Apparatus, system and method for radar antenna calibration

Abstract

For example, a radar apparatus may include an input that receives radar receive (Rx) data, the radar Rx data being based on radar signals received via multiple Rx antennas of a multiple-input multiple-output (MIMO) radar antenna, and a radar processor configured to generate the radar information based on the radar Rx data by calibrating antenna mismatch (MM) of the MIMO radar antenna so that the radar information includes an angle-of-arrival (AoA) spectrum having a peak side lobe level (PSLL) of at least 30 decibels (dB).

Description

[Technical field]

[0001] [Cross reference] This application claims the benefit of and priority to U.S. Provisional Patent Application No. 63 / 005,773, entitled “APPARATUS, SYSTEM AND METHOD OF RADAR ANTENNA CALIBRATION,” filed on April 6, 2020, the entire disclosure of which is incorporated herein by reference.

[0002] The aspects described herein relate generally to radar antenna calibration. [Background technology]

[0003] Multiple Input Multiple Output (MIMO) radar is a technology that allows for a reduction in the number of physical array apertures and antenna elements by transmitting orthogonal signals from a multi-element transmit (Tx) array and processing the received signals via a multi-element receive (Rx) array.

[0004] Since antennas are manufactured with some elevated phase and gain as their base state, antenna arrays can malfunction without proper calibration of the antenna elements. [Brief description of the drawings]

[0005] For simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity of presentation. In addition, reference numerals may be repeated among the figures to indicate corresponding or similar elements. The figures are listed below.

[0006] [Figure 1] FIG. 1 is a schematic block diagram of a vehicle implementing a radar in accordance with some demonstrative aspects.

[0007] [Diagram 2] FIG. 1 is a schematic block diagram of a robot implementing radar in accordance with some demonstrative aspects.

[0008] [Diagram 3] 1 is a schematic block diagram of a radar device in accordance with some demonstrative aspects.

[0009] [Figure 4] FIG. 1 is a schematic block diagram of a frequency modulated continuous wave (FMCW) radar device in accordance with some demonstrative embodiments.

[0010] [Diagram 5] FIG. 1 is a schematic diagram of an extraction scheme that may be implemented to extract range and speed (Doppler) estimates from digital received radar data values ​​in accordance with some demonstrative aspects.

[0011] [Figure 6] 1 is a schematic diagram of an angle determination scheme that may be implemented to determine Angle of Arrival (AoA) information based on incoming wireless signals received by a receive antenna array, in accordance with some demonstrative aspects.

[0012] [Figure 7] FIG. 1 is a schematic diagram of a multiple-input multiple-output (MIMO) radar antenna scheme that may be implemented based on a combination of transmit (Tx) and receive (Rx) antennas in accordance with some demonstrative aspects.

[0013] [Figure 8] FIG. 1 is a schematic block diagram of a radar front end and a radar processor in accordance with some demonstrative aspects.

[0014] [Figure 9] FIG. 1 is a schematic diagram of a radar detection scenario and a graph showing multiple AoA spectral images corresponding to the radar detection scenario to illustrate a technical problem that may be addressed in accordance with some demonstrative aspects.

[0015] [Figure 10] 1 is a schematic diagram of a performance graph of radar processing with antenna mismatch calibration in accordance with some demonstrative aspects.

[0016] [Figure 11A] 1 is a schematic diagram of a graph illustrating signal-to-noise ratio (SNR) performance of radar processing with antenna mismatch calibration in accordance with some demonstrative aspects.

[0017] [Figure 11B] 1 is a schematic diagram of a graph illustrating peak side lobe level (PSLL) performance of radar processing with antenna mismatch calibration in accordance with some demonstrative aspects.

[0018] [Figure 12A] 1 is a schematic diagram of a graph illustrating SNR loss performance of radar processing with antenna mismatch calibration in accordance with some demonstrative embodiments.

[0019] [Figure 12B] 1 is a schematic diagram of a graph illustrating PSLL performance of radar processing with antenna mismatch calibration in accordance with some demonstrative aspects.

[0020] [Figure 13] 1 is a schematic diagram of a graph illustrating antenna gain mismatch that can be used as a reference in accordance with some demonstrative aspects.

[0021] [Figure 14] 1 is a simplified flowchart of a method of radar antenna calibration in accordance with some demonstrative aspects.

[0022] [Figure 15] 1 is a schematic diagram of an article of manufacture in accordance with some demonstrative embodiments. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] In the following detailed description, numerous specific details are set forth to provide a thorough understanding of some aspects. However, it will be understood by those skilled in the art 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 so as not to obscure the discussion.

[0024] For example, discussions herein utilizing terms such as "processing," "calculating," "calculating," "determining," "establishing," "analyzing," "checking," etc. may refer to operations and / or processes of a computer, computing platform, computing system, or other electronic computing device that manipulates and / or transforms data represented as physical (e.g., electronic) quantities in the computer's registers and / or memory into other data that is similarly represented as physical quantities in the computer's registers and / or memory or other information storage medium that may store instructions for performing the operations and / or processes.

[0025] The terms "plurality" and "a plurality" as used herein include, for example, "multiple" or "two or more." For example, "a plurality of items" includes two or more items.

[0026] The words "exemplary" and "demonstrative" are used herein to mean "serving as an example, instance, demonstration, or illustration." Any aspect or design described herein as "exemplary" or "demonstrative" is not necessarily to be construed as preferred or advantageous over other aspects or designs.

[0027] References to "one embodiment," "one embodiment," "exemplary embodiment," "various embodiments," etc. indicate that the embodiment and / or embodiments so described may include a particular feature, structure, or characteristic, but not all embodiments or aspects necessarily include that particular feature, structure, or characteristic. Further, repeated use of the phrase "in one embodiment" does not necessarily refer to the same embodiment or aspects (although they may).

[0028] As used herein, unless otherwise indicated, the use of ordinal numbers "first," "second," "third," etc. to describe a common object indicates only that different instances of a similar object are being referred to, and is not intended to imply that the objects so described must be in any given sequence, either temporally, spatially, ranked, or in any other manner.

[0029] The terms "at least one" and "one or more" may be understood to include a quantity greater than or equal to one, e.g., 1, 2, 3, 4 [...], etc. The term "at least one of" with reference to a group of elements may be used herein to mean at least one element from the group of elements. For example, the term "at least one of" with reference to a group of elements may be used herein to mean one of the listed elements, a plurality of one of the listed elements, a plurality of individual listed elements, or a plurality of a multiplicity of individual listed elements.

[0030] The term "data", as used herein, may be understood to include information in any suitable analog or digital format, for example provided as a file, a portion of a file, a set of files, a signal or stream, a portion of a signal or stream, a set of signals or streams, etc. Additionally, the term "data" may also be used to mean a reference to information, for example in the form of a pointer. However, the term "data" is not limited to the examples mentioned above and may take various forms and / or represent any information as understood in the art.

[0031] The term "processor" or "controller" may be understood to include any kind of technical entity enabling handling of any suitable type of data and / or information. The data and / or information may be handled according to one or more specific functions performed by the processor or controller. Furthermore, a processor or controller may be understood as any kind of circuit, for example, any kind of analog or digital circuit. Thus, 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), etc., or any combination thereof. Any other kind of implementation of the respective functions described in more detail below may also be understood as a processor, controller, or logic circuit. It is understood that any two (or more) processors, controllers, or logic circuits described in detail herein may be implemented as a single entity or the like having equivalent functionality, and conversely, any single processor, controller, or logic circuit described in detail herein may be implemented as two (or more) separate entities or the like having equivalent functionality.

[0032] The term "memory" is understood as a computer-readable medium (e.g., a non-transitory computer-readable medium) within which data or information can be stored for retrieval. References to "memory" may therefore be understood to refer to volatile or non-volatile memory, including random access memory (RAM), read-only memory (ROM), flash memory, solid-state storage, magnetic tape, hard disk drives, optical drives, among others, or any combination thereof. As used herein, registers, shift registers, processor registers, data buffers, among others, are also encompassed by the term memory. The term "software" may be used to refer to any type of executable instructions and / or logic, including firmware.

[0033] A "vehicle" may be understood to include any type of driven object. By way of example, a vehicle may be a driven object having a combustion engine, an electric engine, a reaction engine, an electrically powered object, a hybrid powered object, or a combination thereof. A vehicle may be or include, among others, a car, a bus, a minibus, a van, a truck, a mobile home, a vehicle trailer, a motorcycle, a bicycle, a tricycle, a locomotive, a freight train, a mobile robot, a personal transporter, a boat, a ship, a submarine, a submarine, a drone, an aircraft, a rocket.

[0034] A "ground vehicle" may be understood to include any type of vehicle configured to move on ground, e.g., on a street, road, track, on one or more rails, off-road, etc.

[0035] An "autonomous vehicle" may describe a vehicle capable of implementing at least one navigation change without driver input. A navigation change may describe or include one or more changes in steering, braking, acceleration / deceleration, or any other action related to the motion of the vehicle. A vehicle may be described as autonomous even if the vehicle is not fully autonomous, e.g., the vehicle is fully operational or without driver input. An autonomous vehicle may include a vehicle that can operate under driver control during certain periods and without driver control during other periods. Additionally or alternatively, an autonomous vehicle may include a vehicle that controls only some aspects of vehicle navigation, such as steering to keep the vehicle on course between lane restrictions, or some steering actions under certain circumstances, but not under all circumstances, but leaves other aspects of vehicle navigation, such as braking or braking under certain circumstances, to the driver. Additionally or alternatively, an autonomous vehicle may include a vehicle that shares control of one or more aspects of vehicle navigation under certain circumstances, e.g., hands-on, such as being sensitive to driver input, and / or a vehicle that controls one or more aspects of vehicle navigation under certain circumstances, e.g., hands-off, such as being independent of driver input. Additionally or alternatively, an autonomous vehicle may include a vehicle that controls one or more aspects of vehicle navigation under certain circumstances, e.g., under certain environmental conditions, e.g., spatial domain, road conditions, etc. In some aspects, an autonomous vehicle may handle some or all aspects of vehicle braking, speed control, speed control, steering, and / or any other additional operations. An autonomous vehicle may include a vehicle that can operate without a driver.The level of autonomy of a vehicle may be described or determined by the vehicle's Society of Automotive Engineers (SAE) level, e.g., as defined by the SAE, e.g., in "SAE J3016 2018: Taxonomy and definitions for terms related to driving automation systems for on road motor vehicles," or by other relevant expert organizations. The SAE levels may have values ​​ranging from a minimum level, e.g., Level 0 (illustratively, substantially no driving automation), to a maximum level, e.g., Level 5 (illustratively, full driving automation).

[0036] The phrase "vehicle operational data" may be understood to describe any type of characteristic associated with the operation of a vehicle. By way of example, the "vehicle operational data" may describe the status of a vehicle, such as the type of tires of the vehicle, the type of the vehicle, and / or the year of manufacture of the vehicle. More generally, the "vehicle operational data" may describe or include static characteristics or static vehicle operational data (by way of example, characteristics or data that do not change over time). As another example, in addition to or in the alternative, the "vehicle operational data" may describe or include characteristics that change during the operation of the vehicle, such as environmental conditions, e.g., weather conditions or road conditions during the operation of the vehicle, fuel levels, fluid levels, operating parameters of the vehicle's drive source, etc. More generally, the "vehicle operational data" may describe or include varying characteristics or varying vehicle operational data (by way of example, time-varying characteristics or data).

[0037] Some aspects may be used in conjunction with various devices and systems, such as radar sensors, radar devices, radar systems, vehicles, vehicle systems, autonomous vehicle systems, vehicular communication systems, vehicular devices, airborne platforms, waterborne transportation platforms, road infrastructure, sports capture infrastructure, urban monitoring infrastructure, static infrastructure platforms, indoor platforms, moving platforms, robotic platforms, industrial platforms, sensor devices, user equipment (UE), mobile devices (MD), radio stations (STA), sensor devices, non-vehicular devices, mobile or portable devices, and the like.

[0038] Some aspects may be used in conjunction with radio frequency (RF) systems, radar systems, vehicle radar systems, autonomous systems, robotic systems, detection systems, and the like.

[0039] Some demonstrative embodiments may be used in conjunction with RF frequencies in frequency bands having a start frequency above 10 gigahertz (GHz), e.g., frequency bands having a start frequency between 10 GHz and 120 GHz. For example, some demonstrative embodiments may be used in conjunction with RF frequencies having a start frequency above 30 GHz, e.g., above 45 GHz, e.g., above 60 GHz. For example, some demonstrative embodiments may be used in conjunction with automotive radar frequency bands, e.g., frequency bands between 76 GHz and 81 GHz. However, other embodiments may be implemented utilizing any other suitable frequency bands, e.g., frequency bands above 140 GHz, frequency bands at 300 GHz, sub-terahertz (THz) bands, THz bands, infrared (IR) bands, and / or any other frequency bands.

[0040] As used herein, the term "circuitry" may refer to, be a part of, or include an Application Specific Integrated Circuit (ASIC), an integrated circuit, an electronic circuit, a processor (shared, dedicated, or group), and / or memory (shared, dedicated, or group), combinatorial logic circuitry, and / or other suitable hardware components that provide the described functionality. In some aspects, a circuit may be implemented in, or functionality associated with, one or more software or firmware modules. In some aspects, a circuit may include logic that is at least partially operable in hardware.

[0041] The term "logic" may refer to computing logic embedded in a circuit of a computing device and / or stored in a memory of a computing device, for example. For example, the logic may be accessible by a processor of the computing device to execute the computing logic to perform computing functions and / or operations. In one example, the logic may be embedded in various types of memory and / or firmware, for example, silicon blocks of various chips and / or processors. The logic may be included in and / or implemented as part of various circuits, for example, radio circuits, receiver circuits, control circuits, transmitter circuits, transceiver circuits, processor circuits, etc. In one example, the logic may be embedded in volatile and / or non-volatile memory, including random access memory, read only memory, programmable memory, magnetic memory, flash memory, persistent memory, etc. The logic may be executed by one or more processors, for example, using memory coupled to the one or more processors, for example, registers, buffers, stacks, etc., as needed to execute the logic.

[0042] As used herein with respect to a signal, the term "communicating" includes transmitting a signal and / or receiving a signal. For example, a device capable of communicating a signal may include a transmitter that transmits a signal and / or a receiver that receives a signal. The verb to communicate may be used to refer to the action of transmitting or receiving. In one example, the phrase "communicating a signal" may refer to the action of transmitting a signal by a transmitter and may not necessarily include the action of receiving a signal by a receiver. In another example, the phrase "communicating a signal" may refer to the action of receiving a signal by a receiver and may not necessarily include the action of transmitting a signal by a transmitter.

[0043] The term "antenna," as used herein, may include any suitable configuration, structure, and / or arrangement of one or more antenna elements, components, units, assemblies, and / or arrays. In some aspects, an antenna may implement transmit and receive functions using separate transmit and receive antenna elements. In some aspects, an antenna may implement transmit and receive functions using common and / or integrated transmit / receive elements. An antenna may include, for example, a phased array antenna, a single element antenna, a set of switched beam antennas, etc. In one example, an antenna may be implemented as separate elements or integrated elements, for example, as an on-module antenna, an on-chip antenna, or according to any other antenna architecture.

[0044] Some demonstrative aspects are described herein with respect to RF radar signals. However, other aspects may be implemented with respect to or in conjunction with any 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 utilizing optical and / or acoustic signals, such as Light Detection and Ranging (LiDAR) systems and / or sonar systems.

[0045] Reference is now made to FIG. 1, which generally illustrates a block diagram of a radar-implemented vehicle 100, in accordance with some demonstrative embodiments.

[0046] In some demonstrative aspects, vehicle 100 may include a car, truck, motorcycle, bus, train, air vehicle, water vehicle, cart, golf cart, electric cart, road agent, or any other vehicle.

[0047] In some demonstrative aspects, vehicle 100 may include radar device 101, e.g., as described below. For example, radar device 101 may include a radar detection device, a radar sensing device, a radar sensor, etc., e.g., as described below.

[0048] In some demonstrative aspects, the radar device 101 may be implemented as part of a vehicle system, such as a system that will be implemented and / or mounted in the vehicle 100.

[0049] In one example, the radar device 101 may be implemented as part of an autonomous vehicle system, an automated driving system, a driver assistance and / or support system, etc.

[0050] For example, a radar device 101 may be installed in a vehicle 101 for detection of nearby objects, e.g., for autonomous driving.

[0051] In some demonstrative aspects, radar device 101 may be configured to detect targets in proximity, e.g., far-proximate and / or close-proximate, of vehicle 100 using, e.g., RF and analog chains, capacitor structures, large spiral transformers, and / or any other electronic or electrical elements, e.g., as described below. In one example, radar device 101 may be mounted on vehicle 100, e.g., directly positioned on vehicle 100, or attached to vehicle 100.

[0052] In some demonstrative aspects, the vehicle 100 may be equipped with a single radar device 101. In other aspects, the vehicle 100 may be equipped with multiple radar devices 101, such as at multiple locations, such as around the vehicle 100.

[0053] In some demonstrative aspects, the radar device 101 may be implemented as a component in a suite of sensors used for driver assistance and / or autonomous vehicles, for example, due to the radar's ability to operate in nearly all weather conditions.

[0054] In some demonstrative aspects, the radar device 101 may be configured to support autonomous vehicle use, for example, as described below.

[0055] In one example, the radar device 101 may determine the class, location, orientation, speed, intent, perceptual understanding of the environment, and / or any other information corresponding to objects in the environment.

[0056] In another example, the radar device 101 may be configured to determine one or more parameters and / or information for one or more operations and / or tasks, such as route planning and / or any other task.

[0057] In some demonstrative aspects, the radar device 101 may be configured to map a scene by measuring echoes (reflectivities) of targets and distinguishing them, e.g., primarily in range, velocity, azimuth and / or elevation, e.g., as described below.

[0058] In some demonstrative aspects, the radar device 101 may be configured to detect and / or sense one or more objects located proximate to the vehicle 100, e.g., far-proximate and / or close-proximate, and provide one or more parameters, attributes, and / or information regarding the objects.

[0059] In some demonstrative embodiments, objects may include other vehicles, pedestrians, traffic signs, traffic signals, roads, road elements such as pavement intersections, edge lines, hazards such as tires, boxes, cracks in the road surface, and the like.

[0060] In some demonstrative aspects, the one or more parameters, attributes and / or information regarding the object may include the range of the object from the vehicle 100, the angle of the object relative to the vehicle 100, the location of the object relative to the vehicle 100, the relative speed of the object relative to the vehicle 100, etc.

[0061] In some demonstrative aspects, the radar device 101 may include a multiple-input multiple-output (MIMO) radar device 101, for example as described below. In one example, the MIMO radar device may be configured to utilize “spatial filtering” processing, such as beamforming and / or any other mechanism, for one or both of the transmit (Tx) and / or receive (Rx) signals.

[0062] Some demonstrative aspects are described below with respect to a radar device implemented as a MIMO radar, such as radar device 101. However, in other aspects, radar device 101 may be implemented as any other type of radar utilizing multiple antenna elements, such as a single-input multiple-output (SIMO) radar or a multiple-input single-output (MISO) radar.

[0063] Some demonstrative aspects may be implemented with respect to a radar device implemented as a MIMO radar, such as radar device 101, as described below, for example. In other aspects, however, radar device 101 may be implemented as any other type of radar, such as an electronic beam steering radar that varies its transmission according to the environment and / or ego state, a synthetic aperture radar (SAR), an adaptive and / or cognitive radar, a reflector array radar, etc.

[0064] In some demonstrative aspects, radar device 101 may include an antenna array 102, a radar front end 103 configured to communicate radar signals via antenna array 102, and a radar processor 104 configured to generate radar information based on the radar signals, for example as described below.

[0065] In some demonstrative aspects, the radar processor 104 may be configured to process radar information of the radar device 101 and / or control one or more operations of the radar device 101, for example, as described below.

[0066] In some demonstrative aspects, the radar processor 104 may include or be implemented in part or in whole by circuitry and / or logic, such as one or more processors, memory circuitry and / or logic that include the circuitry and / or logic. Additionally or alternatively, one or more functions of the radar processor 104 may be implemented by logic that may be executed by a machine and / or one or more processors, for example, as described below.

[0067] In one example, the radar processor 104 may include at least one memory, e.g., coupled to the one or more processors, which may be configured to store, e.g., at least temporarily, at least a portion of the information processed by the one or more processors and / or circuits, and / or may be configured to store logic to be utilized by the processors and / or circuits.

[0068] In other aspects, the radar processor 104 may be implemented by one or more additional or alternative elements of the vehicle 100.

[0069] In some demonstrative aspects, the radar front end 103 may comprise, for example, one or more (radar) transmitters and one or more (radar) receivers, for example, as described below.

[0070] In some demonstrative aspects, the antenna array 102 may include multiple antennas for communicating radar signals. For example, the antenna array 102 may include multiple transmit antennas in the form of a transmit antenna array and multiple receive antennas in the form of a receive antenna array. In another example, the antenna array 102 may include one or more antennas used as both transmit and receive antennas. In the latter case, the radar front end 103 may include, for example, a duplexer, e.g., circuitry for separating a transmitted signal from a received signal.

[0071] In some demonstrative aspects, as shown in FIG. 1, the radar front end 103 and antenna array 102 may be controlled, for example, by a radar processor 104 to transmit a wireless transmission signal 105.

[0072] In some demonstrative aspects, as shown in FIG. 1, a wireless transmission signal 105 may be reflected by an object 106, resulting in an echo 107.

[0073] In some demonstrative aspects, the radar device 101 may receive echoes 107, for example via the antenna array 102 and the radar front end 103, and the radar processor 104 may generate radar information, for example, by calculating information regarding the position, axial velocity (Doppler), and / or direction of the object 106, for example relative to the vehicle 100.

[0074] In some demonstrative aspects, the radar processor 104 may be configured to provide radar information to a vehicle controller 108 of the vehicle 100, for example, for autonomous operation of the vehicle 100.

[0075] In some demonstrative aspects, at least some of the functionality of radar processor 104 may be implemented as part of vehicle controller 108. In other aspects, the functionality of radar processor 104 may be implemented as part of any other element of radar device 101 and / or vehicle 100. In other aspects, radar processor 104 may be implemented as a separate part of or as part of any other element of radar device 101 and / or vehicle 100.

[0076] In some demonstrative aspects, the vehicle controller 108 may be configured to control one or more functions, operational modes, components, devices, systems and / or elements of the vehicle 100.

[0077] In some demonstrative aspects, vehicle controller 108 may be configured to control one or more vehicle systems of vehicle 100, for example, as described below.

[0078] In some demonstrative aspects, the vehicle systems may include, for example, a steering system, a braking system, a driving system, and / or any other system of the vehicle 100.

[0079] In some demonstrative aspects, vehicle controller 108 may be configured to control radar device 101 and / or process one or more parameters, attributes and / or information from radar device 101.

[0080] In some demonstrative aspects, the vehicle controller 108 may be configured to control, for example, vehicle systems of the vehicle 100 based on radar information from the radar device 101 and / or one or more other sensors of the vehicle 100, such as a light detection and ranging (LIDAR) sensor, a camera sensor, etc.

[0081] In one example, the vehicle controller 108 may control the steering system, braking system, and / or any other vehicle systems of the vehicle 100 based on, for example, information from the radar device 101, for example, based on one or more objects detected by the radar device 101.

[0082] In other aspects, the vehicle controller 108 may be configured to control any other additional or alternative functions of the vehicle 100 .

[0083] Some demonstrative aspects are described herein with respect to radar device 101 implemented in a vehicle, e.g., vehicle 100. In other aspects, a radar device, e.g., radar device 101, may be implemented as part of any other element of a transportation system or network, e.g., as part of road infrastructure and / or any other element of a transportation network or system. Other aspects may be implemented with respect to any other system, environment, and / or apparatus that may be implemented in any other object, environment, location, or place. For example, radar device 101 may be part of a non-vehicle device that may be implemented, e.g., in an indoor location, an outdoor stationary infrastructure, or any other location.

[0084] In some demonstrative aspects, the radar device 101 may be configured to support security uses. In one example, the radar device 101 may be configured to determine the nature of the motion, such as human intrusion, animal intrusion, environmental movement, etc., and / or any other additional or alternative motion nature, to identify a threat level of a detected event.

[0085] Some demonstrative aspects may be implemented in conjunction with any other additional or alternative devices and / or systems, such as for a robot, for example as described below.

[0086] In other aspects, the radar device 101 may be configured to support any other use and / or application.

[0087] Reference is now made to FIG. 2, which generally illustrates a block diagram of a robot 200 implementing radar, in accordance with some demonstrative embodiments.

[0088] In some demonstrative aspects, the robot 200 may include a robotic arm 201. The robot 200 may be implemented in a factory for handling, for example, an object 213, which may be, for example, a part to be affixed to a product being manufactured. The robotic arm 201 may include multiple moving members, for example, moving members 202, 203, 204, and a support base 205. Movement of the moving members 202, 203, and / or 204 of the robotic arm 201, for example, by actuation of associated motors, may enable physical interaction with an environment to perform a task, for example, handling the object 213.

[0089] In some demonstrative aspects, the robot arm 201 may include multiple joint elements, e.g., joint elements 207, 208, 209, that may connect, for example, members 202, 203, and / or 204 to one another and to the support 205. For example, the joint elements 207, 208, 209 may include one or more joints, each of which may provide rotatable motion, e.g., rotational motion, and / or translational motion, e.g., displacement, and / or movement of the members relative to one another, for the associated members. Movement of members 202, 203, 204 may be initiated by suitable actuators.

[0090] In some demonstrative embodiments, the member furthest from the support base 205, e.g., member 204, may also be referred to as the end effector 204 and may include one or more tools, such as a claw to grip an object, a welding tool, etc. Other members closer to the support base 205, e.g., members 202, 203, may be utilized to change the position of the end effector 204, e.g., in three-dimensional space. For example, the robotic arm 201 may be configured to function similarly to a human arm, e.g., possibly with a tool at its end.

[0091] In some demonstrative aspects, the robot 200 may include a (robot) controller 206 configured to implement interaction with the environment, e.g., by controlling actuators of the robot arm according to a control program, for example to control the robot arm 201 according to a task to be performed.

[0092] In some demonstrative aspects, an actuator may include a component adapted to affect a mechanism or process in response to being actuated. An actuator may respond to a command (so-called actuation) provided by the controller 206 by performing a mechanical movement. This means that an actuator, typically a motor (or electromechanical converter), may be configured to convert electrical energy into mechanical energy when actuated (i.e., actuated).

[0093] In some demonstrative embodiments, the controller 206 may be in communication with a radar processor 210 of the robot 200 .

[0094] In some demonstrative aspects, the radar front 211 and the radar antenna array 212 may be coupled to the radar processor 210. In one example, the radar front 211 and / or the radar antenna array 212 may be included as part of the robotic arm 201, for example.

[0095] In some demonstrative aspects, radar front end 211, radar antenna array 212, and radar processor 210 may be operable as and / or configured to form a radar device. For example, as described above by way of example, antenna array 212 may be configured to perform one or more functions of antenna array 102 (FIG. 1), radar front end 211 may be configured to perform one or more functions of radar front end 103 (FIG. 1), and / or radar processor 210 may be configured to perform one or more functions of radar processor 104 (FIG. 1).

[0096] In some demonstrative aspects, for example, the radar front end 211 and the antenna array 212 may be controlled, for example, by the radar processor 210, to transmit a wireless transmission signal 214.

[0097] In some demonstrative aspects, as shown in FIG. 2, a wireless transmission signal 214 may be reflected by an object 213, resulting in an echo 215.

[0098] In some demonstrative aspects, echoes 215 may be received, for example, via antenna array 212 and radar front end 211, and radar processor 210 may generate radar information, for example, by calculating information regarding the position, speed (Doppler) and / or direction of object 213, for example relative to robot arm 201.

[0099] In some demonstrative aspects, the radar processor 210 may be configured to provide the radar information to a robot controller 206 of the robot arm 201, for example, to control the robot arm 201. For example, the robot controller 206 may be configured to control the robot arm 201 based on the radar information, for example, to grab the object 213 and / or to perform any other action.

[0100] Reference is now made to FIG. 3, which illustrates a schematic of a radar device 300 in accordance with some demonstrative embodiments.

[0101] In some demonstrative aspects, the radar apparatus 300 may be implemented as part of a device or system 301, for example as described below.

[0102] For example, the radar apparatus 300 may be implemented as part of and / or configured to perform one or more of the operations and / or functions of the devices or systems described above with reference to Figures 1 and / or 2. In other aspects, the radar apparatus 300 may be implemented as part of any other device or system 301.

[0103] In some demonstrative aspects, the radar device 300 may comprise an antenna array that may include one or more transmit antennas 302 and one or more receive antennas 303. In other aspects, any other antenna arrangement may be implemented.

[0104] In some demonstrative aspects, the radar device 300 may include a radar front end 304 and a radar processor 309.

[0105] In some demonstrative aspects, for example as described below, as shown in FIG. 3 , one or more transmit antennas 302 may be coupled to a transmitter (or transmitter array) 305 of a radar front-end 304 and / or one or more receive antennas 303 may be coupled to a receiver (or receiver array) 306 of the radar front-end 304.

[0106] In some demonstrative aspects, the transmitter 305 may comprise one or more elements, such as an oscillator, a power amplifier, and / or one or more other elements, configured to generate a wireless transmit signal to be transmitted by one or more transmit antennas 302, e.g., as described below.

[0107] In some demonstrative aspects, for example, the radar processor 309 may provide digital radar transmission data values ​​to the radar front end 304. For example, the radar front end 304 may include a digital-to-analog converter (DAC) 307 that converts the digital radar transmission data values ​​to an analog transmission signal. The transmitter 305 may convert the analog transmission signal to a radio transmission signal to be transmitted by the transmit antenna 302.

[0108] In some demonstrative aspects, the receiver 306 may comprise one or more elements, such as one or more mixers, one or more filters, and / or one or more other elements, configured to process and downconvert radio signals received via one or more receive antennas 303, e.g., as described below.

[0109] In some demonstrative aspects, for example, receiver 306 may convert radio receive signals received via one or more receive antennas 303 to analog receive signals. Radar front end 304 may include an analog-to-digital (ADC) converter 308 that generates digital radar receive data values ​​based on the analog receive signals. For example, radar front end 304 may provide the digital radar receive data values ​​to radar processor 309.

[0110] In some demonstrative aspects, the radar processor 309 may be configured to process the digital radar reception data values, for example, to detect one or more objects, for example, in an environment of the device / system 301. This detection may include, for example, determining information including one or more of the range, speed (Doppler), direction, and / or any other information, of the one or more objects, for example, relative to the system 301.

[0111] In some demonstrative aspects, the radar processor 309 may be configured to provide the determined radar information to a system controller 310 of the device / system 301. For example, the system controller 310 may include a vehicle controller, e.g., if the device / system 301 includes a vehicle device / system, a robot controller, e.g., if the device / system 301 includes a robotic device / system, or any other type of controller for any other type of device / system 301.

[0112] In some demonstrative aspects, the system controller 310 may be configured to control one or more controlled system components 311 of the system 301, such as motors, brakes, steering, etc., via, for example, one or more corresponding actuators.

[0113] In some demonstrative aspects, the radar device 300 may include storage 312 or memory 313 to store, for example, information processed by the radar 300, such as digital radar reception data values ​​processed by the radar processor 309, radar information generated by the radar processor 309, and / or any other data to be processed by the radar processor 309.

[0114] In some demonstrative aspects, the device / system 301 may include, for example, an application processor 314 and / or a communications processor 315 that, for example, at least partially implements one or more functions of the system controller 310 and / or performs communications between the system controller 310, the radar device 300, the controlled system components 311, and / or one or more additional elements of the device / system 301.

[0115] In some demonstrative aspects, radar device 300 may be configured to generate and transmit wireless transmission signals in a manner that may support range, speed, and / or direction determination, e.g., as described below.

[0116] For example, a radar radio transmission signal may be configured to include multiple pulses, e.g., a pulsed transmission may include the transmission of short, high-power bursts in combination with periods during which the radar device listens for echoes.

[0117] For example, continuous wave (CW) could be used instead as the radio transmission signal to better support highly dynamic situations, e.g., in an automotive scenario. However, while a continuous wave, e.g., with a constant frequency, may support speed determination, it may not allow range determination, e.g., due to the lack of time marks that could allow distance calculation.

[0118] In some demonstrative aspects, the wireless transmission signal 105 (FIG. 1) may be transmitted according to a technique such as, for example, Frequency Modulated Continuous Wave (FMCW) radar, Phase Modulated Continuous Wave (PMCW) radar, Orthogonal Frequency Division Multiplexing (OFDM) radar, and / or any other type of radar technique that may support range, velocity, and / or direction determination, e.g., as described below.

[0119] Reference is now made to FIG. 4, which illustrates a schematic diagram of an FMCW radar system in accordance with some demonstrative embodiments.

[0120] In some demonstrative aspects, FMCW radar device 400 may comprise radar front end 401 and radar processor 402. For example, radar front end 304 (FIG. 3) may comprise one or more elements of radar front end 401 and / or perform one or more operations and / or functions of radar front end 401, and / or radar processor 309 (FIG. 3) may comprise one or more elements of radar processor 402 and / or perform one or more operations and / or functions of radar processor 402.

[0121] In some demonstrative aspects, the FMCW radar device 400 may be configured to communicate wireless signals in accordance with FMCW radar techniques, for example, rather than transmitting a wireless transmission signal at a constant frequency.

[0122] In some demonstrative aspects, the radio front end 401 may be configured to periodically increase and reset the frequency of the transmit signal, for example, according to a sawtooth waveform 403. In other aspects, a triangular waveform, or any other suitable waveform, may be used.

[0123] In some demonstrative aspects, for example, the radar processor 402 may be configured to provide the waveform 403 to the front end 401, for example in digital form, for example as a sequence of digital values.

[0124] In some demonstrative aspects, the radar front end 401 may include a DAC 404 that converts the waveform 403 to an analog form and provides it to a voltage controlled oscillator 405. For example, the oscillator 405 may be configured to generate an output signal that may be frequency modulated in accordance with the waveform 403.

[0125] In some demonstrative aspects, the oscillator 405 may be configured to generate an output signal that includes a radio transmission signal, which may be fed and transmitted by one or more transmit antennas 406 .

[0126] In some demonstrative aspects, the radio transmission signal generated by oscillator 405 may have the form of a sequence of chirps 407 , which may be the result of modulation of a sine wave with a sawtooth waveform 403 .

[0127] In one example, the chirp 407 may correspond to a sine wave of an oscillator signal that is frequency modulated by the "teeth" of the sawtooth waveform 403, for example from a minimum frequency to a maximum frequency.

[0128] In some demonstrative aspects, the FMCW radar device 400 may include one or more receive antennas 408 that receive a radio receive signal. The radio receive signal may be based on echoes of the radio transmit signal, for example, in addition to any noise, interference, etc.

[0129] In some demonstrative aspects, the radar front end 401 may include a mixer 409 that mixes the radio transmit signal with the radio receive signal into a mixed signal.

[0130] In some demonstrative aspects, the radar front end 401 may include a filter, such as a low pass filter (LPF) 410, that may be configured to filter the mixed signal from the mixer 409 to provide a filtered signal. For example, the radar front end 401 may include an ADC 411 that converts the filtered signal into digital received data values ​​that may be provided to the radar processor 402. In another example, the filter 410 may be a digital filter, and the ADC 411 may be arranged between the mixer 409 and the filter 410.

[0131] In some demonstrative aspects, the radar processor 402 may be configured to process the digital received data values ​​to provide radar information including, for example, range, speed (velocity / Doppler), and / or direction (AoA) information of one or more objects.

[0132] In some demonstrative aspects, the radar processor 402 may be configured to perform a first Fast Fourier Transform (FFT) to extract a delay response (also referred to as a “range FFT”) that can be used to extract range information from the digital received data values, and / or a second FFT to extract a Doppler shift response (also referred to as a “Doppler FFT”) that can be used to extract velocity information from the digital received data values.

[0133] In other aspects, any other additional or alternative methods may be utilized to extract range information. In one example, in a digital radar implementation, correlation with the transmitted signal may be used, for example, according to a matched filter implementation.

[0134] Reference is now made to Figure 5, which illustrates generally an extraction scheme that may be implemented to extract range and speed (Doppler) estimates from digital received radar data values, according to some demonstrative aspects. For example, radar processor 104 (Figure 1), radar processor 210 (Figure 2), radar processor 309 (Figure 3), and / or radar processor 402 (Figure 4) may be configured to extract range and / or speed (Doppler) estimates from digital received radar data values ​​according to one or more aspects of the extraction scheme of Figure 5.

[0135] 5, wireless receive signals including, for example, echoes of wireless transmit signals may be received by a receive antenna array 501. The wireless receive signals may be processed, for example, as described above, by a wireless radar front end 502 to generate digital receive data values. The wireless radar front end 502 may provide the digital receive data values ​​to a radar processor 503, which may process the digital receive data values ​​to provide radar information, for example, as described above.

[0136] In some demonstrative aspects, the digital received data values ​​may be represented in the form of a data cube 504. For example, the data cube 504 may include digitized samples of wireless received signals that are based on wireless signals transmitted from a transmit antenna and received by M receive antennas. In some demonstrative aspects, for example, for a MIMO implementation, there may be multiple transmit antennas and the number of samples may be doubled accordingly.

[0137] In some demonstrative aspects, a layer of datacube 504, eg, a horizontal layer of datacube 504, may include samples for an antenna, eg, each of the M antennas.

[0138] In some demonstrative aspects, the data cube 504 may include samples for K chirps. For example, as shown in FIG. 5, the chirp samples may be arranged in a so-called "slow time" direction.

[0139] In some demonstrative aspects, the data cube 504 may include L samples for a chirp, e.g., L=512, or any other number of samples per chirp. For example, as shown in FIG. 5, the samples per chirp may be arranged in a so-called "fast time" direction of the data cube 504.

[0140] In some demonstrative aspects, the radar processor 503 may be configured to process multiple samples, e.g., L samples collected per chirp and per antenna, with a first FFT. The first FFT may be performed, for example, per chirp and per antenna, such that the result of processing the data cube 504 with the first FFT may again have three dimensions and may have the size of the data cube 504, e.g., including values ​​for the L range bins rather than values ​​for the L sampling times.

[0141] In some demonstrative aspects, the radar processor 503 may be configured to process the results of the processing of the data cube 504 with a first FFT, for example, by processing the results according to a second FFT along the chirp, e.g., for each antenna and each range bin.

[0142] For example, a first FFT may be in the "fast-time" direction and a second FFT may be in the "slow-time" direction.

[0143] In some demonstrative aspects, the results of the second FFT, e.g., when aggregated across antennas, may provide a range / Doppler (R / D) map 505. The R / D map may have FFT peaks 506, e.g., including peaks of FFT output values ​​(in terms of absolute value) for range / Doppler bins, e.g., for particular range / speed combinations. For example, the range / Doppler bins may correspond to range bins and Doppler bins. For example, the radar processor 503 may consider range and speed peaks, e.g., corresponding to the range bin and speed bin of the peak, as potentially corresponding to an object.

[0144] In some demonstrative aspects, the extraction scheme of Figure 5 may be implemented for an FMCW radar, such as FMCW radar 400 (Figure 4), as described above. In other aspects, the extraction scheme of Figure 5 may be implemented for any other radar type. In one example, the radar processor 503 may be configured to determine a range / Doppler map 505 from digital received data values ​​of a PMCW radar, OFDM radar, or any other radar technology. For example, in an adaptive or cognitive radar, the pulses, waveforms, and / or modulation within a frame may change over time, for example according to the environment.

[0145] 3, in some demonstrative aspects, the receive antenna arrangement 303 may be implemented using a receive antenna array having multiple receive antennas (or receive antenna elements). For example, the radar processor 309 may be configured to determine an angle of arrival of a received wireless signal, e.g., echo 105 (FIG. 1) and / or echo 215 (FIG. 2). For example, the radar processor 309 may be configured to determine a direction of a detected object, e.g., relative to the device / system 301, e.g., based on the angle of arrival of the received wireless signal, e.g., as described below.

[0146] Reference is made to FIG. 6, which illustrates generally an angle determination scheme that may be implemented to determine angle-of-arrival (AoA) information based on incoming radio signals received by a receive antenna array 600, in accordance with some demonstrative aspects.

[0147] 6 shows an angle determination scheme based on signals received at a receive antenna array. In some demonstrative aspects, for example in a virtual MIMO array, the angle determination can also be based on signals transmitted by an array of Tx antennas.

[0148] 6 shows a one-dimensional angle determination scheme. Other multi-dimensional angle determination schemes can be implemented, for example two-dimensional or three-dimensional schemes.

[0149] In some demonstrative aspects, as shown in FIG. 6, a receive antenna array 600 may include M antennas (numbered 1 through M from left to right).

[0150] It is assumed that the echo comes from an object located in the upper left direction, as shown by the arrow in Figure 6. Therefore, the direction of the echo, e.g., the incoming radio signal, may be toward the lower right. According to this example, the further to the left the receiving antenna is located, the earlier it will receive a particular phase of the incoming radio signal.

[0151] For example, the phase difference between two antennas of the receive antenna array 601, denoted Δφ, may be determined, for example, as follows:

number

[0152] In some demonstrative aspects, the radar processor 309 (FIG. 3) may be configured to exploit this relationship between the phase and angle of the incoming radio signal to determine, for example, the angle of arrival of the echo, for example, by performing an FFT across the antenna, such as a third FFT (an “angle FFT”).

[0153] In some demonstrative aspects, multiple transmit antennas, e.g., in the form of an antenna array having multiple transmit antennas, may be used, e.g., to increase spatial resolution, e.g., to provide high resolution radar information. For example, a MIMO radar device may utilize a virtual MIMO radar antenna, which may be formed as a convolution of multiple transmit antennas convolved with multiple receive antennas.

[0154] Reference is now made to FIG. 7, which illustrates generally a MIMO radar antenna scheme that may be implemented based on a combination of transmit (Tx) and receive (Rx) antennas, in accordance with some demonstrative aspects.

[0155] 7, a radar MIMO arrangement may comprise a transmit antenna array 701 and a receive antenna array 702. For example, one or more transmit antennas 302 (FIG. 3) may be implemented to include the transmit antenna array 701 and / or one or more receive antennas 303 (FIG. 3) may be implemented to include the receive antenna array 702.

[0156] In some demonstrative aspects, an antenna array including multiple antennas for both transmitting radio transmission signals and receiving echoes of the radio transmission signals may be utilized to provide multiple virtual channels as shown by the dashed lines in Figure 7. For example, the virtual channels may be formed as convolutions between the transmit and receive antennas, e.g., as Kronecker products, e.g., representing virtual steering vectors of a MIMO radar.

[0157] In some demonstrative aspects, the transmit antennas, eg, each transmit antenna, may be configured to emit an individual wireless transmit signal, eg, having a phase associated with the respective transmit antenna.

[0158] For example, an array of N transmit antennas and M receive antennas may be implemented to provide a virtual MIMO array of size N x M. For example, the virtual MIMO array may be formed according to a Kronecker product operation applied to the Tx and Rx steering vectors.

[0159] 8 is a schematic block diagram of radar front end 804 and radar processor 834, according to some demonstrative aspects. For example, radar front end 103 (FIG. 1), radar front end 211 (FIG. 1), radar front end 304 (FIG. 3), radar front end 401 (FIG. 4), and / or radar front end 502 (FIG. 5) may include one or more elements of radar front end 804 and / or perform one or more operations and / or functions of radar front end 804.

[0160] In some demonstrative aspects, the radar front end 804 may be implemented as part of a MIMO radar utilizing a MIMO radar antenna 881 including multiple Tx antennas 814 configured to transmit multiple Tx RF signals (also referred to as “Tx radar signals”) and multiple Rx antennas 816 configured to receive multiple Rx RF signals (also referred to as “Rx radar signals”), e.g., based on the Tx radar signals, as described below.

[0161] In some demonstrative aspects, the MIMO antenna array 881, antenna 814, and / or antenna 816 may include or be part of any type of antenna suitable for transmitting and / or receiving radar signals. For example, the MIMO antenna array 881, antenna 814, and / or antenna 816 may be implemented as part of any suitable configuration, structure, and / or arrangement of one or more antenna elements, components, units, assemblies, and / or arrays. For example, the MIMO antenna array 881, antenna 814, and / or antenna 816 may be implemented as part of a phased array antenna, a multiple element antenna, a set of switched beam antennas, etc. In some aspects, the MIMO antenna array 881, antenna 814, and / or antenna 816 may be implemented to support transmit and receive functions using separate transmit and receive antenna elements. In some aspects, the MIMO antenna array 881, antenna 814, and / or antenna 816 may be implemented to support transmit and receive functions using common and / or integrated transmit / receive elements.

[0162] In some demonstrative aspects, the MIMO radar antenna 881 may include a rectangular MIMO antenna array and / or a curved array, for example, shaped to accommodate a vehicle design. In other aspects, any other type, shape and / or arrangement of the MIMO radar antenna 881 may be implemented.

[0163] In some demonstrative aspects, the radar front end 804 may include one or more radios configured to generate and transmit Tx RF signals via a Tx antenna 814 and / or process Rx RF signals received via an Rx antenna 816, e.g., as described below.

[0164] In some demonstrative aspects, the radar front end 804 may include at least one transmitter (Tx) 883 including circuitry and / or logic configured to generate and / or transmit a Tx radar signal via the Tx antenna 814.

[0165] In some demonstrative aspects, the radar front end 804 may include at least one receiver (Rx) 885 that includes circuitry and / or logic to receive and / or process an Rx radar signal received via the Rx antenna 816, e.g., based on a Tx radar signal.

[0166] In some demonstrative aspects, the transmitter 883 and / or the receiver 885 may include circuitry; logic; radio frequency (RF) components, circuitry and / or logic; baseband components, circuitry and / or logic; modulation components, circuitry and / or logic; demodulation components, circuitry and / or logic; amplifiers; analog-to-digital converters and / or digital-to-analog converters; filters, etc.

[0167] In some demonstrative aspects, the transmitter 883 may include multiple Tx chains 810, each configured to generate and transmit a Tx RF signal via a Tx antenna 814, and / or the receiver 885 may include multiple Rx chains 812, each configured to receive and process an Rx RF signal received via an Rx antenna 816, for example.

[0168] In some demonstrative aspects, radar processor 834 may be configured to generate radar information 813 based on, for example, radar signals communicated by MIMO radar antenna 881, for example, as described below. For example, radar processor 104 (FIG. 1), radar processor 210 (FIG. 1), radar processor 309 (FIG. 3), radar processor 402 (FIG. 4), and / or radar processor 503 (FIG. 5) may include one or more elements of radar processor 834 and / or perform one or more operations and / or functions of radar processor 834.

[0169] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813, for example, based on radar Rx data 811 received from multiple Rx chains 812. For example, the radar Rx data 811 may be based on an Rx RF signal received via an Rx antenna 816.

[0170] In some demonstrative aspects, the radar processor 834 may have an input 832 that receives radar Rx data 811 from multiple Rx chains 812.

[0171] In some demonstrative aspects, the radar processor 834 may comprise at least one processor 836 that may be configured, for example, to process the radar Rx data 811 and / or execute one or more operations, methods, and / or algorithms.

[0172] In some demonstrative aspects, radar processor 834 may include at least one memory 838, e.g., coupled to processor 836. For example, memory 838 may be configured to store data processed by radar processor 834. For example, memory 838 may store, e.g., at least temporarily, at least a portion of information processed by processor 836 and / or logic to be utilized by processor 836.

[0173] In some demonstrative aspects, memory 838 may be configured to store at least a portion of the radar data, e.g., a portion of the radar Rx data or all of the radar Rx data, for processing by processor 836, e.g., as described below.

[0174] In some demonstrative aspects, memory 838 may be configured to store processed data that may be generated by processor 836, for example, during the process of generating radar information 813, as described below.

[0175] In some demonstrative aspects, the memory 838 may be configured to store range and / or Doppler information that may be generated by the processor 836, for example, based on the radar Rx data, for example, as described below. In one example, the range and / or Doppler information may be determined based on a cross-correlation (XCORR) operation that may be applied to the radar Rx data. Any other additional or alternative operations, algorithms and / or procedures may be utilized to generate the range and / or Doppler information.

[0176] In some demonstrative aspects, the memory 838 may be configured to store AoA information that may be generated by the processor 836 based on, for example, radar Rx data, range information, and / or Doppler information, for example, as described below. In one example, the AoA information may be determined based on an AoA estimation algorithm. Any other additional or alternative operations, algorithms, and / or procedures may be utilized to generate the AoA information.

[0177] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813 including one or more of range information, Doppler information, and / or AoA information, for example, as described below.

[0178] In some demonstrative aspects, radar information 813 may include Point Cloud 1 (PC1) information, including, for example, raw point cloud estimates, for example, range, axial velocity, azimuth angle, and / or elevation angle.

[0179] In some demonstrative aspects, radar information 813 may include point cloud 2 (PC2) information, which may be generated, for example, based on PC1 information. For example, PC2 information may include clustering information, tracking information, such as probability and / or density function tracking, bounding box information, classification information, orientation information, etc.

[0180] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813 in the form of four-dimensional (4D) image information, e.g., a cube, that may represent 4D information corresponding to one or more detected targets.

[0181] In some demonstrative aspects, for example, the 4D image information may include range values, e.g., based on range information, velocity values, e.g., based on Doppler information, azimuth values, e.g., based on azimuth angle AoA information, elevation values, e.g., based on elevation angle AoA information, and / or any other values.

[0182] In some demonstrative aspects, radar processor 834 may be configured to generate radar information 813 in any other form and / or including any other additional or alternative information.

[0183] In some demonstrative aspects, the radar processor 834 may be configured to process signals communicated via the MIMO radar antenna 881 as signals of a virtual MIMO array formed by the convolution of multiple Rx antennas 816 and multiple Tx antennas 814.

[0184] In some demonstrative aspects, the radar front end 804 and / or the radar processor 834 may be configured to utilize MIMO techniques, e.g., to support a reduced physical array aperture, e.g., array size, and / or to utilize a reduced number of antenna elements. For example, the radar front end 804 and / or the radar processor 834 may be configured to transmit orthogonal signals via a Tx array that includes a plurality of N elements, e.g., the Tx antenna 814, and to process received signals via an Rx array that includes a plurality of M elements, e.g., the Rx antenna 816.

[0185] In some demonstrative aspects, utilizing MIMO techniques of transmitting orthogonal signals from a Tx array having N elements and processing the received signals at an Rx array having M elements may be equivalent to a radar utilizing transmission from one antenna and reception with N*M antennas, for example, under the far-field approximation. For example, the radar front end 804 and / or radar processor 834 may be configured to utilize the MIMO antenna array 881 as a virtual array having an equivalent array size of N*M, for example, as a convolution of the locations of the physical elements, e.g., antennas 814 and / or 816, which may define the locations of the virtual elements.

[0186] In some demonstrative aspects, there may be a need to provide a technical solution for efficiently and / or accurately calibrating antenna arrays. For example, antennas may be manufactured with some elevated phase and gain as their base state, and accordingly, the antenna array may malfunction if, for example, antenna elements of the array are not calibrated.

[0187] In some demonstrative aspects, calibrating an antenna array by placing targets at known locations and with expected gains and phases per antenna may have one or more technical inefficiencies, drawbacks, and / or problems in one or more use cases and / or scenarios. For example, a single target may not be sufficient to calibrate an antenna because the antenna pattern is non-isotropic. Thus, multiple antennas may be required at various locations to calibrate the entire antenna array. Such a solution may be costly in terms of time and cost.

[0188] Some demonstrative aspects may be configured to provide a technical solution that supports calibrating the antenna array at multiple instances, e.g., at one or more defined instances, in a dynamic manner, and / or in real time, e.g., after installation and / or during operation of the radar front end 804. In one example, the radar processor 834 may be configured to support calibration of the MIMO antenna array 881, e.g., at or after installation of one or more antenna elements of the MIMO antenna array 881, and / or at one or more later time points, e.g., after processing of one or more antenna elements in the antenna array 881 and / or after processing of the surroundings of the MIMO antenna array 881. In one example, if the MIMO antenna array 881 is located behind a car bumper, the calibration may be performed based on, e.g., installation, processing, and / or changes of the car bumper, e.g., changes after an accident, since the car bumper may add some misalignment to the calibration of the MIMO antenna array 881.

[0189] In some demonstrative aspects, the radar processor 834 may be configured to perform mismatch calibration to calibrate mismatches in the MIMO antenna array 881, for example, to improve performance of the antenna array 881, e.g., as described below.

[0190] In some demonstrative aspects, the radar processor 834 may be configured to perform mismatch calibration, for example to provide a technical solution that may even avoid the use of factory calibration and / or specialized hardware.

[0191] In some demonstrative aspects, there may be a need to provide a technical solution that efficiently and / or accurately calibrates antenna array mismatch (MM) of an antenna array, for example, by calibrating at least one of Gain MM (GMM), Phase MM (PMM), and / or Cross Coupling (CC) between elements of the antenna array.

[0192] In some demonstrative aspects, there may be a need to provide a technical solution that achieves sufficient Peak Side Lobe Level (PSLL) of an estimated AoA spectrum, which may be a key performance indicator (KPI) for a radar system.

[0193] In some empirical aspects, the PSLL of an AoA spectrum may be determined as the difference between the power level (e.g., in decibels (dB)) of a main lobe in the AoA spectrum and the power level (e.g., in dB) of a peak, e.g., a maximum side lobe, corresponding to the main lobe. For example, according to this PSLL determination, a higher PSLL may be considered better than a lower PSLL.

[0194] In some empirical aspects, for example, when the main lobe has a power level of 0 dB, the PSLL may be determined as a positive value according to the power level of the peak side lobe corresponding to the main lobe.

[0195] In other aspects, the PSLL of the AoA spectrum may be determined as the difference between the power level (e.g., in dB) of a peak, e.g., the maximum side lobe, corresponding to the main lobe and the power level (e.g., in dB) of the main lobe in the AoA spectrum. For example, according to this PSLL definition, the PSLL may include negative values. For example, according to this PSLL definition, a lower PSLL may be considered better than a higher PSLL.

[0196] In some demonstrative aspects, PSLL may be affected by antenna array mismatch. For example, to achieve sufficient, e.g., improved PSLL levels, there may be a need for reduced antenna mismatch, e.g., reduced GMM, e.g., gain variation less than about 0.05 dB, and / or reduced PMM, e.g., angle variation less than about 0.25 deg.

[0197] In one example, a first PSLL level of 60 dB and a second PSLL level of 45 dB may be achieved based on, for example, the following mismatch levels: [Table 1]

[0198] For example, in accordance with Table 1, to achieve an improved PSLL level of, for example, at least 30 dB, such as 45 dB or 60 dB, there may be a need to reduce the mismatch parameter, for example, even to less than about 0.5 dB.

[0199] In another example, any other combination of MM parameters may be implemented.

[0200] In some empirical aspects, implementing an antenna array without antenna MM calibration may result in PSLL levels that may result in one or more technical inefficiencies, disadvantages and / or problems in one or more use cases and / or scenarios, e.g., as described below.

[0201] Reference is made to FIG. 9 , which generally illustrates a detection scenario 900 and a graph 910 illustrating a number of AoA spectral images corresponding to the radar detection scenario 900 to illustrate a technical problem that may be addressed in accordance with some demonstrative aspects.

[0202] As shown in FIG. 9, a detection scenario 900 shows a person 912 crossing a road or simply standing on the road, and a parked car 914, which can be detected by vehicle radar 915.

[0203] According to detection scenario 900, human 912 and car 914 may be detected by vehicle radar 915 as being within the same range-Doppler (RD) bin, for example, human 912 and car 914 may be detected by vehicle radar 915 as being at approximately the same range and speed.

[0204] For example, following detection scenario 900, there may be a need to be able to distinguish between a human 912 and a vehicle 914, for example, by detecting different AoAs for the human 912 and the vehicle 914, for example, as estimated by vehicle radar 915.

[0205] In some demonstrative aspects, as shown in FIG. 9, the AoA spectrum image 902 may be based on Rx radar signals received by a MIMO antenna array with no antenna mismatch.

[0206] In some demonstrative aspects, as shown in FIG. 9, the AoA spectral image 904 may be based on Rx radar signals received by a MIMO antenna array with antenna mismatch and without performing antenna mismatch calibration.

[0207] In some demonstrative aspects, as shown in FIG. 9, antenna mismatch can result in a “corrupted” AoA spectrum image 904 having, for example, an increased noise level compared to an AoA image 902 without the mismatch, for example.

[0208] In some demonstrative aspects, as shown in FIG. 9, an AoA spectral image 906 may be determined based on Rx radar signals received by a MIMO antenna array with antenna mismatch when applying antenna MM calibration, for example, as described below.

[0209] In some empirical aspects, as shown in FIG. 9, an AoA spectral image 906 of a MIMO antenna array with antenna mismatch calibration may be relatively similar to an AoA spectral image 902 of an antenna array without antenna mismatch.

[0210] 9, a radar cross section (RCS) 916 corresponding to a car 914 may be about 40 dB higher than an RCS 913 corresponding to a human 912, as shown by the AoA spectrum image 902. Following this example, there may be a need to achieve a PSLL level of about 55 dB for the car's RCS 916 to be able to detect the human's RCS 913, for example, assuming that the post-processing signal-to-noise ratio SNR (PPSNR) of the detection is about 15 dB.

[0211] For example, as shown in FIG. 9, the AoA spectral image 904 may have a PSLL level of less than 20 dB, as may be determined based on the difference between the power level of the main lobe, e.g., about 28 dB, and the power level of the peak side lobe corresponding to the main lobe, e.g., about 10 dB.

[0212] In some demonstrative embodiments, as shown in FIG. 9, the AoA spectral image 904 may suffer from an elevated noise level, which may not allow for differentiation between an RCS 913 corresponding to a human 912 and an RCS 916 corresponding to a vehicle 914.

[0213] In some demonstrative aspects, as shown in FIG. 9, the AoA spectral image 906 may have a PSLL level of about 58 dB, as may be determined based on the difference between the power level of the main lobe, e.g., about 28 dB, and the power level of the peak side lobe corresponding to the main lobe, e.g., about 30 dB.

[0214] In some demonstrative embodiments, as shown in FIG. 9, an AoA spectral image 906 may enable differentiation between an RCS 913 corresponding to a person 912 and an RCS 916 corresponding to a vehicle 914.

[0215] For example, a PSLL of approximately 58 dB for the AoA spectral image 906 may be sufficient to enable differentiation between the AoA of a person 912 and the AoA of a vehicle 914.

[0216] 8 , in some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813 based on, for example, the radar Rx data 811 and mismatch calibration, for example, as described below. For example, the radar processor 834 may receive the radar Rx data 811 via input 832, for example, from the Rx chain 812. For example, the radar Rx data 811 may be based on a radar signal received via the Rx antenna 816.

[0217] In some demonstrative aspects, radar processor 834 may be configured to generate radar information 833 including AoA information, for example, azimuth AoA information, elevation AoA information, and / or any other AoA-based information.

[0218] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 833 including an AoA spectrum, for example, an azimuth AoA spectrum, an elevation AoA spectrum, and / or any other AoA-based spectrum.

[0219] In some demonstrative aspects, the radar processor 834 may be configured to perform mismatch calibration to calibrate mismatch of the MIMO antenna array 881, e.g., to improve performance of the antenna array 881, e.g., to achieve a PSLL of at least 30 dB, e.g., as described below.

[0220] In some demonstrative aspects, the radar processor 834 may be configured to perform mismatch calibration, e.g., as described below, to provide a technical solution that may enable calibrating the mismatch of the antenna array 881, e.g., while utilizing computationally efficient calibration techniques and / or in a manner that may support reduced calibration time.

[0221] In some demonstrative aspects, the radar processor 834 may be configured to perform mismatch calibration of the MIMO antenna array 881, for example, according to a calibration technique that may be performed within a relatively short period of time, for example even within a few minutes.

[0222] In some demonstrative aspects, the radar processor 834 may be configured to perform mismatch calibration of the MIMO antenna array 881, e.g., according to a calibration technique that may be performed in real time and / or according to a suitable timing scheme, e.g., to dynamically calibrate the mismatch calibration of the MIMO antenna array 881.

[0223] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813 based on the radar Rx data 811, e.g., by calibrating the antenna mismatch (MM) of the MIMO radar antenna 881, e.g., such that the radar information 813 includes an AoA spectrum having a PSLL of at least 30 dB, e.g., as described below.

[0224] For example, the PSLL may be defined and / or determined as the difference between the power level of a main lobe of an AoA spectrum and the power level of a peak side lobe corresponding to the main lobe in the AoA spectrum, e.g., as described below.

[0225] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813 including an AoA spectrum having a PSLL of at least 35 dB, e.g., as described below, where the PSLL is determined as the difference between the power level of a main lobe of the AoA spectrum and the power level of a peak side lobe corresponding to the main lobe in the AoA spectrum.

[0226] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813 including an AoA spectrum having a PSLL of at least 40 dB, e.g., as described below, where the PSLL is determined as the difference between the power level of a main lobe of the AoA spectrum and the power level of a peak side lobe corresponding to the main lobe in the AoA spectrum.

[0227] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813 including an AoA spectrum having a PSLL of at least 45 dB, e.g., as described below, where the PSLL is determined as the difference between the power level of a main lobe of the AoA spectrum and the power level of a peak side lobe corresponding to the main lobe in the AoA spectrum.

[0228] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813 including an AoA spectrum having a PSLL of at least 50 dB, e.g., as described below, where the PSLL is determined as the difference between the power level of a main lobe of the AoA spectrum and the power level of a peak side lobe corresponding to the main lobe in the AoA spectrum.

[0229] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813 including an AoA spectrum having a PSLL of at least 55 dB, e.g., as described below, where the PSLL is determined as the difference between the power level of a main lobe of the AoA spectrum and the power level of a peak side lobe corresponding to the main lobe in the AoA spectrum.

[0230] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813 including an AoA spectrum having a PSLL of at least 60 dB, e.g., as described below, where the PSLL is determined as the difference between the power level of a main lobe of the AoA spectrum and the power level of a peak side lobe corresponding to the main lobe in the AoA spectrum.

[0231] In some demonstrative aspects, the radar processor 834 may be configured to generate radar information 813 including an AoA spectrum having any other suitable PSLL level.

[0232] In some demonstrative aspects, the memory 838 may be configured to store a first calibration matrix and a second calibration matrix, eg, as described below.

[0233] 8, memory 838 may be implemented as part of radar processor 834. In other aspects, memory 838 may be implemented as dedicated memory and / or as part of any other elements of radar front end 804 and / or any other device or system implementing radar front end 804 and / or radar processor 834, such as vehicle 100 (FIG. 1).

[0234] In some demonstrative aspects, the radar processor 836 may be configured to generate radar information 813 by retrieving a first calibration matrix and a second calibration matrix from the memory 838 and calibrating the antenna MM of the MIMO radar antenna 881 based on the first calibration matrix and the second calibration matrix, for example as described below.

[0235] In some demonstrative aspects, the first calibration matrix may include an Rx calibration matrix and / or the second calibration matrix may include a Tx calibration matrix, eg, as described below.

[0236] In some demonstrative aspects, for example as described below, the Rx calibration matrix may correspond to an Rx MM of multiple Rx antennas 816 and / or the Tx calibration matrix may correspond to a Tx MM of multiple Tx antennas 814 of the MIMO radar antenna 881.

[0237] In some demonstrative aspects, for example as described below, the first calibration matrix may have a size of M*M and / or the second calibration matrix may have a size of N*N, where M indicates the count of Rx antennas 816 and N indicates the count of Tx antennas 814.

[0238] In some demonstrative aspects, the radar processor 834 may be configured to update at least one of the first calibration matrix and / or the second calibration matrix based on a change in at least one parameter affecting the antenna MM of the MIMO radar antenna 881, for example, as described below.

[0239] In some demonstrative aspects, the radar processor 834 may be configured to dynamically update, e.g., in real time or with low latency, at least one of the first calibration matrix and / or the second calibration matrix based on a detected change in at least one parameter affecting the antenna MM of the MIMO radar antenna, e.g., as described below.

[0240] In some demonstrative aspects, the radar processor 834 may be configured to dynamically update at least one of the first calibration matrix and / or the second calibration matrix, e.g., in real time or with low latency, and perform mismatch calibration of the MIMO antenna array 881 based on the updated first calibration matrix and / or second calibration matrix, e.g., as described below.

[0241] In some demonstrative aspects, the radar processor 834 may be configured to dynamically update at least one of the first calibration matrix and / or the second calibration matrix, e.g., in real time or with low latency, and / or perform mismatch calibration of the MIMO antenna array 881, e.g., at one or more points in time.

[0242] In some demonstrative aspects, the radar processor 834 may be configured to automatically and / or autonomously update at least one of the first calibration matrix and / or the second calibration matrix, e.g., in real-time or with low latency, and / or perform mismatch calibration of the MIMO antenna array 881, e.g., according to a timing scheme, e.g., once a day, once a week, once a month, and / or at any other time interval.

[0243] In some demonstrative aspects, the radar processor 834 may be configured to dynamically update at least one of the first calibration matrix and / or the second calibration matrix, e.g., in real-time or with low latency, and / or perform mismatch calibration of the MIMO antenna array 881, e.g., based on one or more events and / or criteria.

[0244] In one example, the radar processor 834 may be configured to dynamically update at least one of the first calibration matrix and / or the second calibration matrix, e.g., in real time or with low latency, and / or perform mismatch calibration of the MIMO antenna array 881, e.g., based on installation and / or processing of one or more elements of the MIMO antenna array 881, e.g., after installation of the antenna array 881 on the vehicle 100 (FIG. 1), for example, and / or upon processing, replacement, and / or adjustment of one or more elements of the MIMO antenna array 881.

[0245] In one example, the radar processor 834 may be configured to dynamically update at least one of the first calibration matrix and / or the second calibration matrix, e.g., in real time or with low latency, and / or perform a mismatch calibration of the MIMO antenna array 881, e.g., after a process on the vehicle 100 (FIG. 1), e.g., switching the bumper of the vehicle 100 (FIG. 1), and / or any other process, maintenance, or service, based on, e.g., installation and / or processing of one or more other elements that may have an effect on the antenna array 881, e.g., a new calibration of the antenna array, e.g., the Tx antenna 814 and the Rx antenna 816.

[0246] In some demonstrative aspects, configuring the radar processor 834 to perform mismatch calibration of the MIMO antenna array 881, for example as described herein, may provide a technical solution that may mitigate, reduce, and / or even avoid errors in radar information that may be caused by changes in one or more elements of the radar front end 804 and / or the vehicle 100 ( FIG. 1 ), including, for example, aging, temperature changes, vehicle accidents, radar motion, and / or installation, etc.

[0247] In some demonstrative aspects, the radar processor 836 may be configured to generate intermediate radar information 873 based on the Rx radar signals, for example, as described below.

[0248] In some demonstrative aspects, for example, intermediate radar information 873 may include intermediate range-Doppler information based on radar Rx data 811.

[0249] In some demonstrative aspects, the radar processor 836 may be configured to generate intermediate range-Doppler information by processing the radar Rx data 811, for example, according to a range-Doppler processing scheme.

[0250] For example, the radar processor 836 may be configured to generate intermediate range information by applying range-based processing, such as cross-correlation processing, to the radar Rx data 811.

[0251] For example, the radar processor 836 may be configured to generate XCORR information based on the radar Rx data 811 and generate intermediate radar data 873, for example, by applying a fast Fourier transform (FFT) to the XCORR information.

[0252] For example, the radar processor 836 may be configured to generate intermediate range-Doppler information by applying Doppler-based processing, such as FFT processing, to the intermediate range information.

[0253] In other aspects, the intermediate radar information 873 may include any other information, for example, radar information that has been partially processed based on the radar Rx data 811.

[0254] In some demonstrative aspects, the radar processor 834 may include an antenna MM calibrator 871 configured to generate calibrated intermediate radar information 875 by applying antenna MM calibration to the intermediate radar data 873, for example as described below.

[0255] In some demonstrative aspects, the antenna mismatch calibrator 871 may be implemented as part of the radar processor 834. In other aspects, the antenna mismatch calibrator 832 and the radar processor 834 may be implemented as separate and / or dedicated elements, e.g., processors, of the radar front end 804 and / or any other device or system implementing the radar front end 804 and / or radar processor 834, e.g., the vehicle 100 (FIG. 1).

[0256] In some demonstrative aspects, the radar processor 834 may be configured to generate the radar information 813 based on the calibrated intermediate radar information 875, for example, as described below.

[0257] In some demonstrative aspects, the radar processor 834 may be configured to generate the radar information 813 by applying one or more radar processing operations, such as AoA-based processing operations, and / or any other further or alternative radar processing operations, to the calibrated intermediate radar information 875.

[0258] In some demonstrative aspects, the antenna MM calibrator 871 may be configured to retrieve a first calibration matrix and / or a second calibration matrix from memory 838, e.g., as described below, and generate calibrated intermediate radar information 875, e.g., by applying the first calibration matrix and the second calibration matrix to the intermediate radar information 873.

[0259] In some demonstrative aspects, the antenna MM calibrator 871 may be configured to determine the product of a first calibration matrix multiplied by the intermediate radar information 873, for example as described below.

[0260] In some demonstrative aspects, the antenna MM calibrator 871 may be configured to determine calibrated intermediate radar information 875, for example, by multiplying the product of a first calibration matrix and the intermediate radar information 873 by, for example, a second calibration matrix, for example, as described below.

[0261] In some demonstrative aspects, the radar processor 836 and / or the antenna MM calibrator 871 may be configured to calibrate the antenna MM of the MIMO radar antenna 881 by implementing MM calibration techniques, for example as described below.

[0262] In some demonstrative aspects, the MM calibration technique may be configured to calibrate an antenna MM of the MIMO radar antenna 881 based on, for example, a first antenna calibration matrix and a second antenna calibration matrix, for example, as described below.

[0263] In some demonstrative aspects, the MM calibration technique may be configured to calibrate the antenna MM of the MIMO radar antenna 881 based on a first antenna calibration matrix and a second antenna calibration matrix that may be estimated based on measurements at a reduced number of calibration angles, for example compared to other calibration methods.

[0264] In some demonstrative aspects, the MM calibration technique may be configured to calibrate the antenna MM of the MIMO radar antenna 881 using a number of calibration angles based, for example, on the order of the number of Tx antennas 814 and / or the order of the number of Rx antennas 816, e.g., as described below.

[0265] In some demonstrative aspects, the MM calibration technique may be configured to calibrate the antenna MM of the MIMO radar antenna 881 based on a first antenna calibration matrix and a second antenna calibration matrix, which may be estimated using a number of calibration angles that is on the order of twice the number of Tx antennas 814 and / or Rx antennas 816, for example, as described below.

[0266] In some demonstrative aspects, the MM calibration technique may be configured to calibrate the antenna MM of the MIMO radar antenna 881 based on a first antenna calibration matrix and a second antenna calibration matrix that may be estimated using less than 500 calibration angles, for example for a MIMO radar antenna 881 including a total of up to about 200 antenna elements.

[0267] In some demonstrative aspects, the MM calibration technique may be configured to calibrate the antenna MM of the MIMO radar antenna 881 based on a first antenna calibration matrix and a second antenna calibration matrix that may be estimated using less than 150 calibration angles, for example, for a MIMO radar antenna 881 including 16 Tx antennas 814 and 96 Rx antennas 816 corresponding to 1536 virtual elements of a virtual MIMO array.

[0268] In some demonstrative aspects, the radar processor 836 and / or antenna MM calibrator 871 may be configured to calibrate the antenna MM of the MIMO radar antenna 881, for example, by using an algorithm, e.g., a computationally efficient algorithm, e.g., an algorithm based on Alternating Least Squares (ALS), while implementing an MM calibration technique using a reduced number of calibration angles, which may significantly reduce production calibration time. For example, the mismatch calibration technique may use less than 150 calibration angles for the calibration of 1536 virtual elements, e.g., 16×96 virtual elements.

[0269] In other aspects, any other number of calibration angles, Tx antennas 814, and / or Rx antennas 816 may be utilized.

[0270] In some demonstrative aspects, a radar signal model may be defined to represent radar signals communicated between N Tx antennas, e.g., Tx antenna 114, and M Rx antennas, e.g., Rx antenna 116, as follows:

number

number

number

number

number

number

[0271] In some demonstrative aspects, the Tx steering vectors are

number

number

number

number

number

number

number

number

number

number

[0272] In some demonstrative aspects, the radar processor 834 and / or the antenna MM calibrator 871 may, for example, add a first mismatch calibration matrix, e.g.,

number

number

[0273] In some empirical embodiments, the Rx MM calibration matrix

number

number

[0274] In some demonstrative aspects, the Tx MM calibration matrix

number

number

[0275] In some empirical embodiments, the estimated Rx MM matrix

number

number

number

number

[0276] In some demonstrative aspects, the radar processor 834 and / or the antenna MM calibrator 871 calculates Y corrected The calibrated intermediate radar information, e.g., the calibrated intermediate radar information 875, is, e.g., Y corrupted The intermediate radar information, for example, the intermediate radar information 873, is added to the calibration matrix

number

number

number

[0277] In some empirical embodiments, the Rx MM calibration matrix

number

number

[0278] In some empirical embodiments, the Rx MM calibration matrix

number

number

[0279] In some demonstrative aspects, the radar processor 834 and / or the antenna MM calibrator 871 may generate an Rx MM calibration matrix

number

number

[0280] In some demonstrative aspects, the radar processor 834 and / or the antenna MM calibrator 871 may, for example, generate an Rx MM calibration matrix based on changes in one or more parameters that may affect the antenna MM of the MIMO radar antenna 881.

number

number

[0281] In one example, a change in one or more parameters that may affect the antenna MM of the MIMO radar antenna 881 may include, for example, a change in the configuration and / or arrangement of one or more antenna elements of the MIMO radar antenna 881 and / or a change in one or more elements of the vehicle in which the MIMO radar antenna 881 is installed, such as vehicle 100 ( FIG. 1 ), that may affect the functionality of the MIMO radar antenna 881.

[0282] In some demonstrative aspects, the radar processor 834 and / or the antenna MM calibrator 871 may, for example, generate the Rx MM calibration matrix after manufacturing the radar front end 804 and / or after installation of the radar front end 804 on the vehicle 100 (FIG. 1).

number

number

[0283] In some demonstrative aspects, the radar processor 834 and / or the antenna MM calibrator 871 may, for example, in real time, derive an Rx MM calibration matrix based on a detected change in one or more parameters that may affect the antenna MM of, for example, the MIMO radar antenna 881.

number

number

[0284] In some empirical embodiments, the estimated Rx MM matrix

number

number

number

number

number

number

number

number

number

number

number

[0285] In some empirical aspects, a cost function may be defined based on the Normalized Root Mean Square Error (NRMSE), for example, as follows:

number

[0286] In some demonstrative embodiments, a stopping criterion for the nth iteration of the estimation procedure may be defined based on, for example, a cost function, e.g., as follows:

number

[0287] In other aspects, any other cost function and / or stopping criteria may be utilized.

[0288] In other aspects, any other additional or alternative operations and / or procedures may be performed to estimate the Rx MM matrix

number

number

[0289] Reference is made to FIG. 10, which illustrates generally a performance graph of radar processing with antenna mismatch calibration, in accordance with some demonstrative embodiments.

[0290] In one example, the performance graph of FIG. 10 may correspond to a MIMO radar antenna including 24 Tx antenna elements and 64 Rx antenna elements, for a target located at approximately 40 degrees azimuth and approximately 70 degrees elevation.

[0291] As shown in FIG. 10, targets can be clearly identified on a two-dimensional (2D) azimuth-elevation map 1010 that can be generated based on measurements of Rx radar signals received by a MIMO antenna array without an antenna MM.

[0292] As shown in FIG. 10, targets may not be identified on a 2D azimuth-elevation map 1012, which may be generated based on measurements of Rx radar signals received by a MIMO antenna array with antennas MM, for example, if antenna MM calibration is not applied.

[0293] As shown in FIG. 10, the target can be clearly identified on a 2D azimuth-elevation map 1014, which can be generated based on measurements of Rx radar signals received by a MIMO antenna array with antennas MM, for example, when antenna MM calibration is applied in accordance with the antenna MM calibration described above.

[0294] In some demonstrative aspects, as shown in FIG. 10, a 2D azimuth-elevation map 1014 generated using antenna MM calibration can provide similar results to the 2D azimuth-elevation map 1010 in the absence of the antenna MM.

[0295] In some empirical aspects, as shown in FIG. 10, the cost function 1016 may converge after, for example, less than 30 iterations of the ALS estimation method.

[0296] In some demonstrative aspects, as shown in FIG. 10, an azimuth AoA image 1026 that may be generated based on Rx radar signals received by a MIMO antenna array with antenna MM calibration may provide similar results compared to an azimuth AoA image 1022 that may be based on Rx radar signals received by a MIMO antenna array without antenna MM.

[0297] In some demonstrative aspects, as shown in FIG. 10, an elevation AoA image 1036 that may be generated based on Rx radar signals received by a MIMO antenna array using antenna MM calibration may provide similar results compared to an elevation AoA image 1032 that may be based on Rx radar signals received by a MIMO antenna array without antenna MM.

[0298] In some empirical aspects, as shown in FIG. 10, elevation AoA image 1026 and azimuth AoA image 1016 showing antenna MM calibration can achieve a PSLL that is better than, for example, 57 dB.

[0299] In some demonstrative aspects, calibrating an antenna array using boresight calibration may have one or more technical inefficiencies, drawbacks, and / or problems in one or more use cases and / or scenarios. For example, boresight calibration may be implemented to calibrate at only one angle, which may be relatively simple, but the boresight calibration may have reduced side lobe level (SLL) performance, for example, of about 15 dB.

[0300] In some empirical aspects, calibrating an antenna array using empirical maximum likelihood (ML)-based correction may have one or more technical inefficiencies, drawbacks, and / or problems in one or more use cases and / or scenarios. For example, empirical ML-based correction may calibrate an antenna array by scanning an entire 2D AoA grid, which may be greater than the number of virtual elements, constructing an empirical steering matrix, e.g., an array manifold, and projecting the steering matrix onto a received signal, e.g., after range-Doppler (RD) processing. For example, while an ML-based correction method may be suitable for maximizing SNR, the method may not be suitable for minimizing SLL and therefore may not be suitable for achieving a suitable PSLL, e.g., a high PSLL.

[0301] Reference is made to Figures 11A and 11B, where Figure 11A generally illustrates a graph 1110 showing signal-to-noise ratio (SNR) performance of radar processing with antenna mismatch calibration and Figure 11B generally illustrates a graph 1120 showing PSLL performance of radar processing with antenna mismatch calibration, in accordance with some demonstrative embodiments.

[0302] In some demonstrative aspects, as shown in FIG. 11A, curve 1102 represents the SNR based on an Rx radar signal received by a MIMO antenna array using antenna MM calibration, e.g., as described above.

[0303] In some empirical aspects, as shown in FIG. 11A, the SNR performance curve 1102 of a MIMO antenna array using antenna MM calibration may be comparable to the SNR performance of other calibration algorithms.

[0304] In some demonstrative aspects, as shown in FIG. 11A, curve 1106 represents a PSLL that may be achieved based on processing an Rx radar signal received by a MIMO antenna array using antenna MM calibration, e.g., as described above.

[0305] In some empirical aspects, as shown in FIG. 11B, the PSLL performance achieved with antenna MM calibration may be comparable to the PSLL performance 1108 of an antenna array without antenna MM.

[0306] In some empirical aspects, as shown in FIGS. 11A and 11B, antenna MM calibration can achieve significantly improved PSLL while maintaining adequate SNR, e.g., compared to other calibration algorithms, for example.

[0307] Reference is made to Figures 12A and 12B, where Figure 12A generally illustrates a graph 1210 showing SNR loss performance of radar processing with antenna mismatch calibration and Figure 12B generally illustrates a graph 1220 showing PSLL performance of radar processing with antenna mismatch calibration, in accordance with some demonstrative aspects.

[0308] In some empirical aspects, as shown in FIG. 12A, curve 1212 represents the SNR loss of radar processing based on the Rx radar signal received by the MIMO antenna array while applying antenna MM calibration, e.g., as described above.

[0309] In some demonstrative aspects, as shown in FIG. 12B, curve 1222 represents the PSLL achieved by radar processing based on the Rx radar signal received by the MIMO antenna array while applying antenna MM calibration, e.g., as described above.

[0310] In some empirical aspects, as shown in FIG. 12A, when the Tx GMM standard deviation is less than 2 dB (which is the expected inherent GMM), the SNR loss in curve 1212 may be negligible, e.g., less than 1 dB.

[0311] In some empirical aspects, as shown in FIG. 12B, the PSLL performance of curve 1222 can be comparable to the PSLL performance of a theoretical array without antenna MM, while maintaining negligible SNR loss, as shown, for example, in FIG. 12A.

[0312] Reference is now made to FIG. 13, which illustrates diagrammatically graphs 1310, 1320, and 1330 illustrating antenna gain mismatch that may be used as a reference, in accordance with some demonstrative aspects.

[0313] For example, graphs 1310, 1320 and 1330 represent native Tx and Rx GMMs, eg, without any adjustments.

[0314] As shown in Figure 13, both the Tx GMM and the Rx GMM can have a standard deviation of less than 2 dB. Thus, for example, as described above, antenna MM calibration can be implemented to improve PSLL performance, for example, as shown by curve 1222 (Figure 12B), while maintaining very low SNR degradation, for example, less than 1 dB, for example, as shown by curve 1212 (Figure 12A).

[0315] Reference is made to Figure 14, which illustrates generally a method of radar antenna calibration, in accordance with some demonstrative aspects. For example, one or more of the operations of the method of Figure 14 may be performed by one or more elements of a system, such as one or more vehicles, such as vehicle 100 (Figure 1), a radar device, such as radar device 101 (Figure 1), a mismatch calibrator, such as mismatch calibrator 871 (Figure 8), a radar processor, such as radar processor 836 (Figure 8), and / or radar processor 834 (Figure 8).

[0316] As shown in block 1402, the method may include processing radar Rx data, which may be based on radar signals received via multiple Rx antennas of a MIMO radar antenna. For example, radar processor 834 (FIG. 8) may process radar Rx data 811 (FIG. 8), e.g., as described above.

[0317] As shown in block 1404, the method may include generating radar information based on the radar Rx data by calibrating an antenna MM of the MIMO radar antenna such that the radar information includes an AoA spectrum having a PSLL of at least 30 dB, e.g., the PSLL is determined as the difference between a power level of a main lobe of the AoA spectrum and a power level of a peak side lobe corresponding to the main lobe in the AoA spectrum. For example, antenna MM calibrator 871 (FIG. 8) may calibrate an antenna MM of the MIMO radar antenna 881 (FIG. 8), e.g., as described above.

[0318] Reference is now made to FIG. 15, which diagrammatically illustrates an article of manufacture 1500, in accordance with some demonstrative embodiments. Article of manufacture 1500 may include one or more tangible computer-readable ("machine-readable") non-transitory storage media 1502 that may include computer-executable instructions, e.g., implemented by logic 1504, that when executed by at least one computer processor, cause the at least one computer processor to perform one or more operations in a vehicle, e.g., vehicle 100 (FIG. 1), a radar device, e.g., radar device 101 (FIG. 1), a mismatch calibrator, e.g., mismatch calibrator 871 (FIG. 8), a radar processor, e.g., radar processor 836 (FIG. 8), and / or radar processor 834 (FIG. 8). 1-14 and / or described herein. The term "non-transitory machine-readable medium" and "computer-readable non-transitory storage medium" may be intended to include computer-executable instructions operable to enable a vehicle, e.g., vehicle 100 (FIG. 1), a radar device, e.g., radar device 101 (FIG. 1), a mismatch calibrator, e.g., mismatch calibrator 871 (FIG. 8), a radar processor, e.g., radar processor 836 (FIG. 8) and / or radar processor 834 (FIG. 8) to perform, trigger and / or implement one or more operations and / or functions and / or to perform, trigger and / or implement one or more operations and / or functions described with reference to FIGS. 1-14 and / or one or more operations described herein. The terms "non-transitory machine-readable medium" and "computer-readable non-transitory storage medium" may be intended to include all machine and / or computer-readable media with the sole exception being a transitory propagating signal.

[0319] In some demonstrative aspects, product 1500 and / or storage medium 1502 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, writeable or re-writable memory, etc. For example, the storage medium 1502 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), compact disk ROM (CD-ROM), recordable compact disk (CD-R), rewritable compact disk (CD-RW), 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, disk, floppy disk, hard drive, optical disk, magnetic disk, card, magnetic card, optical card, tape, cassette, etc. The computer readable storage medium may include any suitable medium involved in downloading or transferring a computer program carried by a data signal embodied in a carrier wave or other propagation medium from a remote computer to a requesting computer via a communications link, such as a modem, wireless or network connection.

[0320] In some demonstrative aspects, logic 1504 may include instructions, data, and / or code that, when executed by a machine, may cause the machine to perform the methods, processes, and / or operations as described herein. The machine may include, for example, any suitable processing platform, computing platform, computing device, processing device, computing system, processing system, computer, processor, etc., and may be implemented using any suitable combination of hardware, software, firmware, etc.

[0321] In some demonstrative aspects, logic 1504 may include or be implemented as software, a software module, an application, a program, a subroutine, an instruction, an instruction set, computing code, words, values, symbols, etc. The instructions may include any suitable type of code, such as source code, compiled code, interpreted code, executable code, static code, dynamic code, etc. The instructions may be implemented according to a predefined computer language, manner, or syntax that instructs a processor to perform a particular function. The instructions may be implemented using any suitable high-level, low-level, object-oriented, visual, compiled and / or interpreted programming language, such as C, C++, Java, BASIC, Matlab, Pascal, Visual BASIC, assembly language, machine code, etc. example

[0322] The following examples relate to further embodiments.

[0323] Example 1 includes an apparatus comprising: an input for receiving radar receive (Rx) data, the radar Rx data being based on radar signals received via multiple Rx antennas of a multiple-input multiple-output (MIMO) radar antenna; and a radar processor configured to generate radar information based on the radar Rx data by calibrating an antenna mismatch (MM) of the MIMO radar antenna such that the radar information includes an angle-of-arrival (AoA) spectrum having a peak side lobe level (PSLL) of at least 30 decibels (dB), the PSLL being determined as a difference between a power level of a main lobe of the AoA spectrum and a power level of a peak side lobe corresponding to the main lobe in the AoA spectrum.

[0324] Example 2 includes the subject matter of Example 1 and optionally further comprising a memory that stores a first calibration matrix and a second calibration matrix, and the radar processor is configured to generate the radar information by retrieving the first calibration matrix and the second calibration matrix from the memory and calibrating the antenna MM of the MIMO radar antenna based on the first calibration matrix and the second calibration matrix.

[0325] Example 3 includes the subject matter of example 2, and optionally, the first calibration matrix includes an Rx calibration matrix and the second calibration matrix includes a transmit (Tx) calibration matrix, the Rx calibration matrix corresponding to an Rx MM of the multiple Rx antennas and the Tx calibration matrix corresponding to a Tx MM of multiple Tx antennas of the MIMO radar antenna.

[0326] Example 4 includes the subject matter of examples 2 or 3, and optionally, a size of the first calibration matrix is ​​M*M and a size of the second calibration matrix is ​​N*N, where M denotes a count of the Rx antennas and N denotes a count of the Tx antennas.

[0327] Example 5 includes the subject matter of any one of Examples 2-4, and optionally, the radar processor is configured to update at least one of the first calibration matrix or the second calibration matrix based on a change in at least one parameter affecting the antenna MM of the MIMO radar antenna.

[0328] Example 6 includes the subject matter of any one of Examples 2-5, and optionally, the radar processor is configured to update, e.g., dynamically, at least one of the first calibration matrix or the second calibration matrix, e.g., in real time, based on a detected change in at least one parameter affecting the antenna MM of the MIMO radar antenna.

[0329] Example 7 includes the subject matter of any one of Examples 1-6, and optionally, the radar processor is configured to generate intermediate radar data based on the radar Rx data, the radar processor comprising an antenna MM calibrator configured to generate calibrated intermediate radar information by applying an antenna MM calibration to the intermediate radar data, and the radar processor is configured to generate the radar information based on the calibrated intermediate radar information.

[0330] Example 8 includes the subject matter of example 7, and optionally, the intermediate radar information includes intermediate range-Doppler information based on the radar Rx data.

[0331] Example 9 includes the subject matter of Examples 7 or 8, and optionally, the radar processor is configured to generate cross-correlation (XCORR) information based on the radar Rx data and generate the intermediate radar data by applying a Fast Fourier Transform (FFT) to the XCORR information.

[0332] Example 10 includes the subject matter of any one of Examples 7-9, and optionally, the subject matter further includes a memory that stores a first calibration matrix and a second calibration matrix, and the antenna MM calibrator is configured to retrieve the first calibration matrix and the second calibration matrix from the memory and generate the calibrated intermediate radar information by applying the first calibration matrix and the second calibration matrix to the intermediate radar information.

[0333] Example 11 includes the subject matter of example 10, and optionally, the antenna MM calibrator is configured to determine the calibrated intermediate radar information by determining a product of the first calibration matrix multiplied by the intermediate radar information and multiplying the product of the first calibration matrix and the intermediate radar information by the second calibration matrix.

[0334] Example 12 includes the subject matter of examples 10 or 11, and optionally, the first calibration matrix includes an Rx calibration matrix and the second calibration matrix includes a transmit (Tx) calibration matrix, the Rx calibration matrix corresponding to an Rx MM of the multiple Rx antennas and the Tx calibration matrix corresponding to a Tx MM of multiple Tx antennas of the MIMO radar antenna.

[0335] Example 13 includes the subject matter of any one of Examples 10-12, and optionally, a size of the first calibration matrix is ​​M*M and a size of the second calibration matrix is ​​N*N, where M indicates a count of the Rx antennas and N indicates a count of the Tx antennas.

[0336] Example 14 includes the subject matter of any one of Examples 1-13, and optionally, the radar processor is configured to generate the radar information by calibrating the antenna MM of the MIMO radar antenna to provide the radar information including the AoA spectrum having a PSLL of at least 40 dB.

[0337] Example 15 includes the subject matter of any one of Examples 1-14, and optionally, the radar processor is configured to generate the radar information by calibrating the antenna MM of the MIMO radar antenna to provide the radar information including the AoA spectrum having a PSLL of at least 50 dB.

[0338] Example 16 includes the subject matter of any one of Examples 1-15, and optionally, the radar processor is configured to generate the radar information by calibrating the antenna MM of the MIMO radar antenna to provide the radar information including the AoA spectrum having a PSLL of at least 55 dB.

[0339] Example 17 includes the subject matter of any one of Examples 1-16, and optionally, the radar processor is configured to generate the radar information by calibrating the antenna MM of the MIMO radar antenna to provide the radar information including the AoA spectrum having a PSLL of at least 60 dB.

[0340] Example 18 includes the subject matter of any one of Examples 1-17, and optionally, the subject matter includes the MIMO radar antenna, a plurality of transmit (Tx) chains that transmit a plurality of Tx signals via a plurality of Tx antennas of the MIMO radar antenna, and a plurality of Rx chains that generate the radar Rx data based on the radar signals received via the plurality of Rx antennas.

[0341] Example 19 includes the subject matter of any one of Examples 1-18, and optionally, the subject matter includes a vehicle comprising a system controller configured to control one or more vehicle systems of the vehicle based on the radar information.

[0342] Example 20 includes an apparatus comprising means for performing any of the described operations of Examples 1-19.

[0343] Example 21 includes a machine-readable medium storing instructions for execution by a processor to perform any of the described operations of Examples 1-19.

[0344] Example 22 includes an apparatus comprising a memory and a processing circuit configured to perform any of the described operations of Examples 1-19.

[0345] Example 23 includes a method including any of the described operations of examples 1-19.

[0346] Any features, operations, components and / or features described herein with reference to one or more aspects may be combined or utilized in combination with one or more other features, operations, components and / or features described herein with reference to one or more other aspects, and vice versa.

[0347] While certain features have been illustrated and described herein, many modifications, substitutions, changes, and equivalents may occur to those skilled in the art. It is therefore understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the present disclosure. [Other possible items] The following items are charged: [Item 1] An apparatus comprising: an input for receiving radar receive (Rx) data, the radar Rx data being based on radar signals received via multiple Rx antennas of a multiple-input multiple-output (MIMO) radar antenna; a radar processor configured to generate radar information based on the radar Rx data by calibrating an antenna mismatch (MM) of the MIMO radar antenna such that the radar information includes an angle of arrival (AoA) spectrum having a peak side lobe level (PSLL) of at least 30 decibels (dB), the PSLL being determined as a difference between a power level of a main lobe of the AoA spectrum and a power level of a peak side lobe corresponding to the main lobe in the AoA spectrum; An apparatus comprising: [Item 2] 2. The apparatus of claim 1, further comprising a memory that stores a first calibration matrix and a second calibration matrix, wherein the radar processor is configured to generate the radar information by retrieving the first calibration matrix and the second calibration matrix from the memory and calibrating the antenna MM of the MIMO radar antenna based on the first calibration matrix and the second calibration matrix. [Item 3] 3. The apparatus of claim 2, wherein the first calibration matrix includes an Rx calibration matrix and the second calibration matrix includes a transmit (Tx) calibration matrix, the Rx calibration matrix corresponding to an Rx MM of the multiple Rx antennas and the Tx calibration matrix corresponding to a Tx MM of multiple Tx antennas of the MIMO radar antenna. [Item 4] 3. The apparatus of claim 2, wherein the first calibration matrix has a size of M*M and the second calibration matrix has a size of N*N, where M indicates the count of Rx antennas and N indicates the count of Tx antennas. [Item 5] 3. The apparatus of claim 2, wherein the radar processor is configured to update at least one of the first calibration matrix or the second calibration matrix based on a change in at least one parameter affecting the antenna MM of the MIMO radar antenna. [Item 6] 3. The apparatus of claim 2, wherein the radar processor is configured to update at least one of the first calibration matrix or the second calibration matrix in real time based on a detected change in at least one parameter affecting the antenna MM of the MIMO radar antenna. [Item 7] 2. The apparatus of claim 1, wherein the radar processor is configured to generate intermediate radar data based on the radar Rx data, the radar processor comprising an antenna MM calibrator configured to generate calibrated intermediate radar information by applying an antenna MM calibration to the intermediate radar data, and the radar processor is configured to generate the radar information based on the calibrated intermediate radar information. [Item 8] 8. The apparatus of claim 7, wherein the intermediate radar information includes intermediate range-Doppler information based on the radar Rx data. [Item 9] 8. The apparatus of claim 7, wherein the radar processor is configured to generate cross-correlation (XCORR) information based on the radar Rx data and generate the intermediate radar data by applying a fast Fourier transform (FFT) to the XCORR information. [Item 10] 8. The apparatus of claim 7, further comprising a memory that stores a first calibration matrix and a second calibration matrix, wherein the antenna MM calibrator is configured to retrieve the first calibration matrix and the second calibration matrix from the memory and generate the calibrated intermediate radar information by applying the first calibration matrix and the second calibration matrix to the intermediate radar information. [Item 11] Item 11. The apparatus of item 10, wherein the antenna MM calibrator is configured to determine the calibrated intermediate radar information by determining a product of the first calibration matrix multiplied by the intermediate radar information and multiplying the product of the first calibration matrix and the intermediate radar information by the second calibration matrix. [Item 12] Item 11. The apparatus of item 10, wherein the first calibration matrix includes an Rx calibration matrix and the second calibration matrix includes a transmit (Tx) calibration matrix, the Rx calibration matrix corresponding to an Rx MM of the multiple Rx antennas and the Tx calibration matrix corresponding to a Tx MM of multiple Tx antennas of the MIMO radar antenna. [Item 13] Item 11. The apparatus of item 10, wherein the size of the first calibration matrix is ​​M*M and the size of the second calibration matrix is ​​N*N, where M indicates the count of the Rx antennas and N indicates the count of the Tx antennas. [Item 14] 14. The apparatus of any one of claims 1 to 13, wherein the radar processor is configured to generate the radar information by calibrating the antenna MM of the MIMO radar antenna to provide the radar information including the AoA spectrum having a PSLL of at least 40 dB. [Item 15] 14. The apparatus of any one of claims 1 to 13, wherein the radar processor is configured to generate the radar information by calibrating the antenna MM of the MIMO radar antenna to provide the radar information including the AoA spectrum having a PSLL of at least 55 dB. [Item 16] 14. The apparatus of any one of claims 1 to 13, wherein the radar processor is configured to generate the radar information by calibrating the antenna MM of the MIMO radar antenna to provide the radar information including the AoA spectrum having a PSLL of at least 60 dB. [Item 17] 14. The apparatus according to any one of claims 1 to 13, comprising: the MIMO radar antenna; a plurality of transmit (Tx) chains for transmitting a plurality of Tx signals via a plurality of Tx antennas of the MIMO radar antenna; and a plurality of Rx chains for generating the radar Rx data based on the radar signals received via the plurality of Rx antennas. [Item 18] 1. An article of manufacture comprising one or more tangible computer-readable non-transitory storage media containing computer-executable instructions that, when executed by at least one processor, cause the at least one processor to: processing radar receive (Rx) data, the radar Rx data being based on radar signals received via multiple Rx antennas of a multiple-input multiple-output (MIMO) radar antenna; generating radar information based on the radar Rx data by calibrating an antenna mismatch (MM) of the MIMO radar antenna such that the radar information includes an angle of arrival (AoA) spectrum having a peak side lobe level (PSLL) of at least 30 decibels (dB), the PSLL being determined as a difference between a power level of a main lobe of the AoA spectrum and a power level of a peak side lobe corresponding to the main lobe in the AoA spectrum; The product is operable to enable a [Item 19] 20. The product of claim 18, wherein the instructions, when executed, cause the radar device to perform the steps of storing a first calibration matrix and a second calibration matrix in a memory, retrieving the first calibration matrix and the second calibration matrix from the memory, and generating the radar information by calibrating the antenna MM of the MIMO radar antenna based on the first calibration matrix and the second calibration matrix. [Item 20] 20. The product of claim 19, wherein the first calibration matrix includes an Rx calibration matrix and the second calibration matrix includes a transmit (Tx) calibration matrix, the Rx calibration matrix corresponding to an Rx MM of the multiple Rx antennas and the Tx calibration matrix corresponding to a Tx MM of multiple Tx antennas of the MIMO radar antenna. [Item 21] 20. The article of manufacture of claim 18, wherein the instructions, when executed, cause the radar device to perform the steps of generating intermediate radar data based on the radar Rx data, generating calibrated intermediate radar information by applying an antenna MM calibration to the intermediate radar data, and generating the radar information based on the calibrated intermediate radar information. [Item 22] A vehicle, a system controller configured to control one or more vehicle systems of the vehicle based on the radar information; 1. A radar device configured to provide the radar information to the system controller, the radar device comprising: a multiple-input multiple-output (MIMO) radar antenna including a plurality of transmit (Tx) antennas for transmitting Tx radar signals and a plurality of receive (Rx) antennas for receiving Rx radar signals based on the Tx radar signals; a radar processor configured to generate the radar information based on radar Rx data, the radar Rx data being based on the Rx radar signal, the radar processor configured to generate the radar information by calibrating an antenna mismatch (MM) of the MIMO radar antenna such that the radar information includes an angle of arrival (AoA) spectrum having a peak side lobe level (PSLL) of at least 30 decibels (dB), the PSLL being determined as a difference between a power level of a main lobe of the AoA spectrum and a power level of a peak side lobe corresponding to the main lobe in the AoA spectrum; A radar device having A vehicle equipped with: [Item 23] 23. The vehicle of claim 22, further comprising a memory for storing a first calibration matrix and a second calibration matrix, wherein the radar processor is configured to generate the radar information by retrieving the first calibration matrix and the second calibration matrix from the memory and calibrating the antenna MM of the MIMO radar antenna based on the first calibration matrix and the second calibration matrix. [Item 24] 24. The vehicle of claim 23, wherein the first calibration matrix includes an Rx calibration matrix, the second calibration matrix includes a Tx calibration matrix, the Rx calibration matrix corresponds to an Rx MM of the multiple Rx antennas, and the Tx calibration matrix corresponds to a Tx MM of the multiple Tx antennas.

Claims

1. An apparatus for a radar device, comprising: an input for receiving radar receive (Rx) data, the radar Rx data being based on radar signals received via multiple Rx antennas of a multiple-input multiple-output (MIMO) radar antenna; a radar processor configured to generate the radar information based on the radar Rx data by calibrating an antenna mismatch (MM) of the MIMO radar antenna such that the radar information includes an Angle of Arrival (AoA) spectrum having a Peak Side Lobe Level (PSLL) of at least 30 decibels (dB), the PSLL being determined as a difference between a power level of a main lobe of the AoA spectrum and a power level of a peak side lobe corresponding to the main lobe in the AoA spectrum; a memory for storing a first calibration matrix and a second calibration matrix; Equipped with The radar processor includes: generating the radar information by retrieving the first calibration matrix and the second calibration matrix from the memory and calibrating the antenna MM of the MIMO radar antenna based on the first calibration matrix and the second calibration matrix; and updating at least one of the first calibration matrix or the second calibration matrix based on a change in at least one parameter affecting the antenna MM of the MIMO radar antenna. Device.

2. 2. The apparatus of claim 1, wherein the first calibration matrix comprises an Rx calibration matrix and the second calibration matrix comprises a transmit (Tx) calibration matrix, the Rx calibration matrix corresponding to an Rx MM of the multiple Rx antennas and the Tx calibration matrix corresponding to a Tx MM of multiple Tx antennas of the MIMO radar antenna.

3. 3. The apparatus of claim 2, wherein the first calibration matrix has a size of M*M and the second calibration matrix has a size of N*N, where M denotes a count of the Rx antennas and N denotes a count of the Tx antennas.

4. The apparatus of any one of claims 1 to 3, wherein the radar processor is configured to update at least one of the first calibration matrix or the second calibration matrix in real time based on a detected change in at least one parameter affecting the antenna MM of the MIMO radar antenna.

5. 5. The apparatus of claim 1, wherein the radar processor is configured to generate intermediate radar data based on the radar Rx data, the radar processor comprising an antenna MM calibrator configured to generate calibrated intermediate radar information by applying an antenna MM calibration to the intermediate radar data, and the radar processor is configured to generate the radar information based on the calibrated intermediate radar information.

6. The apparatus of claim 5 , wherein the intermediate radar information includes intermediate range-Doppler information based on the radar Rx data.

7. 7. The apparatus of claim 5 or 6, wherein the radar processor is configured to generate cross-correlation (XCORR) information based on the radar Rx data and generate the intermediate radar data by applying a Fast Fourier Transform (FFT) to the XCORR information.

8. 8. The apparatus of claim 5, further comprising a memory that stores a first calibration matrix and a second calibration matrix, and the antenna MM calibrator is configured to retrieve the first calibration matrix and the second calibration matrix from the memory and generate the calibrated intermediate radar information by applying the first calibration matrix and the second calibration matrix to the intermediate radar information.

9. 9. The apparatus of claim 8, wherein the antenna MM calibrator is configured to determine the calibrated intermediate radar information by determining a product of the first calibration matrix multiplied by the intermediate radar information and multiplying the product of the first calibration matrix and the intermediate radar information by the second calibration matrix.

10. 10. The apparatus of claim 8 or 9, wherein the first calibration matrix comprises an Rx calibration matrix and the second calibration matrix comprises a transmit (Tx) calibration matrix, the Rx calibration matrix corresponding to an Rx MM of the multiple Rx antennas and the Tx calibration matrix corresponding to a Tx MM of multiple Tx antennas of the MIMO radar antenna.

11. 11. The apparatus of claim 10, wherein the first calibration matrix is ​​a size of M*M and the second calibration matrix is ​​a size of N*N, where M denotes a count of the Rx antennas and N denotes a count of the Tx antennas.

12. 12. The apparatus of claim 1, wherein the radar processor is configured to generate the radar information by calibrating the antenna MM of the MIMO radar antenna to provide the radar information including the AoA spectrum having a PSLL of at least 40 dB.

13. 12. The apparatus of claim 1, wherein the radar processor is configured to generate the radar information by calibrating the antenna MM of the MIMO radar antenna to provide the radar information including the AoA spectrum having a PSLL of at least 55 dB.

14. 12. The apparatus of claim 1, wherein the radar processor is configured to generate the radar information by calibrating the antenna MM of the MIMO radar antenna to provide the radar information including the AoA spectrum having a PSLL of at least 60 dB.

15. 15. The apparatus of claim 1, comprising: the MIMO radar antenna; a plurality of transmit (Tx) chains for transmitting a plurality of Tx signals via a plurality of Tx antennas of the MIMO radar antenna; and a plurality of Rx chains for generating the radar Rx data based on the radar signals received via the plurality of Rx antennas.

16. 1. A method performed in a radar device, comprising: processing radar receive (Rx) data, the radar Rx data being based on radar signals received via multiple Rx antennas of a multiple-input multiple-output (MIMO) radar antenna; generating the radar information based on the radar Rx data by calibrating an antenna mismatch (MM) of the MIMO radar antenna such that the radar information includes an Angle of Arrival (AoA) spectrum having a Peak Side Lobe Level (PSLL) of at least 30 decibels (dB), the PSLL being determined as a difference between a power level of a main lobe of the AoA spectrum and a power level of a peak side lobe corresponding to the main lobe in the AoA spectrum; Equipped with The step of generating radar information includes: retrieving a first calibration matrix and a second calibration matrix from a memory; generating the radar information by calibrating the antenna MM of the MIMO radar antenna based on the first calibration matrix and the second calibration matrix; updating at least one of the first calibration matrix or the second calibration matrix based on a change in at least one parameter affecting the antenna MM of the MIMO radar antenna; The method comprising:

17. 17. The method of claim 16, wherein the first calibration matrix comprises an Rx calibration matrix and the second calibration matrix comprises a transmit (Tx) calibration matrix, the Rx calibration matrix corresponding to an Rx MM of the multiple Rx antennas and the Tx calibration matrix corresponding to a Tx MM of multiple Tx antennas of the MIMO radar antenna.

18. 18. The method of claim 16 or 17, comprising generating intermediate radar data based on the radar Rx data, generating calibrated intermediate radar information by applying an antenna MM calibration to the intermediate radar data, and generating the radar information based on the calibrated intermediate radar information.

19. A computer program causing a processor to carry out the method according to any one of claims 16 to 18.

20. An arrangement of a radar device, said arrangement comprising processing means for carrying out the method according to any one of claims 16 to 18.

21. A vehicle, a system controller configured to control one or more vehicle systems of the vehicle based on the radar information; 1. A radar device configured to provide the radar information to the system controller, the radar device comprising: a multiple-input multiple-output (MIMO) radar antenna including a plurality of transmit (Tx) antennas for transmitting Tx radar signals and a plurality of receive (Rx) antennas for receiving Rx radar signals based on the Tx radar signals; a radar processor configured to generate the radar information based on radar Rx data, the radar Rx data being based on the Rx radar signal, the radar processor configured to generate the radar information by calibrating an antenna mismatch (MM) of the MIMO radar antenna such that the radar information includes an Angle of Arrival (AoA) spectrum having a Peak Side Lobe Level (PSLL) of at least 30 decibels (dB), the PSLL being determined as a difference between a power level of a main lobe of the AoA spectrum and a power level of a peak side lobe corresponding to the main lobe in the AoA spectrum; a memory for storing a first calibration matrix and a second calibration matrix; A radar device having Equipped with The radar processor includes: generating the radar information by retrieving the first calibration matrix and the second calibration matrix from the memory and calibrating the antenna MM of the MIMO radar antenna based on the first calibration matrix and the second calibration matrix; and updating at least one of the first calibration matrix or the second calibration matrix based on a change in at least one parameter affecting the antenna MM of the MIMO radar antenna. vehicle.

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