Patent Description:
Advanced driver-assistance systems (ADAS) are assistance systems to enhance safety and convenience of a driver and to support driving for the purpose of avoiding a dangerous situation, using sensors installed inside or outside a vehicle.

Sensors used in an ADAS may include, for example, a camera, an infrared sensor, an ultrasonic sensor, a light detection and ranging (lidar) and a radar. Among these sensors, the radar may stably measure an object in a vicinity of a vehicle regardless of a surrounding environment such as weather, in comparison to an optical-based sensor.

<CIT> discloses a two-dimensional Doppler synthetic aperture radar determining target azimuth angle and elevation angle. Based on the relation between Doppler, platform velocity and azimuth and elevation angles, an initial value of the elevation angle is determined assuming a zero azimuth angle. The azimuth and elevation angles are refined in an iterative process using a beamforming matrix.

<CIT> discloses a radar mounted on a movable vehicle. It detects stationary and moving targets by comparing their Doppler speed to the stationary object Doppler value calculated based on the speed of the radar device and the azimuth direction of a reflection relative to the moving direction of the radar. If an object detected as stationary in the current frame was a moving object to be followed by the system in the previous frame, then it is regarded as a moving object to be further followed enhancing thus detection accuracy.

<CIT> discloses a radar system in an autonomous vehicle. A computer located within the vehicle determines whether a detected target is desirable or undesirable and, based on this determination, a range of interest and an angle of interest is determined. After this determination, the radar is operated in FMCW mode operation with beam steering to avoid an undesired object and with determination of angle to a target object.

In one general aspect of the invention, a radar data processing method performed by a processor includes predicting an angle-of-interest (AOI) region based on a Doppler map generated from radar data, the Doppler map being a map indicating Doppler information of target points sensed by a radar sensor, wherein a horizontal axis of the Doppler map represents a Doppler value and a vertical axis of the Doppler map represents a distance to a target point, wherein predicting the AOI region comprises determining a steering angle from a radar data processing apparatus that includes the radar sensor to a target point shown in the Doppler map, based on a velocity of the radar data processing apparatus and a Doppler velocity of the target point and assuming that the target point is stationary, adjusting steering information based on the predicted AOI region, the steering information being used to identify the radar data, and determining direction-of-arrival (DOA) information corresponding to the radar data based on the adjusted steering information. The adjusting of the steering information comprises generating a steering vector of a dimension corresponding to a number of reception channels of the radar sensor, and adding one or more steering vectors within the AOI region to the steering information. The determining of the DOA information comprises searching for a steering vector matched to the sensed radar data among steering vectors included in the steering information, and determining a steering angle mapped to a found steering vector as DOA information corresponding to the radar data.

The adjusting of the steering information may include adding, to the steering information, a steering vector indicating phase information calculated to be represented by radar data within the predicted AOI region.

The adjusting of the steering information may include eliminating at least a portion of steering vectors corresponding to a region other than the predicted AOI region from the steering information.

The predicting of the AOI region may include determining the AOI region based on an angle formed between a movement direction of the radar data processing apparatus and a direction in which radar data reflected from a target point shown in the Doppler map is received.

The determining of the steering angle may include, in response to steering angles being calculated based on the Doppler velocity of the target point and the velocity of the radar data processing apparatus, excluding one steering angle from the steering angles.

The excluding of the steering angle from the steering angles may include selecting a steering angle within a field of view (FOV) of the radar sensor based on the FOV, and excluding a steering angle outside the FOV.

The radar data processing method may further include receiving a radar signal reflected from the target point using the radar sensor to view a side with respect to a movement direction of the radar data processing apparatus.

The excluding of the steering angle from the plurality of steering angles may include excluding one steering angle from the steering angles based on phase information measured from a radar signal reflected from the target point.

The adjusting of the steering information may include adding one or more steering vectors calculated based on an angular resolution designated for the AOI region to the steering information.

The predicting of the AOI region may include determining the AOI region based on a distance to a target point shown in the Doppler map and an angle formed between a movement direction of the radar data processing apparatus and a direction in which a signal reflected from the target point is received.

The predicting of the AOI region may include dynamically adjusting any one or any combination of a location and a size of the AOI region and a number of AOI regions.

The radar data processing method may further include generating a radar scan image for the radar sensor based on the DOA information.

The radar data processing method may further include generating a surrounding map of the radar data processing apparatus based on radar scan images generated for each of a plurality of radar sensors used to sense the radar data.

The predicting of the AOI region may include generating the Doppler map for the radar sensor based on a frequency difference between a signal radiated by a radar sensor used to sense the radar data and a reflected signal.

In another general aspect of the invention, a radar data processing apparatus includes a radar sensor configured to sense radar data, and a processor configured to predict an AOI region based on a Doppler map generated from the radar data, the Doppler map being a map indicating Doppler information of target points sensed by the radar sensor, wherein a horizontal axis of the Doppler map represents a Doppler value and a vertical axis of the Doppler map represents a distance to a target point, wherein predicting the AOI region comprises determining a steering angle from the radar data processing apparatus to a target point shown in the Doppler map, based on a velocity of the radar data processing apparatus and a Doppler velocity of the target point and assuming that the target point is stationary, to adjust steering information based on the predicted AOI region, the steering information being used to identify the radar data, and to determine DOA information corresponding to the radar data based on the steering information. Adjusting the steering information comprises: generating a steering vector of a dimension corresponding to a number of reception channels of the radar sensor, and adding one or more steering vectors within the AOI region to the steering information. Determining the DOA information comprises: searching for a steering vector matched to the sensed radar data among steering vectors included in the steering information, and determining a steering angle mapped to a found steering vector as DOA information corresponding to the radar data.

Generating the surrounding map may include converting information on the target point to coordinates and updating the surrounding map based on the coordinates.

<FIG> illustrates an example of a recognition of a surrounding environment using a radar data processing method.

An apparatus <NUM> for processing radar data (hereinafter, referred to as a "radar data processing apparatus <NUM>") detects an object <NUM> located in front of a vehicle, which is the radar data processing apparatus <NUM>, using a sensor. For example, a sensor to detect an object includes, for example, an image sensor or a radar sensor, and is configured to detect a distance to the object <NUM>.

In <FIG>, a sensor is a radar. The radar data processing apparatus <NUM> analyzes a radar signal received by a radar sensor <NUM> and detects a distance to the object <NUM>. The radar sensor <NUM> may be located inside or outside the radar data processing apparatus <NUM>. Also, the radar data processing apparatus <NUM> detects the distance to the object <NUM> based on data collected by other sensors (for example, an image sensor) as well as the radar signal received from the radar sensor <NUM>.

The radar data processing apparatus <NUM> is installed in a vehicle. The vehicle performs, for example, an adaptive cruise control (ACC) operation, an autonomous emergency braking (AEB) operation, and a blind spot detection (BSD) operation based on a distance to an object detected by the radar data processing apparatus <NUM>.

Also, the radar data processing apparatus <NUM> generates a surrounding map <NUM>, as well as detects a distance. The surrounding map <NUM> is a map that shows locations of targets present in the vicinity of the radar data processing apparatus <NUM>. For example, a target around the radar data processing apparatus <NUM> may be a dynamic object, such as, a vehicle or a person, or a static object (background), such as a guardrail or a traffic light.

To generate the surrounding map <NUM>, a single scan image method is used. The single scan image method is a method of acquiring a single scan image <NUM> from a sensor and generating the surrounding map <NUM> from the acquired scan image <NUM> using the radar data processing apparatus <NUM>. The single scan image <NUM> is an image generated from a radar signal sensed by a single radar sensor <NUM>, and has a relatively low resolution. The single scan image <NUM> is a radar scan image, and represents distances indicated by radar signals received at an arbitrary elevation angle by the radar sensor <NUM>. For example, in the single scan image <NUM> of <FIG>, a horizontal axis represents a steering angle of the radar sensor <NUM> and a vertical axis represents a distance from the radar sensor <NUM> to a target. However, a form of the single scan image is not limited to that of <FIG>, and the single scan image may be expressed in a different format depending on a design.

In the following description, a steering angle is an angle corresponding to a direction from a radar data processing apparatus to a target point. For example, the steering angle may be an angle between a movement direction of the radar data processing apparatus (for example, a vehicle) and a target point based on the radar data processing apparatus.

The radar data processing apparatus <NUM> acquires accurate information about a shape of a target based on a multi-radar map. The multi-radar map is generated from a combination of a plurality of radar scan images. For example, the radar data processing apparatus <NUM> generates the surrounding map <NUM> by spatially and temporally combining radar scan images acquired by a movement of the radar sensor <NUM>.

Radar data includes raw data sensed by the radar sensor <NUM>.

To generate the surrounding map <NUM>, direction-of-arrival (DOA) information is utilized. The DOA information is information indicating a direction in which a radar signal reflected from a target point is received. The DOA information is used to generate radar scan data and a surrounding map. To acquire high-resolution DOA information, the radar data processing apparatus <NUM> needs to receive radar signals for a larger number of angles and/or distances and process a phase. When a larger number of signals is received and a phase is processed in the radar sensor <NUM>, a number of operations and a time for the operations increase. Hereinafter, an example of acquiring high-resolution DOA information based on a relatively low operation load will be described.

<FIG> illustrates an example of a configuration of a radar data processing apparatus <NUM>.

Referring to <FIG>, the radar data processing apparatus <NUM> includes a radar sensor <NUM> and a processor <NUM>.

The radar sensor <NUM> senses radar data. For example, the radar sensor <NUM> externally radiates a radar signal and receives a signal corresponding to the radiated radar signal reflected from a target point. The radar sensor <NUM> includes an antenna corresponding to a plurality of reception (Rx) channels and signals received through the Rx channels have different phases based on directions in which the signals are received. An example of the radar sensor <NUM> will be further described below with reference to <FIG>.

The processor <NUM> generates a Doppler map based on a signal received by the radar sensor <NUM> and reflected from a target point. The Doppler map is a map indicating Doppler information of target points sensed by the radar sensor <NUM>. A horizontal axis of the Doppler map represents a Doppler value and a vertical axis of the Doppler map represents a distance to a target point. The Doppler value is, for example, a Doppler velocity that is a relative velocity (for example, a difference between a velocity of the target point and a velocity of the radar sensor <NUM>) of a target point with respect to the radar sensor <NUM>.

An example of a Doppler map will be described below with reference to <FIG>. For example, the processor <NUM> generates a Doppler map based on a frequency difference between a signal radiated by the radar sensor <NUM> and a reflected signal. However, a shape of a Doppler map is not limited thereto, and may vary depending on a design.

The processor <NUM> predicts an angle-of-interest region (hereinafter, referred to as an "AOI region") based on a Doppler map generated from radar data. The AOI region is a region corresponding to an angle of an object for which an inanimate object or a background is expected to exist. For example, the AOI region is represented by an arbitrary angle range. For example, when an object is expected to exist in a right direction at <NUM> degrees with respect to a movement direction of the radar data processing apparatus <NUM>, the AOI region is set to be in an angle range of <NUM> degrees to <NUM> degrees. However, the AOI region is not limited thereto and may vary depending on a design.

The processor <NUM> adjusts steering information based on the predicted AOI region. The steering information is used to identify radar data. For example, the steering information may be adjusted by adding a new steering vector to the original steering information, or by removing an existing steering vector. The processor <NUM> adjusts the steering information to include steering vectors concentrated in the AOI region, and updates the steering information to focus on the AOI region.

In the following description, steering information is information used to identify radar data and includes, for example, a set of steering vectors. Steering vectors included in the steering information may be referred to as "candidate steering vectors. " For example, when arbitrary radar data is assumed to be received at a predetermined angle, a steering vector includes phase information calculated to be included in the radar data. When a vector including phase information of sensed radar data is a radar vector, a steering vector determined to be matched to the radar vector among candidate steering vectors included in steering information is referred to as a "target steering vector.

Phase information of radar data indicates a phase difference between a reference phase and a phase of a signal received through each of a plurality of Rx channels included in the radar sensor <NUM>. The reference phase may be an arbitrary phase, or may be set as a phase of one of the plurality of Rx channels. The processor <NUM> generates a radar vector of a dimension corresponding to a number of Rx channels of the radar sensor <NUM> based on radar data. For example, when a radar sensor includes four Rx channels, the processor <NUM> generates a four-dimensional radar vector including a phase value corresponding to each Rx channel. A phase value corresponding to each Rx channel is a numerical value representing the above-described phase difference.

An example in which the radar sensor <NUM> includes one transmission (Tx) channel and four Rx channels is described below. A radar signal radiated through the TX channel is reflected from a target point, and radar signals received through the four RX channels are received at different angles for each channel. The radar sensor <NUM> generates a radar vector including phase values for each of the four RX channels from radar data. The processor <NUM> identifies a target steering vector having the most similar phase value to phase information of the radar vector among a plurality of candidate steering vectors, and determines an Rx direction indicated by the identified target steering vector as DOA information.

The processor <NUM> determines a direction of a sensed target point with respect to the radar data processing apparatus <NUM> based on steering information, as described above.

<FIG> illustrates an example of a configuration of a radar sensor <NUM>.

The radar sensor <NUM> radiates a signal through an antenna <NUM> and receives a signal through the antenna <NUM>. The radar sensor <NUM> is, for example, an millimeter wave (mmWave) radar, and is configured to measure a distance to an object by analyzing a change in a signal waveform and a time of flight (TOF) that a radiated electric wave returns after hitting an object. The radar sensor <NUM> is implemented as, for example, a frequency-modulated continuous-wave radio detection and ranging (FMCW radar).

A chirp transmitter <NUM> generates a frequency modulated (FM) signal <NUM> by modulating a frequency of a chirp signal <NUM>. The chirp signal <NUM> is a signal having an amplitude linearly increasing or decreasing over time. For example, the chirp transmitter <NUM> generates the FM signal <NUM> with a frequency corresponding to an amplitude of the chirp signal <NUM>. For example, as shown in <FIG>, the FM signal <NUM> has a waveform of a gradually increasing frequency in an interval in which the amplitude of the chirp signal <NUM> increases, and has a waveform of a gradually decreasing frequency in an interval in which the amplitude of the chirp signal <NUM> decreases. The chirp transmitter <NUM> transfers the FM signal <NUM> to a duplexer <NUM> of the radar sensor <NUM>.

The duplexer <NUM> determines a transmission path and a reception path of a signal through the antenna <NUM>. For example, while the radar sensor <NUM> is radiating the FM signal <NUM>, the duplexer <NUM> forms a signal path from the chirp transmitter <NUM> to the antenna <NUM>, transfers the FM signal <NUM> to the antenna <NUM> through the formed signal path, and externally radiates the FM signal <NUM>.

When the radar sensor <NUM> currently receives a signal reflected from an object, the duplexer <NUM> forms a signal path from the antenna <NUM> to a spectrum analyzer <NUM>. The antenna <NUM> receives a signal that is reflected and returned after a radiated signal arrives at an obstacle, and the radar sensor <NUM> transfers the reflected signal through the signal path from the antenna <NUM> to the spectrum analyzer <NUM>.

A frequency mixer <NUM> demodulates the received signal to a linear signal (for example, an original chirp signal) before a frequency modulation. An amplifier <NUM> amplifies an amplitude of the demodulated linear signal.

The spectrum analyzer <NUM> compares the radiated chirp signal <NUM> to a signal <NUM> that is reflected from an object and that is returned. The spectrum analyzer <NUM> detects a frequency difference between the radiated chirp signal <NUM> and the reflected signal <NUM>. The frequency difference between the radiated chirp signal <NUM> and the reflected signal <NUM> indicates a constant difference during an interval in which an amplitude of the radiated chirp signal <NUM> linearly increases along a time axis of a graph <NUM> of <FIG>, and is proportional to a distance between the radar sensor <NUM> and the object. Thus, the distance between the radar sensor <NUM> and the object is derived from the frequency difference between the radiated chirp signal <NUM> and the reflected signal <NUM>. The spectrum analyzer <NUM> transmits analyzed information to a processor of a radar data processing apparatus.

For example, the spectrum analyzer <NUM> calculates the distance between the radar sensor <NUM> and the object using Equation <NUM> shown below.

In Equation <NUM>, R denotes the distance between the radar sensor <NUM> and the object, and c denotes a velocity of light. Also, T denotes a duration of an interval in which the radiated chirp signal <NUM> increases. fb denotes the frequency difference between the radiated chirp signal <NUM> and the reflected signal <NUM> at an arbitrary point in time within an increase interval, and is referred to as a "beat frequency. " B denotes a modulated bandwidth. For example, the beat frequency fb is derived using Equation <NUM> shown below.

In Equation <NUM>, fb denotes the beat frequency, and td denotes a time difference (for example, a delay time) between a point in time at which the chirp signal <NUM> is radiated and a point in time at which the reflected signal <NUM> is received.

For example, a plurality of radar sensors is installed at different locations of a vehicle, and the radar data processing apparatus calculates relative velocities, directions, and distances to target points with respect to all directions of the vehicle, based on information sensed by the plurality of radar sensors. The radar data processing apparatus is installed in the vehicle. The vehicle provides various functions, for example, an ACC, a BSD, and a lane change assistance (LCA), which are helpful for driving, based on information obtained based on information collected by the radar sensors.

Each of the plurality of radar sensors externally radiates a chirp signal after frequency modulation, and receives a signal reflected from a target point. The processor of the radar data processing apparatus determines a distance from each of the plurality of radar sensors to a target point from a frequency difference between the radiated chirp signal and the received signal.

<FIG> is a flowchart illustrating an example of a radar data processing method.

Referring to <FIG>, in operation <NUM>, a radar data processing apparatus generates a Doppler map from sensed radar data, and predicts an AOI region based on the generated Doppler map. An example of predicting an AOI region will be further described below with reference to <FIG>.

In operation <NUM>, the radar data processing apparatus adjusts, based on the predicted AOI region, steering information used to identify the radar data. An example of adjusting steering information will be further described below with reference to <FIG> and <FIG>.

In operation <NUM>, the radar data processing apparatus determines DOA information based on the adjusted steering information.

The steering information is, for example, a set of a plurality of candidate steering vectors that are set and stored in advance, and eigenvalues are one-to-one mapped to the candidate steering vectors. For example, when the plurality of stored candidate steering vectors have phase information and when an eigenvalue mapped to each of the candidate steering vectors is a steering angle, the radar data processing apparatus determines a target steering vector corresponding to a radar vector of received radar data among the plurality of stored candidate steering vectors. The radar data processing apparatus outputs a steering angle mapped to the determined target steering vector.

An operation of determining the target steering vector includes, for example, determining, as a target steering vector, a steering vector (for example, a steering vector with a smallest Euclidean distance from the radar vector) with a smallest difference from the radar vector among the plurality of stored candidate steering vectors. Also, the operation of determining the target steering vector includes determining, as a target steering vector, a candidate steering vector having a most similar parameter to a predetermined parameter among several parameters of the radar vector. In addition, the operation of determining the target steering vector is implemented using various schemes.

The radar data processing apparatus determines a steering angle mapped to the determined target steering vector as DOA information corresponding to the radar data.

When a number of candidate steering vectors included in the steering information increases, a steering angle indicated by a candidate steering vector is subdivided. Thus, the radar data processing apparatus determines, as the DOA information, a value of a relatively high angular resolution.

<FIG> is a flowchart illustrating an example of processing DOA information.

A radar data processing apparatus processes DOA information by applying a multiple signal classification (MUSIC) algorithm to radar data.

Referring to <FIG>, in operation <NUM>, the radar data processing apparatus calculates a sample covariance matrix. For example, the radar data processing apparatus calculates the sample covariance matrix based on a result obtained by sampling a radar signal received by an individual Rx channel of a radar sensor.

In operation <NUM>, the radar data processing apparatus performs an eigen decomposition. For example, the radar data processing apparatus calculates eigenvalues and eigenvectors by performing an eigen decomposition of the above-described sample covariance matrix.

In operation <NUM>, the radar data processing apparatus calculates a noise covariance matrix. For example, the radar data processing apparatus divides the sample covariance matrix into a signal component and a noise component.

In operation <NUM>, the radar data processing apparatus calculates a spatial spectrum. The radar data processing apparatus forms the spatial spectrum based on the noise covariance matrix, and acquires DOA information by searching for a peak.

For example, a resolution of a surrounding map is proportional to an algorithm processing time for acquisition of the DOA information. When a resolution increases, an amount of time used to calculate DOA information in operation <NUM> increases.

However, the above-described MUSIC algorithm is merely an example, and other algorithms may also be applied to radar data depending on a design. For example, conventional digital beamforming (CDBF), Bartlett, or minimum variance distortionless response (MVDR) may be used.

<FIG> illustrates an example of a resolution in processing of DOA information.

<FIG> illustrates a sensing result based on steering information for different resolutions of an object <NUM>. An individual space of a grid pattern of <FIG> corresponds to a candidate steering vector included in steering information. When a number of steering vectors included in steering information increases, a degree of precision of identification of a direction in which a signal is received by a radar data processing apparatus increases. Thus, a sensing result of a higher resolution is acquired.

A left portion of <FIG> illustrates target points <NUM> sensed based on steering information with a relatively high resolution. A middle portion of <FIG> illustrates target points <NUM> sensed based on steering information with a medium resolution. A right portion of <FIG> illustrates target points <NUM> sensed based on steering information with a relatively low resolution. In an example, when a resolution of steering information increases, a density increases, that is, a number of candidate steering vectors included in the steering information increases, which leads to acquisition of an accurate image. However, a computational complexity increases. In another example, when the resolution of the steering information decreases, the density decreases, that is, the number of candidate steering vectors in the steering information decreases, which leads to acquisition of an inaccurate image. However, the computational complexity decreases.

A radar data processing apparatus performs a method of detecting an object <NUM> from an important region, with a reduced computational complexity and a relatively high resolution. Hereinafter, an example of an operation of the radar data processing apparatus to acquire an image having an increased resolution, with a relatively low computational complexity, based on steering information including candidate steering vectors focused on an AOI region in which the object <NUM> is expected to exist, will be described with reference to <FIG>.

<FIG> and <FIG> illustrate an example of a process of processing radar data.

Referring to <FIG>, in operation <NUM>, a radar data processing apparatus detects a distance to a target point. For example, the radar data processing apparatus processes a radar signal, and identifies a distance to a target point from which the radar signal is reflected.

In operation <NUM>, the radar data processing apparatus performs a DOA focusing. The radar data processing apparatus locally increases a resolution of a radar sensor by focusing on a predicted AOI region. The radar data processing apparatus adds a candidate steering vector corresponding to an AOI region to steering information. In operation <NUM>, the radar data processing apparatus generates a Doppler map. The radar data processing apparatus generates a Doppler map based on a frequency difference between a radiated signal and a reflected signal. The radar data processing apparatus determines distances to target points and Doppler velocities of the target points from radar data, to generate a Doppler map. In operation <NUM>, the radar data processing apparatus predicts an AOI region. The radar data processing apparatus determines an AOI region based on an angle formed between a movement direction of the radar data processing apparatus with a radar sensor and a direction in which radar data reflected from a target point shown in the Doppler map is received.

For example, the radar data processing apparatus adds a candidate steering vector corresponding to an optimal AOI region to steering information every time frame, to efficiently acquire DOA information, which will be further described below.

In operation <NUM>, the radar data processing apparatus estimates DOA information. For example, the radar data processing apparatus identifies radar data of each target point based on adjusted steering information. The radar data processing apparatus identifies a target steering vector matched to radar data from steering information including a candidate steering vector focused on an AOI region. The radar data processing apparatus determines a steering angle corresponding to the identified target steering vector as DOA information for the radar data. For example, the radar data processing apparatus estimates DOA information using an MUSIC algorithm, an MVDR algorithm, or estimation of signal parameters via rotational invariance technique (ESPRIT). The radar data processing apparatus identifies a target steering vector matched to a radar vector of sensed radar data from steering information and determines a steering angle corresponding to the identified target steering vector as DOA information.

In operation <NUM>, the radar data processing apparatus generates a map. For example, the radar data processing apparatus generates a surrounding map based on DOA information determined for radar data. For example, in operation <NUM>, the radar data processing apparatus converts acquired information on a target point (for example, a distance to a target point, or DOA information for the target point) to coordinates. The radar data processing apparatus uses, for example, a constant false alarm rate (CFAR) detection scheme, or a Max-Op. In operation <NUM>, the radar data processing apparatus updates a surrounding map based on the coordinates. For example, the radar data processing apparatus generates a radar scan image for the radar sensor based on DOA information. The radar data processing apparatus generates a surrounding map of the radar data processing apparatus based on radar scan images generated for each of a plurality of radar sensors.

Also, although not shown in <FIG>, the radar data processing apparatus selects a target point in operation <NUM>, as shown in <FIG>. The radar data processing apparatus selects a target point to be applied to a generation of a map among target points from which the DOA information is estimated in operation <NUM>. In an example, the radar data processing apparatus selects a target point within a field of view (FOV) of the radar sensor. The radar data processing apparatus excludes a target point outside the FOV from operation <NUM>. In another example, when a similarity between DOA information of two target points is greater than or equal to a threshold similarity, the radar data processing apparatus selects one of the two target points and excludes the other, because when the DOA information of the two target points is identical or very similar to each other, the two target points are substantially the same point. Thus, due to a generation of a map based on the same target point, an operation load of the radar data processing apparatus increases, but a resolution is not increased.

Hereinafter, an example of determining the AOI region of operation <NUM> will be described with reference to <FIG>.

<FIG> illustrate an example of a Doppler map and an example of dynamically adjusting steering information corresponding to the Doppler map.

A radar data processing apparatus <NUM> determines an AOI region based on an angle formed between a movement direction of the radar data processing apparatus <NUM> and a direction in which radar data is received. The received radar data is data corresponding to a signal reflected from a target point shown in a Doppler map <NUM>.

The Doppler map <NUM> is a map representing Doppler information of target points sensed by a radar sensor <NUM>, and shows a Doppler value and a relative location of each target point based on a traveling direction of a vehicle. In the Doppler map <NUM>, a horizontal axis represents a Doppler value, and a vertical axis represents a distance (range) to a target point. The Doppler value is, for example, a Doppler velocity, and is a relative velocity to a target point based on the radar sensor <NUM>.

For example, <FIG> illustrates a situation in which a target A <NUM>, a target B <NUM> and a target C <NUM> are present around the radar data processing apparatus <NUM>. The target A <NUM> is located at ΘA based on the movement direction of the radar data processing apparatus <NUM>, the target B <NUM> is located at ΘB based on the movement direction of the radar data processing apparatus <NUM>, and the target C <NUM> is located at ΘC based on the movement direction of the radar data processing apparatus <NUM>.

<FIG> illustrates the Doppler map <NUM> generated based on radar data collected by the radar sensor <NUM> in the situation of <FIG>.

When results obtained as described above are mapped to the Doppler map <NUM>, the target A <NUM> has a Doppler velocity vA and is present at a point <NUM> corresponding to a range rA. The target B <NUM> has a Doppler velocity vB and is present at a point <NUM> corresponding to a range rB. The target C <NUM> has a Doppler velocity vC and is present at a point <NUM> corresponding to a range re.

The radar data processing apparatus <NUM> determines a steering angle for a target point from the Doppler map <NUM>. A steering angle for a target point detected from the Doppler map <NUM> is referred to as a "steering angle of interest. " A relationship among the movement velocity of the radar data processing apparatus <NUM>, a Doppler velocity of an individual target and a steering angle of interest is represented as shown in Equation <NUM> below.

In Equation <NUM>, vd denotes a Doppler velocity of a target, Θ denotes a steering angle of interest, and v denotes a velocity of a movement of the radar data processing apparatus <NUM> (for example, a vehicle). Thus, the radar data processing apparatus <NUM> determines a steering angle Θ of interest from the radar data processing apparatus <NUM> to a target point shown in the Doppler map <NUM>, based on a velocity of the radar data processing apparatus <NUM> and a Doppler velocity of the target point. For example, the steering angle Θ of interest is calculated using Equation <NUM> shown below.

Based on Equation <NUM>, the radar data processing apparatus <NUM> calculates the steering angle Θ of interest based on the Doppler velocity vd of the target and the velocity v of the movement of the radar data processing apparatus <NUM>.

The radar data processing apparatus <NUM> determines an AOI region of <FIG> based on a distance to a target point shown in the Doppler map <NUM> and an angle formed between the movement direction of the radar data processing apparatus <NUM> and a direction in which a signal reflected from the target point is received.

<FIG> illustrates an arrangement <NUM> based on ranges and steering angles of candidate steering vectors included in steering information. For example, <FIG> illustrates examples of AOI regions <NUM>, <NUM> and <NUM> predicted based on the Doppler map <NUM> of <FIG>. A size of Θ calculated from the Doppler map <NUM> is derived, but a sign (for example, + or -) is not limited, and accordingly the radar data processing apparatus <NUM> sets the AOI regions <NUM>, <NUM> and <NUM> to be symmetrical to each other based on a range axis as shown in <FIG>.

A point at which two straight lines of a grid of <FIG> intersect indicates that a candidate steering vector is located at an angle of the point. The radar data processing apparatus <NUM> determines the AOI regions <NUM>, <NUM> and <NUM> based on the range and the steering angle of interest calculated for a target point from the steering information using Equation <NUM> as described above.

Because the target A <NUM> of <FIG> is located on a central portion of the movement direction of the radar data processing apparatus <NUM>, a Doppler velocity vd of the target A <NUM> is equal to the velocity v of the movement of the radar data processing apparatus <NUM>. Thus, a steering angle ΘA of interest for the target A <NUM> may be "<NUM>. " As shown in <FIG>, the radar data processing apparatus <NUM> forms the AOI region <NUM> corresponding to the target A <NUM> based on the steering angle ΘA of interest. The radar data processing apparatus <NUM> adds, to steering information, a candidate steering vector mapped to a steering angle within the AOI region <NUM>.

Because the targets B <NUM> and C <NUM> deviate from the movement direction of the radar data processing apparatus <NUM>, Doppler velocities vd of the targets B <NUM> and C <NUM> are different from the velocity v of the movement of the radar data processing apparatus <NUM>. Thus, the radar data processing apparatus <NUM> acquires positive steering angles ΘB and ΘC of interest and negative steering angles ΘB and ΘC of interest for the targets B <NUM> and C <NUM> based on the movement direction of the radar data processing apparatus <NUM>. In <FIG>, the radar data processing apparatus <NUM> determines an AOI region corresponding to each of two steering angles of interest. For the target B <NUM>, the radar data processing apparatus <NUM> determines AOI regions <NUM> corresponding to both the positive steering angle ΘB of interest and the negative steering angle ΘB of interest. Also, for the target C <NUM>, the radar data processing apparatus <NUM> determines AOI regions <NUM> corresponding to both the positive steering angle ΘC of interest and the negative steering angle ΘC of interest.

A target point shown in the Doppler map <NUM> by the radar data processing apparatus <NUM> is assumed to be a static background. In an example, when a target point is actually a static background, the detected target point may be used to update a radar map. In another example, when a target point is a dynamic object instead of a static background, the dynamic object is naturally excluded from updating of a radar map because the dynamic object deviates from an AOI region based on a movement of the radar data processing apparatus <NUM>. Thus, in <FIG>, a Doppler velocity of an individual target is regarded as a relative velocity at which the radar data processing apparatus <NUM> approaches a stationary target.

<FIG> illustrate an example of determining an AOI region.

In an example, in response to a plurality of steering angles of interest being calculated based on a Doppler velocity and a velocity of a radar data processing apparatus <NUM>, the radar data processing apparatus <NUM> excludes a portion of the plurality of steering angles of interest. For example, the radar data processing apparatus <NUM> excludes a steering angle of interest outside an FOV of a radar sensor <NUM> based on the FOV, and selects a steering angle of interest within the FOV. The radar data processing apparatus <NUM> determines an AOI region based on the selected steering angle of interest.

<FIG> illustrates an example in which the radar sensor <NUM> is located obliquely to a longitudinal axis of a vehicle.

In <FIG>, the radar sensor <NUM> is installed on one side (for example, a left side) of the radar data processing apparatus <NUM> with respect to a movement direction of the radar data processing apparatus <NUM> to view the side. The radar data processing apparatus <NUM> receives, using the radar sensor <NUM>, a radar signal reflected from a target point.

In <FIG>, the radar data processing apparatus <NUM> generates a Doppler map <NUM>, similarly to that of <FIG>. The generated Doppler map <NUM> includes a point <NUM> corresponding to a target B <NUM>. The radar data processing apparatus <NUM> determines a steering angle ΘB of interest based on a Doppler velocity of the target B <NUM> and a velocity of a movement of the radar data processing apparatus <NUM>. Based on Equation <NUM> described above, the steering angle ΘB of interest for the target B <NUM> is represented by a positive value and a negative value. However, it is impossible to observe a positive steering angle of interest (for example, a right side of the radar data processing apparatus <NUM> of <FIG>) using the radar sensor <NUM> located as shown in <FIG>. Thus, the radar data processing apparatus <NUM> determines a negative value as the steering angle ΘB of interest for the target B <NUM>.

<FIG> illustrates an arrangement <NUM> based on ranges and steering angles of candidate steering vectors included in steering information. For example, <FIG> illustrates an AOI region determined based on the above-described steering angle ΘB of interest. Similar to <FIG>, in <FIG>, candidate AOI regions <NUM> and <NUM> are determined, and the radar data processing apparatus <NUM> excludes the AOI region <NUM> on the right side because the radar sensor <NUM> is installed on the left side.

The radar data processing apparatus <NUM> adds a candidate steering vector to a single AOI region, that is, the AOI region <NUM> determined for the target B <NUM> in the steering information. The radar data processing apparatus <NUM> excludes an addition of a candidate steering vector for the AOI region <NUM> corresponding to a positive steering angle of interest.

In another example, the radar data processing apparatus <NUM> excludes a portion of a plurality of steering angles of interest based on phase information measured from a radar signal reflected from a target point. For example, the radar data processing apparatus <NUM> determines whether the target point is located on a right side or a left side with respect to the movement direction of the data processing apparatus <NUM> based on a simplified phase comparison between radar data for the target point. The radar data processing apparatus <NUM> selects a portion of the plurality of steering angles of interest based on a side in which the target point is located. The radar data processing apparatus <NUM> determines an AOI region based on the selected portion of the steering angles of interest.

<FIG> illustrates an example of determining a resolution of a candidate steering vector added to an AOI region.

<FIG> is described based on the target C <NUM> of <FIG>. <FIG> illustrates an example of steering resolution configuration data <NUM> and steering information <NUM> generated based on the steering resolution configuration data <NUM> when a steering angle of interest is <NUM> degrees.

For example, a horizontal axis and a vertical axis of the steering resolution configuration data <NUM> represents an angle and an angular resolution, respectively. The steering resolution configuration data <NUM> indicates an angular resolution based on a steering angle corresponding to an individual target point. Also, the angular resolution corresponds to an angular difference between candidate steering vectors <NUM> within an AOI region. When the angular difference decreases, a density of the steering information <NUM> increases.

A radar data processing apparatus adds a predetermined number of candidate steering vectors <NUM> within the AOI region in the steering information <NUM>. For example, the radar data processing apparatus adds a number of candidate steering vectors <NUM> calculated based on an angular resolution designated for the AOI region to the steering information <NUM>.

The steering information <NUM> is a set of candidate steering vectors <NUM> with respect to an arbitrary distance. For example, the steering information <NUM> includes candidate steering vectors <NUM> that are spaced apart by the angular difference corresponding to the angular resolution indicated by the steering resolution configuration data <NUM>. Although <FIG> illustrates the steering information <NUM> in one dimension for convenience of description, examples are not limited thereto. The steering information <NUM> also includes candidate steering vectors <NUM> with different densities for each distance and for each steering angle.

The radar data processing apparatus determines a number of candidate steering vectors <NUM> added based on an angular difference from an AOI <NUM> within an AOI region, and an angular interval between candidate steering vectors <NUM>. For example, the radar data processing apparatus adds a larger number of candidate steering vectors <NUM> to a region close to a central portion of the AOI region. The radar data processing apparatus adds a smaller number of candidate steering vectors <NUM> to a region far away from the central portion of the AOI region. Thus, the steering information <NUM> includes candidate steering vectors <NUM> at a relatively high density in a region close to the AOI <NUM>, and includes candidate steering vectors <NUM> at a relatively low density in a region far away from the AOI <NUM>.

For the target C, because the angle of interest is <NUM> degrees, the steering resolution configuration data <NUM> is expressed in the same form as a resolution indicating line <NUM>. Thus, the radar data processing apparatus sets an angular interval to increase as a distance from an AOI increases.

Although a curved resolution indicating line is shown in <FIG>, a form of a resolution indicating line is not limited thereto. In <FIG>, the resolution indicating line <NUM> is shown as a downwardly concave curve that is symmetric about the AOI <NUM> and converges to a minimum value (for example, "<NUM>") near the AOI <NUM>, but examples are not limited thereto. For example, the resolution indicating line <NUM> may be a downwardly convex curve that is symmetric about the AOI <NUM> and converges to a minimum value (for example, "<NUM>") near the AOI <NUM>. Also, resolution indicating lines <NUM> are two straight lines symmetrical to each other about the AOI <NUM> while converging to a minimum value (for example, "<NUM>") near the AOI <NUM>. Although the resolution indicating lines <NUM> are symmetrical to each other about the AOI <NUM> as shown in <FIG>, examples are not limited thereto.

The resolution indicating line <NUM> is used to set an angular interval between candidate steering vectors included in the steering information <NUM>. The resolution indicating line <NUM> indicates an angular interval that decreases in a region close to the AOI <NUM> and an angular interval that increases in a region far away from the AOI <NUM>.

Thus, the radar data processing apparatus determines an angular interval between candidate steering vectors <NUM> within the AOI region based on the resolution indicating line <NUM>.

The steering resolution configuration data <NUM> includes resolution indicating lines for a plurality of targets sensed by an arbitrary radar sensor. The radar data processing apparatus determines a density of candidate steering vectors <NUM> for each steering angle with respect to the radar sensor by an overlapping of a plurality of resolution indicating lines. For example, when each of the plurality of resolution indicating lines individually indicates an angular interval for an arbitrary target point, the radar data processing apparatus determines an average of angular intervals as an angular resolution for the target point.

Also, the radar data processing apparatus determines a minimum interval threshold within the AOI region. For example, the radar data processing apparatus limits an angular interval between candidate steering vectors <NUM> near the AOI <NUM> within the AOI region to be greater than or equal to the minimum interval threshold, despite the resolution indicating lines <NUM>. The minimum interval threshold is a threshold indicating a minimum angular interval between candidate steering vectors <NUM>. For example, when the minimum interval threshold is set to "<NUM>," the radar data processing apparatus adds candidate steering vectors <NUM> at an interval of at least <NUM> degrees within the AOI region to the steering information <NUM>. Thus, the radar data processing apparatus may prevent an unnecessary operation by identifying radar data at a finer resolution than a required resolution.

The radar data processing apparatus determines a maximum interval threshold outside the AOI region. For example, the radar data processing apparatus limits an angular interval between candidate steering vectors <NUM> in a region (for example, <NUM> degrees, <NUM> degrees, -<NUM> degrees or -<NUM> degrees) far away from the AOI <NUM> (for example, <NUM> degrees for the target C) to be less than or equal to the maximum interval threshold, despite the resolution indicating lines <NUM>. The maximum interval threshold is a threshold indicating a maximum angular interval between candidate steering vectors <NUM>. For example, when the maximum interval threshold is set to "<NUM>," the radar data processing apparatus adds, to the steering information <NUM>, candidate steering vectors <NUM> at an interval less than or equal to <NUM> degrees with respect an entire sensing range of a radar sensor. Thus, even for regions other than the AOI region, the radar data processing apparatus may ensure a user's safety by identifying radar data at a resolution corresponding to a minimum degree of precision.

<FIG> illustrates an example of determined steering information.

A radar data processing apparatus dynamically adjusts any one or any combination of a location of an AOI region, a size of an AOI region, and a number of AOI regions. The location of the AOI region is defined by a candidate steering angle and a range in steering information. The size of the AOI region is determined as a circle around an AOI, but examples are not limited thereto. The AOI region corresponds to angles around the AOI with respect to a range corresponding to a target point. The number of AOI regions corresponds to a number of target points detected from a Doppler map.

For example, the radar data processing apparatus generates adaptive steering information <NUM> from default steering information <NUM>. The radar data processing apparatus changes a distribution of candidate steering vectors included in the default steering information <NUM> based on configuration data <NUM>, to generate the adaptive steering information <NUM>. For example, the radar data processing apparatus adjusts a number of candidate steering vectors added to an AOI region. In the configuration data <NUM>, a horizontal axis represents a number by which an FOV of a radar sensor is divided, and a vertical axis represents a steering angle. The configuration data <NUM> is merely an example, and examples are not limited thereto.

A point shown in the adaptive steering information <NUM> corresponds to a candidate steering vector. For example, a point shown at an arbitrary steering angle and an arbitrary range may be a candidate steering vector including phase information of a radar signal calculated to be received at the steering angle and the range. Points of <FIG> indicate candidate steering vectors. In an AOI region <NUM> of the adaptive steering information <NUM>, candidate steering vectors have a relatively high density.

The radar data processing apparatus adds a candidate steering vector to the AOI region. Also, the radar data processing apparatus eliminates at least a portion of candidate steering vectors corresponding to a region other than the predicted AOI region from steering information. Thus, the radar data processing apparatus further focuses on the AOI region. The radar data processing apparatus dynamically adjusts a resolution of a radar image based on the adaptive steering information <NUM> that includes candidate steering vectors densely distributed in the AOI region and candidate steering vectors sparsely distributed in the other regions.

The radar data processing apparatus increases a radar resolution for an AOI region in which a target is expected to exist, by dynamically adjusting candidate steering vectors included in steering information.

The radar data processing apparatuses <NUM>, <NUM> and <NUM>, the radar sensors <NUM> and <NUM>, <NUM> and <NUM>, other apparatuses, units, modules, devices, and other components described herein with respect to <FIG>, <FIG>, <FIG> and <FIG> are implemented by hardware components. Examples of hardware components that may be used to perform the operations described in this application where appropriate include 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 in this application. In other examples, one or more of the hardware components that perform the operations described in this application are implemented by computing hardware, for example, by one or more processors or computers. A processor or computer may be implemented by one or more processing elements, such as an array of logic gates, a controller and an arithmetic logic unit, a digital signal processor, a microcomputer, a programmable logic controller, a field-programmable gate array, a programmable logic array, a microprocessor, or any other device or combination of devices that is configured to respond to and execute instructions in a defined manner to achieve a desired result. In one example, a processor or computer includes, or is connected to, one or more memories storing instructions or software that are executed by the processor or computer. Hardware components implemented by a processor or computer may execute instructions or software, such as an operating system (OS) and one or more software applications that run on the OS, to perform the operations described in this application. The hardware components may also access, manipulate, process, create, and store data in response to execution of the instructions or software. For simplicity, the singular term "processor" or "computer" may be used in the description of the examples described in this application, but 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 another processor and another controller. One or more processors, or a processor and a controller, may implement a single hardware component, or two or more hardware components. A hardware component may have any one or more of different processing configurations, examples of which include a single processor, independent processors, parallel processors, single-instruction single-data (SISD) multiprocessing, single-instruction multiple-data (SIMD) multiprocessing, multiple-instruction single-data (MISD) multiprocessing, and multiple-instruction multiple-data (MIMD) multiprocessing.

The methods illustrated in <FIG>, <FIG> and <FIG> that perform the operations described in this application are performed by computing hardware, for example, by one or more processors or computers, implemented as described above executing instructions or software to perform the operations described in this application that are performed by the methods.

Instructions or software to control a processor or computer to implement the hardware components and perform the methods as described above are written as computer programs, code segments, instructions or any combination thereof, for individually or collectively instructing or configuring the processor or computer to operate as a machine or special-purpose computer to perform the operations performed by the hardware components and the methods as described above. In one example, the instructions or software include machine code that is directly executed by the processor or computer, such as machine code produced by a compiler. In another example, the instructions or software include higher-level code that is executed by the processor or computer using an interpreter. Programmers of ordinary skill in the art can readily write the instructions or software based on the block diagrams and the flow charts illustrated in the drawings and the corresponding descriptions in the specification, which disclose algorithms for performing the operations performed by the hardware components and the methods as described above.

The instructions or software to control a processor or computer to implement the hardware components and perform the methods as described above, and any associated data, data files, and data structures, are recorded, stored, or fixed in or on one or more non-transitory computer-readable storage media. Examples of a non-transitory computer-readable storage medium 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-ROMs, CD-Rs, CD+Rs, CD-RWs, CD+RWs, DVD-ROMs, DVD-Rs, DVD+Rs, DVD-RWs, DVD+RWs, DVD-RAMs, BD-ROMs, BD-Rs, BD-R LTHs, BD-REs, blue-ray or optical disk storage, hard disk drive (HDD), solid state drive (SSD), flash memory, a card type memory such as multimedia card micro or a card (for example, secure digital (SD) or extreme digital (XD)), magnetic tapes, floppy disks, magneto-optical data storage devices, optical data storage devices, hard disks, solid-state disks, and any other device that is configured to store the instructions or software and any associated data, data files, and data structures in a non-transitory manner and providing the instructions or software and any associated data, data files, and data structures to a processor or computer so that the processor or computer can execute the instructions.

Claim 1:
A radar data processing method performed by a processor, the method comprising:
predicting (<NUM>) an angle-of-interest, AOI, region based on a Doppler map generated from radar data, the Doppler map being a map indicating Doppler information of target points sensed by a radar sensor (<NUM>), wherein a horizontal axis of the Doppler map represents a Doppler value and a vertical axis of the Doppler map represents a distance to a target point;
wherein predicting the AOI region comprises determining a steering angle from a radar data processing apparatus (<NUM>) that includes the radar sensor (<NUM>) to a target point shown in the Doppler map, based on a velocity of the radar data processing apparatus (<NUM>) and a Doppler velocity of the target point and assuming that the target point is stationary;
adjusting (<NUM>) steering information based on the predicted AOI region, the steering information being used to identify the radar data; and
determining (<NUM>) direction-of-arrival, DOA, information corresponding to the radar data based on the adjusted steering information;
characterized in that adjusting the steering information comprises:
generating a steering vector of a dimension corresponding to a number of reception (Rx) channels of the radar sensor (<NUM>); and
adding one or more steering vectors within the AOI region to the steering information; and
in that determining the DOA information comprises:
searching for a steering vector matched to the sensed radar data among steering vectors included in the steering information; and
determining a steering angle mapped to a found steering vector as DOA information corresponding to the radar data.