Electromagnetic response simulation for arbitrary road surface profiles
Through the optimization algorithm and bounce ray method based on image theory, the accuracy and efficiency problems of electromagnetic response simulation of complex road surfaces in the prior art are solved, and efficient and accurate simulation of radar signals is achieved, reducing calculation costs.
Patent Information
- Application Number
- CN202311272426.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Priority Date
- 2023-06-07
- Filing Date
- 2023-09-28
- Publication Date
- 2024-12-17
AI Technical Summary
Existing electromagnetic response models are difficult to accurately simulate the electromagnetic response in real-world in computer simulation environments, especially when the road surface has complex geometric profiles, which makes it difficult to accurately represent the vertical multipath problem of radar signals, resulting in high computational costs and The results are inaccurate.
Using a bounce ray method based on image theory, the reflection points of electromagnetic rays along the geometric profile of the road surface are estimated through an optimization algorithm, and the positions of the electromagnetic sensor and target are converted into a local coordinate system, the electromagnetic response is calculated, and simulated rays are output to simulate The measurement value of the radar system.
Accurate simulation of electromagnetic responses on complex road surfaces is achieved, which reduces the computational complexity and cost, improves the accuracy of simulation results, and is close to real-world electromagnetic response measurements.
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Figure CN119150504A_ABST
Abstract
Description
Background Art
[0001] Radars are useful devices that can detect and track objects. As such, radars offer many advantages for autonomous driving applications or driver assistance applications. During engineering and development, radar simulations can be run to evaluate performance under various conditions. These simulations can benefit from incorporating electromagnetic response models that simulate the electromagnetic response associated with the radar in a simulated environment. However, existing electromagnetic response models may be too complex or too slow to be used in some computer simulation environments; if they are used at all, some electromagnetic response models may not accurately simulate the real-world electromagnetic response. Summary of the invention
[0002] The various aspects described below include accurate and efficient electromagnetic responses of sensor simulators. In one example, the method includes: receiving the position and orientation of the electromagnetic sensor and the target by the electromagnetic response simulator. The method further includes: receiving the geometric profile of the road surface by the electromagnetic response simulator. The method further includes: using an optimization algorithm by the electromagnetic response simulator to estimate the reflection point of the electromagnetic ray along the geometric profile of the road surface. The method further includes: converting the position and orientation of the electromagnetic sensor and the target into a local coordinate system of each estimated reflection point by the electromagnetic response simulator. The method further includes: calculating the electromagnetic response based on the position of the electromagnetic sensor and the target in the corresponding local coordinate system of each estimated reflection point by the electromagnetic response simulator. The method further includes: collecting simulated rays corresponding to the electromagnetic response by the electromagnetic response simulator. The method further includes: outputting the simulated rays to an electromagnetic sensor simulator for simulating an electromagnetic sensor system by the electromagnetic response simulator.
[0003] These and other described techniques may be performed by hardware or a combination of hardware and software executed thereon. For example, a computer readable storage medium (CRM) may have instructions stored thereon, and when the instructions are executed, the processor is configured to perform the described techniques. The system may include means for performing the described techniques. The processor or processor unit may be part of a system configured to perform the methods and techniques described herein.
[0004] This summary introduces simplified concepts related to electromagnetic response simulation for arbitrary road surface profiles, which are further described in the detailed description and figures. This summary is not intended to identify essential features of the claimed subject matter, nor is it intended to be used to determine the scope of the claimed subject matter. BRIEF DESCRIPTION OF THE DRAWINGS
[0005] Details of electromagnetic response simulation for arbitrary road surface profiles are described in this document with reference to the accompanying drawings, which may use the same numerals to refer to similar features and components, and hyphen numbers to indicate variations of these similar features and components. The drawings are organized as follows: Figure 1-1 and Figure 1-2 An example environment and an example simulation environment are respectively shown, in which electromagnetic response simulation for arbitrary road surface contours can be applied according to the techniques of the present disclosure; Figure 2 An example flow chart showing data of an electromagnetic simulator associated with electromagnetic response simulation for an arbitrary road surface profile in accordance with the techniques of the present disclosure; Figure 3 A non-flat road scenario is shown, where electromagnetic response simulation for arbitrary road surface contours is applicable, in accordance with the techniques of this disclosure. Figure 4-1 to Figure 4-3 shows an example optimization algorithm that may be used for electromagnetic response simulation for arbitrary road surface profiles in accordance with the techniques of this disclosure; and Figure 5 An example method for electromagnetic response simulation of an arbitrary road surface profile in accordance with the techniques of this disclosure is shown. DETAILED DESCRIPTION Overview
[0006] The Automotive Radar Environment Simulation Tool uses computers to simulate the wave propagation and scattering phenomena of millimeter wave (MMW) radar signals in traffic scenarios, as well as simulating the propagation of such signals through radar hardware and the processing by the software backend. Compared to road testing, radar environment simulation is much cheaper and easier to repeat in certain key scenarios. Moreover, it can provide deep insights into the interaction between the environment and radar signals, and therefore, it facilitates and accelerates the development of radars. The propagation and scattering aspects of this simulation utilize electromagnetic response simulations.
[0007] Accurate representation of vertical multipath due to road reflections of electromagnetic signals (e.g., radar signals) is critical to accurately estimate elevation measurements, but many current tools fail to adequately account for such effects. Typically, these tools may attempt to address this issue by modeling the road as a stationary target. However, this solution may require firing too many rays to cover the entire road, which can result in high computational costs while still not guaranteeing accurate results.
[0008] One way to overcome these shortcomings is to use a shooting and bouncing rays approach based on image theory to solve the vertical multipath problem due to road reflections. Image theory assumes that the road is flat (e.g., the surface height of the road is considered constant). However, the geometric contours of the road may not always be flat, which can lead to differences between sensor measurements and simulated data, especially for sensors with vertical discrimination capabilities.
[0009] This document describes techniques and systems for electromagnetic response simulation of any road surface profile. The electromagnetic response simulator receives the position and orientation of both an electromagnetic sensor (e.g., a radar sensor) and a target, as well as the geometric profile of the road surface. The elevation of the road surface may vary in the lateral and / or longitudinal directions. The electromagnetic response simulator estimates the reflection points of electromagnetic rays along the geometric profile of the road surface, and converts the position and orientation of the electromagnetic sensor and the target into corresponding local coordinates corresponding to each reflection point. The electromagnetic response can then be calculated, and the corresponding simulated rays can be output to the sensor simulator. In this way, changes in the elevation of the road surface can be included in the generation of simulated rays, and the electromagnetic response simulator can more accurately simulate the electromagnetic response of the real world. Example Environment
[0010] Figure 1-1 and Figure 1-2 An example environment 100-1 and an example simulation environment 100-2 are respectively shown, in which electromagnetic response simulation for arbitrary road surface contours can be applied according to the techniques of the present disclosure. Figure 1-1 In the environment 100-1 depicted in FIG. 1 , a radar system 102 is mounted to or integrated within a vehicle 104 traveling on a road 106 toward a target 108. The road 106 may have an arbitrary geometric profile. That is, the height of the road (e.g., the z direction) may vary along its surface in a lateral direction (e.g., the x direction) and / or in a longitudinal direction (e.g., the y direction). The vehicle may travel on the road 106 along a route 110.
[0011] Radar system 102 is capable of detecting one or more targets that are in close proximity to vehicle 104 and are associated with a signal-to-noise ratio greater than a detection threshold of radar system 102. Although illustrated as an automobile, vehicle 104 may represent other types of motorized vehicles (e.g., motorcycles, buses, tractors, semi-trailers, or construction equipment), various types of non-motorized vehicles (e.g., bicycles), various types of rail vehicles (e.g., trains or trams), watercraft (e.g., ships or boats), aircraft (e.g., airplanes or helicopters), or spacecraft (e.g., satellites). Generally, radar system 102 may be mounted to any type of mobile platform, including mobile machinery or robotic equipment.
[0012] In the depicted implementation, the radar system 102 is mounted to the front side of the vehicle 104. In other implementations, the radar system 102 may be mounted to the underside, top side, rear side, left side, or right side of the vehicle 104. In some cases, the vehicle 104 includes multiple radar systems 102, such as a first rear-mounted radar system 102 positioned near the left side of the vehicle 104 and a second rear-mounted radar system 102 positioned near the right side of the vehicle 104. Generally, the position of one or more radar systems 102 may be designed to provide a specific field of view covering an area of interest where the target 108 may be present. Example fields of view include a 360 degree field of view, one or more 180 degree fields of view, one or more 90 degree fields of view, etc., which may overlap (e.g., four 120 degree fields of view).
[0013] Target 108 is made of one or more types of materials that reflect radar signals. Depending on the application, target 108 can represent an object of interest or clutter. In some cases, target 108 is a moving target, such as another vehicle, a person, or an animal. In other cases, target 108 is a stationary target, such as a continuous or discontinuous road obstacle (e.g., a traffic cone, a concrete barrier, a guardrail, or a fence), a tree, or a parked vehicle.
[0014] The vehicle 104 may implement one or more automotive systems that utilize the data provided by the radar system 102. Example types of automotive systems include driver assistance systems or autonomous driving systems. The driver assistance system may use the data provided by the radar system 102 to monitor one or more blind spots of the vehicle 104 and alert the driver of a potential collision with an object 108. The autonomous driving system may move the vehicle 104 to a position to avoid a collision with another object 108, perform emergency braking, change lanes, or adjust the speed of the vehicle 104 while analyzing the data provided by the radar system 102.
[0015] To detect the target 108, the radar system 102 transmits signals along a direct path 112 and along one or more multipaths 114 and receives reflected signals as the vehicle 104 travels along the route 110. The radar system 102 transmits and receives these signals using at least one antenna 116 (e.g., a multiple input multiple output (MIMO) antenna). The radar system 102 includes at least one monolithic microwave integrated circuit (MMIC) 118. The MMIC 118 includes circuitry and logic for transmitting and receiving radar signals via the antenna 116. The radar system 102 may also include one or more processors 120 and a computer readable storage medium (CRM) 122. The CRM 122 includes radar software 124 for analyzing radar received signals, detecting the target 108, and determining one or more characteristics (e.g., position or velocity) of the target 108.
[0016] Figure 1-2 The simulation environment 100-2 depicted in Figure 1-1 1. Radar simulator 126 simulates radar system 102 traveling on road model 130, which may be modeled after road 106, having the same geometric profile as road 106. Similar to radar system 102, radar simulator 126 travels along route 134 on road 130 toward target 132 during simulation.
[0017] The radar simulator 126 models the hardware and / or software of the radar system 102 so that the performance of the radar system 102 can be evaluated for a given simulated environment. The radar simulator 126 can be used, for example, to evaluate different system designs (e.g., different hardware configurations or different operating modes), test different versions of the radar software 124, or verify requirements throughout the development cycle of the radar system 102. Using the radar simulator 126 enables design or implementation problems within the radar system 102 to be quickly discovered during design, integration, and testing before field testing is performed.
[0018] The radar simulator 126 performs operations to simulate the radar system's hardware (e.g., antenna 116 and / or portions of MMIC 118), the radar software 124 executed by the processor 120, or a combination thereof. The radar simulator 126 may also account for non-ideal characteristics of the radar system 102 or environment 100-1, such as noise or nonlinearity. Specifically, the radar simulator 126 may model phase noise, waveform nonlinearity, and uncorrelated noise within the MMIC 118. With these capabilities, the radar simulator 126 may have a noise floor and dynamic range similar to that of the radar system 102.
[0019] The radar simulator 126 includes at least one processor 136 and a CRM 138. The CRM 138 may be implemented by one or more memory devices capable of persistent and / or non-transient data storage. In some cases, the processor 136 and the CRM 138 are packaged together within an integrated circuit or on a printed circuit board. In other cases, the processor 136 and the CRM 138 may be implemented separately and operably coupled together so that the processor 136 can access instructions stored by the CRM 138.
[0020] The CRM 138 includes at least one interface module 140 and at least one radar hardware simulator 142. Optionally, the CRM 138 may also include at least one radar software simulator 144. The interface module 140, the radar hardware simulator 142, and the radar software simulator 144 may be implemented using hardware, software, firmware, or a combination thereof. In this example, the processor 136 implements the interface module 140, the radar hardware simulator 142, and the radar software simulator 144.
[0021] Interface module 140 enables radar simulator 126 to process environmental response data provided by electromagnetic simulator 146. Generally speaking, interface module 140 transforms the environmental response data into a form usable by radar hardware simulator 142. In some cases, interface module 140 adjusts the environmental response data to account for the antenna response of antenna 116.
[0022] The radar hardware simulator 142 models the MMIC 118. Specifically, the radar hardware simulator 142 performs operations that simulate waveform generation, modulation, demodulation, multiplexing, amplification, frequency conversion, filtering, and / or analog-to-digital conversion operations performed by the MMIC 118. In other words, the radar hardware simulator 142 performs the operations of the MMIC 118, which occur between the processor 120 and the antenna 116. The radar hardware simulator 142 can take into account the dynamic range of the radar system 102, as well as the presence of nonlinear effects and noise. The radar hardware simulator 142 can be used to verify different hardware configurations and operating modes of the radar system 102.
[0023] The radar software simulator 144 models the radar software 124 of the radar system 102. Specifically, the radar software simulator 144 performs digital baseband processing operations that simulate the operations performed by the processor 120. These operations may include Fourier transforms (e.g., fast Fourier transforms), noise floor estimation, clutter map generation, constant false alarm rate thresholding, object detection, and object position estimation (e.g., digital beamforming). In some cases, the radar software simulator 144 includes a version of the radar software 124. In this way, the radar simulator 126 can be used to verify software requirements and evaluate different software versions of the radar system 102.
[0024] During operation, radar simulator 126 receives electromagnetic response data from electromagnetic simulator 146 and generates a radar report. The radar report can be used to evaluate the performance of radar system 102 for a given simulated environment. By providing accurate electromagnetic response data, electromagnetic simulator 146 can enable the performance of radar system 102 to be reliably evaluated.
[0025] The electromagnetic simulator 146 includes at least one processor 148 and a CRM 150. The CRM 150 may be implemented by one or more memory devices capable of persistent and / or non-transient data storage. In some cases, the processor 148 and the CRM 150 are packaged together within an integrated circuit or on a printed circuit board. In other cases, the processor 148 and the CRM 150 may be implemented separately and operably coupled together so that the processor 148 can access instructions stored by the CRM 150.
[0026] CRM 150 includes an electromagnetic response module 152. Electromagnetic response module 152 may include instructions that, when executed, cause processor 148 to execute instructions to generate an electromagnetic response in simulation environment 100-2. Specifically, electromagnetic response module 152 may include instructions that cause processor 148 to adaptively emit rays, trace rays (including reflections of rays from target 132), and calculate an electromagnetic response for each of the traced rays. Example System
[0027] Figure 2 An example flow chart 200 of data from an electromagnetic simulator 146 associated with electromagnetic response simulation for an arbitrary road surface profile in accordance with the techniques of this disclosure is shown. The electromagnetic simulator 146 (e.g., simulation model) evaluates propagation and scattering effects of simulated electromagnetic signals (such as radio frequency signals). Generally, the electromagnetic simulator 146 evaluates one or more propagation paths that originate from a reference point and return to a reference point within the simulation environment 100-2. Example types of propagation paths may include direct line-of-sight paths (e.g., direct path 112) or indirect paths associated with multipath (e.g., multipath 114) propagation.
[0028] During operation, the electromagnetic simulator 146 determines the characteristics of different propagation paths within the simulated environment 100-2. As input, the electromagnetic simulator 146 receives traffic scene data 202 (including the road profile of the road 130 (e.g., the geometric profile of the road surface)), as well as the position and orientation of both the electromagnetic sensor (e.g., the radar simulator 126, in particular the position of the simulated antenna) and the target 132. The road profile may include height changes in both the lateral direction and the longitudinal direction. As another input, the electromagnetic simulator 146 receives radar parameters 204. These parameters may include the operating frequency and field of view of the simulated sensor, as well as other parameters.
[0029] The geometric profile of the road surface may be based on real-world road profiles measured by sensors such as global navigation satellite system sensors or inertial measurement unit sensors. The real-world measurements may be used to verify the accuracy of the simulated rays generated by the electromagnetic simulator 146 .
[0030] The electromagnetic response module 152 receives traffic scene data 202 and radar parameters 204. An optimization algorithm such as the maximum likelihood method is used to estimate the reflection point of the electromagnetic energy on the surface of the road 130. Since the road 130 may have elevation changes, the position and orientation of the electromagnetic sensor and the target 132 are converted from the global coordinate system to the local coordinate system relative to the corresponding reflection point. In the corresponding local coordinate system, the electromagnetic response module 152 uses the bouncing ray (SBR) method to calculate the radar response. In some cases, this is a modified SBR method that uses image theory to more accurately calculate the multipath response. The electromagnetic response module 152 generates simulated electromagnetic rays 206 based on the calculated electromagnetic response, and removes repeated simulated rays 206. The remaining simulated rays 206 can be output to an electromagnetic sensor simulator (e.g., a radar simulator 126). In this way, the radar simulator can more accurately simulate the measurement values of the radar system without increasing the computing resources required to generate the simulation. Example Implementation
[0031] Figure 3 A non-flat road scenario according to the techniques of the present disclosure is shown, in which electromagnetic response simulation for arbitrary road surface profiles is applicable. The road in the simulation model has a geometric profile with elevation changes (e.g., z direction) in both the lateral (e.g., x direction) and longitudinal (e.g., y direction) directions relative to the radar sensor 304. The geometry of the road surface can be represented by a height function of x and y in global coordinates: s(x, y). The position and orientation of the radar sensor 304 and the target 306 can also be described relative to the global coordinate system. The position of the radar sensor 304 is represented as The reference position of target 306 is represented as It can be estimated on the road 302 that = potential ray reflection locations 308. Since the road profile can be arbitrary, there is no analytical solution to directly find the reflection locations 308. The search problem can be transformed into an optimization problem. For any given point on the road surface Normal vector It can be calculated based on its neighboring positions. Based on image theory, the image position of radar sensor 304 is given by the following formula:
[0032] Using geometric optics, ray 312 can be Tracked The intersection point 314 of the reflected ray 316 can be found on the xz plane 318 (denoted as ), the xz plane 318 contains Where P′ y =P y The other two coordinates of the intersection point 314 can be given by the following formula: If the point is a reflection point on the road, then Equation 4 should satisfy: F is the cost function, and the goal of the optimization problem is to search the xy plane to minimize F: Then, you can use Figure 4-1 to Figure 4-3 The described optimization algorithm is used to find the reflection position
[0033] Figure 4-1 to Figure 4-3 An example optimization algorithm 400 is shown that can be used for electromagnetic response simulation for arbitrary road surface profiles according to the techniques of the present disclosure. At step 402, as Figure 4-2 As shown, based on the orientation of radar 418 traveling along route 420 toward target 422 To define a rectangular search xy area 416. A smaller rectangular search xy area may be defined to reduce computation time.
[0034] At 404, a cost function map is calculated for the entire search area based on Equation 4. The cost function map associates the intersection point (e.g., intersection point 314) with the location of target 422 (e.g., location of target 306). ) related.
[0035] At 406, all local minima in the search xy region 416 and the global minimum are determined within the search region 416 based on Equation 5, and at 408, the global minimum is compared to a threshold. The threshold may have a small value, such as one or two centimeters. If the global minimum is greater than the threshold, then at 412, the coordinates of the reflection point 426 (e.g., a single valid reflection point) associated with the global minimum and the corresponding normal vector are recorded. As in Figure 4-3 If the global minimum is less than or equal to the threshold, the coordinates of the reflection point 426 and the corresponding normal vector associated with each local minimum less than or equal to the threshold are recorded.
[0036] At 414, the position and orientation of radar 418 and target 422 are transformed into the respective local coordinate systems of recorded reflection points 426. Figure 4-3 This transformation is described in more detail.
[0037] like Figure 4-3 As shown, the original z direction is the global vector of each corresponding reflection point 426 In each local coordinate system associated with the corresponding reflection point 426, the new z direction is along the normal vector and the new x direction is along the tangent vector Tangent vector Derived from: Normal vector and the global vector The angle between is denoted as θ, and The rotation matrices that transform the global coordinates 432 and 434 associated with the radar 418 and the target 422, respectively, are given by: Then, for example, the position and orientation of the target in the local coordinate system can be given by: This data can be fed to an image theory based SBR method to compute simulated rays. For one target, thousands to millions of rays may be required in an SBR simulation, but this optimization process only needs to be performed once because we can assume that the road surface is locally flat, so the computational burden may not increase much, and the data processing can be the same as traditional methods that do not include the ability to estimate reflection points on a road surface with elevation changes. By adding this capability, the simulated electromagnetic response produced by the techniques described in this document can be closer to the electromagnetic response measured in a real-world environment with little or no sacrifice in processing speed. Example Method
[0038] Figure 5 An example method 500 for electromagnetic response simulation of arbitrary road surface profiles according to the technology of the present disclosure is shown. The method 500 is shown as a plurality of sets of operations (or actions) being performed, but is not necessarily limited to the order or combination of operations shown herein. In addition, any one or more operations may be repeated, combined or reorganized to provide other methods.
[0039] At 502, an electromagnetic response simulator receives the position and orientation of an electromagnetic sensor and a target. The orientation of the radar and the target may be relative to each other. The position and orientation may be provided in a global coordinate system of the simulated environment.
[0040] At 504, the electromagnetic response simulator receives a geometric profile of the road surface (eg, a road profile). The elevation of the geometric profile may vary in both the lateral and longitudinal directions. That is, the elevation in the z direction may vary in the xy plane.
[0041] At 506, the electromagnetic response simulator estimates the reflection points of the electromagnetic rays along the geometric contour of the road surface. The simulator can achieve this by defining a rectangular search area (e.g., in the xy plane) based on the position and orientation of the electromagnetic sensor and the target. A cost function for the search area can then be calculated. Based on the cost function, all local minima of the cost function and the global minimum of the cost function are found. Based on a comparison of the global minimum with a threshold, a valid reflection point corresponding to the global minimum or to each local minimum is determined. If the global minimum is greater than a threshold (e.g., one centimeter, two centimeters), the coordinates and normal vector associated with the global minimum are recorded. If the global minimum is less than or equal to the threshold, the coordinates and normal vector of each valid reflection point of each local minimum that is less than or equal to the threshold are recorded.
[0042] At 508, the electromagnetic response simulator transforms the position and orientation of the electromagnetic sensor and target into a local coordinate system for each estimated reflection point. Each local coordinate system is based on rotating the plane of the estimated reflection point so that the global z direction is aligned with the normal vector of the estimated reflection point. The rotation matrix can then be used to transform the position and orientation of the sensor and target into the local coordinate system.
[0043] At 510, the electromagnetic response simulator calculates the electromagnetic response based on the positions of the sensor and the target in each corresponding local coordinate system. The simulator may use an SBR method based on graph theory to perform the calculations.
[0044] The electromagnetic response simulator collects simulated rays corresponding to the calculated electromagnetic responses at 512. Any duplicate rays may be discarded.
[0045] At 514, the electromagnetic response simulator outputs the simulated rays to an electromagnetic sensor simulator, such as a radar simulator. In this manner, the simulated rays may be more closely compared to measured rays in a real-world environment than simulated rays generated by a simulator that does not account for elevation changes in the road surface. Furthermore, the techniques described herein may not increase the computational complexity required to generate the rays, thereby resulting in a significant increase in processing time. Additional Examples
[0046] Some additional examples for simulation of electromagnetic response of arbitrary road surface profiles are provided below.
[0047] Example 1: A method, comprising: receiving, by an electromagnetic response simulator, a position and orientation of an electromagnetic sensor and a target; receiving, by the electromagnetic response simulator, a geometric profile of a road surface; using, by the electromagnetic response simulator, an optimization algorithm to estimate, by the electromagnetic response simulator, a reflection point of electromagnetic rays along the geometric profile of the road surface; converting, by the electromagnetic response simulator, the position and orientation of the electromagnetic sensor and the target into a local coordinate system of each estimated reflection point; calculating, by the electromagnetic response simulator, an electromagnetic response based on the position of the electromagnetic sensor and the target in the corresponding local coordinate system of each estimated reflection point; collecting, by the electromagnetic response simulator, simulated rays corresponding to the electromagnetic response; and outputting, by the electromagnetic response simulator, the simulated rays to an electromagnetic sensor simulator for simulating an electromagnetic sensor system.
[0048] Example 2: The method of Example 1, wherein the geometric profile of the road surface includes changes in elevation of the road surface.
[0049] Example 3: The method of any of the preceding examples, wherein the geometric profile of the road surface includes changes in elevation of the road surface.
[0050] Example 4: The method of any of the preceding examples, wherein the change in elevation of the road surface is in a longitudinal direction relative to the position and orientation of the electromagnetic sensor and the target.
[0051] Example 5: The method of any of the preceding examples, wherein the geometric profile of the road surface is based on sensor measurements of the road surface used to verify the accuracy of the simulated rays.
[0052] Example 6: The method of any of the preceding examples, wherein the sensor measurements include: measurements based on a global navigation satellite system sensor; or measurements based on an inertial measurement unit sensor.
[0053] Example 7: The method of any of the preceding examples, wherein using an optimization algorithm to estimate reflection points along a geometric contour of a road model comprises: defining a rectangular search area based on the position and orientation of an electromagnetic sensor and a target; calculating a cost function of the search area; finding all local minima of the cost function and a global minimum of the cost function; determining valid reflection points corresponding to the global minimum or to each local minimum based on a comparison of the global minimum with a threshold; and recording the coordinates and normal vector of each valid reflection point.
[0054] Example 8: The method of any of the preceding examples, wherein determining the valid reflection point corresponding to the global minimum or corresponding to each local minimum based on comparison of the global minimum with a threshold comprises: determining a single valid reflection point corresponding to the global minimum based on the global minimum being greater than the threshold; or determining a valid reflection point corresponding to each local minimum based on the global minimum being less than or equal to the threshold.
[0055] Example 9: The method of any of the preceding examples, wherein using an optimization algorithm to estimate reflection points along a geometric profile of the road model is performed once for a corresponding target.
[0056] Example 10: The method of any of the preceding examples, wherein calculating the electromagnetic response comprises: calculating the electromagnetic response using a bouncing ray method.
[0057] Example 11: The method of any of the preceding examples, wherein the bouncing ray method is further based on image theory.
[0058] Example 12: The method of any of the preceding examples, wherein collecting simulated rays corresponding to the electromagnetic response further comprises: removing duplicate simulated rays.
[0059] Example 13: The method of any of the preceding examples, wherein: the electromagnetic sensor simulator comprises a radar simulator; and the electromagnetic sensor system comprises a radar system.
[0060] Example 14: A system, comprising: at least one processor, wherein the at least one processor is configured to: receive a position and orientation of an electromagnetic sensor and a target; receive a geometric profile of a road surface; use an optimization algorithm to estimate reflection points of electromagnetic rays along the geometric profile of the road surface; convert the position and orientation of the electromagnetic sensor and the target into a local coordinate system for each estimated reflection point; calculate an electromagnetic response based on the position of the electromagnetic sensor and the target in the corresponding local coordinate system of each estimated reflection point; collect simulated rays corresponding to the electromagnetic response; and output the simulated rays to an electromagnetic sensor simulator for simulating an electromagnetic sensor system.
[0061] Example 15: The system of any of the preceding examples, wherein the geometric profile of the road surface includes changes in elevation of the road surface.
[0062] Example 16: The system of any of the preceding examples, wherein the change in elevation of the road surface is in a lateral direction relative to the position and orientation of the electromagnetic sensor and the target.
[0063] Example 17: The system of any of the preceding examples, wherein the change in elevation of the road surface is in a longitudinal direction relative to the position and orientation of the electromagnetic sensor and the target.
[0064] Example 18: A system of any of the preceding examples, wherein the processor is configured to estimate reflection points along a geometric contour of a road model using an optimization algorithm by at least: defining a rectangular search area based on the position and orientation of the electromagnetic sensor and the target; calculating a cost function for the search area; finding all local minima of the cost function and a global minimum of the cost function; determining valid reflection points corresponding to the global minimum or to each local minimum based on a comparison of the global minimum with a threshold; and recording the coordinates and normal vector of each valid reflection point.
[0065] Example 19: The system of any of the preceding examples, wherein the processor is configured to determine a valid reflection point corresponding to the global minimum or to each local minimum based on a comparison of the global minimum with a threshold in at least the following manner: based on the global minimum being greater than the threshold, determining a single valid reflection point corresponding to the global minimum; or based on the global minimum being less than or equal to the threshold, determining a valid reflection point corresponding to each local minimum.
[0066] Example 20: A computer-readable medium comprising instructions that, when executed, cause a processor to: receive a position and orientation of an electromagnetic sensor and a target; receive a geometric profile of a road surface; use an optimization algorithm to estimate reflection points of electromagnetic rays along the geometric profile of the road surface; convert the position and orientation of the electromagnetic sensor and the target into a local coordinate system for each estimated reflection point; calculate an electromagnetic response based on the position of the electromagnetic sensor and the target in the corresponding local coordinate system of each estimated reflection point; collect simulated rays corresponding to the electromagnetic response; and output the simulated rays to an electromagnetic sensor simulator for simulating an electromagnetic sensor system. Conclusion
[0067] Although various embodiments of the present disclosure are described in the foregoing description and shown in the accompanying drawings, it should be understood that the present disclosure is not limited thereto, but may be implemented into practice in various ways within the scope of the following claims. From the foregoing description, it will be apparent that various changes may be made without departing from the spirit and scope of the present disclosure as defined by the following claims. Problems associated with closely matching simulated electromagnetic responses to real-world measurements may arise in other systems. Therefore, although described as a way to incorporate elevation changes of a road into an electromagnetic response simulator, the techniques described above may be applied to other systems that would benefit from including uneven surfaces in the generation of simulated electromagnetic responses. In addition, these techniques may also be applied to any system where electromagnetic response simulation is desired.
[0068] Unless the context clearly dictates otherwise, the use of "or" and grammatically related terms represents unlimited, non-exclusive alternatives. As used herein, a phrase referring to "at least one" of a list of items refers to any combination of those items, including individual members. As an example, "at least one of a, b, or c" is intended to cover: a, b, c, ab, ac, bc, and abc, as well as any combination with multiple identical elements (e.g., aa, aaa, aab, aac, abb, acc, bb, bbb, bbc, cc, and ccc, or any other ordering of a, b, and c).
Claims
1. A method, comprising: receiving the position and orientation of the electromagnetic sensor and the target by the electromagnetic response simulator; Receiving, by the electromagnetic response simulator, a geometric profile of a road surface; estimating, by the electromagnetic response simulator, reflection points of electromagnetic rays along the geometric contour of the road surface using an optimization algorithm; converting the position and orientation of the electromagnetic sensor and the target into a local coordinate system of each estimated reflection point by the electromagnetic response simulator; calculating, by the electromagnetic response simulator, an electromagnetic response based on positions of the electromagnetic sensor and the target in a corresponding local coordinate system at each estimated reflection point; The electromagnetic response simulator collects simulated rays corresponding to the electromagnetic response; as well as The electromagnetic response simulator outputs the simulated ray to an electromagnetic sensor simulator for simulating an electromagnetic sensor system.
2. The method according to claim 1, characterized in that The geometric profile of the road surface includes changes in elevation of the road surface.
3. The method according to claim 2, characterized in that The change in elevation of the road surface is in a lateral direction relative to the position and orientation of the electromagnetic sensor and the target.
4. The method according to claim 2, characterized in that The change in elevation of the road surface is in a longitudinal direction relative to the position and orientation of the electromagnetic sensor and the target.
5. The method according to claim 1, characterized in that The geometric profile of the road surface is based on sensor measurements of the road surface used to verify the accuracy of the simulated rays.
6. The method according to claim 5, characterized in that The sensor measurements include: Measurements based on global navigation satellite system sensors; or Measurements based on inertial measurement unit sensors.
7. The method according to claim 1, characterized in that Using the optimization algorithm to estimate reflection points along the geometric profile of the road model includes: defining a rectangular search area based on the position and orientation of the electromagnetic sensor and the target; Calculating a cost function for the search area; Find all local minima of the cost function and a global minimum of the cost function; Determining a valid reflection point corresponding to the global minimum value or to each local minimum value based on a comparison of the global minimum value with a threshold value; and Record the coordinates and normal vector of each valid reflection point.
8. The method according to claim 7, characterized in that Determining a valid reflection point corresponding to the global minimum value or corresponding to each local minimum value based on the comparison between the global minimum value and the threshold value comprises: Based on the fact that the global minimum value is greater than the threshold value, determining a single valid reflection point corresponding to the global minimum value; or Based on the global minimum being less than or equal to the threshold, a valid reflection point corresponding to each local minimum is determined.
9. The method according to claim 1, characterized in that Estimating reflection points along the geometric profile of the road model using the optimization algorithm is performed once for a corresponding target.
10. The method according to claim 1, characterized in that Calculation of electromagnetic response includes: The electromagnetic response is calculated using a bouncing ray method.
11. The method according to claim 10, characterized in that The bouncing ray method is further based on image theory.
12. The method according to claim 1, characterized in that Collecting the simulated rays corresponding to the electromagnetic response further comprises: Remove duplicate simulation rays.
13. The method of claim 1, wherein: The electromagnetic sensor simulator comprises a radar simulator; and The electromagnetic sensor system includes a radar system.
14. A system, comprising: at least one processor configured to: receiving the position and orientation of the electromagnetic sensor and the target; receiving a geometric profile of a road surface; using an optimization algorithm to estimate reflection points of electromagnetic radiation along the geometric contour of the road surface; transforming the position and orientation of the electromagnetic sensor and the target into a local coordinate system for each estimated reflection point; calculating an electromagnetic response based on the positions of the electromagnetic sensor and the target in respective local coordinate systems at each estimated reflection point; collecting simulated rays corresponding to the electromagnetic response; as well as The simulated rays are output to an electromagnetic sensor simulator for simulating an electromagnetic sensor system.
15. The system of claim 14, wherein: The geometric profile of the road surface includes changes in elevation of the road surface.
16. The system of claim 15, wherein: The change in elevation of the road surface is in a lateral direction relative to the position and orientation of the electromagnetic sensor and the target.
17. The system of claim 15, wherein: The change in elevation of the road surface is in a longitudinal direction relative to the position and orientation of the electromagnetic sensor and the target.
18. The system of claim 14, wherein: The processor is configured to estimate reflection points along the geometric profile of the road model using the optimization algorithm by at least: defining a rectangular search area based on the position and orientation of the electromagnetic sensor and the target; Calculating a cost function for the search area; Find all local minima of the cost function and a global minimum of the cost function; Determining a valid reflection point corresponding to the global minimum value or to each local minimum value based on a comparison of the global minimum value with a threshold value; and Record the coordinates and normal vector of each valid reflection point.
19. The system of claim 18, wherein: The processor is configured to determine a valid reflection point corresponding to the global minimum or to each local minimum based on a comparison of the global minimum with a threshold value by at least: Based on the fact that the global minimum value is greater than the threshold value, determining a single valid reflection point corresponding to the global minimum value; or Based on the global minimum being less than or equal to the threshold, a valid reflection point corresponding to each local minimum is determined.
20. A computer readable medium comprising instructions which, when executed, cause a processor to: receiving the position and orientation of the electromagnetic sensor and the target; receiving a geometric profile of a road surface; using an optimization algorithm to estimate reflection points of electromagnetic radiation along the geometric contour of the road surface; transforming the position and orientation of the electromagnetic sensor and the target into a local coordinate system for each estimated reflection point; calculating an electromagnetic response based on the positions of the electromagnetic sensor and the target in respective local coordinate systems at each estimated reflection point; collecting simulated rays corresponding to the electromagnetic response; as well as The simulated rays are output to an electromagnetic sensor simulator for simulating an electromagnetic sensor system.