature indicates that the target vehicle visible section starts from the front to the end of the left side of the vehicle.

In Step 2 of the millimeter wave radar modeling-based method for object visibility determination, in the case where the course angle of the target vehicle changes relative to the host vehicle:the target vehicle moves in the same direction as the host vehicle when the course angle of the target vehicle ranges from 0 to 45° or 315° to 360°;the target vehicle moves to the left relative to the host vehicle when the course angle of the target vehicle ranges from 45° to 135°;the target vehicle moves in the opposite direction of the host vehicle when the course angle of the target vehicle ranges from 135° to 225°;the target vehicle moves to the right of the host vehicle when the course angel of the target vehicle ranges from 225° to 315°.

Step 2 of the millimeter wave radar modeling-based method for object visibility determination may further include: calculating a vector projection of the obtained reflection intensity, considering the angle between the target vehicle and the radar, which causes refraction loss, and based on calculating a position vector of the current target vehicle relative to the radar, which includes: supposing the visible section has endpoints A and B, the midpoint of the line AB is O1, the mounting position of the radar, i.e., is O, obtaining an actual object reflection intensity by calculating the vector projection of the obtained reflection intensity onto the line segment OO1.

Step 3 of the millimeter wave radar modeling-based method for object visibility determination may further include: sequentially extracting relevant data from the target vehicle reflection intensity result list obtained from step 2, determining whether a target vehicle reflection intensity result is greater than a target vehicle reflection intensity visibility threshold in the simulated sensor, and if the target vehicle reflection intensity result is greater than the target vehicle reflection visibility intensity threshold, determining the inputted object is visible to the simulated sensor, and converting and outputting the information of the target vehicle such as position, angle, speed and acceleration obtained in the simulation scene according to an output data format required by the current radar model; if the target vehicle reflection intensity result is not greater than the target vehicle reflection intensity visibility threshold, determining the inputted object is invisible to the simulated sensor. In the calculation above, the target vehicle intensity visibility threshold may be defined a reflection intensity value of the target vehicle when the simulated sensor can effectively identify the target vehicle.

