DEVICE, SYSTEM AND METHOD FOR RADAR SIMULATION

Abstract

For example, a radar simulator may be configured to determine simulated radar information corresponding to a simulated scene for a simulated radar system, for example, by processing simulated scene information corresponding to the simulated scene, for example, based on a path loss model and one or more point spread functions (PSFs). For example, the path loss model may represent path loss of radar signals transmitted by one or more transmitters of the simulated radar system and received by one or more receivers of the simulated radar system. For example, the one or more PSFs may correspond to one or more radar processing methods applied by the simulated radar system. For example, the radar simulator may be configured to provide an output based on the simulated radar information.

Description

CROSS-REFERENCE

[0001] This application claims the benefit of and priority to U.S. Provisional Patent Application No. 63 / 621,491, entitled "APPARATUS, SYSTEM, AND METHOD OF SIMULATION TESTING," filed January 16, 2024, the entire disclosure of which is incorporated herein by reference. BACKGROUND

[0002] Simulation testing techniques can be used to test and validate control systems, for example vehicle control systems and / or any other control systems.

[0003] For example, software-in-the-loop (SIL) testing techniques can be used for testing and validating software, e.g., vehicle control systems and / or any other systems, to quickly and cost-effectively identify any problems and / or to improve the quality of the software.

[0004] For example, hardware-in-the-loop (HIL) testing techniques can be used to validate electronic control units (ECUs), e.g., automotive ECUs, using simulation and / or modeling techniques, e.g., to reduce test times and / or increase test coverage. BRIEF DESCRIPTION OF THE DRAWINGS

[0005] For simplicity and clarity, the elements depicted in the figures are not necessarily drawn to scale. For example, the dimensions of some elements may be exaggerated relative to others for clarity. Furthermore, reference numbers may be repeated in the figures to indicate corresponding or analogous elements. The figures are listed below. Fig. Figure 1 shows a schematic block diagram illustration of a system according to some demonstrative aspects. Fig.Figure 2 shows a schematic illustration of the components and operations of a system for simulation testing, according to some demonstrative aspects. Fig. Figure 3 shows a schematic illustration of a method for generating simulated radar information according to some demonstrative aspects. Fig. 4A and Fig. 4B show schematic illustrations of a radar simulation technique for simulating radar information according to some demonstrative aspects. Fig. Figure 5 shows a schematic illustration of a radar simulation path and a complete radar signal level simulation path, according to some demonstrative aspects. Fig. Figure 6 shows a schematic illustration of a method for radar simulation according to some demonstrative aspects. Fig. Figure 7 shows a schematic illustration of a product according to some demonstrative aspects. DETAILED DESCRIPTION

[0006] In the following detailed description, numerous specific details are provided in order to provide a thorough understanding of some aspects. However, those skilled in the art will understand that some aspects may be practiced without these specific details. In other instances, well-known methods, procedures, components, units, and / or circuits have not been described in detail to avoid obscuring the discussion.

[0007] Some sections of the following detailed description are presented in terms of algorithms and symbolic representations of operations on data bits or binary digital signals within a computer memory. These algorithmic descriptions and representations may be techniques used by those skilled in the art to process data and communicate the substance of their work to others skilled in the art.

[0008] An algorithm is considered here and generally to be a self-consistent sequence of actions or operations leading to a desired result. These include physical manipulations of physical quantities. Usually, but not necessarily, these quantities are recorded in the form of electrical or magnetic signals that can be stored, sent, combined, compared, and otherwise manipulated. It has sometimes been found convenient, primarily for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. It should be understood, however, that all these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities.

[0009] Terms such as "processing", "calculating", "determining", "ascertaining", "analyzing", "testing" or the like may refer to the operation(s) and / or process(es) of a computer, computer platform, computer system, or other electronic computing device that manipulates and / or converts data represented as physical (e.g., electronic) quantities in the registers and / or memories of the computer into other data similarly represented as physical quantities in the registers and / or memories of the computer or other information storage medium that can store instructions for performing operations and / or processes.

[0010] The terms "variety" and "a plurality," as used herein, include, for example, "several" or "two or more." For example, "a plurality of items" includes two or more items.

[0011] The words "exemplary" and "demonstrative" are used herein to mean "by way of example, instance, demonstration, or illustration." Any aspect or design described herein as "exemplary" or "demonstrative" should not necessarily be construed as preferential or advantageous over any other aspect or design.

[0012] References to "an aspect", "an aspect", "demonstrative aspect", "various aspects", etc., mean that the aspect(s) so described may include a particular feature, structure, or property, but not every aspect necessarily includes the particular feature, structure, or property. Furthermore, repeated use of the phrase "in an aspect" does not necessarily refer to the same aspect, although it may.

[0013] As used herein, the use of the ordinal adjectives "first," "second," "third," etc., to describe a common object, unless otherwise noted, merely indicates that different instances of like objects are being referred to and is not intended to imply that the objects so described must be in any particular sequence, whether temporally, spatially, in order of precedence, or in any other way.

[0014] The terms "at least one" and "one or more" may be understood to include a numerical quantity greater than or equal to one, e.g., one, two, three, four, [...], etc. The phrase "at least one of" with respect to a group of items may be used herein to mean at least one item from the group of items. For example, the phrase "at least one of" with respect to a group of items may be used herein to mean one of the listed items, a plurality of one of the listed items, a plurality of individual listed items, or a plurality of a multiple of individual listed items.

[0015] The term "data" as used herein may be understood to include information in any suitable analog or digital form, e.g., provided as a file, as a portion of a file, as a set of files, as a signal or stream, as a portion of a signal or stream, as a set of signals or streams, and the like. Furthermore, the term "data" may also be used to refer to information, e.g., in the form of a pointer. However, the term "data" is not limited to the aforementioned examples and may take various forms and / or represent any information as understood in the art.

[0016] The terms "processor" or "controller" can be understood to include any type of technological unit capable of handling any suitable type of data and / or information. The data and / or information can be handled according to one or more specific functions performed by the processor or controller. Furthermore, a processor or controller can be understood to include any type of circuit, e.g., any type of analog or digital circuit.A processor or controller may be or include an analog circuit, a digital circuit, a mixed-signal circuit, a logic circuit, a processor, a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), a field-programmable gate array (FPGA), an integrated circuit, an application-specific integrated circuit (ASIC), or any combination thereof. Any other implementation of the respective functions, described in more detail below, may also be considered a processor, controller, or logic circuit.It is to be understood that two (or more) processors, controllers, or logic circuits described herein may be implemented as a single unit with equivalent functionality or the like, and conversely, that any individual processor, controller, or logic circuit described herein may be implemented as two (or more) separate units with equivalent functionality or the like.

[0017] The term "memory" refers to a computer-readable medium (e.g., a non-transitory computer-readable medium) in which data or information can be stored for retrieval. References to "memory" may be understood to include volatile or non-volatile memory, including random-access memory (RAM), read-only memory (ROM), flash memory, solid-state memory, hard disk drive, optical drive, and others, or any combination thereof. Registers, shift registers, processor registers, data buffers, among others, are also summarized herein under the term "memory." The term "software" may be used to refer to any type of executable instruction and / or logic, including firmware.

[0018] A "vehicle" can include any type of powered object. For example, a vehicle can be a powered object with an internal combustion engine, an electric motor, a reaction engine, an electrically powered object, a hybrid powered object, or a combination thereof. A vehicle can be or include an automobile, a bus, a minibus, a van, a truck, a camper van, a vehicle trailer, a motorcycle, a bicycle, a tricycle, a train locomotive, a train car, a moving robot, a personnel carrier, a boat, a ship, a submersible, a submarine, a drone, an aircraft, a rocket, and many more.

[0019] A “land vehicle” includes any type of vehicle configured to move on the ground, such as a road, path, track, one or more rails, off-road, or the like.

[0020] An "autonomous vehicle" can describe a vehicle capable of implementing at least one navigation change without driver input. A navigation change can describe or include a change in steering, braking, acceleration / deceleration, or any other operation related to the vehicle's movement. A vehicle can be described as autonomous even if it is not fully autonomous, for example, if it operates with or without driver input. Autonomous vehicles can include vehicles that can operate under driver control during certain periods and without driver control during other periods.Additionally or alternatively, autonomous vehicles may include vehicles that control only some aspects of vehicle navigation, such as steering to maintain a vehicle course between lane boundaries, or some steering actions under certain circumstances, e.g., not under all circumstances, but leave other aspects of vehicle navigation to the driver, e.g., braking or deceleration under certain circumstances. Additionally or alternatively, autonomous vehicles may include vehicles that jointly control one or more aspects of vehicle navigation under certain circumstances, e.g., "hands-on," i.e., in response to driver input; and / or vehicles that control one or more aspects of vehicle navigation under certain circumstances, e.g., "hands-off," i.e., independent of driver input.Additionally or alternatively, autonomous vehicles may include vehicles that control one or more aspects of vehicle navigation under specific circumstances, such as specific environmental conditions, e.g., spatial areas, roadway conditions, or the like. In some aspects, autonomous vehicles may assume control of some or all aspects of braking, speed control, steering, and / or other additional operations of the vehicle. An autonomous vehicle may include those vehicles that can drive without a driver. A vehicle's level of autonomy may be described or determined by the vehicle's Society of Automotive Engineers (SAE) level, e.g., as defined by the SAE, for example, in SAE J3016 2018: Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles, or by other relevant professional organizations.The SAE level can have a value ranging from a minimum level, e.g., Level 0 (essentially no automation of driving), to a maximum level, e.g., Level 5 (essentially full automation of driving).

[0021] An “assisted vehicle” can describe a vehicle that is capable of informing a driver or occupants of the vehicle about collected data or information derived from it.

[0022] The term "vehicle operating data" may be understood to describe any type of characteristic related to the operation of a vehicle. For example, "vehicle operating data" may describe the condition of the vehicle, such as the type of tires the vehicle has, the type of vehicle, and / or the age of manufacture of the vehicle. In general, the term "vehicle operating data" may describe or include static characteristics or static vehicle operating data (e.g., characteristics or data that do not change over time). As another example, additionally or alternatively, "vehicle operating data" may describe or include characteristics that change during the operation of the vehicle, for example, environmental conditions, such as weather conditions or road conditions during operation of the vehicle, fuel levels, fluid levels, operating parameters of the vehicle's power source, or the like.In general, the term “vehicle operating data” may describe or include different characteristics or varying vehicle operating data (e.g., time-varying characteristics or data).

[0023] Some aspects may be used in connection with various devices and systems, for example, with a radar sensor, a radar device, a radar system, a vehicle, a vehicle system, an autonomous vehicle system, a vehicle communication system, a vehicle device, an airborne platform, a waterborne platform, road infrastructure, sports infrastructure, city surveillance infrastructure, static infrastructure platforms, indoor platforms, moving platforms, robotic platforms, industrial platforms, a sensor device, a user equipment (UE), a mobile device (MD), a wireless station (STA), a sensor device, a non-vehicular device, a mobile or portable device, and the like.

[0024] Some aspects may be used in connection with radio frequency (RF) systems, radar systems, vehicle radar systems, autonomous systems, robotic systems, detection systems, or the like.

[0025] Some demonstrative aspects may be used in connection with an RF frequency in a frequency band having a starting frequency above 10 gigahertz (GHz), for example, a frequency band with a starting frequency between 10 GHz and 120 GHz. For example, some demonstrative aspects may be used in connection with an RF frequency having a starting frequency above 30 GHz, for example, above 45 GHz, e.g., above 60 GHz. For example, some demonstrative aspects may be used in connection with an automotive radar frequency band, e.g., a frequency band between 76 GHz and 81 GHz. However, other aspects may also be implemented in other suitable frequency bands, for example, in a frequency band above 140 GHz, a frequency band of 300 GHz, a sub-terahertz (THz) band, a THz band, an infrared (IR) band, and / or another frequency band.

[0026] As used herein, the term "circuitry" may refer to, be part of, or include an application-specific integrated circuit (ASIC), an integrated circuit, an electronic circuit, a processor (common, dedicated, or group) and / or memory (common, dedicated, or group) executing one or more software or firmware programs, a combinational logic circuit, and / or other suitable hardware components that provide the described functionality. In some cases, some functions of the circuitry may be implemented by one or more software or firmware modules. In some aspects, the circuitry may include logic operable at least partially in hardware.

[0027] The term "logic" may refer, for example, to computational logic embedded in the circuitry of a computing device and / or computational logic stored in a memory of a computing device. For example, a processor of the computing device may access the logic to execute the computational logic to perform computational functions and / or operations. For example, the logic may be embedded in various types of memory and / or firmware, e.g., in silicon blocks of various chips and / or processors. The logic may be included in and / or implemented as part of various circuitry, e.g., in radio circuitry, receive circuitry, control circuitry, receive circuitry, transceiver circuitry, processor circuitry, and / or the like.In one example, the logic may be embedded in volatile memory and / or non-volatile memory, including random access memory, read-only memory, programmable memory, magnetic memory, flash memory, persistent memory, and / or the like. The logic may be executed by one or more processors, using memory, e.g., registers, buffers, stacks, and the like, associated with the one or more processors, e.g., as required to execute the logic.

[0028] The term "communicate," as used herein with reference to a signal, includes sending the signal and / or receiving the signal. For example, a device capable of communicating a signal may include a transmitter to send the signal and / or a receiver to receive the signal. The verb "communicate" may be used with reference to the act of transmitting or receiving. For example, the phrase "communicate a signal" may refer to the sending of the signal by a transmitter and may not necessarily include the receiving of the signal by a receiver. In another example, the phrase "communicate a signal" may refer to the receiving of the signal by a receiver and may not necessarily include the sending of the signal by a transmitter.

[0029] Some demonstrative aspects are described here with respect to RF radar signals. However, other aspects may be implemented with respect to or in conjunction with other radar signals, wireless signals, IR signals, acoustic signals, optical signals, wireless communication signals, communication schemes, networks, standards, and / or protocols. For example, some demonstrative aspects may be implemented with respect to systems, such as light detection systems (LiDAR) and / or sonar systems, that utilize light and / or acoustic signals.

[0030] For example, some aspects may take the form of a complete hardware aspect, a complete software aspect, or an aspect including both hardware and software elements. Some aspects may be implemented in software, including, but not limited to, firmware, resident software, microcode, or the like.

[0031] Furthermore, some aspects may take the form of a computer program product accessible from a computer-usable or computer-readable medium that provides program code for use by or in connection with a computer or any instruction execution system. For example, a computer-usable or computer-readable medium may be or include any device that can contain, store, communicate, distribute, and / or transport the program for use by or in connection with the instruction execution system, device, and / or apparatus.

[0032] In some aspects, the medium may be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or device or apparatus) or a distribution medium.

[0033] In some demonstrative aspects, a data processing system capable of storing and / or executing program code may include at least one processor coupled directly or indirectly to storage elements, for example, via a system bus. The storage elements may include, for example, local memory used during actual execution of the program code, as well as mass storage and cache memory that enable temporary storage of at least a portion of the program code to reduce the number of code retrievals from mass storage during execution.

[0034] In some demonstrative aspects, input / output or I / O devices (including, but not limited to, keyboards, displays, pointing devices, etc.) may be coupled to the system either directly or through intermediate I / O controllers. In some demonstrative aspects, network adapters may be coupled to the system to enable the data processing system to be coupled to other data processing systems or remote printers or storage devices, for example, through intervening private or public networks. In some demonstrative aspects, modems, cable modems, and Ethernet cards are demonstrative examples of types of network adapters.

[0035] Other suitable components may also be used. Some aspects may include one or more wired or wireless connections, use one or more wireless communication components, use one or more wireless communication methods or protocols, or the like. Some aspects may use wired communication and / or wireless communication.

[0036] It will be Fig. 1, which schematically illustrates a system 100 according to some demonstrative aspects.

[0037] In some demonstrative aspects, the system 100 may include a simulator (also referred to as a "tester," "test simulator," or "test station") 102 that may be configured to test a controller under test 150, e.g., as described below.

[0038] In some demonstrative aspects, the simulator 102 may include a software-in-the-loop (SIL) simulator (also referred to as a "SIL tester" or "SIL test station") 102 that may be configured to test software and / or code of the controller under test 150, e.g., as described below.

[0039] In some demonstrative aspects, the simulator 102 may include a hardware-in-the-loop (HIL) simulator (also referred to as a "HIL tester" or "HIL test station") 102 that may be configured to test an electronic control unit (embedded control unit) in test 150, e.g., as described below.

[0040] In some demonstrative aspects, the controller in test 150 may include an automotive controller, e.g., as described below.

[0041] In some demonstrative aspects, the controller in test 150 may include a vehicle system controller for controlling one or more vehicle systems of a vehicle.

[0042] In some demonstrative aspects, the control in test 150 may include control of an autonomous vehicle or an assisted vehicle.

[0043] In some demonstrative aspects, the controller in test 150 may include an advanced driver assistance system (ADAS) and / or autonomous vehicle (AV) (ADAS / AV) controller that may be configured to control one or more ADAS / AV functions.

[0044] In some demonstrative aspects, the controller in test 150 may be implemented as part of a vehicle system, for example, a system that is implemented and / or installed in the vehicle.

[0045] For example, the controller in test 150 may be implemented as part of an autonomous vehicle system, an automated driving system, an assisted vehicle system, a driver assistance and / or support system, and / or the like.

[0046] In other aspects, the controller in test 150 may include any additional or alternative type of controller for use in any other suitable device and / or system, e.g., a robotic device or system, a drone device or system, or the like.

[0047] In some demonstrative aspects, one or more operations and / or functions of the simulator 102 may be implemented by one or more elements of a computing system including one or more computing devices 101.

[0048] For example, the computing device 101 may be implemented using suitable hardware components and / or software components, such as processors, controllers, memory units, storage units, input units, output units, communication units, operating systems, applications, or the like.

[0049] In some demonstrative aspects, computing device 101 may include, for example, one or more of a processor 191, an input device 192, an output device 193, a memory unit 194, and / or a storage unit 195. Computing device 101 may optionally include other suitable hardware components and / or software components. In some demonstrative aspects, some or all of the components of one or more computing devices 101 may be enclosed in a common housing or package and connected or operatively associated with one another using one or more wired or wireless connections. In other aspects, the components of computing component 101 may be distributed across multiple or separate devices.

[0050] In some demonstrative aspects, the processor 191 may include, for example, a central processing unit (CPU), a digital signal processor (DSP), a GPU, an FPGA, a microcontroller unit (MCU), one or more processor cores, a single-core processor, a dual-core processor, a multi-core processor, a microprocessor, a host processor, a controller, a plurality of processors or controllers, a chip, a microchip, one or more circuits, circuit logic, a logic unit, an integrated circuit (IC), an application-specific integrated circuit (ASIC), or any other suitable general-purpose or specific processor or controller.

[0051] In some demonstrative aspects, input device 192 may include, for example, a keyboard, a keypad, a mouse, a touchscreen, a touchpad, a trackball, a stylus, a microphone, or other suitable pointing device or input device. Output device 193 may include, for example, a monitor, a screen, a touchscreen, a light-emitting diode (LED) display, a flat panel display, a liquid crystal display (LCD) display, a plasma display, one or more audio speakers or headphones, or other suitable output devices.

[0052] In some demonstrative aspects, memory unit 194 may include, for example, random access memory (RAM), read-only memory (ROM), dynamic random access memory (DRAM), synchronous DRAM (SD-RAM), flash memory, volatile memory, non-volatile memory, cache memory, a buffer, a short-term storage unit, a long-term storage unit, or other suitable storage units. Storage unit 195 may include, for example, a hard disk drive, solid-state storage (SSD), or other suitable removable or non-removable storage units. For example, data processed by computing device 101 may be stored in memory unit 194 and / or storage unit 195.

[0053] In some demonstrative aspects, computing device 101 may be configured to communicate with one or more other communication devices over at least one network, e.g., a wireless and / or wired network.

[0054] In some demonstrative aspects, the network 103 may include a wired network, a communications bus, a local area network (LAN), a wireless LAN (WLAN) network, a radio network, a cellular network, a wireless fidelity (Wi-Fi) network, a Bluetooth (BT) network, and / or the like.

[0055] In some demonstrative aspects, computing device 101 may be configured to perform and / or execute one or more operations, modules, processes, procedures, and / or the like, e.g., as described below.

[0056] In some demonstrative aspects, one or more operations and / or functions of the simulator 102 may be implemented by at least one simulator application 107, which may be implemented by, as part of, and / or in the form of at least one service, module, and / or controller, e.g., as described below.

[0057] In some demonstrative aspects, the simulator application 107 may include or be implemented as software, a software module, an application, a program, a subroutine, instructions, an instruction set, a calculation code, words, values, symbols, and / or the like.

[0058] In some demonstrative aspects, the simulator application 107 may include a local application to be executed by the work device 101 implementing the simulator 102.

[0059] In some demonstrative aspects, the memory unit 194 and / or the storage unit 195 of the computing device 101 may store instructions that result in the simulator application 107, and / or the processor 191 may be configured to execute the instructions that result in the simulator application 107 and / or perform one or more calculations and / or processes of the simulator application 107, e.g., as described below.

[0060] In other aspects, the simulator application 107 may include a remote application to be executed by a suitable computing system, e.g., a server 170.

[0061] In some demonstrative aspects, the server 170 may include at least one of a remote server, a web-based server, a cloud server, and / or any other server.

[0062] In some demonstrative aspects, the computing device 101 implementing the simulator 102 may communicate with the server 170, for example, via the network 103.

[0063] In some demonstrative aspects, the server 170 may include a suitable memory and / or storage device 174 having instructions thereon that lead to the simulator application 107, and a suitable processor 171 to execute the instructions.

[0064] In some demonstrative aspects, the simulator application 107 may include a combination of a remote application and a local application.

[0065] In one example, the simulator application 107 may be downloaded and / or received by the computing device 101 from another computing system, e.g., the server 170, so that the simulator application 107 may be executed locally by the computing system 101 implementing the simulator 102. For example, some or all of the instructions of the simulator application 107 may be received and, e.g., temporarily stored in memory or any suitable short-term storage or buffer of the computing device 101 implementing the simulator 102, e.g., before being executed by the processor 191 of the computing device 101.

[0066] In another example, the simulator application 107 may include a front end (FE) 162 executed locally by the computing device 101 implementing the simulator 102, and a back end (BE) 164 executed by the server 170. For example, the front end 107 may include and / or be implemented as a local application, a web application, a website, a web client, e.g., a Hypertext Markup Language (HTML) web application, or the like.

[0067] For example, one or more first operations of the simulator application 107 may be performed locally, for example, by the computing device 101 implementing the simulator 102, and / or one or more second operations of the simulator application 107 may be performed remotely, for example, by the server 170.

[0068] In other aspects, the simulator application 107 may be included and / or implemented by any other suitable computing arrangement and / or scheme.

[0069] In some demonstrative aspects, the simulator 102 may be configured to perform one or more operations and / or functions of a simulation (test) mechanism, e.g., a synthetic test mechanism, which may be configured to provide a technical solution to support the validation of SW and / or HW solutions intended for production vehicles, e.g., as described below.

[0070] In some demonstrative aspects, the simulator 102 may be configured to perform one or more operations and / or functions of a simulation (test) mechanism that may be configured to provide a technical solution to simulate operations and / or functions with which the controller in test 150 may be configured to interact.

[0071] In some demonstrative aspects, the simulator 102 may be configured to perform one or more operations and / or functions of a simulation (test) mechanism, e.g., a SIL simulation (test) mechanism and / or a HIL simulation (test) mechanism, which may be configured to provide a technical solution to support testing and / or validation, e.g., of relatively complex systems.

[0072] In some demonstrative aspects, the SIL simulation (test) mechanism and / or a HIL simulation (test) mechanism can be implemented as part of a closed-loop decision system, e.g., a driving simulator. For example, in a closed-loop decision system, an action, e.g., a driving action, performed for a specific scenario of a scene in a particular frame can have an effect on the scene to be generated for a next frame.

[0073] In some demonstrative aspects, the simulator 102 may be configured to perform one or more operations and / or functions of a simulation (test) mechanism that may be configured to provide a technical solution to simulate operations and / or functions with which the controller in test 150 may be configured to interact.

[0074] For example, the simulation (test) mechanism may be configured to provide a technical solution to support the control in test 150 stimulated by the test station 102 using the exact same configuration, e.g., SW and / or HW, as will run in the vehicle after deployment to production.

[0075] In some demonstrative aspects, the simulation (test) mechanism may be configured to provide a technical solution to support the reliable injection of one or more sensor models, for example, under the constraint that the SW and / or HW configuration of the controller under test 150, which may be used, for example, to control the sensors, remains substantially untouched, for example, as described below.

[0076] In some demonstrative aspects, the simulator 102 may be configured to perform one or more operations and / or functions of a simulation (testing) mechanism that may be configured according to a simulation setup, e.g., as described below.

[0077] In some demonstrative aspects, the controller in test 150 may be connected to the simulation setup and may, for example, be performed without being able to distinguish between the tester 102 and the actual sensors, e.g., how they are connected when the controller in test 150 is actually deployed in the vehicle.

[0078] In some demonstrative aspects, such as Fig. 1, the simulator 102 may be configured according to a simulation setup, including a sensor simulator 111, e.g., as described below. Simulator 102 may also include additional components, units, and / or entities that are Fig.1 are not shown.

[0079] In some demonstrative aspects, the sensor simulator 111 may be configured to receive environmental information ("scene information") 130, for example, a three-dimensional (3D) description or a four-dimensional (4D) description (scene) of the environment ("world"), which may be provided, for example, by a suitable modeling component 119 (also referred to as a "scene simulator" or "environment (world) modeling component"). For example, the scene simulator 119 may provide the scene information 130 to the sensor simulator 111, for example, based on one or more control commands, e.g., vehicle control commands, provided by the controller under test 150.

[0080] In some demonstrative aspects, one or more, e.g., some or all, components and / or functions of the scene simulator 119 may be implemented as part of the simulator 102.

[0081] In other aspects, one or more, e.g., some or all, components and / or functions of the scene simulator 119 may be implemented separately from the simulator 102, e.g., by an external modeling device and / or unit.

[0082] In some demonstrative aspects, the sensor simulator 111 may include a radar simulator 110 configured to provide simulated radar information based on the scene information 130, e.g., as described below.

[0083] In some demonstrative aspects, the sensor simulator 111 may include one or more other sensor simulators (in Fig. 1 not shown) that may be configured to provide simulated sensor information corresponding to one or more other types of sensors, for example, based on the scene information 130, e.g., as described below.

[0084] It will also be Fig.2, which schematically illustrates components and operations of a system 200 for simulation testing that may be implemented according to some demonstrative aspects.

[0085] In some demonstrative aspects, a sensor simulator 211, e.g., sensor simulator 111 ( Fig. 1), be configured to represent a scene, e.g., according to one or more definitions of a sensor model to be simulated. For example, the sensor simulator 211 may receive scene information 231 of a simulated scene from a scene simulator 219, e.g., scene simulator 119 ( Fig. 1), received.

[0086] For example, the sensor simulator 111 ( Fig. 1) include one or more components of the sensor simulator 211 and / or the sensor simulator 111 ( Fig. 1) may be configured to perform one or more operations and / or functions of the sensor simulator 211.

[0087] In some demonstrative aspects, the sensor simulator 211 may be configured to provide simulated sensor information 239, e.g., including simulated radar information 233, to a controller under test 250, e.g., the controller under test 150 ( Fig. 1), to send.

[0088] In some demonstrative aspects, the sensor simulator 211 may be configured to provide the simulated sensor information 239, e.g., including the simulated radar information 233, to the controller under test 250 such that the controller under test 250 is unaware that the sensor simulator 211 is being used, e.g., instead of one or more real sensors.

[0089] In some demonstrative aspects, the controller in test 250 may receive and process the simulated sensor information 239 from the sensor simulator 211. For example, the controller in test 250 may generate one or more commands, e.g., based on the analysis of the simulated sensor information 239, e.g., including the simulated radar information 233, from the sensor simulator 211.

[0090] For example, in test 250, the controller may generate one or more vehicle control commands 235, e.g., based on the analysis of the simulated sensor information 239 from the sensor simulator 211.

[0091] For example, the controller in test 250 may generate sensor control commands 237, e.g., including radar control commands, to control one or more sensors, e.g., including a radar, and may transmit the sensor control commands 237, which may be intended for receipt by the one or more sensors, e.g., from the perspective of the controller in test 250.

[0092] In some demonstrative aspects, the sensor simulator 211 may include a radar simulator 210 or be configured to perform one or more functions and / or operations of a radar simulator, which may be configured to generate simulated radar data 233 for the controller in test 250, e.g., as described below.

[0093] For example, the radar simulator 110 ( Fig. 1) include one or more components of the radar simulator 210 and / or the radar simulator 110 ( Fig.1) may be configured to perform one or more operations and / or functions of the radar simulator 210.

[0094] In some demonstrative aspects, the sensor simulator 211 may include one or more other sensor simulators 213 or be configured to perform one or more functions and / or operations of one or more other sensor simulators. For example, the one or more sensor simulators 213 may include a light detection and ranging (LiDAR) sensor, an image sensor, and / or any other suitable type of sensor.

[0095] In some demonstrative aspects, the radar simulator 210 may be configured to process the simulated scene information 231 from the scene simulator 219. For example, the simulated scene information 231 may include information representing a simulated scene, including, for example, one or more simulated objects (targets), e.g., cars, pedestrians, or the like, and / or a simulated environment, e.g., a road surface, a guardrail, or the like.

[0096] In some demonstrative aspects, the radar simulator 210 may be configured to generate the simulated radar data 233, for example, based on a given scene frame.

[0097] In some demonstrative aspects, the simulated radar data 233 may include, for example, a simulated radar point cloud, e.g., as described below.

[0098] In some demonstrative aspects, the simulated radar data 233 may include any other additional or alternative simulated processed radar data based, for example, on the simulated radar point cloud and / or any other processed radar information corresponding to the simulated radar system.

[0099] For example, in some demonstrative aspects, the simulated radar data 233 may include any suitable additional or alternative higher layer for processing, sensing, and / or merging a point cloud with a frame.

[0100] In some demonstrative aspects, the simulated radar data 233 may include, for example, an object list, a tracked object list, bounding boxes, a classification of objects, an accumulated point cloud, a multi-frame filtered point cloud, drivable spatial information, or the like.

[0101] In some demonstrative aspects, the simulated radar data 233, e.g., including the simulated radar point cloud, may be configured according to one or more radar point cloud input requests for the controller in test 250. For example, the simulated radar point cloud may be configured according to one or more radar point cloud input requests for one or more higher-level algorithms, e.g., perception and / or driving decision algorithms, that may be implemented by the controller in test 250.

[0102] In some demonstrative aspects, in some use cases and / or scenarios, there may be one or more technical aspects that can be satisfied when implementing a radar simulation based on a full radar simulation and processing of a scene.

[0103] For example, a full radar simulation may be configured to include a precise simulation of the time- and space-domain signals for a given scene frame and real-time radar processing of the frame. This full radar processing may require a large amount of computing resources, which may necessitate the use of a dedicated radar chip to interface with the scene simulator. Such an implementation of a full radar simulation may therefore require a high-speed interface to be implemented in hardware and / or software, e.g., FPGAs and / or DSPs. Accordingly, the implementation of this full radar simulation may be complex and / or require significant effort and / or expense.

[0104] For example, it may take a relatively long time to generate the simulated radar data after a full radar simulation, for example, when using a SW implementation of the full operations of precise simulation of the time and space domain signals for a given scene frame, and the real-time radar processing of the frame may take a long time, for example, when no dedicated high-speed HW is implemented.

[0105] With reference to Fig. 1, in some demonstrative aspects, the radar simulator 110 may implement a radar simulation technique (also referred to as “fast radar simulation” or “simplified radar simulation”) that may be configured to generate output information (output) 133 that includes simulated radar data, e.g., the simulated radar data 233 ( Fig.2) may include or be based on, for example, a latency that may correspond to a latency requirement of a real radar system that may be simulated by the radar simulator 110, e.g., as described below.

[0106] In some demonstrative aspects, the radar simulator 110 may be configured to generate output information 133 comprising simulated radar data, e.g., the simulated radar data 233 ( Fig. 2), for example, with a latency that must not exceed the latency requirement of the real radar system, e.g., as described below.

[0107] In some demonstrative aspects, the radar simulator 110 may be configured to generate output information 133 that includes the simulated radar data, e.g., the simulated radar data 233 ( Fig.2), for example, with a latency that may be lower, e.g., even significantly lower, than the real-time latency of the actual radar system. For example, the latency of the radar simulator 110 may improve over time, e.g., after a learning curve.

[0108] In some demonstrative aspects, the radar simulator 110 may be configured to generate output information 133 that includes the simulated radar data, e.g., the simulated radar data 233 ( Fig. 2), for example, with a latency substantially equal to or less than the real latency of the real radar system that can be simulated by the radar simulator 110, e.g., as described below.

[0109] In some demonstrative aspects, the radar simulator 110 may be configured to provide output information 133 that includes the simulated radar data, e.g., the simulated radar data 233 ( Fig. 2), may include or be based on simulated real-time radar output, e.g., to simulate a substantially real-time output of a radar system, e.g., after one or more real-time radar system latency constraints that may be defined and / or expected by the controller in test 150, e.g., as part of SIL and / or HIL testing, e.g., as described below.

[0110] In some demonstrative aspects, the radar simulator 110 may be configured to generate output information 133 that includes the simulated radar data, e.g., the simulated radar data 233 ( Fig. 2), with a latency that may correspond to the latency constraint of the real radar system, for example, to provide a technical solution to support the operation of the simulator 102 while the controller in test 150 is operating in a production mode.

[0111] In some demonstrative aspects, the radar simulator 110 may be configured to generate output information 133 that includes the simulated radar data, e.g., the simulated radar data 233 ( Fig. 2), with a latency that may match the latency constraint of the real radar system, for example, to provide a technical solution to avoid the need for a dedicated SIL or HIL mode.

[0112] In some demonstrative aspects, the radar simulator 110 may be implemented as part of a simulator, e.g., simulator 102, which may be configured for simulation testing, for example, for SIL testing and / or HIL testing, e.g., as described below.

[0113] In other aspects, radar simulator 110 may be implemented as part of any other suitable device and / or system that may be configured to perform any other additional or alternative type of processing based on the simulated radar data. For example, radar simulator 110 may be implemented as part of any other suitable device and / or system that may use the simulated radar data for training artificial intelligence (AI) of one or more algorithms, e.g., perception algorithms, driving decision algorithms, or the like.

[0114] In some demonstrative aspects, the radar simulator 110 may be configured to implement the fast radar simulation, for example, to generate output information 133 that may include or be based on the simulated radar point cloud information, for example, with a latency that may not exceed the latency requirement of the real radar system, e.g., as described below.

[0115] In some demonstrative aspects, the radar simulator 110 may be configured to process the simulated scene information 130 from the scene simulator 119 to, for example, identify a map of the reflectors (“reflector map”) in the scene, e.g., as described below.

[0116] For example, in some demonstrative aspects, the reflector map may include a five-dimensional (5D) reflector list or map, e.g., as described below.

[0117] For example, in some demonstrative aspects, the 5D reflector list may include four-dimensional (4D) spectrum information, e.g., including a range dimension, a Doppler dimension, an azimuth dimension, and an elevation dimension, e.g., as described below.

[0118] For example, in some demonstrative aspects, the 5D reflector list may include the four-dimensional (4D) spectrum information and a radar cross-section (RCS) dimension, e.g., as described below. This type of 5D reflector list is also referred to as a "4D+RCS map."

[0119] In some demonstrative aspects, the 5D reflector list may be provided in part or in whole by the scene simulator 119, for example, as part of the simulated scene information 130, e.g., as described below.

[0120] In some demonstrative aspects, at least a portion of the 5D reflector list may be determined by the radar simulator 110, for example, based on the simulated scene information 130 from the scene simulator 119, e.g., as described below.

[0121] In some demonstrative aspects, the radar simulator 110 may be configured to simulate a radar output spectrum, for example, based on the reflector map and a point spread function (PSF) that may be based on, represent, and / or characterize one or more, e.g., some or all, attributes of the simulated radar system, e.g., as described below.

[0122] In some demonstrative aspects, the radar simulator 110 may be configured to simulate the radar output spectrum, for example, based on a multidimensional convolution, for example, between the reflector map, e.g., the 5D reflector list, and the point spread function, e.g., as described below.

[0123] In other aspects, the radar simulator 110 may be configured to simulate the radar output spectrum based on any other additional or alternative operations and / or functions applied to the reflector map and / or the point spread function.

[0124] In some demonstrative aspects, the radar simulator 110 may be configured to generate an adjusted simulated radar spectrum, for example, by applying one or more adjustments to the radar output spectrum, e.g., as described below.

[0125] For example, in some demonstrative aspects, the one or more settings may be configured to represent one or more impairments, e.g., noise, transmit (Tx) / receive (Rx) impairments, and / or any other suitable setting, e.g., as described below.

[0126] In some demonstrative aspects, the radar simulator 110 may be configured to generate the simulated radar point cloud information, for example, by applying one or more detection operations and / or techniques to the simulated radar spectrum, for example, as described below.

[0127] In some demonstrative aspects, the radar simulator 110 may be configured to generate the simulated radar point cloud information to represent, for example, one or more key radar characteristics of the simulated radar system, e.g., signal-to-noise ratio (SNR), resolutions, dynamic range, or the like, e.g., as described below.

[0128] In some demonstrative aspects, the radar simulator 110 may be configured to generate the simulated radar point cloud information, for example, based on the input configuration information 138 to define a configuration of the simulated radar system and / or a configuration of a radar environment, for example, as described below.

[0129] For example, the input configuration information 138 may include PSF information to define one or more PSFs of the simulated radar system, for example, for range, Doppler, azimuth, and / or elevation dimensions, e.g., as described below.

[0130] For example, the input configuration information 138 may include radar setting information representing one or more settings of the simulated radar system that may be used to derive the PSF information, e.g., as described below.

[0131] For example, the input configuration information 138 may include grid information about grids used in one or more, e.g., some or all, domains, e.g., as described below.

[0132] For example, the input configuration information 138 may include detector information indicating one or more detector parameters implemented by the simulated radar system, e.g., one or more SNR thresholds or the like, e.g., as described below.

[0133] For example, the input configuration information 138 may include impairment information indicating one or more impairments of the simulated radar system. For example, the impairment information may include a Tx / Rx impairment, e.g., phase noise, Tx / Rx leakage, or the like, e.g., as described below.

[0134] In some demonstrative aspects, the radar simulator 110 may be configured to implement the fast radar simulation, for example, to generate the simulated radar point cloud information to provide a technical solution to avoid a full time / space domain radar signal simulation, e.g., as described below.

[0135] In some demonstrative aspects, the radar simulator 110 may be configured to implement the fast radar simulation, for example, to provide a technical solution for generating the simulated radar point cloud information, for example, in real time, e.g., using GPU accelerators or the like.

[0136] In some demonstrative aspects, the radar simulator 110 may be configured to implement the fast radar simulation, for example, to provide a technical solution for generating the simulated radar point cloud information, for example, with reduced cost and / or reduced complexity, e.g., as described below.

[0137] In some demonstrative aspects, the radar simulator 110 may be configured to implement the fast radar simulation, for example, to provide a technical solution for generating the simulated radar point cloud information that may be suitable, for example, for bulk data generation for closed-loop massive MIMO radar validation.

[0138] In some demonstrative aspects, the radar simulator 110 may be configured to implement the fast radar simulation, for example, to provide a technical solution for generating the simulated radar point cloud information that may be suitable, for example, for SIL and / or HIL testing and / or validation of one or more algorithms, e.g., perception and driving algorithms, that may be implemented by the controller in the test 150.

[0139] In some demonstrative aspects, the radar simulator 110 may be configured to implement the fast radar simulation, for example, to provide a technical solution for generating the simulated radar point cloud information, which may be suitable, for example, for mass data generation for AI training of one or more algorithms, e.g., perception and driving algorithms.

[0140] In some demonstrative aspects, the radar simulator 110 may be configured to determine simulated radar information 139 corresponding to a simulated scene for a simulated radar system, for example, by processing simulated scene information 131 corresponding to the simulated scene, e.g., as described below.

[0141] In some demonstrative aspects, the radar simulator 110 may be configured to receive the simulated scene information 131 from the scene simulator 119, for example, as part of the scene information 130, e.g., as described below.

[0142] In other aspects, the radar simulator 110 may be configured to determine at least a portion of the simulated scene information 131, for example, based on any suitable input information corresponding to the simulated scene, and / or the radar simulator 110 may be configured to receive at least a portion of the simulated scene information 131 from one or more other elements of the simulator 102.

[0143] In some demonstrative aspects, the radar simulator 110 may include an input (IN) 135 that may be configured to receive the simulated scene information 131, the input configuration information 138, and / or any other input information, e.g., as described below.

[0144] In some demonstrative aspects, the input 135 may include any suitable input interface, input unit, input module, input component, input circuitry, memory interface, memory access unit, memory reader, digital storage unit, bus interface, processor interface, or the like that may be capable of receiving the simulated scene information 131, the input configuration information 138, and / or any other input information from a memory, a processor, and / or any other suitable component.

[0145] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 corresponding to the simulated scene, for example, for a simulated multiple input multiple output (MIMO) radar system including a plurality of transmit antennas and a plurality of receive antennas, e.g., as described below.

[0146] In other aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 corresponding to the simulated scene, for example, for any other additional or alternative type of simulated radar system.

[0147] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 corresponding to the simulated scene, for example, by processing simulated scene information 131 corresponding to the simulated scene, for example, based on a path loss model and one or more point spread functions (PSFs), as described below.

[0148] In some demonstrative aspects, the path loss model may represent path loss of radar signals transmitted by one or more transmitters of the simulated radar system and received by one or more receivers of the simulated radar system, e.g., as described below.

[0149] In one example, the path loss model may include a mathematical representation that may describe a change, e.g., a decrease, in the signal strength and / or other signal properties of the radar signals, e.g., between one or more transmitters of the simulated radar system and the one or more receivers of the simulated radar system.

[0150] In one example, the path loss model may be based on one or more properties of the simulated scene, for example, the location, orientation, and / or other properties of one or more objects in the simulated scene, an environment in the simulated scene, and the like.

[0151] In one example, the path loss model may be based on one or more properties of the radar signals communicated by the simulated radar system, such as Tx strength, frequency, and the like.

[0152] In some demonstrative aspects, the one or more PSFs may correspond to one or more radar processing techniques applied by the simulated radar system, e.g., as described below.

[0153] In some demonstrative aspects, the radar simulator 110 may be configured to provide output information (Output) 133 based on the simulated radar information 139, e.g., as described below.

[0154] In some demonstrative aspects, the output information 133 may include at least a portion, e.g., some or all, of the simulated radar information 139, e.g., as described below.

[0155] In some demonstrative aspects, the output information 133 may be based on any suitable processing of at least a portion, e.g., some or all, of the simulated radar information 139, e.g., as described below.

[0156] In some demonstrative aspects, the radar simulator 110 may include an output (OUT) 137 configured to provide the output information 133, e.g., as described below.

[0157] In some demonstrative aspects, the output 137 may include any suitable output interface, output unit, output module, output component, output circuitry, memory interface, memory access unit, memory writer, digital storage unit, bus interface, processor interface, or the like that may be capable of outputting the output information 133 to a memory, a processor, and / or any other suitable component for handling the output information 133.

[0158] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 corresponding to the simulated scene, for example, by processing simulated scene information 131 corresponding to the simulated scene, for example, based on the one or more PSFs, which may include a PSF based on a range processing method of the simulated radar system, e.g., as described below.

[0159] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 corresponding to the simulated scene, for example, by processing simulated scene information 131 corresponding to the simulated scene, for example, based on the one or more PSFs, which may include a PSF based on a Doppler processing method of the simulated radar system, e.g., as described below.

[0160] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 corresponding to the simulated scene, for example, by processing simulated scene information 131 corresponding to the simulated scene, for example, based on the one or more PSFs, which may include a PSF based on an azimuth processing method of the simulated radar system, e.g., as described below.

[0161] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 corresponding to the simulated scene, for example, by processing simulated scene information 131 corresponding to the simulated scene, for example, based on the one or more PSFs, which may include a PSF based on an elevation processing method of the simulated radar system, e.g., as described below.

[0162] In another aspect, the one or more PDFs used by radar simulator 110 may include any other suitable additional or alternative PSFs, for example, corresponding to another additional or alternative processing method of the simulated radar system.

[0163] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 corresponding to the simulated scene, for example, by processing simulated scene information 131, which may include, for example, a five-dimensional (5D) energy map, e.g., as described below.

[0164] For example, in some demonstrative aspects, the 5D energy map may include a range dimension, a Doppler dimension, an azimuth dimension, an elevation dimension, and a radar cross section (RCS) dimension, e.g., as described below.

[0165] In other aspects, the simulated scene information 131 may include any other additional or alternative type and / or format of simulated scene information.

[0166] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 to include, for example, simulated radar point cloud information corresponding to the simulated scene, e.g., as described below.

[0167] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 to include, for example, an object list.

[0168] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 to include, for example, a tracked object list.

[0169] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 to include, for example, bounding box information of one or more bounding boxes.

[0170] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 to include, for example, classification information for classifying one or more objects.

[0171] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 to include, for example, an accumulated point cloud.

[0172] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 to include, for example, a multi-frame filtered point cloud.

[0173] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 to include, for example, drivable spatial information.

[0174] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139 to include, for example, any other additional or alternative type of information.

[0175] In some demonstrative aspects, the radar simulator 110 may be configured to provide the output information 133, which may include and / or be based on the simulated radar point cloud information, the object list, the tracked object list, the bounding box information, the classification information, the accumulated point cloud, the multi-frame filtered point cloud, the drivable space information, and / or any other suitable type of information.

[0176] In some demonstrative aspects, the radar simulator 110 may be configured to provide the output information 133, including, for example, simulated radar data to be provided from a SIL simulator to the controller under test 150, e.g., as described above.

[0177] In some demonstrative aspects, the radar simulator 110 may be configured to provide the output information 133, including, for example, simulated radar data to be provided from a HIL simulator to the controller under test 150, e.g., as described above.

[0178] In some demonstrative aspects, the radar simulator 110 may be configured to provide the output information 133, including, for example, simulated radar data that may be configured to train, for example, an artificial intelligence (AI)-based algorithm, e.g., as described above.

[0179] In some demonstrative aspects, the radar simulator 110 may be configured to provide the output information 133, which may be configured, for example, in accordance with one or more real-time radar system latency constraints for the simulated radar system, e.g., as described above.

[0180] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one path loss model and / or the one or more PSFs to be used in determining the simulated radar information 139, for example, based on simulation setting information to define one or more settings of the simulated radar system, e.g., as described below.

[0181] In some demonstrative aspects, the radar simulator 110 may be configured to receive at least a portion, e.g., some or all, of the simulation setting information, for example, as part of the input configuration information 138, e.g., as described below.

[0182] In some demonstrative aspects, at least a portion, e.g., some or all, of the simulation setting information may be preconfigured at radar simulator 110, for example, based on one or more preconfigured settings of the simulated radar system, e.g., as described below.

[0183] In some demonstrative aspects, the radar simulator 110 may be configured to configure the path loss model to be used in determining the simulated radar information 139, for example, based on one or more parameters and / or criteria, e.g., as described below.

[0184] In some demonstrative aspects, the radar simulator 110 may be configured to configure the path loss model, for example, based on one or more radar communication settings, to configure the communication of the radar signals by the simulated radar system, for example, as described below.

[0185] In some demonstrative aspects, the one or more radar communication settings may include, for example, a Tx power for transmitting the radar signals through the simulated radar system, e.g., as described below.

[0186] In some demonstrative aspects, the one or more radar communication settings may include, for example, a Tx antenna pattern of the simulated radar system, e.g., as described below.

[0187] In some demonstrative aspects, the one or more radar communication settings may include, for example, an Rx antenna pattern of the simulated radar system, e.g., as described below.

[0188] In some demonstrative aspects, the one or more radar communication settings may include, for example, a radar frame structure for transmitting the radar signals through the simulated radar system, e.g., as described below.

[0189] In some demonstrative aspects, the one or more radar communication settings may include, for example, a Tx method for transmitting the radar signals through the simulated radar system, e.g., as described below.

[0190] In other aspects, the one or more radar communication settings may include any other additional or alternative settings to configure the communication of the radar signals by the simulated radar system.

[0191] In some demonstrative aspects, the radar simulator 110 may be configured to receive radar communication setting information to define at least a portion, e.g., some or all, of the radar communication settings, for example, as part of the input configuration information 138, e.g., as described below.

[0192] In some demonstrative aspects, at least a portion, e.g., some or all, of the radar communication settings at radar simulator 110 may be preconfigured, for example, based on one or more preconfigured communication settings of the simulated radar system, e.g., as described below.

[0193] In some demonstrative aspects, the radar simulator 110 may be configured to configure the path loss model, for example, based on installation information defining an installation of one or more antennas of the simulated radar system, e.g., as described below.

[0194] In some demonstrative aspects, the radar simulator 110 may be configured to configure the path loss model, for example, based on installation information defining an installation location of one or more antennas of the simulated radar system, e.g., as described below.

[0195] In some demonstrative aspects, the radar simulator 110 may be configured to configure the path loss model, for example, based on installation information defining an installation orientation of one or more antennas of the simulated radar system, e.g., as described below.

[0196] In some demonstrative aspects, the radar simulator 110 may be configured to receive at least a portion, e.g., some or all, of the installation information, for example, as part of the input configuration information 138, e.g., as described below.

[0197] In some demonstrative aspects, at least a portion, e.g., some or all, of the installation information may be preconfigured at radar simulator 110, for example, based on one or more preconfigured installation settings of the simulated radar system, e.g., as described below.

[0198] In some demonstrative aspects, the radar simulator 110 may be configured to configure the path loss model, for example, based on one or more interference conditions for the simulated scene, e.g., as described below.

[0199] In some demonstrative aspects, the radar simulator 110 may be configured to configure the path loss model, for example, based on one or more weather conditions for the simulated scene, e.g., as described below.

[0200] In other aspects, the radar simulator 110 may be configured to configure the path loss model based on any other additional or alternative information.

[0201] In some demonstrative aspects, the radar simulator 110 may be configured to receive information defining at least a portion, e.g., some or all, of the one or more interference conditions, the one or more weather conditions, and / or any other condition, for example, as part of the input configuration information 138, e.g., as described below.

[0202] In some demonstrative aspects, at least a portion, e.g., some or all, of the one or more interference conditions, the one or more weather conditions, and / or any other conditions may be preconfigured at the radar simulator 110, for example, based on one or more preconfigured settings of the simulated radar system, e.g., as described below.

[0203] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one or more PSFs to be used in determining the simulated radar information, for example, based on one or more parameters and / or criteria, e.g., as described below.

[0204] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one or more PSFs, for example, based on one or more settings of the simulated radar system, e.g., as described below.

[0205] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one or more PSFs, for example, based on a processing window setting of the simulated radar system, e.g., as described below.

[0206] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one or more PSFs, for example, based on a signal bandwidth setting of the simulated radar system, e.g., as described below.

[0207] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one or more PSFs, for example, based on a pulse repetition interval (PRI) setting of the simulated radar system, e.g., as described below.

[0208] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one or more PSFs, for example, based on a pulse count per frame setting of the simulated radar system, e.g., as described below.

[0209] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one or more PSFs, for example, based on a frame length setting of the simulated radar system, e.g., as described below.

[0210] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one or more PSFs, for example, based on an array aperture setting of the simulated radar system, e.g., as described below.

[0211] In other aspects, the radar simulator 110 may be configured to configure the one or more PSFs based on any other additional or alternative information.

[0212] In some demonstrative aspects, the radar simulator 110 may be configured to receive radar setting information defining at least a portion, e.g., some or all, of the one or more settings of the simulated radar system, for example, as part of the input configuration information 138, e.g., as described below.

[0213] In some demonstrative aspects, at least a portion, e.g., some or all, of the one or more settings of the simulated radar system may be preconfigured at the radar simulator 110, for example, based on one or more preconfigured settings of the simulated radar system, e.g., as described below.

[0214] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one path loss model and / or the one or more PSFs to be used in determining the simulated radar information 139, for example, based on the preconfigured simulation setting information, which may define one or more preconfigured settings of the simulated radar system.

[0215] In some demonstrative aspects, the preconfigured simulation setting information may include at least a portion, e.g., some or all of the types of simulation setting information described above.

[0216] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one path loss model and / or the one or more PSFs to be used in determining the simulated radar information 139, for example, based on user-provided simulation setting information that may be provided by a user, e.g., as described below.

[0217] In some demonstrative aspects, the user-provided simulation setting information may include at least a portion, e.g., some or all of the types of simulation setting information described above.

[0218] In some demonstrative aspects, the radar simulator 110 may be configured to provide a user interface (UI) 181 that may be configured to receive simulation setting information 132 from a user, e.g., as described below.

[0219] In some demonstrative aspects, the simulation settings information 132 received via the UI 181 may include information to define one or more settings of the simulated radar system.

[0220] For example, the simulation settings information 132 received via the UI 181 may include information defining one or more, e.g., some or all, of the settings of the simulated radar system described above, and / or other additional or alternative settings.

[0221] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information, for example, based on the simulation setting information 132 received via the UI 181.

[0222] In some demonstrative aspects, the radar simulator 110 may be configured to configure at least one PSF to be used in determining the simulated radar information, for example, based on the simulation setting information 132 received via the UI 181.

[0223] In some demonstrative aspects, the radar simulator 110 may be configured to configure the path loss model to be used in determining the simulated radar information, for example, based on the simulation setting information 132 received via the UI 181.

[0224] In some demonstrative aspects, the radar simulator 110 may be configured to determine a multidimensional energy map, for example, by processing the simulated scene information 131 based on the path loss model, e.g., as described below.

[0225] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139, for example, by processing the multidimensional energy map based on the one or more PSFs, e.g., as described below.

[0226] In some demonstrative aspects, the radar simulator 110 may be configured to determine the multidimensional energy map, for example, according to a ray tracing mechanism, e.g., as described below.

[0227] In other aspects, the radar simulator 110 may be configured to determine the multidimensional energy map based on another additional or alternative mechanism and / or method.

[0228] In some demonstrative aspects, the radar simulator 110 may be configured to determine the multidimensional energy map to include, for example, a four-dimensional (4D) energy map, e.g., as described below.

[0229] In some demonstrative aspects, the 4D energy map may, for example, have a range dimension, a Doppler dimension, an azimuth dimension, and an elevation dimension, e.g., as described below.

[0230] In other aspects, the multidimensional energy map may include any other suitable type of multidimensional energy map.

[0231] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139, for example, by applying one or more multidimensional convolutions to the multidimensional energy map, for example, based on the one or more PSFs, e.g., as described below.

[0232] In some demonstrative aspects, the radar simulator 110 may be configured to configure the one or more multidimensional convolutions to include at least one sparse convolution, e.g., as described below.

[0233] In another aspect, any additional or alternative multidimensional convolutions may be implemented.

[0234] In some demonstrative aspects, the radar simulator 110 may be configured to determine a first convolution result, for example, based on a first multidimensional convolution of the multidimensional energy map with at least a first PSF, e.g., as described below.

[0235] For example, in some demonstrative aspects, the at least one first PSF may be configured according to one or more first processing methods of the simulated radar system, e.g., as described below.

[0236] In some demonstrative aspects, the at least one first PSF may be configured, for example, according to range processing techniques of the simulated radar system, e.g., as described below.

[0237] In some demonstrative aspects, the at least one first PSF may be configured, for example, according to Doppler processing techniques of the simulated radar system, e.g., as described below.

[0238] In other aspects, the at least one first PSF may be configured according to any other additional or alternative processing method of the simulated radar system.

[0239] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139, for example, based on a second convolution result, e.g., as described below.

[0240] For example, in some demonstrative aspects, the second convolution result may be based on a second multidimensional convolution of the first convolution result with at least a second PSF, e.g., as described below.

[0241] For example, in some demonstrative aspects, the at least one second PSF may be configured according to one or more second processing methods of the simulated radar system, e.g., as described below.

[0242] In some demonstrative aspects, the at least one second PSF may be configured, for example, according to an azimuth processing method of the simulated radar system, e.g., as described below.

[0243] In some demonstrative aspects, the at least one second PSF may be configured, for example, according to an elevation processing method of the simulated radar system, e.g., as described below.

[0244] In other aspects, the at least one second PSF may be configured according to any other additional or alternative processing method of the simulated radar system.

[0245] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139, for example, by applying the first or second multidimensional convolutions to the multidimensional energy map, e.g., as described below.

[0246] In other aspects, the radar simulator 110 may be configured to determine the simulated radar information 139, for example, by any other suitable number of multidimensional convolutions to the multidimensional energy map.

[0247] In one example, the radar simulator 110 may be configured to determine the simulated radar information 139, for example, by applying a single multidimensional convolution to the multidimensional energy map.

[0248] In one example, the radar simulator 110 may be configured to determine the simulated radar information 139, for example, by applying three or more multidimensional convolutions to the multidimensional energy map.

[0249] In some demonstrative aspects, the radar simulator 110 may be configured to determine a simulated radar spectrum, for example, by processing the multidimensional energy map based on the one or more PSFs, e.g., as described below.

[0250] In some demonstrative aspects, the radar simulator 110 may be configured to determine an adjusted simulated radar spectrum, for example, by adjusting the simulated radar spectrum according to one or more adjustment models, e.g., as described below.

[0251] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139, for example, based on the adjusted simulated radar spectrum, e.g., as described below.

[0252] In some demonstrative aspects, the one or more adjustment models may include a noise adjustment model that may be configured to, for example, model noise affecting the simulated radar system, e.g., as described below.

[0253] In one example, the noise adjustment model may be configured to, for example, model the noise affecting the simulated radar system, for example, based on the simulated scene information 131, the input configuration information 138, and / or based on the simulation adjustment information 132.

[0254] In some demonstrative aspects, the one or more adjustment models may include a phase noise adjustment model that may be configured to, for example, model phase noise affecting the simulated radar system, e.g., as described above.

[0255] In one example, the phase noise adjustment model may be configured to, for example, model the phase noise affecting the simulated radar system, for example, based on the simulated scene information 131, the input configuration information 138, and / or based on the simulation adjustment information 132.

[0256] In some demonstrative aspects, the one or more setting models may include a transmit-to-receive (Tx-RX) leak setting model that may be configured to model, for example, a Tx-Rx leak of the simulated radar system, e.g., as described below.

[0257] In one example, the phase noise adjustment model may be configured to, for example, model the phase noise affecting the simulated radar system, for example, based on the input configuration information 138 and / or based on the simulation adjustment information 132.

[0258] In some demonstrative aspects, the one or more attitude models may include an interference model configured to, for example, model interference affecting the simulated radar system, e.g., as described below.

[0259] In one example, the interference model may be configured to, for example, model the interference affecting the simulated radar system, for example, based on the simulated scene information 131, the input configuration information 138, and / or based on the simulation settings information 132.

[0260] In some demonstrative aspects, the one or more setting models may include a weather model configured to model, for example, one or more weather conditions affecting the simulated radar system, e.g., as described below.

[0261] In one example, the weather model may be configured to model, for example, one or more weather conditions that affect the simulated radar system, for example, based on the simulated scene information 131, the input configuration information 138, and / or based on the simulation settings information 132.

[0262] In other aspects, the one or more adjustment models may include any other suitable additional or alternative models for adjusting the simulated radar spectrum based on one or more additional or alternative types of conditions, parameters, and / or settings that may affect the simulated radar system.

[0263] In some demonstrative aspects, the radar simulator 110 may be configured to determine the simulated radar information 139, for example, by applying a detection mechanism to the adjusted simulated radar spectrum, e.g., as described below.

[0264] It will be Fig. 3, which illustrates a method for generating simulated radar data of a simulated radar system according to some demonstrative aspects. For example, a radar simulator, e.g., radar simulator 110 ( Fig. 1) and / or radar simulator 210 ( Fig. 2), be configured to perform one or more, e.g., some or all, operations of the method of Fig. 3 to carry out, for example, the simulated radar data, e.g., the simulated radar data 139 ( Fig. 1), to determine.

[0265] In some demonstrative aspects, as indicated in block 302, the method may include processing simulated scene information 303 corresponding to a scene frame.

[0266] In some demonstrative aspects, the simulated scene information 303 may be provided by a scene simulator. For example, as in Fig. 3, the simulated scene information 303 is determined, for example, based on one or more installation parameters corresponding to an installation of the simulated radar system. For example, the one or more installation parameters may include the radar unit location and / or a radar unit orientation.

[0267] For example, the scene information 130 ( Fig. 1), which is generated by the scene simulator 119 ( Fig. 1) are provided, including the simulated scene information 303.

[0268] In some demonstrative aspects, the simulated scene information 303 may include information about a modeled multidimensional spectrum.

[0269] In some demonstrative aspects, the simulated scene information 303 may include a 5D reflector list, e.g., in the form of a 4D+RCS map.

[0270] In some demonstrative aspects, the simulated scene information 303 may include information about, e.g., a list of reflectors located in 4D space. For example, a reflector, e.g., each reflector, may be characterized by an RCS.

[0271] In some demonstrative aspects, the 4D+RCS map can be provided, for example by a suitable ray tracing engine.

[0272] For example, the ray tracing engine may be configured to provide information about one or more emulated objects in the simulated scene. For example, the information for an emulated object may include some or all of an angle of arrival (AoA) of one or more reflections from the object, e.g., an azimuth (Az) AoA and / or an elevation (El) AoA; an angle of departure (AoD), e.g., an Az AoD and / or an El AoD of one or more reflections from the object; a radial velocity of one or more reflections from the object; a distance of one or more reflections from the object; and a received energy of one or more reflections from the object, e.g., a reflector RCS at a spatial view angle; and / or any other suitable additional or alternative information for the one or more reflections from the emulated object.

[0273] For example, the scene simulator 119 ( Fig. 1) include a suitable ray tracing engine that can generate the 4D+RCS map (5D reflector list), for example based on a scene generated by the controller in test 150 ( Fig. 1). For example, the scene simulator 119 ( Fig. 1) the simulated scene information 130 ( Fig. 1), including the 5D reflector list.

[0274] For example, the 5D reflector list may include a plurality of entries corresponding to a plurality of point reflections.

[0275] In one example, an entry in the 5D reflector list might include the following information, e.g., for a single point reflection: Table 1 Area [m] Doppler [m / s] Az [deg] El [deg] RCS [dBsm] 43,6543 -13,587 -35 7 -5

[0276] In other aspects, an entry in the 5D reflector list may also include any other additional or alternative information corresponding to the point reflection.

[0277] In some demonstrative aspects, as indicated in block 304, the method may include determining a multidimensional energy map 305, for example, by processing the simulated scene information 303 based on a path loss model, e.g., as described below.

[0278] In some demonstrative aspects, as indicated in block 304, determining the multidimensional energy map 305 may include determining the multidimensional energy map 305, e.g., a 4D energy map, for example, according to the path loss model, which may be applied to the 5D reflector list (4D+RCS map) 303.

[0279] For example, the energy reflected by the reflectors can be modeled and scaled according to the free path loss equations of a suitable free path loss model, e.g., assuming that the transmit (Tx) energy of the simulated radar system is known, e.g., as an input parameter of the system.

[0280] For example, an effect of Tx and / or receive (Rx) antenna patterns of the simulated radar system can be modeled and considered as part of the free path loss model.

[0281] For example, the path loss model may be modeled according to one or more second surface parameters, which may define one or more second surface modifications applied to the Tx and / or Rx beam patterns of the simulated radar system.

[0282] For example, the path loss model may be modeled according to one or more parameters related to a SW boundary configuration of the simulated radar system, for example, an elevation angle range boundary, an azimuth angle range boundary, a distance boundary, or the like.

[0283] For example, the path loss model may be modeled according to one or more parameters related to a frame structure and / or a Tx method implemented by the simulated radar system.

[0284] In one example, the Tx energy may have a different gain, e.g., due to constructive interference at the object within its beam forming (BF) beam when Tx BF is used by the simulated radar system.

[0285] For example, the path loss model can be modeled according to one or more weather conditions, e.g., using a path loss model for rain, fog, snow, or similar.

[0286] In some demonstrative aspects, as indicated in block 306, the method may include determining a multidimensional radar spectrum 307, e.g., a 4D radar spectrum, for example, based on the multidimensional energy map 305, e.g., as described below.

[0287] In some demonstrative aspects, as indicated in block 306, the method may include determining the multidimensional radar spectrum 307, for example, by processing the multidimensional energy map 305 based on one or more PSFs corresponding to the simulated radar system, e.g., as described below.

[0288] In some demonstrative aspects, the one or more PSFs may be based on, define, and / or represent one or more radar processing techniques employed by the simulated radar system.

[0289] In some demonstrative aspects, the one or more PSFs may be based on, define, and / or represent one or more attributes and / or capabilities of the simulated radar system.

[0290] For example, the one or more PSFs may represent the resolution and / or dynamic range capabilities of the radar and / or any other suitable characteristic and / or capability of the radar system that may affect the output radar data provided by the simulated radar system.

[0291] For example, in some demonstrative aspects, the one or more PSFs may include a PSF corresponding to a range processing method employed by the simulated radar system.

[0292] For example, in some demonstrative aspects, the one or more PSFs may include a PSF corresponding to a Doppler processing technique employed by the simulated radar system.

[0293] For example, in some demonstrative aspects, the one or more PSFs may include a PSF corresponding to an azimuth processing method employed by the simulated radar system.

[0294] For example, in some demonstrative aspects, the one or more PSFs may include a PSF corresponding to an elevation processing method applied by the simulated radar system.

[0295] In other aspects, the one or more PSFs may include any other additional or alternative PSFs corresponding to any other additional or alternative radar processing operations and / or methods to be performed by the simulated radar system.

[0296] In some demonstrative aspects, as indicated in block 306, the method may include determining the multidimensional radar spectrum 307, for example, based on one or more multidimensional convolutions, e.g., a 4D convolution, of the multidimensional energy map 305 with the one or more PSFs, e.g., as described below.

[0297] In some demonstrative aspects, the method may include receiving one or more PSFs as an input by the radar simulator. For example, the radar simulator 110 ( Fig. 1) be configured to receive an input including information, e.g., input information 138 ( Fig. 1) and / or information 132 ( Fig. 1) to define one or more of the PSFs of the simulated radar system, e.g. as described above.

[0298] In some demonstrative aspects, the method may include determining one or more PSFs by the radar simulator. For example, the radar simulator 110 ( Fig. 1) be configured to determine one or more of the PSFs of the simulated radar system.

[0299] For example, the radar simulator, e.g., the radar simulator 110 ( Fig. 1), be configured to derive a PSF, for example, from one or more radar parameters of the simulated radar system, e.g., processing window parameters, signal bandwidth, pulse repetition interval (PRI), number of pulses, or similar.

[0300] In some demonstrative aspects, the method may include determining the multidimensional radar spectrum 307, for example, based on a sparse convolution, e.g., based on the knowledge that the 4D energy map 305 is sparse. For example, the sparse convolution may be implemented to provide a technical solution that reduces processing time and / or complexity.

[0301] In some demonstrative aspects, as indicated in block 306, applying the one or more multidimensional convolutions to the multidimensional energy map 305 may include determining a first convolution result, for example, based on a first multidimensional convolution of the multidimensional energy map 305 with at least a first PSF, e.g., as described below.

[0302] For example, in some demonstrative aspects, the at least one first PSF may be configured according to one or more first processing methods of the simulated radar system.

[0303] In some demonstrative aspects, the at least one first PSF may be configured, for example, according to a range processing method of the simulated radar system and / or a Doppler processing method of the simulated radar system.

[0304] In some demonstrative aspects, as indicated in block 306, applying the one or more multidimensional convolutions to the multidimensional energy map 305 may include determining the multidimensional radar spectrum 307 based on a second convolution result, which may be based, for example, on a second multidimensional convolution of the first convolution result with at least a second PSF.

[0305] For example, in some demonstrative aspects, the at least one second PSF may be configured according to one or more second processing methods of the simulated radar system.

[0306] In some demonstrative aspects, the at least one second PSF may be configured, for example, according to an azimuth processing method of the simulated radar system and / or an elevation processing method of the simulated radar system.

[0307] In some demonstrative aspects, as indicated in block 308, the method may include determining an adjusted simulated radar spectrum 309, for example, by adjusting the simulated radar spectrum 307 according to one or more adjustment models.

[0308] For example, as indicated in block 308, the method may include determining the adjusted multidimensional radar spectrum 309, e.g., an adjusted 4D radar spectrum, for example, by adjusting the multidimensional radar spectrum 307 after one or more impairments.

[0309] In some demonstrative aspects, the one or more attitude models may include a noise attitude model configured to model noise affecting the simulated radar system.

[0310] In some demonstrative aspects, the one or more adjustment models may include a phase noise adjustment model configured to model phase noise affecting the simulated radar system.

[0311] In some demonstrative aspects, the one or more adjustment models may include a Tx-RX leak adjustment model configured to model a Tx-Rx leak of the simulated radar system.

[0312] For example, noise and / or Tx / Rx impairments, e.g., leaks, may be added to the generated 4D radar spectrum 307 to provide the adjusted simulated radar spectrum 309.

[0313] In some demonstrative aspects, the one or more setting models may include a weather model configured to model one or more weather conditions affecting the simulated radar system.

[0314] For example, the one or more impairments applied to the generated 4D radar spectrum 307 may be modeled according to one or more adverse weather condition models, such as a model for rain, fog, snow, or the like.

[0315] In some demonstrative aspects, the one or more attitude models may include an interference model configured to model interference affecting the simulated radar system.

[0316] For example, the one or more impairments applied to the generated 4D radar spectrum 307 may be modeled, for example, according to one or more interference models.

[0317] For example, the adjusted 4D radar spectrum 309 may be configured to be substantially similar to a simulated radar spectrum, e.g., generated using full time / space domain processing.

[0318] In some demonstrative aspects, as indicated in block 310, the method may include generating a simulated radar point cloud 311, for example, based on the simulated multidimensional radar spectrum 307, e.g., based on the adjusted multidimensional radar spectrum 309.

[0319] For example, the 4D spectrum 307, e.g., the adjusted 4D spectrum 309, can be processed, e.g., by a suitable detector to simulate, e.g., a detector used by the simulated radar system, e.g., with little computational effort to generate, e.g., the simulated radar point cloud 311.

[0320] In some demonstrative aspects, the simulated radar point cloud 311 provided by the radar simulator, e.g., following the fast radar simulation technique described above, may be compared to a reference point cloud, for example, to assess a quality of the simulated radar point cloud and / or improve a quality of the simulated radar point cloud. In one example, the reference point cloud may include a point cloud determined after a full radar signal level simulation.

[0321] It will be Fig. 4A and Fig. 4B, which schematically illustrate a radar simulation technique for simulating radar data to be provided by a simulated radar system, according to some demonstrative aspects.

[0322] For example, the radar simulation technology of Fig. 4A and Fig.4B to simulate a range of an object to be provided by the simulated radar system.

[0323] For example, a similar radar simulation technique can be implemented to simulate a Doppler of the object, an azimuth of the object, and / or an elevation of the object to be provided by the simulated radar system.

[0324] For example, as in Fig. 4A, a radar system may transmit a radar Tx signal pulse 402 that may be reflected by a target 401 and received by the radar system as a radar Rx signal 404.

[0325] For example, as in Fig. 4A, the radar system may process the radar Rx signal 404, for example, through matched filtering (MF) and / or any other suitable radar processing technique to provide a radar spectrum 403.

[0326] For example, as in Fig.4A, detections of targets may be determined based on one or more peaks 405 of the radar spectrum 403.

[0327] For example, as in Fig. 4B, the radar spectrum 405 can be simulated, for example, even without a complete simulation of the radar propagation path of the radar Tx signal 402 and the radar Rx signal 404.

[0328] For example, as in Fig. 4B, a simulated radar spectrum 416 may be determined to simulate a radar spectrum, e.g., similar to radar spectrum 403, for example, based on knowledge of the target locations of targets 412 in a simulated scenario. For example, the target locations may be determined based on the simulated scene input provided by radar simulator 110 ( Fig. 1) is received, e.g. as described above.

[0329] For example, the MF output can be modeled, for example by a PSF 418, which represents an MF response that can be based on the setting of the simulated radar system.

[0330] For example, as in Fig. 4B, the simulated radar spectrum 416 may be determined based on a convolution of the known target locations of the targets 412 with the PSF 418.

[0331] For example, the simulated radar spectrum 416 can be determined, e.g., even without any time simulation.

[0332] It will be Fig. 5, which schematically illustrates a radar signal level simulation path 502 compared to a full radar signal level simulation path 504, according to some demonstrative aspects.

[0333] For example, the radar simulator 110 ( Fig. 1) be configured to implement one or more operations following the radar simulation path 502.

[0334] For example, the radar simulation path 502 may be executed after one or more, e.g., some or all, of the operations of the method of Fig. 3 be implemented.

[0335] For example, as in Fig. 5, the radar simulation path 502 may include the simulation of a radar scene 511, for example, using the 4D+RCS map (5D reflector list) corresponding to a radar frame, e.g., as described above.

[0336] For example, as in Fig. 5, the simulation path 502 may include determining a 4D energy map 513, for example, according to a path loss model, which may be applied to the 4D+RCS map (5D reflector list) 511, e.g., as described above.

[0337] For example, as in Fig.5, the simulation path 502 may include determining a simulated 4D spectrum 517 by performing convolutions of the 4D energy map 513 with the PSFs corresponding to the range, Doppler, azimuth, and elevation domains, e.g., as described above.

[0338] For example, as in Fig. 5, the simulation path 502 may include determining a first convolution result 515, for example, based on a first multidimensional convolution of the 4D energy map 513 with at least a first PSF configured according to the range and Doppler processing techniques of the simulated radar system.

[0339] For example, as in Fig.5, the simulation path 502 may include determining the simulated 4D spectrum 517, for example, based on a second convolution result, which may be based on a second multidimensional convolution of the first convolution result 515 with at least a second PSF configured by the azimuth and elevation processing methods of the simulated radar system.

[0340] For example, as in Fig. 5, the simulation path 502 may include determining an adjusted simulated 4D radar spectrum 519, for example, by adjusting the simulated 4D radar spectrum 517 after one or more impairments, e.g., as described above.

[0341] For example, as in Fig. 5, the simulation path 502 may include determining a simulated radar point cloud 521, for example, based on the simulated 4D radar spectrum 519, e.g., as described above.

[0342] For example, as in Fig. 5, the simulation path 502 may include applying a detector to the 4D spectrum 519 to output, for example, the simulated radar point cloud 521.

[0343] For example, as in Fig. 5, the simulation path 502 may use a scene simulator, e.g., the scene simulator 119 ( Fig. 1) to provide the 5D reflector list 511, e.g., including the RD-Az-EI-RCS dimensions. For example, as in Fig. 5, the simulation path 502 may use the 5D reflector list 511 and radar design parameters, which may be represented, for example, by the associated 4D PSF and / or other parameters, to generate an estimate of the radar point cloud 521, for example, as described above.

[0344] For example, as in Fig.5, the simulation path 504 may be performed as part of a complete time-space domain simulation for a single radar frame.

[0345] For example, as in Fig. 5, the simulation path 504 may require simulating the transmission and reception of the broadband radar signals, which in turn may require significant computational effort, e.g., to generate the 4D spectrum (range, Doppler, AZ, EL).

[0346] For example, as in Fig. 5, the simulation path 504 may use a scene simulator to perform a simulation of the channel and propagation, for example, from each Tx antenna to each reflector and then from each reflector to each Rx antenna.

[0347] For example, as in Fig.5, the simulation path 504 may use the scene simulator and the channel simulator to provide a waveform, e.g., in each Rx antenna port, which may be processed, e.g., after the complete radar processing flow, to provide the radar point cloud.

[0348] For example, as in Fig. 5, the simulation path 504 may include processing the Rx signals using range pulse compression, Doppler processing, and AoA processing (beam forming).

[0349] For example, as in Fig. 5, the simulation path 504 may include applying a detector to the 4D spectrum to output the point cloud, for example.

[0350] For example, as in Fig.5, the azimuth and / or elevation convolutions in simulation path 502 may be used to replace, for example, the spatial transmission (Tx signal) and / or beamforming operations of simulation path 504.

[0351] For example, as in Fig. 5, the range and / or Doppler convolutions in simulation path 502 may be used to replace, for example, the range pulse compression and / or Doppler processor operations of simulation path 504.

[0352] In one example, one or more attributes of simulation path 502 may be compared to the attributes of simulation path 504, e.g., as follows: Table 2. type input Process output Complete radar signal simulation Received sample reflections from the scene to each individual Rx antenna element Radar signal processing like in a product sensor Point cloud Fast radar simulation 5D reflector list Implementing 4D-PSF and detector Estimated point cloud

[0353] It will be Fig. 6, which illustrates a method for radar simulation according to some demonstrative aspects. For example, the simulator 102 ( Fig. 1), the radar simulator 110 ( Fig.1) and / or the radar simulator 210 ( Fig. 2) be configured to perform one or more operations and / or functions according to the procedure of Fig. 6 to be implemented.

[0354] In some demonstrative aspects, as indicated in block 602, the method may include determining simulated radar information corresponding to a simulated scene for a simulated radar system, for example, by processing simulated scene information corresponding to the simulated scene based on a path loss model and one or more point spread functions (PSFs). For example, the path loss model may represent a path loss of radar signals transmitted by one or more transmitters of the simulated radar system and received by one or more receivers of the simulated radar system. For example, the one or more PSFs may correspond to one or more radar processing methods applied by the simulated radar system. For example, the radar simulator 110 ( Fig. 1) be configured to display the simulated radar information 139 ( Fig.1) corresponding to the simulated scene for the simulated radar system, for example by processing the simulated scene information 131 ( Fig. 1) corresponding to the simulated scene, based on a path loss model and one or more point spread functions (PSF), e.g., as described above.

[0355] In some demonstrative aspects, as indicated in block 604, determining the simulated radar information corresponding to the simulated scene may include determining a multidimensional energy map, for example, by processing the simulated scene information based on the path loss model. For example, the radar simulator 110 ( Fig. 1) be configured to determine a multidimensional energy map, for example by processing the simulated scene information 131 ( Fig. 1), based on the path loss model, e.g., as described above.

[0356] In some demonstrative aspects, as indicated in block 606, determining the simulated radar information corresponding to the simulated scene may include determining the simulated radar information, for example, by processing the multidimensional energy map based on the one or more PSFs. For example, the radar simulator 110 ( Fig. 1) be configured to display the simulated radar information 139 ( Fig. 1), for example by processing the multidimensional energy map based on the one or more PSFs, e.g. as described above.

[0357] In some demonstrative aspects, as indicated in block 608, the method may include providing an output based on the simulated radar information. For example, the radar simulator 110 ( Fig. 1) be configured, output information 133 ( Fig.1), for example based on the simulated radar information 139 ( Fig. 1), e.g. as described above.

[0358] With reference to Fig. 7, which schematically illustrates a product of manufacture 700, according to some demonstrative aspects. Product 700 may include one or more tangible, computer-readable ("machine-readable") non-transitory storage media 702 that may include computer-executable instructions, e.g., implemented by logic 704, that, when executed by at least one computer processor, enable the at least one computer processor to perform one or more operations on the simulator 102 ( Fig. 1), Radar Simulator 110 ( Fig. 1) and / or radar simulator 210 ( Fig. 2) to implement the simulator 102 ( Fig. 1), Radar Simulator 110 ( Fig. 1) and / or radar simulator 210 ( Fig.2) to cause one or more operations and / or functions to be carried out, triggered and / or implemented; and / or one or more operations and / or functions that are specified by reference to the Fig. 1-6, and / or to perform, initiate, and / or implement one or more operations described herein. The terms "non-transitory machine-readable medium" and "computer-readable non-transitory storage medium" may be understood to include all machine-readable and / or computer-readable media, with the sole exception of a transitory transmission signal.

[0359] In some demonstrative aspects, the product 700 and / or the machine-readable storage medium 702 may include one or more types of computer-readable storage media capable of storing data, including volatile memory, non-volatile memory, removable or non-removable memory, erasable or non-erasable memory, writable or rewritable memory, and the like. For example, machine-readable storage media 702 may include RAM, DRAM, double data rate DRAM (DDR-DRAM), SDRAM, static RAM (SRAM), ROM, programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory (e.g., NOR or NAND flash memory), content-addressable memory (CAM), polymer memory, phase-change memory, ferroelectric memory, silicon oxide-nitride-oxide-silicon (SONOS) memory, a disk, a hard disk, and the like.The computer-readable storage medium may include any suitable medium related to downloading or sending a computer program from a remote computer to a requesting computer, carried by data signals embodied in a carrier wave or other propagation medium over a communications link, such as a modem, radio, or network connection.

[0360] In some demonstrative aspects, logic 704 may include instructions, data, and / or code that, when executed by a machine, may cause the machine to perform a method, process, and / or operations as described herein. For example, the machine may include any suitable processing platform, computing system, computing device, computing system, computer, processor, or the like, and may be implemented with any suitable combination of hardware, software, firmware, and the like.

[0361] In some demonstrative aspects, the logic 704 may include or be implemented as software, a software module, an application, a program, a subroutine, instructions, an instruction set, arithmetic code, words, values, symbols, and the like. The instructions may include any suitable type of code, such as source code, compiled code, interpreted code, executable code, static code, dynamic code, and the like. The instructions may be implemented according to a predefined computer language, type, or syntax to instruct a processor to perform a particular function. The implementation of the instructions may be performed using any suitable high-level, low-level, object-oriented, visual, compiled and / or interpreted programming language, machine code, and the like. EXAMPLES

[0362] The following examples refer to further aspects.

[0363] Example 1 includes a product comprising one or more tangible computer-readable non-transitory storage media comprising instructions that, when executed by at least one computer processor, enable the at least one processor to cause a radar simulator to determine simulated radar information corresponding to a simulated scene for a simulated radar system by processing simulated scene information corresponding to the simulated scene based on a path loss model and one or more point spread functions (PSFs), wherein the path loss model represents a path loss of radar signals transmitted by one or more transmitters of the simulated radar system and received by one or more receivers of the simulated radar system, wherein the one or more PSFs correspond to one or more radar processing techniques employed by the simulated radar system;and provide an output based on the simulated radar information.;

[0364] Example 2 includes the subject matter of Example 1, and optionally, wherein the instructions, when executed, cause the radar simulator to determine a multidimensional energy map by processing the simulated scene information based on the path loss model; and to determine the simulated radar information by processing the multidimensional energy map based on the one or more PSFs.

[0365] Example 3 includes the subject matter of Example 2, and optionally, wherein the instructions, when executed, cause the radar simulator to determine the simulated radar information by applying one or more multidimensional convolutions to the multidimensional energy map based on the one or more PSFs.

[0366] Example 4 includes the subject matter of Example 3, and optionally, wherein the instructions, when executed, cause the radar simulator to determine a first convolution result based on a first multidimensional convolution of the multidimensional energy map with at least a first PSF, wherein the at least one first PSF is configured according to one or more first processing methods of the simulated radar system; and determine the simulated radar information based on a second convolution result, wherein the second convolution result is based on a second multidimensional convolution of the first convolution result with at least a second PSF, wherein the at least one second PSF is configured according to one or more second processing methods of the simulated radar system.

[0367] Example 5 includes the subject matter of Example 4, and optionally, wherein the at least one first PSF is configured according to at least one of a range processing method of the simulated radar system or a Doppler processing method of the simulated radar system, wherein the at least one second PSF is configured according to at least one of an azimuth processing method of the simulated radar system or an elevation processing method of the simulated radar system.

[0368] Example 6 includes the subject matter of any of Examples 3 to 5, and optionally, wherein the instructions, when executed, cause the radar simulator to configure the one or more multidimensional convolutions comprising at least one sparse convolution.

[0369] Example 7 includes the subject matter of any of Examples 2 to 6, and optionally, wherein the instructions, when executed, cause the radar simulator to determine a simulated radar spectrum by processing the multidimensional energy map according to the one or more PSFs; determine an adjusted simulated radar spectrum by adjusting the simulated radar spectrum according to one or more adjustment models; and determine the simulated radar information based on the adjusted simulated radar spectrum.

[0370] Example 8 includes the subject matter of Example 7, and optionally, wherein the one or more adjustment models comprise a noise adjustment model configured to model noise affecting the simulated radar system.

[0371] Example 9 includes the subject matter of Example 7 or 8, and optionally, wherein the one or more adjustment models comprise a phase noise adjustment model configured to model phase noise affecting the simulated radar system.

[0372] Example 10 includes the subject matter of any of Examples 7 to 9, and optionally, wherein the one or more adjustment models comprise a transmit-to-receive (Tx-RX) leak adjustment model configured to model a Tx-RX leak of the simulated radar system.

[0373] Example 11 includes the subject matter of any of Examples 7 to 10, and optionally, wherein the one or more adjustment models comprise an interference model configured to model interference affecting the simulated radar system.

[0374] Example 12 includes the subject matter of any of Examples 7 to 11, and optionally, wherein the one or more attitude models comprise a weather model configured to model one or more weather conditions affecting the simulated radar system.

[0375] Example 13 includes the subject matter of any of Examples 7 to 12, and optionally, wherein the instructions, when executed, cause the radar simulator to determine the simulated radar information by applying a detection mechanism to the adjusted simulated radar spectrum.

[0376] Example 14 includes the subject matter of any of Examples 2 to 13, and optionally, wherein the instructions, when executed, cause the radar simulator to determine the multidimensional energy map according to a ray tracing mechanism.

[0377] Example 15 includes the subject matter of any of Examples 2 to 14, and optionally, wherein the multidimensional energy map comprises a four-dimensional (4D) energy map comprising a range dimension, a Doppler dimension, an azimuth dimension, and an elevation dimension.

[0378] Example 16 includes the subject matter of any of Examples 1 to 15, and optionally, wherein the one or more PSFs comprise at least one PSF based on at least one of a range processing method of the simulated radar system or a Doppler processing method of the simulated radar system.

[0379] Example 17 includes the subject matter of any of Examples 1 to 16, and optionally, wherein the one or more PSFs comprise a PSF based on at least one of an azimuth processing method of the simulated radar system or an elevation processing method of the simulated radar system.

[0380] Example 18 includes the subject matter of any of Examples 1 to 17, and optionally, wherein the instructions, when executed, cause the radar simulator to configure the path loss model based on one or more radar communication settings to configure communication of the radar signals by the simulated radar system.

[0381] Example 19 includes the subject matter of Example 18, and optionally, wherein the one or more radar communication settings comprise at least one of a transmit (Tx) power for transmitting the radar signals, a Tx antenna pattern of the simulated radar system, a receive (Rx) antenna pattern of the simulated radar system, a radar frame structure for transmitting the radar signals, or a Tx method for transmitting the radar signals.

[0382] Example 20 includes the subject matter of any of Examples 1 to 19, and optionally, wherein the instructions, when executed, cause the radar simulator to configure the path loss model based on installation information defining at least one of an installation location and an installation orientation for one or more antennas of the simulated radar system.

[0383] Example 21 includes the subject matter of any of Examples 1 to 20, and optionally, wherein the instructions, when executed, cause the radar simulator to configure the path loss model based on one or more interference conditions for the simulated scene.

[0384] Example 22 includes the subject matter of any of Examples 1 to 21, and optionally, wherein the instructions, when executed, cause the radar simulator to configure the path loss model based on one or more weather conditions for the simulated scene.

[0385] Example 23 includes the subject matter of any of Examples 1 to 22, and optionally, wherein the instructions, when executed, cause the radar simulator to configure the one or more PSFs based on one or more settings of the simulated radar system.

[0386] Example 24 includes the subject matter of any of Examples 1 to 23, and optionally, wherein the instructions, when executed, cause the radar simulator to configure the one or more PSFs based on at least one of a processing window setting of the simulated radar system, a signal bandwidth setting of the simulated radar system, a pulse repetition interval (PRI) setting of the simulated radar system, a pulse count per frame setting of the simulated radar system, a frame length setting of the simulated radar system, or an array aperture setting of the simulated radar system.

[0387] Example 25 includes the subject matter of any of Examples 1 to 24, and optionally, wherein the instructions, when executed, cause the radar simulator to provide a user interface to receive simulation setting information from a user, the simulation setting information defining one or more settings of the simulated radar system; and to determine the simulated radar information based on the simulation setting information.

[0388] Example 26 includes the subject matter of Example 25, and optionally, wherein the instructions, when executed, cause the radar simulator to configure at least one PSF of the one or more PSFs based on the simulation setting information.

[0389] Example 27 includes the subject matter of example 25 or 26, and optionally, wherein the instructions, when executed, cause the radar simulator to configure the path loss model based on the simulation settings information.

[0390] Example 28 includes the subject matter of any of Examples 1 to 27, and optionally, wherein the simulated scene information comprises a five-dimensional (5D) energy map comprising a range dimension, a Doppler dimension, an azimuth dimension, an elevation dimension, and a radar cross section (RCS) dimension.

[0391] Example 29 includes the subject matter of any of Examples 1 to 28, and optionally, wherein the instructions, when executed, cause the radar simulator to provide the output in accordance with one or more real-time radar system latency constraints for the simulated radar system.

[0392] Example 30 includes the subject matter of any of Examples 1 to 29, and optionally, wherein the simulated radar information comprises simulated radar point cloud information corresponding to the simulated scene.

[0393] Example 31 includes the subject matter of any of Examples 1 to 30, and optionally, wherein the simulated radar information comprises at least one of an object list, a tracked object list, bounding box information of one or more bounding boxes, classification information for classifying one or more objects, an accumulated point cloud, a multi-frame filtered point cloud, or drivable spatial information.

[0394] Example 32 includes the subject matter of any of Examples 1 to 31, and optionally, wherein the instructions, when executed, cause the radar simulator to provide the output comprising simulated radar data to be provided by a software-in-the-loop (SIL) simulator to a controller under test.

[0395] Example 33 includes the subject matter of any of Examples 1 to 31, and optionally, wherein the instructions, when executed, cause the radar simulator to provide the output comprising simulated radar data to be provided by a hardware-in-the-loop (HIL) simulator to a controller under test.

[0396] Example 34 includes the subject matter of any of Examples 1 to 31, and optionally, wherein the instructions, when executed, cause the radar simulator to provide the output comprising simulated radar data configured to train an artificial intelligence (AI)-based algorithm.

[0397] Example 35 includes the subject matter of any of Examples 1 to 34, and optionally, wherein the simulated radar system comprises a multiple input multiple output (MIMO) radar system comprising a plurality of transmit antennas and a plurality of receive antennas.

[0398] Example 36 includes a test simulator comprising a scene generator for generating simulated scene information corresponding to a simulated scene based on control information from a controller under test;and a radar simulator configured to provide simulated radar data for the controller under test based on the simulated scene information, wherein the radar simulator is configured to determine simulated radar information corresponding to the simulated scene by processing the simulated scene information based on a path loss model and one or more point spread functions (PSFs), wherein the path loss model represents a simulated path loss of radar signals transmitted by one or more transmitters of a simulated radar system and received by one or more receivers of the simulated radar system after the simulated scene, wherein the one or more PSFs correspond to one or more radar processing methods applied by the simulated radar system, wherein the simulated radar data is based on the simulated radar information.;

[0399] Example 37 includes the test simulator of Example 36, and optionally, wherein the radar simulator is configured according to the subject matter of any of Examples 1 to 35.

[0400] Example 38 includes an apparatus comprising means for performing any of the described operations of any of Examples 1 to 37.

[0401] Example 39 includes a machine-readable medium storing instructions for execution by a processor to perform any of the described operations of any of Examples 1 to 37.

[0402] Example 40 includes a device comprising memory and processing circuitry configured to perform any of the described processes of any of Examples 1 to 37.

[0403] Example 41 includes a method including any of the described operations of any of Examples 1 to 37.

[0404] Functions, operations, components and / or features described herein with reference to one or more aspects may be combined with or used in combination with one or more other functions, operations, components and / or features described herein with reference to one or more other aspects, or vice versa.

[0405] While certain features have been illustrated and described herein, many modifications, substitutions, changes, and equivalents will occur to those skilled in the art. It is therefore to be understood that the appended claims are intended to cover all modifications and changes that remain within the true spirit of the disclosure. QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] US 63 / 621,491

[0001] Cited non-patent literature

[0000] SAE J3016 2018: Taxonomy and definitions for terms related to driving automation systems for on road motor vehicles

[0020]

Claims

[1] A method for performing on a radar simulator, the method comprising: Determining simulated radar information corresponding to a simulated scene for a simulated radar system by processing simulated scene information corresponding to the simulated scene based on a path loss model and one or more point spread functions (PSFs), wherein the path loss model represents a path loss of radar signals transmitted by one or more transmitters of the simulated radar system and received by one or more receivers of the simulated radar system, wherein the one or more PSFs correspond to one or more radar processing methods applied by the simulated radar system; and Provide output based on the simulated radar information. [2] A method according to claim 1, comprising: Determining a multidimensional energy map by processing the simulated scene information based on the path loss model; and Determining the simulated radar information by processing the multidimensional energy map based on one or more PSFs. [3] The method of claim 2, comprising determining the simulated radar information by applying one or more multidimensional convolutions to the multidimensional energy map based on the one or more PSFs. [4] A method according to claim 3, comprising: Determining a first convolution result based on a first multidimensional convolution of the multidimensional energy map with at least one first PSF, wherein the at least one first PSF is configured according to one or more first processing methods of the simulated radar system; and Determining the simulated radar information based on a second convolution result, wherein the second convolution result is based on a second multidimensional convolution of the first convolution result with at least one second PSF, wherein the at least one second PSF is configured according to one or more second processing methods of the simulated radar system. [5] The method of claim 4, wherein the at least one first PSF is configured according to at least one of a range processing method of the simulated radar system or a Doppler processing method of the simulated radar system, wherein the at least one second PSF is configured according to at least one of an azimuth processing method of the simulated radar system or an elevation processing method of the simulated radar system. [6] Method according to one of claims 2 to 5, comprising: Determining a simulated radar spectrum by processing the multidimensional energy map based on one or more PSFs; Determining a set simulated radar spectrum by setting the simulated radar spectrum according to one or more setting models; and Determine the simulated radar information based on the set simulated radar spectrum. [7] The method of claim 6, wherein the one or more adjustment models comprise a noise adjustment model configured to model noise affecting the simulated radar system, a phase noise adjustment model configured to model phase noise affecting the simulated radar system, a transmit-to-receive (Tx-RX) leakage adjustment model configured to model a Tx-Rx leakage of the simulated radar system, an interference model configured to model interference affecting the simulated radar system, and / or a weather model configured to model one or more weather conditions affecting the simulated radar system. [8] A method according to claim 6 or 7, comprising determining the simulated radar information by applying a detection mechanism to the adjusted simulated radar spectrum. [9] Method according to one of claims 2 to 8, comprising determining the multidimensional energy map according to a ray tracing mechanism. [10] The method of any one of claims 2 to 9, wherein the multidimensional energy map comprises a four-dimensional (4D) energy map comprising a range dimension, a Doppler dimension, an azimuth dimension, and an elevation dimension. [11] The method of any one of claims 1 to 10, wherein the one or more PSFs comprise at least one PSF based on at least one of a range processing method of the simulated radar system or a Doppler processing method of the simulated radar system. [12] The method of any one of claims 1 to 11, wherein the one or more PSFs comprise a PSF based on at least one of an azimuth processing method of the simulated radar system or an elevation processing method of the simulated radar system. [13] The method of any one of claims 1 to 12, comprising configuring the path loss model based on one or more radar communication settings to configure communication of the radar signals by the simulated radar system. [14] The method of claim 13, wherein the one or more radar communication settings comprise at least one of a transmit (Tx) power for transmitting the radar signals, a Tx antenna pattern of the simulated radar system, a receive (Rx) antenna pattern of the simulated radar system, a radar frame structure for transmitting the radar signals, or a Tx method for transmitting the radar signals. [15] The method of any one of claims 1 to 14, comprising configuring the path loss model based on at least one of the following: Installation information defining at least one of an installation location and an installation orientation for one or more antennas of the simulated radar system; one or more interference conditions for the simulated scene; and / or one or more weather conditions for the simulated scene. [16] The method of any one of claims 1 to 15, comprising configuring the one or more PSFs based on one or more settings of the simulated radar system. [17] The method of any one of claims 1 to 16, comprising configuring the one or more PSFs based on at least one of a processing window setting of the simulated radar system, a signal bandwidth setting of the simulated radar system, a pulse repetition interval (PRI) setting of the simulated radar system, a pulse count per frame setting of the simulated radar system, a frame length setting of the simulated radar system, or an array aperture setting of the simulated radar system. [18] A method according to any one of claims 1 to 17, comprising: Providing a user interface to receive simulation setting information from a user, wherein the simulation setting information defines one or more settings of the simulated radar system; and Determine the simulated radar information based on the simulation setting information. [19] The method of claim 18, comprising configuring at least one PSF of the one or more PSFs based on the simulation setting information. [20] The method of claim 18 or 19, comprising configuring the path loss model based on the simulation setting information. [21] The method of any one of claims 1 to 20, wherein the simulated scene information comprises a five-dimensional (5D) energy map comprising a range dimension, a Doppler dimension, an azimuth dimension, an elevation dimension, and a radar cross section (RCS) dimension. [22] A method according to any one of claims 1 to 21, comprising providing the output in accordance with one or more real-time radar system latency constraints for the simulated radar system. [23] The method of any one of claims 1 to 22, wherein the simulated radar information comprises simulated radar point cloud information corresponding to the simulated scene. [24] The method of any one of claims 1 to 23, wherein the simulated radar information comprises at least one of an object list, a tracked object list, bounding box information of one or more bounding boxes, classification information for classifying one or more objects, an accumulated point cloud, a multi-frame filtered point cloud, or drivable spatial information. [25] A method according to any one of claims 1 to 24, comprising providing the output comprising simulated radar data provided by a simulator to a controller under test. [26] The method of any one of claims 1 to 24, comprising providing the output comprising simulated radar data configured to train an artificial intelligence (AI) based algorithm. [27] A product comprising one or more tangible computer-readable non-transitory storage media comprising instructions which, when executed by at least one computer processor, enable the at least one processor to cause a radar simulator to perform the method of any one of claims 1 to 26. [28] Apparatus comprising means for performing radar simulation operations according to the method of any one of claims 1 to 26. [29] Test simulator, comprising: a scene generator for generating simulated scene information corresponding to a simulated scene based on control information from a controller under test; and a radar simulator configured to provide simulated radar data for control in the test based on the simulated scene information according to the method of any one of claims 1 to 24.

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