Method and apparatus for processing radar signals by correcting phase distortion

Abstract

Disclosed are a method and apparatus for processing a radar signal by correcting phase distortion. The method includes generating radar data based on a radar transmission signal and a radar reception signal, the radar transmission signal being transmitted through an array antenna of a radar sensor based on a frequency modulation model, the radar reception signal being received through the array antenna when the radar transmission signal is reflected by a target; correcting the radar data using a correction vector for correcting a feeder error occurring due to a feeder delay difference between channels of the array antenna; and estimating a direction of arrival corresponding to the corrected radar data using a direction matrix reflecting a phase shift of the corrected radar data according to a frequency modulation characteristic of the frequency modulation model.

Description

[0001] This application claims the benefit of Korean Patent Application No. 10-2020-0069571, filed on June 9, 2020, with the Korean Intellectual Property Office, and Korean Patent Application No. 10-2020-0100625, filed on August 11, 2020, the entire disclosure of which is incorporated herein by reference for all purposes. Technical Field

[0002] The following description relates to methods and apparatus for processing radar signals by correcting phase distortion. Background Technology

[0003] Advanced driver assistance systems (ADAS) are systems that use sensors installed inside or outside a vehicle to support driving, improve driver safety and convenience, and avoid dangerous situations.

[0004] Sensors used in ADAS can include cameras, infrared sensors, ultrasonic sensors, LiDAR, and radar. Among these sensors, radar, compared to optical-based sensors, can reliably measure objects near the vehicle without being affected by the surrounding environment (such as weather). Summary of the Invention

[0005] This summary is provided to introduce, in a simplified form, the selection of concepts further described in the following detailed description. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to help determine the scope of the claimed subject matter.

[0006] In one general aspect, a method for processing radar signals is provided, the method comprising: generating radar data based on radar transmitted signals and radar received signals, wherein the radar transmitted signals are transmitted through an array antenna of a radar sensor based on a frequency modulation model, and the radar received signals are received through the array antenna when the radar transmitted signals are reflected by a target; correcting the radar data using a correction vector for correcting feeder errors caused by differences in feeder delay between channels of the array antenna; and estimating the direction of arrival corresponding to the corrected radar data using a direction matrix reflecting the phase shift of the corrected radar data, based on the frequency modulation characteristics of the frequency modulation model.

[0007] The correction vector can be configured to correct the radar data in response to the radar receiving signal being received from a target located in front of the radar sensor, so that the phase components of the radar data channels have the same value.

[0008] The direction matrix may include multiple sub-direction matrices, each corresponding to a different sampling index.

[0009] The step of estimating the direction of arrival may include: obtaining a first sub-direction matrix corresponding to a first sampling index from the plurality of sub-direction matrices; and using the first sub-direction matrix to estimate a first direction of arrival of the first sub-radar data corresponding to the first sampling index from the calibrated radar data.

[0010] The steps for generating radar data may include: generating radar data by sampling an intermediate frequency (IF) signal generated based on radar transmitted signals and radar received signals.

[0011] The steps for estimating the direction of arrival may include: correcting element beam pattern (EBP) errors that occur due to the influence of the beam patterns of the antenna elements in the array antenna on the beam pattern of the array antenna.

[0012] The steps for estimating the direction of arrival (DOA) may include: estimating the initial DOA corresponding to the corrected radar data using a direction matrix; and estimating the final DOA corresponding to the corrected radar data by removing the EBP error in the initial DOA, the EBP error in which occurs due to the influence of the beam pattern of the antenna elements of the array antenna on the beam pattern of the array antenna.

[0013] The steps for estimating the final direction of arrival may include: determining the EBP error value of the initial direction of arrival corresponding to the corrected radar data based on an EBP error model configured to represent the EBP error value for each angle; and estimating the final direction of arrival corresponding to the corrected radar data by correcting the initial direction of arrival with the determined EBP error value.

[0014] An EBP error model can be generated by estimating the EBP error values ​​for other angles based on the EBP error values ​​of a base angle measured by testing.

[0015] Radar transmitted signals may include linear frequency modulated signals with a carrier frequency modulated based on a frequency modulation model.

[0016] Radar signals can be received through receiving antenna elements in an array antenna, and channels are formed based on the receiving antenna elements.

[0017] The method may include: estimating at least one of the target's distance and velocity based on radar data, wherein a vehicle equipped with a device for processing radar signals is controlled based on any one or any combination of the direction of arrival, distance, and velocity.

[0018] In another general aspect, an apparatus for processing radar signals is provided, the apparatus comprising: a radar sensor configured to: transmit a radar signal via an array antenna based on a frequency modulation model, and receive a radar signal via the array antenna when the transmitted radar signal is reflected by a target; and a processor configured to: generate radar data based on the transmitted and received radar signals; correct the radar data using a correction vector for correcting feeder errors caused by differences in feeder delay between channels of the array antenna; and estimate the direction of arrival corresponding to the corrected radar data using a direction matrix reflecting the phase shift of the corrected radar data, based on the frequency modulation characteristics of the frequency modulation model.

[0019] The correction vector can be configured to correct the radar data in response to the radar receiving signal being received from a target located in front of the radar sensor, so that the phase components of the radar data channels have the same value.

[0020] The direction matrix may include multiple sub-direction matrices corresponding to different sampling indices; and the processor may be configured to: obtain a first sub-direction matrix corresponding to a first sampling index from the multiple sub-direction matrices, and use the first sub-direction matrix to estimate a first direction of arrival of the first sub-radar data corresponding to the first sampling index from the corrected radar data.

[0021] The processor can be configured to correct element beam pattern error (EBP) caused by the influence of the beam pattern of the antenna elements in the array antenna on the beam pattern of the array antenna.

[0022] In another general aspect, a vehicle is provided, the vehicle comprising: a radar sensor configured to: transmit a radar signal via an array antenna based on a frequency modulation model, and receive a radar signal via the array antenna when the radar signal is reflected by a target; a processor configured to: generate radar data based on the radar transmitted signal and the radar received signal, correct the radar data using a correction vector for correcting feeder errors caused by feeder delay differences between channels of the array antenna, and estimate the direction of arrival (DOA) corresponding to the corrected radar data using a direction matrix reflecting the phase shift of the corrected radar data according to the frequency modulation characteristics of the frequency modulation model; and a controller configured to control the vehicle based on the DOA.

[0023] The direction matrix may include multiple sub-direction matrices corresponding to different sampling indices; and the processor may be configured to: obtain a first sub-direction matrix corresponding to a first sampling index from the multiple sub-direction matrices, and use the first sub-direction matrix to estimate a first direction of arrival of the first sub-radar data corresponding to the first sampling index from the corrected radar data.

[0024] The processor can be configured to correct element beam pattern error (EBP) caused by the influence of the beam pattern of the antenna elements in the array antenna on the beam pattern of the array antenna.

[0025] In another general aspect, a method for processing radar signals is provided, the method comprising: generating radar data based on radar transmitted signals and radar received signals, the radar transmitted signals being transmitted through an array antenna of a radar sensor based on a frequency modulation model, and the radar received signals being received through the array antenna when the radar transmitted signals are reflected by a target; correcting the radar data using a correction vector, the correction vector being used to correct feeder errors caused by feeder delay differences between channels of the array antenna; estimating an initial direction of arrival corresponding to the corrected radar data using a direction matrix; and determining a final direction of arrival corresponding to the corrected radar data by removing the EBP error from the initial direction of arrival based on an EBP error model configured to represent element beam pattern (EBP) error values ​​for each angle, wherein the EBP error includes the influence of the beam pattern of the antenna elements of the array antenna on the beam pattern of the array antenna.

[0026] The direction matrix may include multiple sub-direction matrices corresponding to different sampling indices; and the step of estimating the initial direction of arrival includes: obtaining a first sub-direction matrix corresponding to a first sampling index from the multiple sub-direction matrices; and using the first sub-direction matrix, estimating a first direction of arrival of the first sub-radar data corresponding to the first sampling index from the calibrated radar data.

[0027] Other features and aspects will become clear from the following detailed description, the accompanying drawings, and the claims. Attached Figure Description

[0028] Figure 1 This illustrates an example of identifying the surrounding environment using radar signal processing methods.

[0029] Figure 2 An example of the configuration of a radar signal processing device is shown.

[0030] Figure 3 An example of radar sensor configuration is shown.

[0031] Figure 4 An example of processing radar signals through phase distortion correction is shown.

[0032] Figure 5 An example of feeder delay in an array antenna is shown.

[0033] Figure 6 An example of using a correction vector to correct feeder errors is shown.

[0034] Figure 7An example of the receiving antenna element of an array antenna is shown.

[0035] Figure 8 This illustrates an example of phase shift variation based on the carrier frequency at each sampling point in a radar signal processing method.

[0036] Figure 9 An example of sampling an intermediate frequency (IF) signal is shown.

[0037] Figure 10 An example is shown of correcting frequency modulation (FM) parasitic errors by phase normalization.

[0038] Figure 11 and Figure 12 An example of correcting element beam pattern (EBP) error is shown.

[0039] Figure 13 An example of a radar signal processing method is shown.

[0040] Figure 14 An example of an electronic device is shown.

[0041] Throughout the accompanying drawings and detailed embodiments, unless otherwise described or provided, the same reference numerals will be understood to denote the same elements, features, and structures. The drawings may not be to scale, and for clarity, illustration, and convenience, the relative dimensions, scale, and depiction of elements in the drawings may be exaggerated. Detailed Implementation

[0042] The following detailed embodiments are provided to aid the reader in gaining a comprehensive understanding of the methods, apparatus, and / or systems described herein. However, various changes, modifications, and equivalents of the methods, apparatus, and / or systems described herein will become apparent upon understanding this disclosure. For example, the order of operations described herein is merely illustrative and is not limited to those orders set forth herein, but may be changed as will become clear upon understanding this disclosure, except for operations that must occur in a specific order. Furthermore, for clarity and conciseness, descriptions of known features may be omitted.

[0043] The features described herein may be implemented in different forms and should not be construed as limited to the examples described herein. Rather, the examples described herein have been provided merely to illustrate some of the many feasible ways of implementing the methods, apparatus, and / or systems described herein that will be clear upon understanding the disclosure of this application.

[0044] The terminology used herein is for the purpose of describing particular examples only and is not intended to limit disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. As used herein, the term "and / or" includes any one and any combination of any two or more of the associated listed items. As used herein, the terms "comprising," "including," and "having" indicate the presence of the described features, quantities, operations, elements, components, and / or combinations thereof, but do not exclude the presence or addition of one or more other features, quantities, operations, elements, components, and / or combinations thereof.

[0045] Additionally, terms such as first, second, A, B, (a), (b), etc., may be used herein to describe components. Each of these terms is not intended to define the nature, order, or sequence of the corresponding component, but only to distinguish the corresponding component from one or more other components.

[0046] Throughout this specification, when an element such as a layer, region, or substrate is described as being "on" another element, "connected to," or "bonded to" another element, the element may be directly "on" the other element, "connected to," or "bonded to" the other element, or there may be one or more other elements in between. Conversely, when an element is described as being "directly on" another element, "directly connected to," or "directly bonded to" another element, there may be no other elements in between. Similarly, expressions such as "between" and "immediately between," and "adjacent to" and "closely adjacent to" can also be interpreted as described above.

[0047] When describing the examples with reference to the accompanying drawings, the same reference numerals denote the same constituent elements, and repetitive descriptions related to the same constituent elements will be omitted. In the description of the examples, detailed descriptions of well-known related structures or functions will be omitted where such detailed descriptions would lead to an obscure interpretation of this disclosure.

[0048] The same names can be used to describe components included in the examples described above and components with common functions. Unless otherwise stated, the descriptions of the examples are applicable to the examples below, therefore, for the sake of brevity, repeated descriptions will be omitted.

[0049] Figure 1 This illustrates an example of identifying the surrounding environment using radar signal processing methods. (See reference...) Figure 1The radar signal processing device 110 can detect information about a forward target 180 (e.g., range, speed, direction, etc.) by analyzing radar signals received from the radar sensor 111. The radar sensor 111 can be located inside or outside the radar signal processing device 110, and the radar signal processing device 110 can detect information about the forward target 180 based on radar signals received from the radar sensor 111 and data collected by other sensors (e.g., image sensors, etc.). Resolving power in radar data processing can be divided into hardware-related resolving power performance and software-related resolving power performance. The following description will primarily focus on improvements in software-related resolving power performance.

[0050] In one example, resolution refers to a device's ability to distinguish very small changes (e.g., the smallest unit of resolution), and resolution can be expressed as "resolution = (smallest distinguishable unit) / (total operating range)". The smaller the resolution value of a device, the more accurate the results it can output. The resolution value can also be called the resolution unit. For example, if a device has a small resolution value, it can distinguish relatively small units, and therefore can output results with increased resolution and improved accuracy. If a device has a large resolution value, it may not be able to distinguish small units, and therefore output results with decreased resolution and reduced accuracy.

[0051] like Figure 1 As shown, the radar signal processing device 110 can be installed on the vehicle. The vehicle can perform adaptive cruise control (ACC), automatic emergency braking (AEB), blind spot detection (BSD), lane change assist (LCA), and other similar operations based on the distance to the target 180 detected by the radar signal processing device 110.

[0052] In addition to detecting range, the radar signal processing device 110 can also generate a surrounding map 130. The surrounding map 130 is a map showing the positions of various targets (such as target 180) present around the radar signal processing device 110. Targets may include moving objects (such as vehicles and people) and static objects (such as guardrails and traffic lights present in the background).

[0053] Single-scan imaging can be used to generate a surrounding map 130. Single-scan imaging refers to the technique by which radar signal processing device 110 acquires a single-scan image 120 from a sensor and generates a surrounding map 130 from the acquired single-scan image 120. The single-scan image 120 is an image generated from radar signals sensed by a single radar sensor 111 and can represent distances indicated by radar signals received at a predetermined elevation angle with relatively high resolution. For example, in Figure 1In the single-scan image 120 shown, the horizontal axis can represent the steering angle of the radar sensor 111, and the vertical axis can represent the distance from the radar sensor 111 to the target 180. However, the format of the single-scan image is not limited to... Figure 1 The format shown is illustrated. Single-scan images can be represented in different formats depending on the design.

[0054] The steering angle can be an angle corresponding to the target direction from the radar signal processing device 110 toward the target 180. For example, the steering angle can be the angle between the target direction and the direction of travel of the radar signal processing device 110 (or the vehicle including the radar signal processing device 110). In one example, the steering angle is described primarily based on the horizontal angle, but is not limited to this. For example, the steering angle can also be applied to the elevation angle.

[0055] The radar signal processing device 110 can obtain information about the shape of the target 180 through multiple radar maps. Multiple radar maps can be generated from a combination of multiple radar scan images. For example, the radar signal processing device 110 can generate a surrounding map 130 by combining radar scan images acquired as the radar sensor 111 moves in a spatiotemporal manner. The surrounding map 130 can be a radar image map and can be used for driver parking.

[0056] Radar signal processing device 110 can use direction of arrival (DOA) information to generate a surrounding map 130. DOA information indicates the direction from which a radar signal reflected from a target is received. Radar signal processing device 110 can use the DOA information described above to determine the direction in which a target exists relative to radar sensor 111. Therefore, such DOA information can be used to generate radar scan data and a surrounding map.

[0057] Radar information about target 180 generated by radar signal processing device 110 (such as range, speed, DOA, and map information) can be used to control a vehicle equipped with radar signal processing device 110. For example, controlling the vehicle may include controlling the vehicle's speed and steering (such as ACC, AEB, BSD, and LCA). The vehicle's control system may control the vehicle directly or indirectly based on the radar information.

[0058] Figure 2 An example configuration of a radar signal processing device is shown. (Refer to...) Figure 2The radar signal processing device 200 may include a radar sensor 210 and a processor 220. The radar sensor 210 can transmit radar signals to an external location and receive signals when the transmitted radar signals are reflected by a target. Here, the transmitted radar signal will be referred to as the radar transmitted signal, and the received signal may be referred to as the radar received signal. The radar transmitted signal may include a linear frequency modulated signal (chirp signal, also known as a chirped signal) having a carrier frequency modulated based on a frequency modulation model. The frequency of the radar transmitted signal can be varied within a predetermined frequency band. For example, the frequency of the radar transmitted signal can be linearly varied within a predetermined frequency band.

[0059] The radar sensor 210 may include an array antenna and can be configured to transmit radar signals and receive radar signals via the array antenna. The array antenna may include multiple antenna elements. Multiple-input multiple-output (MIMO) can be implemented using multiple antenna elements. In this case, multiple MIMO channels can be formed using multiple antenna elements. For example, multiple channels corresponding to A×B virtual antennas can be formed using A transmit antenna elements and B receive antenna elements. Here, the radar received signals received through the channels may have different phases depending on the receiving direction.

[0060] Radar data can be generated based on radar transmitted and received signals. For example, radar sensor 210 can transmit radar signals through an array antenna based on a frequency modulation model, receive radar signals through the array antenna when the transmitted signals are reflected by a target, and generate an intermediate frequency (IF) signal based on the transmitted and received signals. The IF signal may have a frequency corresponding to the difference between the frequency of the transmitted radar signal and the frequency of the received radar signal. Processor 220 can generate radar data by sampling the IF signal. The radar data may correspond to the raw data of the IF signal.

[0061] Processor 220 can generate and use information about a target based on radar data. For example, processor 220 can perform range fast Fourier transform (FFT), Doppler FFT, constant false alarm rate (CFAR) detection, DOA estimation, etc., based on radar data, and obtain information about the target (such as range, velocity, and orientation). Such information about the target can be provided for various applications (such as AAC, AEB, BSD, and LCA).

[0062] Figure 3 An example of radar sensor configuration is shown. (See reference...) Figure 3The radar sensor 310 may include a chirp transmitter 311, a duplexer 312, an antenna 313, a mixer 314, an amplifier 315, and a spectrum analyzer 316. The radar sensor 310 can transmit and receive signals via the antenna 313. Although... Figure 3 A single antenna 313 is shown, but antenna 313 may include at least one transmitting antenna element and at least one receiving antenna element. For example, antenna 313 may correspond to an array antenna. For example, antenna 313 may include three or more receiving antenna elements. In this case, the receiving antenna elements may be spaced apart at equal intervals.

[0063] Radar sensor 310 can be, for example, a millimeter-wave (mmWave) radar and can be configured to measure the distance to a target by analyzing changes in the time-of-flight (ToF) and the waveform of the radar signal, where ToF is the time it takes for the emitted electromagnetic wave to return after being reflected by the target. For reference, compared to optical sensors including cameras, millimeter-wave radar can detect objects regardless of changes in the external environment (such as fog, rain, etc.). Furthermore, millimeter-wave radar offers excellent cost-performance compared to LiDAR, and is therefore one of the sensors that can compensate for the shortcomings of cameras described above. For example, radar sensor 310 can be implemented as a frequency-modulated continuous wave (FMCW) radar. FMCW radar is robust to external noise.

[0064] A linear frequency modulation (FM) transmitter 311 can generate a frequency-modulated signal (FM signal) 302 with a frequency that changes over time. For example, the FM transmitter 311 can generate the FM signal 302 by performing frequency modulation according to the frequency modulation characteristics of a frequency modulation model 301. The FM signal 302 can also be referred to as a linear frequency modulation signal. Here, the frequency modulation model 301 can be a model configured to represent the change in the carrier frequency of a radar-transmitted signal during a provided transmission time. The vertical axis of the frequency modulation model 301 can represent the carrier frequency (Freq), and the horizontal axis of the frequency modulation model 301 can represent time (t). For example, the frequency modulation model 301 can have frequency modulation characteristics that linearly change (e.g., linearly increase or linearly decrease) the carrier frequency. As another example, the frequency modulation model 301 can have frequency modulation characteristics that non-linearly change the carrier frequency.

[0065] Figure 3 A frequency modulation model 301 with frequency modulation characteristics that increase linearly with time is shown. A linear frequency modulation transmitter 311 can generate an FM signal 302 with a carrier frequency according to the frequency modulation model 301. For example, as... Figure 3As shown, the FM signal 302 can exhibit a waveform where the carrier frequency gradually increases in some intervals and gradually decreases in the remaining intervals. The linear frequency modulation transmitter 311 can transmit the FM signal 302 to the duplexer 312.

[0066] The duplexer 312 determines the transmission and reception paths of the signal through the antenna 313. For example, when the radar sensor 310 transmits an FM signal 302, the duplexer 312 can form a signal path from the linear frequency modulated transmitter 311 to the antenna 313, transmitting the FM signal 302 to the antenna 313 via the formed signal path, and then transmitting the FM signal 302 to the outside. When the radar sensor 310 receives a signal reflected from a target, the duplexer 312 can form a signal path from the antenna 313 to the spectrum analyzer 316. The antenna 313 can receive the received signal when the transmitted signal reaches an obstacle and is reflected back by the obstacle. The radar sensor 310 can send the received signal to the spectrum analyzer 316 via the signal path from the antenna 313 to the spectrum analyzer 316. The signal transmitted through the antenna 313 can be referred to as the radar transmitted signal, and the signal received through the antenna 313 can be referred to as the radar received signal.

[0067] Mixer 314 demodulates the received signal to obtain a linear signal before frequency modulation (e.g., the original linear frequency modulated signal). Amplifier 315 amplifies the amplitude of the demodulated linear signal.

[0068] The spectrum analyzer 316 compares the frequency 308 of the radar received (Rx) signal reflected from and received by the target with the frequency 307 of the radar transmitted (Tx) signal. For reference, the frequency 307 of the radar transmitted signal can change with the carrier frequency indicated by the frequency modulation model 301. The spectrum analyzer 316 can detect the frequency difference between the frequency 308 of the radar received signal and the frequency 307 of the radar transmitted signal. Figure 3 In the curve 309 shown, the frequency difference between the radar transmitted signal and the radar received signal remains constant during the interval in the frequency modulation model 301 where the carrier frequency increases linearly along the time axis, and is proportional to the distance between the radar sensor 310 and the target. Therefore, the distance between the radar sensor 310 and the target can be derived from the frequency difference between the radar transmitted signal and the radar received signal. The spectrum analyzer 316 can send the analyzed information to the processor of the radar signal processing device.

[0069] For example, the spectrum analyzer 316 can use Equation 1 to calculate the distance between the radar sensor 310 and the target.

[0070] [Equation 1]

[0071]

[0072] In Equation 1, R represents the distance between radar sensor 310 and the target. c represents the speed of light. T chirp f represents the time length of the rise interval of the carrier frequency in frequency modulation model 301. IF This represents the frequency difference between the radar transmitted and received signals at a point in the rising interval, and can be referred to as the IF or beat frequency. B represents the modulation bandwidth. In one example, f can be derived from Equation 2. IF .

[0073] [Equation 2]

[0074]

[0075] In equation 2, f IF Indicates IF, t d It represents the time difference (e.g., delay time) between the time the transmitting radar transmits a signal and the time the receiving radar receives a signal, i.e., the round-trip delay time of the target.

[0076] Multiple radar sensors can be installed in various parts of the vehicle, and the radar signal processing equipment can calculate the distance to the target, direction, and relative speed of the vehicle in all directions based on the information sensed by the multiple radar sensors. The radar signal processing equipment can be installed on the vehicle and can provide various functions useful for driving (e.g., ACC, AEB, BSD, LCA, etc.) by using the calculated information.

[0077] Each of the multiple radar sensors can transmit a radar signal including a linear frequency modulated signal having a frequency modulated based on a frequency modulation model, and receive a signal reflected from a target. The processor of the radar signal processing device can determine the distance from each of the multiple radar sensors to the target from the frequency difference between the transmitted radar signal and the received radar signal. Furthermore, when the radar sensor 310 has multiple channels, the processor of the radar signal processing device can derive the DOA of the received radar signal reflected from the target based on phase information in the radar data.

[0078] Radar sensor 310 can utilize wide bandwidth and employ MIMO to meet the wide field of view (FoV) and high resolution (HR) requirements for various applications. Range resolution can be increased through wide bandwidth, and angular resolution can be increased through MIMO. Range resolution can represent the smallest unit used to distinguish range information about a target, and angular resolution can represent the smallest unit used to distinguish DOA information about a target. For example, radar sensor 210 can use a wide bandwidth (such as 4 GHz, 5 GHz, or 7 GHz) instead of a narrow bandwidth (such as 200 MHz, 500 MHz, or 1 GHz). When employing MIMO, the possibility of phase distortion between channels may increase. Therefore, phase distortion correction for wide FoV array antennas is required.

[0079] The processor of a radar signal processing device can correct such phase distortion of the array antenna during the processing of radar data to generate information about the target. The beam pattern of the array antenna can be modeled as including: feed errors caused by differences in feed delay between channels, phase shift errors of the radar data according to the frequency modulation characteristics of the frequency modulation model, and element beam pattern (EBP) errors caused by the influence of the beam patterns of the antenna elements on the beam pattern of the array antenna. The processor can eliminate the phase distortion present in the beam pattern of the array antenna by correcting each error. The process of correcting each error will be described in detail later.

[0080] Figure 4 An example of processing radar signals through phase distortion correction is shown. This can be performed in the order and manner shown. Figure 4 The operations described herein may be altered in order or omitted without departing from the spirit and scope of the exemplary examples described. Figure 4 Many of the operations shown can be performed in parallel or simultaneously. Figure 4 One or more blocks, and combinations thereof, can be implemented by a computer based on dedicated hardware (such as a processor) or a combination of dedicated hardware and computer instructions to perform the specified functions. In addition to the following... Figure 4 In addition to the description, Figures 1 to 3 The description also applies to Figure 4 And it is included here by reference. Therefore, the above description need not be repeated here.

[0081] Reference Figure 4In operation 410, the radar signal processing equipment acquires radar data. The radar signal processing equipment can generate radar data based on radar transmitted signals and radar received signals. The radar transmitted signals are transmitted through the array antenna of the radar sensor based on a frequency modulation model, and the radar received signals are received through the array antenna when the radar transmitted signals are reflected by the target. For example, the radar signal processing equipment can generate an IF signal based on the radar transmitted signals and radar received signals, and generate radar data by sampling the IF signal.

[0082] The radar signal processing equipment can generate information about the target based on radar data. For example, the radar signal processing equipment can perform range FFT in operation 430, Doppler FFT in operation 440, CFAR in operation 450, and estimate DOA in operation 460. Thus, the radar signal processing equipment can obtain information about the target (such as range, velocity, direction, etc.).

[0083] More specifically, radar data is three-dimensional data. The axes of the radar data correspond to the time taken from the time the radar sensor emits electromagnetic waves to the time the radar sensor receives electromagnetic waves, the change between the linear frequency modulated (LFM) signals emitted in one scan, and the change in the LFM signal received at the virtual antenna. The axes of the radar data can be preprocessed to convert them into range, radial velocity, and angle axes. Radial velocity can be the relative velocity of the target when the radar sensor is facing the target.

[0084] For example, radar signal processing equipment can process radar data in the order of range FFT, Doppler FFT, and DOA estimation. However, since the axes of radar data correspond to separable information, the same results can be obtained even when FFT and digital beamforming (DBF) operations are applied in different orders. For reference, an angle axis can be an axis related to horizontal angles (e.g., azimuth). Although horizontal angles are primarily described here, the examples are not limited to this. An angle axis can be an axis related to both horizontal and elevation angles.

[0085] In one example, in a range FFT operation, the radar signal processing device can obtain the range value by applying the FFT operation to the time spent transmitting and receiving electromagnetic waves in the radar data. The radar signal processing device can estimate the angle corresponding to the DOA of the radar signal reflected from the target using DOA estimation. For example, the radar signal processing device can estimate the DOA using the MUSIC algorithm, Bartlett algorithm, MVDR algorithm, DBF, and Estimation of Signal Parameter via Rotational Invariance Techniques (ESPIRT). The radar signal processing device can estimate the radial velocity (e.g., Doppler velocity) from the signal change between linear frequency modulated signals along the Doppler axis using a Doppler FFT. In a Doppler FFT operation, the radar signal processing device can obtain the radial velocity at a predetermined distance and a predetermined angle by applying the FFT operation to the signal change between linear frequency modulated signals at a predetermined distance and an predetermined angle.

[0086] CFAR is a technique for determining the probability that a point is a target based on neighboring cells of a predetermined point (e.g., a cell under test, CUT), and for using a threshold determined based on the signal strength (e.g., a noise floor) of neighboring cells and for thresholding the signal strength sensed by a radar sensor for that point. For example, if the signal strength sensed from that point is greater than the threshold determined based on the signal strength sensed from neighboring cells, the radar signal processing device may identify that point as a target. In another example, if the signal strength sensed from that point is less than or equal to the threshold, the radar signal processing device may identify that point as a non-target.

[0087] The beam pattern of the array antenna of the radar sensor can be defined as in Equation 3.

[0088] [Equation 3]

[0089]

[0090] In Equation 3, n represents the index used to identify the antenna element. n can be an integer value between 1 and N. N is the total number of antenna elements. EP n (θ) represents the EBP of the nth antenna element with respect to DOAθ. t The wavenumber represents time t. d represents the distance between two adjacent antenna elements. This represents the feed delay in the nth antenna element.

[0091] Referring to Equation 3, the beam pattern may include, according to Feeder error, according to kt FM parasitic error and according to EP n The EBP error of (θ). These errors can cause phase distortion. In detail, This indicates that feeder delay differences may occur between channels, and that these differences can lead to feeder errors. Additionally, k t The wave number, wavelength, and frequency can change over time.

[0092] If the radar signal processing equipment uses FMCW, the frequency can change over time, allowing the radar data to include phase shift errors caused by the frequency change. Because phase shift errors are caused by frequency modulation, they can also be referred to as FM parasitic errors. Additionally, EP... n (θ) may affect the array factor (AF) of the array antenna and distort the AF. Therefore, EP n (θ) may cause EBP error.

[0093] In the processing of radar signals, such errors can be corrected. For example, error correction may include operation 420 for correcting feeder errors, operation 461 for correcting FM parasitic errors, and operation 462 for correcting EBP errors. The processing for correcting each error will be described in detail below.

[0094] In operation 420, the radar signal processing equipment corrects feed line errors in the radar data. The radar signal processing equipment can use correction vectors to correct the radar data. These correction vectors are designed to correct feed line errors caused by feed line delays in the channels of the array antenna.

[0095] For example, if the radar transmitted signal is reflected by a target located in front of the radar sensor, and the radar received signal is received through multiple channels of the radar sensor in a test environment (e.g., an anechoic chamber), then the phase components associated with the channels in the reference data of the radar received signal (radar data obtained with the target angle known in the test environment) should have the same value. For example, since the target is located in front of the radar sensor, the DOA of the reference data corresponds to 0 degrees. In this case, all the phase components of the channels should have the same value corresponding to 0 degrees.

[0096] If the phase components do not have the same value, a vector can be determined to correct the phase components so that they have the same value. This correction vector can be determined through this process. Therefore, if the correction vector is predetermined through this process and the radar received signal is received from a target located in front of the radar sensor, the correction vector can correct the radar data so that the phase components associated with the channels of the radar data have the same value.

[0097] In operation 460, the radar signal processing equipment estimates the DOA. In this case, operation 461, which corrects FM parasitic errors, and operation 462, which corrects EBP errors, can be performed based on the DOA estimation.

[0098] First, FM parasitic errors can be corrected by compensating for frequency changes over time using various methods. A direction matrix can be designed to reflect frequency changes. The direction matrix may include multiple direction vectors, each corresponding to a predetermined angle, and each direction vector may have a phase value for each channel. Each phase value can be mathematically determined. For example, assuming the radar received signal is received from the target at a known first angle, the phase value corresponding to the radar received signal can be calculated, and the phase value can be assigned to a first direction vector at the first angle. Through this process, the phase value of each direction vector can be calculated.

[0099] If the radar received signal is received during actual radar use after the direction matrix has been completed, the direction vector corresponding to the radar data can be selected based on the operation of each direction vector in the radar data and direction matrix of the received radar signal. The DOA of the radar received signal can be estimated as the angle of the selected direction vector. For example, if a first direction vector is selected in the direction matrix, the DOA of the radar received signal can be estimated as a first angle. In one example, the actual use processing (online) can be interpreted differently from the design and derived processing (offline).

[0100] In the process of deriving the direction matrix described above, the change of frequency over time can be considered. For example, separate sub-direction matrices can be designed based on the sampling index. In one example, in the actual use of the radar after the direction matrix is ​​derived, the corresponding direction matrix can be selected according to the sampling index of the radar data. For example, the first sub-direction matrix of the direction matrix can be designed for the first sampling index, and the second sub-direction matrix of the direction matrix can be designed for the second sampling index.

[0101] In one example, to estimate DOA during actual processing, a first sub-direction matrix can be used for the first sub-radar data corresponding to the first sampling index of the radar data, and a second sub-direction matrix can be used for the second sub-radar data corresponding to the second sampling index of the radar data. For example, a radar signal processing device can obtain the first sub-direction matrix corresponding to the first sampling index from multiple sub-direction matrices, and can use the first sub-direction matrix to estimate the first direction of arrival (DOA) of the first sub-radar data corresponding to the first sampling index from the corrected radar data. In this way, FM parasitic errors can be corrected by designing a direction matrix that takes into account changes in frequency. The process of deriving the direction matrix will be described in more detail later.

[0102] EBP errors can be corrected using an EBP error model. An EBP error model represents the EBP error value for each angle. For example, a radar signal processing device can estimate the initial direction of arrival (DOA) corresponding to the corrected radar data using a direction matrix, and estimate the final DOA corresponding to the corrected radar data by removing the EBP error included in the initial DOA. EBP errors occur due to the influence of the beam pattern of the antenna elements on the beam pattern of the array antenna. For example, a radar signal processing device can determine the EBP error value of the initial DOA corresponding to the radar data based on the EBP error model, and estimate the final DOA by correcting the initial DOA with the determined EBP error value. An EBP error model can be generated by estimating the EBP error values ​​for other angles based on the EBP error values ​​of a base angle measured via testing. For example, other EBP error values ​​can be estimated using multinomial regression (PR) or various interpolation or fitting techniques.

[0103] Feeder error, FM parasitic error, and EBP error can be corrected sequentially. For example, when a correction vector for correcting the feeder error is obtained, the corrected direction matrix can be derived using the AF from which the feeder error is removed. Then, corrected reference data can be obtained by applying the correction vector to reference data obtained for the base angle, and the EBP error value for the base angle can be obtained based on the corrected reference data and the corrected direction matrix. Subsequently, an EBP error model can be obtained by performing PR, interpolation, or fitting on the EBP error value for the base angle. The sequential correction operations described above can relatively easily eliminate errors that may act in complex ways.

[0104] Figure 5 This illustrates an example of feeder delay in an array antenna. (See reference...) Figure 5 The radar sensor 500 may include an array antenna and a power divider 510. The array antenna includes first antenna elements to Nth antenna elements. Adjacent antenna elements (e.g., first antenna element and second antenna element) are defined as being spaced apart by a distance d. The first antenna elements to the Nth antenna elements may individually form an element beam pattern (EBP), and the EBP may form the overall beam pattern of the array antenna.

[0105] Power divider 510 can distribute the transmitted signal to the first antenna element through the Nth antenna element. In this example, due to physical factors (e.g., transmission line length, impedance, etc.) between power divider 510 and the first through Nth antenna elements, the transmitted signal may arrive at each of the first through Nth antenna elements at different times. For example, the time when the transmitted signal arrives at the first antenna element may differ from the time when the transmitted signal arrives at the second antenna element. The times when the transmitted signal arrives at the first through Nth antenna elements can be referred to as feeder delays, respectively. to And delayed by the feeder to The error caused by the difference can be called feeder error.

[0106] Assuming the channels have the same phase, the radar signal can be transmitted to each channel of the array antenna. Therefore, such feeder error can cause phase distortion in the radar signal. Correction is needed to eliminate this phase distortion. In Equation 3 above, the feeder error is reflected as a component... And the amount It can be removed through correction.

[0107] Figure 6 An example of using a correction vector to correct feeder errors is shown. Figure 6 Curves 611 and 613 correspond to reference data measured about the target at a 45-degree angle in the test environment. Curve 611 represents the reference data before correcting for feeder errors, and curve 613 represents the reference data after correcting for feeder errors. Curve 611 shows the results at different angles (45 degrees) from the target, and curve 613 shows the results matching the angle (45 degrees) from the target. Curve 612 represents the per-channel correction value of the correction vector used to correct for feeder errors.

[0108] The correction value of the correction vector can be obtained in various ways. It can be derived from reference data of a target located in front of the radar sensor (therefore, the target is at a 0-degree angle). More specifically, the reference data can be obtained in a test environment by transmitting a radar signal to a target located in front of the radar sensor and receiving the signal reflected by the target through multiple channels. Since the reference data is obtained with the target at a 0-degree angle, the phase components of the channels of the reference data should have the same value (e.g., e). 0 =1).

[0109] When the phase components of a channel do not have the same value, a correction value is calculated to correct the phase components to have the same value, and a correction vector with the correction value is derived. The correction vector and correction value can be expressed as Equation 4.

[0110] [Equation 4]

[0111]

[0112] In Equation 4, C represents the correction vector, and n represents the channel. n can have values ​​between 1 and N. n (θ0) represents the correction value of the nth channel when the target is at an angle of θ0. θ0 can be 0 degrees. G represents the reference data. n (θ0) represents the reference data corresponding to the target at angle θ0, and |G n(θ0)| represents G n The absolute value of (θ0). By using G n (θ0) divided by |G n (θ0)|, the amplitude component from G n (θ0) is removed, and only the phase component remains.

[0113] When the target is positioned at 0 degrees, the phase components of the reference data channels should have the same value (e.g., e). 0 =1). If feeder error exists, the value of the phase component may not be equal to 1. In this example, there may be cases where G does not satisfy... n (θ0) / |G n A channel with (θ0)|=1, and the phase component of this channel can be divided by G. n (θ0) / |G n (θ0)| becomes 1. Therefore, the correction vector can be defined as shown in Equation 4, and the correction value of the correction vector can be determined by measuring the phase component of the channel of the reference data.

[0114] Once the correction vector is derived and all correction values ​​of the correction vector are determined, feed line errors can be removed from radar data by dividing the phase components of the channels by the correction values ​​used in the actual processing. For example, this can be achieved by dividing the phase component of the first channel of the radar data by the correction value C1(θ0) and by dividing the phase component of the nth channel of the radar data by the correction value C... n (θ0) is used to remove feeder error from the reference data. Figure 6 Beam diagram 602 shows the result of removing feeder error components from beam diagram 601 by means of correction vectors.

[0115] Figure 7 An example of a receiving antenna element for an array antenna is shown. (See reference...) Figure 7 The array antenna 710 may include multiple receiving antenna elements 711 to 714. Multiple channels can be formed by the multiple receiving antenna elements 711 to 714. Although Figure 7 It is not shown in the figure, but the array antenna 710 may also include at least one of at least one transmitting antenna element and at least one receiving antenna element.

[0116] When a radar sensor implements multiple channels, the phase information in the radar data can indicate the phase difference between the phase of the signal received through each channel and a reference phase. The reference phase can be a predetermined phase or can be set as the phase of one of the multiple channels. For example, a radar signal processing device can set the phase of a receiving antenna element adjacent to that receiving antenna element as the reference phase for a given receiving antenna element.

[0117] Additionally, the processor can generate radar vectors from radar data with dimensions corresponding to the number of channels in the radar sensor. For example, if the radar sensor includes 7 channels, the processor can generate 7D radar vectors that include phase values ​​corresponding to the channels. The phase values ​​corresponding to the channels can be numerical values ​​representing the phase differences described above.

[0118] For example, it can be assumed that the radar sensor includes one transmit channel and four receive channels. In this case, the radar signal transmitted through the transmit channel can be reflected by the target and then received through the four receive channels. Figure 7 As shown, if the array antenna 710 includes multiple receiving antenna elements 711 to 714, the phase of the signal received at the receiving antenna element 711 can be set as a reference phase. When the radar receiving signal 708 reflected from the same target is received at the array antenna 710, the additional distance Δ between the distance from the target to the receiving antenna element 711 and the distance from the target to the receiving antenna element 712 can be expressed as Equation 5.

[0119] [Equation 5]

[0120] Δ=d·sin(θ)

[0121] In Equation 5, θ represents the DOA of the radar signal 708 received from the target. d represents the distance between the receiving antenna elements. c represents the speed of light in air, which is considered constant. Since c = fλ, the phase shift W at the receiving antenna element 712 due to the additional distance Δ can be derived as Equation 6.

[0122] [Equation 6]

[0123]

[0124] The phase shift W corresponds to the phase difference between the waveform of the signal received at receiving antenna element 712 and the waveform of the signal received at receiving antenna element 711. In Equation 6, f represents the frequency of the radar received signal 708, and λ represents the wavelength of the radar received signal 708. λ is inversely proportional to the frequency f. If the carrier frequency changed by the frequency modulation model is small, the frequency f in Equation 6 can be considered as a single initial frequency (e.g., f0) in the frequency modulation model. Therefore, if the phase shift W is determined solely based on the received signal, the radar signal processing device can determine the DOA θ.

[0125] However, if the carrier frequency of the frequency modulation model varies over a wide bandwidth (e.g., a bandwidth greater than or equal to 2 GHz (specifically, 2 GHz, 5 GHz, or 7 GHz)), the carrier frequency variation may be non-negligible. Therefore, errors may occur during the processing of estimating target information (such as DOA).

[0126] Figure 8An example of phase shift variation based on carrier frequency at each sampling point is shown in a radar signal processing method. For ease of description, an example of a frequency modulation model 801 illustrating a pattern in which the carrier frequency increases linearly over a given transmission time will be described below. For example, the sampling interval in the frequency modulation model 801 can be an interval from which the carrier frequency increases linearly to a final frequency f0+BW with a bandwidth BW increasing from an initial frequency f0. The bandwidth BW is the sampling bandwidth corresponding to the sampling interval and may be less than the modulation bandwidth B described in Equation 1. The radar reflection signal 802 received at the radar sensor can represent a frequency corresponding to the carrier frequency described above. The radar reflection signal 802 can be sensed individually by multiple receiving antenna elements.

[0127] Since the radar reflected signal 802 corresponding to a linear frequency modulation (chirp) is reflected from the same target point, the round-trip time can be the same. Because the round-trip time is the same, the radar signal processing equipment needs to calculate the same DOA at the initial, intermediate, and final time points of the radar reflected signal 802. However, because the phase shift W changes with time even within a linear frequency modulation due to frequency variations, errors may occur in the phase component used for DOA estimation (FM parasitic errors described above).

[0128] For example, a radar signal processing device can generate a first IF signal 811, a second IF signal 812, and a third IF signal 813 based on radar transmitted signals and radar received signals received through a first receiving antenna element, a second receiving antenna element, and a third receiving antenna element, respectively. In this example, a phase shift 881 at the initial time point, a phase shift 882 at an intermediate time point, and a phase shift 883 at the end time point may occur within a predetermined linear frequency modulation.

[0129] Radar signal processing equipment can generate phase-normalized radar data by phase normalizing the carrier frequency by 850°. Figure 8 In this context, y(t) represents the IF signal. This represents phase-normalized radar data. For example... Figure 8 As shown, the first IF signal 821, the second IF signal 822, and the third IF signal 823 in the phase-normalized radar data can exhibit the same phase shifts 891, 892, and 893 during the chirp interval of the radar reflection signal 802. Therefore, radar signal processing equipment can eliminate FM parasitic errors through phase normalization.

[0130] Figure 9An example of sampling an intermediate frequency (IF) signal is shown. A radar signal processing device can obtain the IF signal based on a radar transmitted signal 970 and a radar received signal 980, whereby the radar transmitted signal 970 is generated based on a frequency modulation model, and the radar received signal 980 is received when the radar transmitted signal 970 is reflected by a target. For example, the radar signal processing device can calculate the IF signal corresponding to the frequency change between the frequency 907 of the radar transmitted signal 970 and the frequency 908 of the radar received signal 980.

[0131] Radar signal processing equipment can measure IF f without directly measuring it. IF The radar signal processing device can measure the signal waveform 981 of the radar received signal 980 and generate an IF signal based on the pre-provided signal waveform 971 of the radar transmitted signal 970 and the measured signal waveform 981 of the radar received signal 980. The radar signal processing device can calculate the IF signal described above from the mixing 950 (e.g., multiplication) of the radar transmitted signal 970 and the radar received signal 980.

[0132] Figure 9 y in m (t) represents the IF signal calculated for the radar transmitted signal 970 and the radar received signal 980 received through the m-th receiving antenna element among the M receiving antenna elements. M can be an integer greater than or equal to 2, and m can be an integer between 1 and M, inclusive. For reference, Figure 9 The radar transmit signal 970, radar receive signal 980, and IF signal with a frequency lower than the actual frequency are shown for better understanding, and the frequency of the signal is not limited to... Figure 9 The frequencies shown in the figure.

[0133] Radar signal processing equipment can obtain sampled data by sampling the IF signal at multiple sampling points. The sampled data may include sampled values ​​obtained at predetermined sampling points. For example, refer to... Figure 9 s m (i) represents the value obtained by sampling the signal strength received by the m-th receiving antenna element among the M receiving antenna elements at the i-th sampling point. i represents the sampling index, and I represents the number of samples of the IF signal, where I can be an integer greater than or equal to 1, and i can be an integer between 1 and I, inclusive. I (For example, t1, t2, t3, etc.) represent the sampling time, f I (For example, f1, f2, f3, etc.) represent frequencies corresponding to different sampling times. Radar data can be determined based on sampled data. For example, sampled data can be determined as radar data, or the result of performing some processing on the sampled data can be determined as radar data.

[0134] like Figure 9 As shown, due to this change in carrier frequency between the radar transmitted signal 970 and the radar received signal 980, the phase shift can vary at each sampling point. Figure 9 As shown, due to the frequency change at each sampling point described above, the frequency and phase of the IF signal can change rather than remain constant. For ease of description, Figure 9 The diagram clearly shows the time delay between the radar transmitted signal 970 and the radar received signal 980. However, since radar signals propagate at the speed of light, this time delay is very small, and the corresponding frequency difference is also very small. Therefore, the carrier frequency of the radar transmitted signal 970 and the carrier frequency of the radar received signal 980 can be considered to be substantially the same at the provided sampling point.

[0135] Although the primary description herein is of methods for processing radar signals, the examples are not limited thereto. The phase normalization described above can generally be applied to reflected signals such as those received when a transmitted signal, whose carrier frequency is altered according to a frequency modulation model, is transmitted by a signal processing device performing the signal processing method and reflected from a target point. For example, the transmitted and reflected signals are signals that propagate as waves according to a carrier frequency, and can be radar signals, ultrasonic signals, electromagnetic wave signals, or optical signals.

[0136] Figure 10 An example of correcting frequency modulation (FM) parasitic errors by phase normalization is shown. According to the FMCW described above, the carrier frequency can change over time. The AF of the array antenna can be defined to reflect such changes in the carrier frequency, as shown in Equation 7.

[0137] [Equation 7]

[0138]

[0139] In Equation 7, n represents the index used to identify the antenna element. n can be an integer value between 1 and N. N is the total number of antenna elements. k t d represents the wave number at time t. d represents the distance between two adjacent antenna elements. Let represent the feed delay in the nth antenna element. Equation 7 represents AF where the feed error is removed, showing the components according to the feed error. Removed. k in Equation 7 t It can be represented as Equation 8.

[0140] [Equation 8]

[0141]

[0142] In equation 8, f c B represents the carrier frequency, and T represents the modulation bandwidth. chirpLet represent the time length of the rise interval of the carrier frequency in the frequency modulation model, c represent the speed of light, λ represent the wavelength, k represent the wavenumber, and t represent time. According to Equations 7 and 8, λ and k depend on time t. This is due to the frequency modulation model of FMCW, and therefore FM parasitic errors may occur. When phase normalization is applied to Equations 7 and 8, Equations 9 and 10 can be derived. In Equations 9 and 10, k corresponds to a constant, such that FM parasitic errors do not occur.

[0143] [Equation 9]

[0144]

[0145] [Equation 10]

[0146]

[0147] The phase shift W in Equation 6 can be redefined as ω(τ) in Equation 11.

[0148] [Equation 11]

[0149]

[0150] In Equation 11, ω(τ) is based on the phase shift of τ. τ represents the sampling index (time index). Since FM parasitic errors occur when the carrier frequency changes while the DOA remains constant, ω(τ) can be defined as λ changing while θ remains constant. GT Let θ represent a fixed DOA. If θ is defined as changing, then λ can be fixed at λ0. Therefore, Equation 12 can be defined. Furthermore, Equation 13 can be defined based on Equation 12.

[0151] [Equation 12]

[0152]

[0153] [Equation 13]

[0154]

[0155] f(τ) = f can be expressed based on Equation 8. c +(B / T chirp Substitute τ into Equation 13 to calculate the change in DOA based on τ. For example, the result can be derived from the calculation. Figure 10 Line 1010. Lines 1010 and 1020 represent the DOA according to the sampling index. The sloping line 1010 indicates that the DOA changes over time and that FM parasitic errors are present. Phase normalization can be performed by various methods used to change line 1010 to line 1020 by compensating for changes in DOA.

[0156] FM parasitic errors can be compensated for by referring to radar design parameters (e.g., f(τ)). For example, individual sub-direction matrices can be designed based on sampling indices (e.g., τ = 0, 1, 2, ..., 511). Therefore, the direction matrix can include multiple sub-direction matrices, each corresponding to a different sampling index. In one example, multiple sub-direction matrices corresponding to the number of sampling indices (e.g., 512) can be derived. In this example, Equation 11 can be used to determine the phase value of the channel of the direction vector of each sub-direction matrix.

[0157] In one example, a first sub-direction matrix of the direction matrix is ​​designed for a first sampling index, and a second sub-direction matrix of the direction matrix is ​​designed for a second sampling index. In another example, during actual processing, the first sub-direction matrix can be used for first sub-radar data corresponding to the radar data at the first sampling index, and the second sub-direction matrix can be used for second sub-radar data corresponding to the radar data at the second sampling index. The sub-radar data and sub-direction matrices will be further described below.

[0158] For example, sampled data Y can be represented by Equation 14. Sampled data Y can correspond to radar data.

[0159] [Equation 14]

[0160] Y=[Y(1),Y(2),...,Y(i),...,Y(I-1),Y(I)]

[0161] In Equation 14, i represents the sampling index, and I represents the number of times the sampled data is sampled. I can be an integer greater than or equal to 1, and i can be an integer between 1 and I, inclusive. If the radar sensor's antenna array forms M channels, the sampled data Y(i) at the i-th sampling point corresponding to the sampling index i can be expressed as Equation 15. The sampled data Y(i) can correspond to sub-radar data.

[0162] [Equation 15]

[0163] Y(i) = [s1(i), s2(i), ... s m (i), ..., s M-1 (i), s M (i)] T

[0164] In equation 15, s m (i) represents the value obtained by sampling the strength of the signal received by the m-th sub-receiving antenna among the M sub-receiving antennas at the i-th sampling point. M can be an integer greater than or equal to 2, and m can be an integer between 1 and M, inclusive. Furthermore, the direction matrix can be as shown in Equation 16, and the direction vector of the direction matrix can be as shown in Equation 17.

[0165] [Equation 16]

[0166]

[0167] [Equation 17]

[0168]

[0169] In Equation 16, the direction matrix A fi It can be represented as a set of direction vectors α fi (θ k Here, K can be an integer greater than or equal to 1, and k can be an integer between 1 and K, inclusive. For example, if the radar's FoV is 180 degrees and K is 512, the angular resolution can be 0.35 degrees. However, the examples are not limited to this. If K is 180, the angular resolution can be 1 degree, and if K is 360, the angular resolution can be 0.5 degrees. K can be determined based on the desired angular resolution (e.g., less than or equal to 1 degree). Here, each A is determined based on the change in sampling index i. fi (For example, A) f1 A f2 ,...,A fN ) can correspond to a sub-direction matrix.

[0170] In Equation 17, d represents the distance between radar antenna elements. θ represents the wavelength corresponding to the carrier frequency at the i-th sampling index. k A represents fi The angle in the k-th direction. The directional angle θ is represented by the angle θ at the carrier frequency corresponding to the i-th sampling index of the frequency modulation model. k The corresponding direction vector.

[0171] In one example, A fi It can be a K×M matrix consisting of K rows and M columns. The direction matrix A can be determined according to Equation 16. fi The result A of the matrix multiplication with Y(i) according to Equation 15 fi Y(i) is calculated as a (K×1) dimensional vector. In the matrix multiplication result A... fi In Y(i), the element in the k-th row can be related to Y(i), where DOA is the k-th turning angle θ. k The probability corresponds to the value and can indicate DOA information. For example, the i-th sampled data Y(i) (corresponding to the sub-radar data) and the i-th direction matrix A fi The calculation result (corresponding to the sub-direction matrix) can correspond to the DOA information related to the i-th sampled data Y(i) (corresponding to the sub-radar data).

[0172] Figure 11 and Figure 12 An example of correction element beam pattern (EBP) error is shown. The beam pattern of an array antenna can be defined by Equation 18.

[0173] [Equation 18]

[0174]

[0175] Referring to Equation 18, after the feed line error and the FM parasitic error are removed, the beam pattern of the array antenna can be classified into array factor (AF) components and element pattern (EP) components. For example, as mentioned above, the feed line error can be removed by a correction vector, and the FM parasitic error can be removed by a special design of the directional matrix.

[0176] When antenna elements have the same EP (i.e., assuming EP = EP1 = ... = EP), N When N is the number of antenna elements, such as Figure 11 The graphs shown, relating to the antenna pattern, can be obtained. Figure 11 In the diagram, curve 1110 corresponds to EP, curve 1120 corresponds to AF, and curve 1130 corresponds to the beam pattern (BP). (See reference...) Figure 11 The beam pattern is not formed entirely based on AF, but is influenced by EP, and in this processing, errors caused by EP can be included in the radar data. Such errors are referred to as EBP errors.

[0177] EBP error models can be used to correct for EBP errors. An EBP error model represents the EBP error value for each angle. EBP error models can be generated by estimating the EBP error values ​​for other angles based on the EBP error values ​​of a base angle measured via testing. For example, other EBP error values ​​can be estimated using multinomial regression (PR) or various interpolation or fitting techniques.

[0178] The fundamental EBP error can be determined by measuring reference data at multiple fundamental angles (e.g., -40 degrees, 0 degrees, and 40 degrees). Feed errors in the reference data can be corrected using a correction vector, and the EBP error can be determined by comparing the corrected reference data with the sub-direction matrix for each sampling index. For example, if the DOA at -58 degrees is estimated as a result of a comparison with the sub-direction matrix, the EBP error for the DOA at -58 degrees can be determined to be 2 degrees, even though the corrected reference data is obtained through a target at -60 degrees.

[0179] When the fundamental EBP errors for multiple fundamental angles are determined as described above, an EBP error model can be obtained by performing polynomial regression or fitting based on the fundamental EBP errors. The error value corresponding to the desired resolution can then be obtained from the EBP error model. Figure 12 The curves 1210 to 1230 show the results of iteratively performing double, triple, and quadruple polynomial regressions based on reference data, and each line in curves 1210 to 1230 corresponds to the EBP error model.

[0180] The EBP error model can be estimated based on multiple fundamental EBP errors because feeder errors and FM parasitic errors have been removed beforehand. If the EBP error model is estimated based on multiple fundamental EBP errors while both feeder and FM parasitic errors are present, it may not be successful. In this case, processing of each reference data point is required according to the desired resolution, which demands significant effort due to the high accuracy required. Therefore, the EBP error model can alleviate such effort.

[0181] The EBP error model can be used in various ways. In practical processing, if the initial DOA is derived based on the sub-direction matrix for each sampling index and radar data corrected using a correction vector, the final DOA can be estimated by correcting the initial DOA via the matching relationship between the DOA and the EBP error defined in the EBP error model. More specifically, the radar signal processing device can determine the EBP error value that matches the initial DOA based on the EBP error model and estimate the final DOA by correcting the initial DOA with the determined EBP error value. The correction of the initial DOA can be performed in reverse order of the process of estimating the EBP error. For example, if an initial DOA of -58 degrees is derived based on the corrected radar data and the sub-direction matrix, and the EBP error of the -58 degree DOA is 2 degrees, then the final DOA can be estimated as -60 degrees.

[0182] Figure 13 An example of a radar signal processing method is shown. It can be performed in the order and manner shown. Figure 13 The operations described herein may be ordered differently or omitted without departing from the spirit and scope of the exemplary examples described. Figure 13 Many of the operations shown can be performed in parallel or simultaneously. Figure 13 One or more blocks, and combinations thereof, can be implemented by performing specified functions using a dedicated hardware computer (such as a processor) or a combination of dedicated hardware and computer instructions. In addition to the following... Figure 13 In addition to the description, Figures 1 to 12 The description also applies to Figure 13And it is included here by reference. Therefore, the above description need not be repeated here.

[0183] Reference Figure 13 In operation 1310, the radar signal processing device generates radar data based on the radar transmitted signal and the radar received signal. The radar transmitted signal is transmitted through the array antenna of the radar sensor based on a frequency modulation model, and the radar received signal is received through the array antenna when the radar transmitted signal is reflected by the target. In operation 1320, the radar signal processing device uses a correction vector to correct the radar data. The correction vector is used to correct feeder errors caused by differences in feeder delay between channels of the array antenna. In operation 1330, the radar signal processing device estimates the DOA corresponding to the corrected radar data using a direction matrix reflecting the phase shift of the corrected radar data, based on the frequency modulation characteristics of the frequency modulation model. As mentioned above, the phase shift (FM parasitic error) can be corrected without using a correction vector. For example, a sub-direction matrix for each sampling index can be used to correct the phase shift. The direction matrix reflecting the phase shift of the corrected radar data can correspond to these sub-direction matrices.

[0184] Figure 14 An example of an electronic device is shown. (See reference) Figure 14 The electronic device 1400 can perform the radar signal processing methods described above. For example, the electronic device 1400 may include functionally and / or structurally... Figure 2 Radar signal processing equipment 200. Electronic device 1400 may be, for example, an image processing device, a smartphone, a wearable device, a tablet computer, a netbook, a laptop computer, a desktop computer, a personal digital assistant (PDA), a head-mounted display (HMD), a robot, a walking aid, a vehicle (e.g., an autonomous vehicle), and a driver assistance device to be installed on the vehicle.

[0185] Reference Figure 14 The electronic device 1400 may include a processor 1410, a storage device 1420, a camera 1430, an input device 1440, an output device 1450, and a network interface 1460. The processor 1410, storage device 1420, camera 1430, input device 1440, output device 1450, and network interface 1460 may communicate with each other via a communication bus 1470.

[0186] Processor 1410 can execute instructions or functions that will be executed in electronic device 1400. For example, processor 1410 can process instructions stored in storage device 1420. Processor 1410 can execute instructions via... Figures 1 to 13 One or more operations are described. Further details about the processor 1410 are provided below.

[0187] Storage device 1420 stores information or data required for execution by processor 1410. For example, a pre-computed phase normalization matrix may be stored in storage device 1420. Storage device 1420 may include a computer-readable storage medium or a computer-readable storage device. Storage device 1420 may store instructions to be executed by processor 1410, and may store relevant information when software and / or applications are executed by electronic device 1400. Further details regarding storage device 1420 are provided below.

[0188] Camera 1430 can capture images comprising multiple image frames. For example, camera 1430 can generate frame images.

[0189] Input device 1440 may receive input from a user via tactile, video, audio, or touch input. Input device 1440 may include a keyboard, mouse, touchscreen, microphone, or any other device that detects input from the user and transmits the detected input.

[0190] Output device 1450 can provide the output of electronic device 1400 to a user through visual, auditory, or tactile channels. Output device 1450 may include, for example, a display, touch screen, speaker, vibration generator, or any other device that provides output to the user. Network interface 1460 can communicate with external devices through a wired or wireless network. Output device 1450 can provide the user with the results of processing radar data using at least one of visual, auditory, and tactile information.

[0191] For example, when the electronic device 1400 is installed in a vehicle, it can visualize a radar image map on a display. As another example, the electronic device 1400 can change any or any combination of the speed, acceleration, and steering of the vehicle equipped with it based on DOA information, distance information, and / or a radar image map. However, the examples are not limited to this, and the electronic device 1400 can perform functions such as ACC, AEB, BSD, LCA, and self-localization. The electronic device 1400 may structurally and / or functionally include a control system for such control of the vehicle.

[0192] The radar signal processing apparatus, linear frequency modulated transmitter 311, duplexer 312, mixer 314, amplifier 315, spectrum analyzer 316, and other devices, apparatuses, units, modules, and components described herein are implemented by hardware components. Examples of hardware components that can be used to perform the operations described herein include, where appropriate, controllers, sensors, generators, drivers, memories, comparators, arithmetic logic units, adders, subtractors, multipliers, dividers, integrators, and any other electronic components configured to perform the operations described herein. In other examples, one or more of the hardware components performing the operations described herein are implemented by computing hardware (e.g., by one or more processors or computers). A processor or computer may be implemented by one or more processing elements (such as logic gate arrays, controllers and arithmetic logic units, digital signal processors, microcomputers, programmable logic controllers, field-programmable gate arrays, programmable logic arrays, microprocessors, or any other means or combination of means configured to respond to and execute instructions in a defined manner to achieve a desired result). In one example, the processor or computer includes or is connected to one or more memories storing instructions or software executed by the processor or computer. Hardware components implemented by a processor or computer can execute instructions or software (such as an operating system (OS) and one or more software applications running on the OS) for performing the operations described in this application. Hardware components can also access, manipulate, process, create, and store data in response to the execution of instructions or software. For simplicity, the singular terms "processor" or "computer" may be used in the description of the examples described in this application; however, in other examples, multiple processors or computers may be used, or a processor or computer may include multiple processing elements or multiple types of processing elements or both. For example, a single hardware component or two or more hardware components may be implemented by a single processor, or two or more processors, or a processor and a controller. One or more hardware components may be implemented by one or more processors, or a processor and a controller, and one or more other hardware components may be implemented by one or more other processors, or additional processors and additional controllers. One or more processors, or a processor and a controller, may implement a single hardware component or two or more hardware components.The hardware components may be any one or more with different processing configurations. Examples of different processing configurations include: a single processor, a standalone processor, a parallel processor, a single instruction single data (SISD) multiprocessor, a single instruction multiple data (SIMD) multiprocessor, a multiple instruction single data (MISD) multiprocessor, a multiple instruction multiple data (MIMD) multiprocessor, a controller and arithmetic logic unit (ALU), a DSP, a microcomputer, an FPGA, a programmable logic unit (PLU), a central processing unit (CPU), a graphics processing unit (GPU), a neural processing unit (NPU), or any other device capable of responding to and executing instructions in a defined manner.

[0193] The methods for performing the operations described in this application are executed by computing hardware (e.g., by one or more processors or a computer), which is implemented to execute instructions or software as described above to perform the operations performed by the methods described in this application. For example, a single operation or two or more operations may be performed by a single processor, or two or more processors, or a processor and a controller. One or more operations may be performed by one or more processors, or a processor and a controller, and one or more other operations may be performed by one or more other processors, or additional processors and additional controllers. One or more processors, or a processor and a controller, may perform a single operation or two or more operations.

[0194] Instructions or software for controlling a processor or computer to implement hardware components and perform the methods described above are written as computer programs, code segments, instructions, or any combination thereof to individually or collectively instruct or configure the processor or computer, such as a machine or special-purpose computer, to perform the operations performed by the hardware components and methods described above. In one example, the instructions or software include machine code (such as machine code generated by a compiler) that is directly executed by the processor or computer. In one example, the instructions or software include at least one of a applet, dynamic link library (DLL), middleware, firmware, device driver, or application that stores a method for processing radar signals. In another example, the instructions or software include high-level code that is executed by the processor or computer using an interpreter. Programmers skilled in the art can readily write instructions or software based on the block diagrams and flowcharts shown in the accompanying drawings and the corresponding descriptions in the specification, which disclose algorithms for performing the operations performed by the hardware components and methods described above.

[0195] Instructions or software for controlling a processor or computer to implement hardware components and perform the methods described above, along with any associated data, data files, and data structures, are recorded, stored, or fixed on one or more non-transitory computer-readable storage media. Examples of non-transitory computer-readable storage media include: read-only memory (ROM), random access programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), flash memory, non-volatile memory, CD-ROM, CD-R, CD+R, CD-RW, CD+RW, DVD-ROM, DVD-R, DVD+R, DVD-RW, DVD+RW, DVD-RAM, BD-ROM, BD-R, BD-R LTH, BD-RE, Blu-ray or optical disc storage, hard disk drive (HDD), solid-state drive (SSD), flash memory, card storage (such as multimedia cards or microcards (e.g., Secure Digital (SD) or Extreme Digital (XD))), magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid-state drive, and any other device configured to store instructions or software and any associated data, data files and data structures in a non-transitory manner and to provide instructions or software and any associated data, data files and data structures to a processor or computer such that the processor or computer can execute the instructions.

[0196] While this disclosure includes specific examples, it will be clear upon understanding this disclosure that various changes in form and detail may be made in these examples without departing from the spirit and scope of the claims and their equivalents. The examples described herein are to be considered descriptive only and not for limiting purposes. The description of features or aspects in each example should be considered applicable to similar features or aspects in other examples. Suitable results may be achieved if the described techniques are performed in a different order, and / or if components in the described system, architecture, apparatus, or circuit are combined in a different manner, and / or replaced or supplemented by other components or their equivalents. Therefore, the scope of the disclosure is not limited by the specific embodiments but by the claims and their equivalents, and all variations within the scope of the claims and their equivalents should be construed as included in the disclosure.

Claims

1. A method for processing radar signals, the method comprising: Radar data is generated based on radar transmitted signals and radar received signals. The radar transmitted signals are transmitted through the array antenna of the radar sensor based on a frequency modulation model, and the radar received signals are received through the array antenna when the radar transmitted signals are reflected by the target. A correction vector is used to correct radar data; the correction vector is used to correct feed errors caused by differences in feed delay between channels of the array antenna; and Based on the frequency modulation characteristics of the frequency modulation model, the direction of arrival corresponding to the corrected radar data is estimated using the direction matrix reflecting the phase shift of the corrected radar data. The steps for estimating the direction of arrival include: The initial direction of arrival corresponding to the corrected radar data is estimated using a direction matrix; and The final direction of arrival (DOA) corresponding to the corrected radar data is estimated by removing the EBP error in the initial DOA based on an EBP error model configured to represent the EBP error value of the element beammap for each angle. The EBP error in the initial DOA occurs due to the influence of the beammap of the array antenna elements on the array antenna's beammap. Specifically, an EBP error model is generated by estimating the EBP error values ​​of other angles based on the EBP error values ​​of the base angle measured by testing.

2. The method according to claim 1, wherein, The correction vector is configured to correct the radar data in response to the radar receiving signal being received from a target located in front of the radar sensor, such that the phase components of the radar data channels have the same value.

3. The method according to claim 1, wherein, The orientation matrix includes multiple sub-orientation matrices, each corresponding to a different sampling index.

4. The method according to claim 3, wherein, The steps for estimating the direction of arrival include: Obtain the first sub-direction matrix corresponding to the first sampling index from the plurality of sub-direction matrices; and Using the first sub-direction matrix, the first direction of arrival of the first sub-radar data corresponding to the first sampling index is estimated from the corrected radar data.

5. The method according to claim 1, wherein, The steps for generating radar data include: Radar data is generated by sampling intermediate frequency signals generated based on radar transmitted and received signals.

6. The method according to claim 1, wherein, The steps for estimating the final direction of arrival include: Based on the EBP error model, the EBP error value of the initial direction of arrival corresponding to the corrected radar data is determined; and The final direction of arrival (DOA) corresponding to the corrected radar data is estimated by correcting the initial DOA with a determined EBP error value.

7. The method according to any one of claims 1 to 6, wherein, Radar transmitted signals include linear frequency modulated signals with a carrier frequency modulated based on a frequency modulation model.

8. The method according to claim 7, wherein, The radar signal is received through the receiving antenna elements in the array antenna, and the channel is formed based on the receiving antenna elements.

9. The method according to any one of claims 1 to 6, further comprising: Estimate at least one of the target's range and velocity based on radar data. The vehicle is controlled based on any one or any combination of the direction of arrival, distance, and speed, and is equipped with a device for processing radar signals.

10. A non-transitory computer-readable storage medium storing instructions, which, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 9.

11. An apparatus for processing radar signals, the apparatus comprising: The radar sensor is configured to transmit radar signals through an array antenna based on a frequency modulation model, and to receive radar signals through an array antenna when the radar transmitted signals are reflected by a target. and The processor is configured to generate radar data based on radar transmitted signals and radar received signals; A correction vector is used to correct the radar data. This correction vector is used to correct feeder errors caused by differences in feeder delay between channels of the array antenna. Furthermore, based on the frequency modulation characteristics of the frequency modulation model, the direction of arrival corresponding to the corrected radar data is estimated using a direction matrix reflecting the phase shift of the corrected radar data. The processor is configured as follows: The initial direction of arrival corresponding to the corrected radar data is estimated by using the direction matrix; and The final direction of arrival (DOA) corresponding to the corrected radar data is estimated by removing the EBP error in the initial DOA based on an EBP error model configured to represent the EBP error value of the element beammap for each angle. The EBP error in the initial DOA occurs due to the influence of the beammap of the array antenna elements on the array antenna's beammap. Specifically, an EBP error model is generated by estimating the EBP error values ​​of other angles based on the EBP error values ​​of the base angle measured by testing.

12. The device according to claim 11, wherein, The correction vector is configured to correct the radar data in response to the radar receiving signal being received from a target located in front of the radar sensor, such that the phase components of the radar data channels have the same value.

13. The device according to claim 11, wherein, The orientation matrix includes multiple sub-orientation matrices, each corresponding to a different sampling index; and The processor is also configured to: obtain a first sub-direction matrix corresponding to a first sampling index from the plurality of sub-direction matrices, and use the first sub-direction matrix to estimate a first direction of arrival of the first sub-radar data corresponding to the first sampling index from the calibrated radar data.

14. A vehicle comprising: The radar sensor is configured to transmit radar signals through an array antenna based on a frequency modulation model, and to receive radar signals through an array antenna when the radar transmitted signals are reflected by a target. The processor is configured to: generate radar data based on radar transmitted and received signals; correct the radar data using a correction vector to correct feeder errors caused by differences in feeder delay between channels of the array antenna; and estimate the direction of arrival (DOA) corresponding to the corrected radar data using a direction matrix reflecting the phase shift of the corrected radar data, based on the frequency modulation characteristics of the frequency modulation model; and The controller is configured to control the vehicle based on the direction of arrival. The processor is configured as follows: The initial direction of arrival corresponding to the corrected radar data is estimated by using the direction matrix; and The final direction of arrival (DOA) corresponding to the corrected radar data is estimated by removing the EBP error in the initial DOA based on an EBP error model configured to represent the EBP error value of the element beammap for each angle. The EBP error in the initial DOA occurs due to the influence of the beammap of the array antenna elements on the array antenna's beammap. Specifically, an EBP error model is generated by estimating the EBP error values ​​of other angles based on the EBP error values ​​of the base angle measured by testing.

15. The vehicle according to claim 14, wherein, The orientation matrix includes multiple sub-orientation matrices, each corresponding to a different sampling index; and The processor is also configured to: obtain a first sub-direction matrix corresponding to a first sampling index from the plurality of sub-direction matrices, and use the first sub-direction matrix to estimate a first direction of arrival of the first sub-radar data corresponding to the first sampling index from the calibrated radar data.

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