CN114859337A - Data processing method and device, electronic equipment and computer storage medium - Google Patents
Data processing method and device, electronic equipment and computer storage medium Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
- G01S13/60—Velocity or trajectory determination systems; Sense-of-movement determination systems wherein the transmitter and receiver are mounted on the moving object, e.g. for determining ground speed, drift angle, ground track
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
- G01S13/581—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of interrupted pulse modulated waves and based upon the Doppler effect resulting from movement of targets
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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Abstract
The embodiment of the application provides a data processing method and device, electronic equipment and a computer storage medium. The data processing method comprises the following steps: periodically transmitting a detection signal through a radar carried by mobile equipment, and acquiring an echo signal generated by a reflection point of a target reflecting the detection signal when the detection signal irradiates a corresponding target; determining a frame range Doppler spectrum according to the echo signals received in a detection period; determining a stationary clutter cluster formed by reflection points which are stationary relative to the earth according to the distance from the reflection points indicated by the one-frame distance Doppler spectrum to the radar and the relative speed of the reflection points relative to the radar; and determining the driving speed of the mobile equipment relative to the ground according to the relative speed of the stationary reflecting points included in the stationary clutter cluster. The method has more accurate estimation of the running speed.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to a data processing method and device, electronic equipment and a computer storage medium.
Background
Currently, mobile devices are generally equipped with sensors (such as cameras, positioning modules, radars, etc.). Taking an intelligent driving vehicle as an example, the vehicle can detect the driving speed of the vehicle and other moving objects (pedestrians or vehicles), obstacles and the like around the vehicle, so as to assist or replace a driver to make a correct driving decision and improve the driving safety.
In the prior art, the running speed of the mobile equipment is detected by a plurality of sensors which work cooperatively, so that the running speed can be accurately measured. However, the types and the number of the sensors mounted on different mobile devices are different, and therefore, how to accurately measure the traveling speed of the mobile device by using fewer sensors is a problem to be solved by those skilled in the art.
Disclosure of Invention
In view of the above, embodiments of the present application provide a data processing scheme to at least partially solve the above problems.
According to a first aspect of embodiments of the present application, there is provided a data processing method, including: periodically transmitting a detection signal through a radar carried by mobile equipment, and acquiring an echo signal generated by a reflection point of a target reflecting the detection signal when the detection signal irradiates a corresponding target; determining a frame range Doppler spectrum according to the echo signals received in a detection period; determining stationary clutter cluster formed by the reflecting points which are stationary relative to the ground according to the distance from the reflecting points indicated by the one-frame distance Doppler spectrum to the radar and the relative speed of the reflecting points relative to the radar; and determining the driving speed of the mobile equipment relative to the ground according to the relative speed of the static reflection points included in the static clutter cluster.
According to a second aspect of embodiments of the present application, there is provided a data processing apparatus including: the acquisition module is used for periodically transmitting a detection signal through a radar carried by mobile equipment and acquiring an echo signal generated by a reflection point of a target reflecting the detection signal when the detection signal irradiates a corresponding target; the first determining module is used for determining a frame distance Doppler spectrum according to the echo signal received in a detection period; the second determination module is used for determining a stationary clutter cluster formed by reflecting points which are stationary relative to the ground according to the distance from the reflecting points indicated by the one-frame distance Doppler spectrum to the radar and the relative speed of the reflecting points relative to the radar; and the third determination module is used for determining the driving speed of the mobile equipment relative to the ground according to the relative speed of the static reflection points included in the static clutter cluster.
According to a third aspect of embodiments herein, there is provided an electronic device comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus; the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the corresponding operation of the data processing method according to the first aspect.
According to a fourth aspect of embodiments of the present application, there is provided a computer storage medium having stored thereon a computer program which, when executed by a processor, implements the data processing method according to the first aspect.
According to the data processing scheme provided by the embodiment of the application, when the driving speed of the mobile equipment is estimated, no other sensor is needed, a frame of range Doppler spectrum is obtained through the echo signal of the detection signal transmitted by the radar, the stationary reflection point which is relatively static to the ground is determined from the multiple reflection points according to the range Doppler spectrum, and the speed of the radar which is relatively large to the ground is estimated as the driving speed of the mobile equipment carrying the radar based on the relative speed between the stationary reflection point and the radar indicated on the range Doppler spectrum.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the embodiments of the present application, and other drawings can be obtained by those skilled in the art according to the drawings.
FIG. 1a is a flowchart illustrating steps of a data processing method according to an embodiment of the present application;
FIG. 1b is a diagram illustrating an example of a scenario in the embodiment shown in FIG. 1 a;
FIG. 1c is a range-Doppler spectrum for the embodiment shown in FIG. 1 a;
FIG. 2 is a flow chart illustrating steps of a data processing method according to a second embodiment of the present application;
FIG. 3a is a flowchart illustrating steps of a data processing method according to a third embodiment of the present application;
FIG. 3b is a diagram of a reference velocity dimension for the embodiment shown in FIG. 3 a;
FIG. 3c is a graphical illustration of the filtered-before and filtered travel speeds over time in the embodiment of FIG. 3 a;
FIG. 3d is a schematic illustration of acceleration over time in the embodiment of FIG. 3 a;
fig. 4 is a block diagram of a data processing apparatus according to a fourth embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application shall fall within the scope of protection of the embodiments in the present application.
The following further describes specific implementations of embodiments of the present application with reference to the drawings of the embodiments of the present application.
Example one
Referring to fig. 1a, a schematic flow chart illustrating steps of a data processing method according to a first embodiment of the present application is shown, where the method includes:
step S102: the method comprises the steps of periodically transmitting a detection signal through a radar carried by mobile equipment, and obtaining an echo signal generated by reflecting the detection signal by a reflection point of a target when the detection signal irradiates a corresponding target.
The mobile device in the present application may be a mobile device equipped with a sensor (such as a camera, a positioning module, or a radar), and includes an automobile, a robot, and the like. Taking a mobile device as an intelligent driving vehicle as an example, at least one radar is mounted on the intelligent driving vehicle. The radar may periodically emit an electromagnetic wave as a detection signal, and when a target (such as a pedestrian, a vehicle, a building, a tree, and the like) exists in a detection range of the radar, the target reflects the detection signal to form an echo signal. The location at which the target reflects the probe signal may be referred to as a reflection point.
The electromagnetic wave signals transmitted by the radar can be modulated into different frequencies, signal bandwidths and frame periods according to different requirements. For example, in an example, in order to meet the requirement of the detection range and reduce the data amount as much as possible to reduce the calculation load, for a 77GHz millimeter wave radar, the signal bandwidth of the detection signal may be modulated to be 0.75GHz, the sampling frequency is 10MHz, the frame period is 100ms, and the number of accumulation cycles is 256. The frame period of 100ms means that the time difference between two adjacent detection periods of the radar is 100ms, and the accumulation period number of 256 means that 256 detection signals are transmitted in one detection period to obtain corresponding echo signals.
Based on the above-mentioned detection signals, the corresponding range resolution of 0.2m, the maximum detection range of 50m, the velocity resolution of 0.23m/s, and the maximum detection velocity of 14.76m/s can be calculated.
Of course, in other examples, the detection signal may be appropriately modulated according to the required detection distance and the storable data amount based on the principle that the distance resolution and the speed resolution are positively correlated with the data amount and the signal bandwidth is negatively correlated with the detection distance, and the appropriate detection signal may be selected for detection.
In a detection period, a radar transmits a plurality of detection signals outwards at the initial stage, and if a target (such as a wall or a tree) exists in the detection range of the radar, reflection points on the wall or the tree reflect the detection signals to form echo signals. One or more reflection points may exist on one target, which is not limited by the embodiment.
Step S104: determining a frame range Doppler spectrum according to the echo signals received in a detection period.
Taking the foregoing example of transmitting 256 detection signals in one detection period, N echo signals reflected by different targets are received in the detection period, where N is greater than or equal to 1, and the maximum value of N is 256.
A one-frame range-doppler spectrum (denoted as RD spectrum) is obtained by processing the received echo signals. For example, a beat signal is determined from the received N echo signals and the corresponding probe signals. The range-doppler spectrum is obtained by processing (e.g., fast fourier transform) the beat signal. The load of computation and the memory requirements are lower due to the smaller number of beat signals.
The range-doppler spectrum includes a range dimension (i.e., abscissa), a velocity dimension (i.e., ordinate), and a plurality of points, which correspond to reflection points in the target and are used to indicate the range and relative velocity of the reflection points with respect to the radar. In addition, the color of the midpoint of the range-doppler spectrum is used to indicate the amplitude of the corresponding echo signal.
In this embodiment, the echo signals formed are different due to the different range, position and velocity of different targets relative to the radar on the mobile device. The range and azimuth of the target corresponding to the echo signal relative to the radar can be determined based on the time delay of the echo signal relative to the detection signal. The relative velocity of the target with respect to the radar may be determined based on the amplitude of the echo signal and the doppler frequency between the echo signal and the probe signal.
Doppler frequency is understood to mean the frequency difference between the echo signal and the probe signal, for example, when the radar transmits a probe signal (e.g. a pulse wave) of a fixed frequency to scan a space, such as when a target is encountered, the frequency difference between the frequency of the echo signal reflected by the target and the frequency of the transmitted probe signal occurs, which is caused by the relative motion between the target and the radar.
According to the magnitude of the Doppler frequency, the radial motion speed of the target relative to the radar can be determined. According to the time difference between the emission time of the detection signal and the receiving time of the echo signal, the distance of the measured target relative to the radar can be determined. The Doppler frequency spectral line of the target is detected by a frequency filtering method, the spectral line of the interference clutter is filtered, the radar can distinguish the echo signal corresponding to the target from the strong clutter, and therefore the pulse Doppler radar has stronger clutter interference resistance than a common radar and can detect the moving target hidden in the environment.
Based on the foregoing principle, the distance and relative speed of the corresponding target with respect to the radar can be determined based on the frequency and phase of the beat signal, and the like.
Generally, targets in the detection range of the radar include noise targets such as air, rain, snow, sea waves, clutter and the like, and reflection points formed by corresponding to the noise targets are marked as noise reflection points, and due to insufficient reflection capability of the corresponding noise targets, the amplitude of reflected echo signals is low, and the reflected echo signals are dark in color in a range-doppler spectrum.
The reflection points formed by corresponding actual targets are marked as candidate reflection points, and the candidate reflection points have better reflection capability of the corresponding actual targets, so that the amplitude of the reflected echo signal is higher, and the color in the range Doppler is brighter.
Step S106: and determining a stationary clutter cluster formed by the reflecting points which are relatively geostationary according to the distance from the reflecting points indicated by the one-frame range Doppler spectrum to the radar and the relative speed of the reflecting points relative to the radar.
When estimating the traveling speed of the mobile device relative to the earth, the traveling speed of the radar relative to a stationary object located immediately in front of the radar can be estimated as the traveling speed of the mobile device relative to the earth, with the stationary object fixed on the earth and located immediately in front of the radar as a reference.
In order to prevent the targets from adversely affecting the speed estimation, a stationary clutter cluster formed by reflection points that are stationary relative to the earth may be determined based on the distance from each reflection point indicated by the range-doppler spectrum to the radar and the relative speed with respect to the radar.
One possible way to determine stationary clutter clusters may be: and (4) screening out reflection points which have consistent relative speeds and continuous distances from the radar from the range-Doppler spectrum to form the stationary clutter cluster. The principle of doing so is: the detection period corresponding to one frame distance from the doppler spectrum is very short (for example, 100ms in this embodiment), so the moving speed of the mobile device is considered to be substantially constant within the time range corresponding to one frame distance from the doppler spectrum, that is, the relative speed of the stationary reflection point and the radar in one frame distance from the doppler spectrum is unchanged or slightly changed, and since the mobile device is in continuous motion, the distance from the stationary reflection point to the radar is continuously changed.
Step S108: and determining the driving speed of the mobile equipment relative to the ground according to the relative speed of the static reflection points included in the static clutter cluster.
In one possible approach, to ensure accuracy of the estimation of the running speed, an average value may be calculated as the estimated running speed from the relative speeds of the stationary reflection points. Of course, the driving speed may be determined in other manners in other feasible manners, and the embodiment is not limited to this.
The following describes the driving speed estimation process with reference to a specific usage scenario: as shown in fig. 1b, in the present usage scenario, taking the case that a radar is installed on the vehicle as an example, the radar may be a 77GHz millimeter wave radar, the radar has 1 transmit and 4 receive antennas, and the mobile device installed on the radar is a smart driving vehicle, which is installed on the front bumper of the vehicle.
During the running of the vehicle, the radar periodically emits a probe signal. For example, if the frame period is 100ms and the accumulation period is 256, 256 electromagnetic wave pulses need to be transmitted at the initial stage of 100ms to form 256 detection signals. The detection signal is a linear frequency modulation sawtooth wave signal, the signal bandwidth is 0.75GHz, and the sampling rate is 10 MHz.
After the radar receives the echo signal corresponding to the detection signal, the corresponding beat signal is determined according to the detection signal and the echo signal, so that the data storage capacity can be reduced under the condition of not losing the information of relative speed, relative distance and azimuth angle, and the load on a storage space is reduced.
A one-frame range doppler spectrum corresponding to the detection period is obtained by processing (e.g., fast fourier transform) the beat signal, as shown in fig. 1 c. The abscissa of the range-doppler spectrum is the relative distance, the ordinate is the relative velocity, the white point in fig. 1c corresponds to the reflection point of the actual target, and the gray point corresponds to the reflection point of the noise target.
After a frame of range-doppler spectrum is obtained, according to the distance (noted as the relative distance) from the reflection point indicated in the range-doppler spectrum to the radar, the relative speed between the reflection point and the radar, and the amplitude of the echo signal, static reflection points which are positioned right in front of the radar and are relatively static to the ground are screened out from the reflection points, and according to the relative speed of the static reflection points, the speed of the radar relative to the static reflection points is determined, so that the traveling speed of the vehicle relative to the ground is estimated.
Through the embodiment, when the driving speed of the mobile equipment is estimated, no other sensor is needed to be additionally used, a frame of range Doppler spectrum is obtained through the echo signal of the detection signal transmitted by the radar, the stationary reflection point which is relatively static to the ground is determined from the multiple reflection points according to the range Doppler spectrum, and the speed of the radar which is relatively large to the ground is estimated as the driving speed of the mobile equipment carrying the radar based on the relative speed between the stationary reflection point and the radar indicated on the range Doppler spectrum. Further, if the mobile device is an autonomous moving vehicle, robot, or the like, the surrounding pedestrians may be alerted based on the traveling speed in the form of voice, light, text display on the vehicle body, projected text display, or the like.
The data processing method of the present embodiment may be performed by any suitable electronic device having data processing capabilities, including but not limited to: a server, a mobile terminal (such as a tablet computer, a mobile phone and the like), a PC and the like.
Example two
Referring to fig. 2, a schematic step flow diagram of a data processing method according to a second embodiment of the present application is shown.
In the embodiment, the data processing method can be executed by a chip with data processing capability provided on the mobile device, so as to realize the estimation of the running speed. Or the data processing method may be performed by other devices having data processing capabilities in data connection with the mobile device.
The data processing method includes the aforementioned steps S102 to S108. Wherein, step S104 includes the following sub-steps:
substep S1041: and determining a beat signal according to the echo signal and the detection signal.
After the echo signal is received by the receiving antenna, the corresponding beat signal can be determined according to the echo signal and the detection signal.
For example, a high-frequency chirp sawtooth signal generated by a radar transmitter is directly mixed with a received echo signal reflected by a reflection point of a target, and because a time difference exists between a detection signal and the echo signal, the frequency and the phase of a beat signal obtained after mixing are related to the distance from the target to the radar, the relative speed between the target and the radar, and an azimuth angle, and then the distance from the reflection point on the target to the radar, the relative speed between the target and the radar, and the like can be obtained by processing the beat signal.
Substep S1042: the beat signal is fast fourier transformed (i.e., FFT) in both the fast and slow time dimensions to obtain range-doppler spectra.
In one example, the detection period of the radar may be referred to as a frame period, for example, the travel speed of the mobile device is detected every 100ms, and then one 100ms may be regarded as one detection period. In the detection period, the radar transmits 256 detection signals, the echo signals of each detection signal are stored in one row, the detection signals transmitted at different moments are stored in different rows, one echo signal (namely one row) is a fast time dimension, and different echo signals (namely multiple rows) are slow time dimensions.
In this embodiment, since the number of detection signals (which may also be referred to as a cycle number) is 256, the range-doppler spectrum obtained after performing fast fourier transform on the fast time dimension and the slow time dimension is 128 × 512-dimensional range-doppler spectrum.
In this way, a range-doppler spectrum of one frame can be obtained quickly, and the driving speed of the mobile device can be estimated according to the range-doppler spectrum in the subsequent steps. The driving speed estimation is carried out in the mode, other sensors are not needed, the driving speed of the mobile equipment can be accurately estimated by processing the echo signals of the detection signals transmitted by the radar, the calculation amount of the obtained distance Doppler spectrum is small, and the calculation speed is high.
The data processing method of the present embodiment may be performed by any suitable electronic device having data processing capabilities, including but not limited to: servers, mobile terminals (such as tablet computers, mobile phones and the like), PCs and the like.
EXAMPLE III
Referring to fig. 3a, a schematic flow chart illustrating steps of a data processing method according to an embodiment of the present application is shown.
In the present embodiment, the data processing method includes the aforementioned steps S102 to S108. Step S104 can be implemented in the manner of the first embodiment or the second embodiment. Step S106 includes the following substeps:
substep S1061: at least one candidate reflection point other than a noise reflection point is screened out from the plurality of reflection points indicated by the range-doppler spectrum.
In the range-doppler spectrum, the amplitudes of the echo signals of the reflection points corresponding to different points are different, for example, the amplitude of the echo signal generated by the reflection point of the noise target is usually much smaller than the amplitude of the echo signal generated by the reflection point of the actual target, so that the candidate reflection point corresponding to the actual target can be screened accordingly.
When the reflecting points are screened, due to the fact that characteristics of noise such as rain, snow, sea waves, air, clutter interference and the like are different, a constant false alarm detection algorithm which is appropriate to characteristics can be adopted to screen out possible candidate reflecting points, and therefore the static reflecting points can be determined from the candidate reflecting points in the follow-up process. The constant false alarm detection algorithm can be CA-CFAR, GO-CFAR, SO-CFAR, OS-CFAR, etc.
In the urban road environment of the embodiment, candidate reflection points are screened out in the distance dimension and the speed dimension respectively through a specific constant false alarm detection algorithm (for example, OS-CFAR). The obtained candidate reflection points may be represented as discrete or continuous points.
Specifically, the sub-step S1061 includes the following processes:
procedure a 1: and acquiring a set protection threshold value and a reference threshold value according to the total number of the velocity dimensions of the range-Doppler spectrum.
The protection threshold value and the reference threshold value are used for determining screening conditions corresponding to the candidate reflecting points when the candidate reflecting points are determined.
Taking a 128-dimensional velocity dimension as an example, due to different moving speeds of objects such as pedestrians, vehicles, and fixed objects, the velocity dimensions of different types of objects distributed in the range-doppler spectrum may be relatively far apart, while the moving speeds of objects of the same type may be relatively close, and thus may be distributed in adjacent velocity dimensions or the same velocity dimension in the range-doppler spectrum.
For example, in vehicles, pedestrians, and stationary objects, the vehicle may move at the same speed as the radar, and thus the vehicle is distributed in the range-doppler spectrum in the speed dimension with a relative speed of 0. The relative velocity of the fixture to the radar will be large, distributed in-5 and adjacent velocity dimensions.
Since the stationary reflection points may be distributed in different adjacent velocity dimensions, a protection threshold value needs to be set in order to accurately screen out the candidate reflection points and prevent the candidate reflection points from being missed. The reference threshold is used to determine the speed dimension used in the screening. The guard threshold and the reference threshold may be determined on a case-by-case basis. For example, the protection threshold value may be 2 and the reference threshold value may be 5.
Procedure a 2: and determining at least one candidate reflection point according to the protection threshold value, the reference threshold value and the amplitude of the echo signal corresponding to the plurality of reflection points indicated by the range-Doppler spectrum.
The implementation of process a2 is illustratively described below in conjunction with fig. 3 b. For any reflection point indicated in the range-doppler spectrum, it has a corresponding amplitude.
In the screening, the following actions may be performed for each reflection point indicated by the range-doppler spectrum, thereby determining whether it is a candidate reflection point.
Process a2 may be implemented as: aiming at a plurality of reflection points indicated by the range-Doppler spectrum, determining excluded speed dimensions according to the speed dimensions and the protection threshold values of the current reflection points; determining the speed boundary of the current reflection point according to the excluded speed dimension; determining the reference speed dimension of the current reflection point according to the speed boundary and the reference threshold value; and determining the screening condition of the current reflecting point according to the amplitude values of the echo signals of the reflecting points indicated in the reference speed dimension, and determining whether the current reflecting point is a candidate reflecting point according to the screening condition and the amplitude value of the echo signal of the current reflecting point.
Taking the point a shown in fig. 3b as an example, if the protection threshold is 2 and the reference threshold is 5, taking the point a as the current transmission point, recording the speed dimension of the point a as the speed dimension a, and determining the excluded speed dimension according to the speed dimension of the point a and the protection threshold, that is, excluding 2 speed dimensions adjacent above the speed dimension a and 2 speed dimensions adjacent below the speed dimension a (4 speed dimensions in total). Dashed line B1 as shown in fig. 3B serves as the upper velocity boundary and dashed line B2 as shown in fig. 3B serves as the lower velocity boundary. If the speed dimension a is less than 2 below adjacent speed dimensions, all the below speed dimensions can be directly excluded, and if the above adjacent speed dimension is less than 2 above adjacent speed dimensions, all the above speed dimensions can be excluded.
And determining the reference speed dimension corresponding to the point A according to the determined upper and lower speed boundaries and the reference threshold value. For example, if the reference threshold value is 5, then the upper speed boundary takes the adjacent 5 speed dimensions upward as the upper reference speed dimension (the areas shown in fig. 3B from B1 to C1), and the lower speed boundary takes the adjacent 5 speed dimensions downward as the lower reference speed dimension (the areas shown in fig. 3B from B2 to C2).
And determining the screening condition of the current reflecting point according to the amplitudes of the echo signals of the plurality of reflecting points indicated in the reference speed dimension. For example, the average value of the amplitudes is calculated from the amplitudes of the echo signals of the respective reflection points indicated in the reference velocity dimension, and the average value is used as the screening condition.
According to the screening condition, if the amplitude of the point A is larger than or equal to the mean value, the point A is determined to be the candidate reflection point, otherwise, if the amplitude of the point A is smaller than the mean value, the point A is determined not to be the candidate reflection point.
In this way, each reflection point indicated by the range-doppler spectrum can be traversed to screen out candidate reflection points. Respective protection and reference thresholds may be determined for different current reflection points.
Substep S1062: and determining a stationary clutter cluster consisting of stationary reflection points which are relatively geostationary from the at least one candidate reflection point according to the distance from the at least one candidate reflection point to the radar and the relative speed of the at least one candidate reflection point relative to the radar.
Since the distance to the radar is continuously changed when the stationary reflection point which is relatively earth stationary is located right in front of the radar, but the relative speed is not changed, that is, it is a straight line in a certain speed dimension in the range-doppler spectrum, when determining the stationary clutter cluster formed by the stationary reflection points, the sub-step S1062 may be implemented by the following procedure:
procedure B1: determining a distance unit threshold according to the distance of the at least one candidate reflection point to the radar and the relative speed.
For example, for a certain velocity dimension, according to the distance from the candidate reflection points to the radar, candidate reflection points which are continuous in the distance dimension are determined from the candidate reflection points located in the velocity dimension, and then the region in which the candidate reflection points which are continuous in the distance dimension are located is determined as a stationary clutter region.
To avoid errors in the velocity estimation due to azimuth angle between the candidate reflection points and the radar, a distance threshold is determined for each candidate reflection point in the stationary clutter region to exclude the portion of doppler-azimuth coupling in the stationary clutter region.
For example, the candidate reflection points in the doppler-azimuth coupling part are not straight lines in a certain velocity dimension, but there are candidate reflection points in the range dimension (see the doppler-azimuth coupling part in fig. 1 c), and the relative velocity of the candidate reflection points in this coupling part is affected by the azimuth angle, so that the driving velocity of the radar cannot be accurately estimated by using the candidate reflection points, and needs to be excluded. Based on which the distance threshold can be determined from the range dimension corresponding to the doppler method coupling section.
In the range-doppler spectrum shown in fig. 1c, the range threshold can be set to 257 to 512, and the detected target in this region is in a straight line in the velocity dimension, which indicates that these candidate reflection points are located right in front of the radar, and the reflected echo signal does not affect the frequency, amplitude, time delay and the like due to the position deviation relative to the radar, so that an error is avoided, and the accuracy of velocity estimation is ensured.
Procedure B2: determining, from the at least one candidate reflection point, a preliminary screening reflection point that satisfies the distance unit threshold.
And according to the distance threshold, the candidate reflection points which belong to the distance threshold in the candidate reflection points can be used as the primary screening reflection points. The primary screening reflection points may be static reflection points or moving primary screening reflection points (such as reflection points on vehicles and the like).
Procedure B3: and performing density clustering on the relative speed of the primary screening reflection points, determining the clustering result with the longest span as the static clutter clustering cluster, and taking the primary screening reflection points contained in the static clutter clustering cluster as the static reflection points.
In order to determine the stationary reflection points from the primary screened reflection points, the primary screened reflection points are clustered by Density, for example, by means of Density-Based Spatial Clustering of Applications with Noise (DBSCAN). DBSCAN density clustering can set the radius of the clustering parameter to 0.3m/s, and the minimum number is 3. And clustering the primary screening reflection points by traversing all the primary screening reflection points, thereby obtaining at least one cluster.
The density-based DBSCAN clustering algorithm can set reasonable threshold parameters according to the distance from the primary screening reflection points to the radar, the primary screening reflection points with different dimensionalities tending to gather are divided into the same clustering cluster, and the clustering characteristic is very suitable for the primary screening reflection points with higher precision obtained by the millimeter wave radar.
And determining the cluster with the longest span as a static clutter cluster for the acquired cluster.
For example, the difference of the relative distances between any two primary-screened reflection points in the cluster is calculated, the maximum difference in the cluster is determined, the cluster with the maximum difference is selected as a static clutter cluster, and the primary-screened reflection points in the static clutter cluster are used as static reflection points.
In this way, stationary reflection points, that is, reflection points located directly in front of the radar and stationary relative to the ground, can be determined from the reflection points indicated by the range-doppler spectrum, and the echo signals reflected by these stationary reflection points will not generate errors due to azimuth angles and the like, and can be used for accurately estimating the driving speed.
After obtaining the stationary reflection points, the subsequent steps may be performed to estimate the traveling speed of the mobile device according to the relative speed of the stationary reflection points to obtain an accurate traveling speed.
For example, in the present embodiment, step S108 may be implemented as: and using a centroid algorithm for the stationary clutter cluster to determine an average speed of the stationary reflection point relative to the mobile equipment according to the relative speed of the stationary reflection point contained in the stationary clutter cluster, wherein the average speed is used as the driving speed of the mobile equipment relative to the earth. In this way, the relative speed of the radar with respect to the stationary reflecting point can be accurately estimated.
Optionally, in this embodiment, in order to improve the accuracy of speed estimation, in addition to estimating the running speed corresponding to the current detection period through the echo signal of the radar in each detection period, the running speeds estimated in a plurality of detection periods may be processed, and a more accurate running speed may be obtained. For this, when the detection period is two or more, the method further includes the step S110: and performing Kalman filtering processing according to the running speed of the mobile equipment obtained in a plurality of continuous detection periods, and determining the running speed of the mobile equipment relative to the ground according to a processing result.
For example, a state equation and an observation equation are established through measurement vectors of continuous multiple frames, and then the accuracy of the running speed estimation is improved by using Kalman filtering, so that more accurate running speed is obtained.
In this embodiment, taking an example of obtaining a range-doppler spectrum of 800 frames in 80s, a range-doppler spectrum of 1 frame corresponds to a time of 100ms, 256 probe signals are continuously transmitted in an initial stage of 100ms (such as the previous 10ms), a beat signal is determined according to the obtained echo signal, and the beat signal is processed to obtain a range-doppler spectrum of the corresponding frame.
When the frame number of the obtained range-doppler spectrum is greater than or equal to 2, a state equation and an observation equation can be constructed according to the range-doppler spectrums of at least two adjacent frames, and the state equation is processed by using kalman filtering, so that the accuracy of estimating the running speed of the mobile equipment is improved.
For example, an observation vector may be represented as Z ═ v]Since the traveling speed of the mobile device is estimated in the present embodiment, the state vector describes the traveling speed, and at the k-th time, the state vector may be expressed as:
the corresponding observation equation at time k +1 can be expressed as: z (k +1) ═ HX (k +1), where Z (k +1) is the observation vector at the k +1 th time, and H is a weight coefficient, which can be appropriately determined as necessary, for example, [1,0 ]. X (k +1) is the state vector at time k + 1.
the equation of state can be expressed as: x (k +1) ═ ax (k), where X (k +1) is the state vector at time k +1 and a is a weight coefficient, which can be calculated as needed, for example, asT is the time interval between two adjacent frames, which is 0..1s in this embodiment, and x (k) is the state vector at the kth time. That is, the state equation can be expressed as:
after the state equation and the observation equation are established, a Kalman filtering method can be adopted to calculate a Kalman filtering coefficient, the observation speed is determined according to the observation equation at the k +1 moment, the prediction speed at the k +1 moment is determined through the state equation at the k +1 moment, the Kalman filtering coefficient is used for weighting the observation speed, and the weighted observation speed and the prediction speed are summed to obtain the running speed at the k +1 moment.
The optimal estimated speed under the interference of linear white Gaussian noise can be obtained through Kalman filtering. The accuracy of the speed estimation of the vehicle can be improved by using Kalman filtering estimation. Fig. 3c shows a schematic representation of the travel speed before and after the filtering as a function of time, and fig. 3d shows a schematic representation of the acceleration change.
In this way, in a detection period, a radar fixed at the front end of the mobile equipment is used for transmitting a detection signal, and the distance dimension and Doppler dimension signal processing is carried out on the obtained echo signal to obtain a distance Doppler spectrum. Under the scene that continuous static clutter exists, constant false alarm detection and density clustering are carried out on the obtained range-Doppler spectrum, the constant false alarm detection result and the density clustering result are combined, a certain distance threshold value is set, static reflection points with characteristics conforming to the characteristics of the static clutter are extracted from the range-Doppler spectrum, and then the speed of the radar relative to the ground is estimated according to the relative speed of the static reflection points, namely the driving speed of the mobile equipment relative to the ground. In order to enable estimation to be more accurate, a state equation and an observation equation are constructed for the driving speed estimated in a plurality of continuous detection periods, and then filtering is carried out, so that the estimation precision of the driving speed is improved.
The driving speed of the vehicle is measured by the millimeter wave radar, the estimation precision is improved by the Kalman filtering mode, the speed of the radar relative to the ground can be obtained without other sensors, the subsequent output speed compensation of the vehicle by the radar is facilitated, and the precision of the vehicle information detection is improved. On the basis of ensuring the basic functions of radar ranging, speed measurement and angle measurement, the static clutter information in the range-Doppler spectrum is fully utilized to estimate the speed of the vehicle. On the basis of ensuring the speed estimation of each frame of range-Doppler spectrum, a Kalman filtering algorithm is introduced to improve the estimation precision of the speed of the bicycle by using multi-frame information.
The data processing method of the present embodiment may be executed by any suitable electronic device with data processing capability, including but not limited to: servers, mobile terminals (such as tablet computers, mobile phones and the like), PCs and the like.
Example four
Referring to fig. 4, a block diagram of a data processing apparatus according to a fourth embodiment of the present application is shown.
In this embodiment, a data processing apparatus includes:
an obtaining module 402, configured to periodically transmit a detection signal through a radar carried by a mobile device, and obtain an echo signal generated when a reflection point of a target reflects the detection signal when the detection signal irradiates a corresponding target;
a first determining module 404, configured to determine a frame range doppler spectrum according to the echo signal received in a detection period;
a second determining module 406, configured to determine a stationary clutter cluster formed by reflection points that are relatively geostationary according to a distance from a reflection point indicated by the one-frame range-doppler spectrum to the radar and a relative speed of the reflection point with respect to the radar;
a third determining module 408 for determining a driving speed of the mobile device relative to the earth based on the relative speed of stationary reflection points comprised by the stationary clutter clusters.
Optionally, the second determining module 406 includes:
a screening module 4061, configured to screen at least one candidate reflection point other than the noise reflection point from the multiple reflection points indicated by the range-doppler spectrum;
a fourth determining module 4062, configured to determine a cluster of stationary clutter clusters consisting of stationary reflection points that are relatively geostationary from the at least one candidate reflection point according to a distance of the at least one candidate reflection point to the radar and a relative speed of the at least one candidate reflection point with respect to the radar.
Optionally, the screening module 4061 is configured to obtain a set protection threshold value and a set reference threshold value according to the total number of velocity dimensions of the range-doppler spectrum, where the protection threshold value and the reference threshold value are used to determine a screening condition corresponding to each candidate reflection point when determining the candidate reflection point; and determining at least one candidate reflection point according to the protection threshold value, the reference threshold value and the amplitude of the echo signal corresponding to the plurality of reflection points indicated by the range-Doppler spectrum.
Optionally, the screening module 4061 is configured to determine, when at least one candidate reflection point is determined according to the protection threshold value, the reference threshold value, and the amplitudes of the echo signals corresponding to the multiple reflection points indicated by the range-doppler spectrum, an excluded velocity dimension according to the velocity dimension of the current reflection point and the protection threshold value for the multiple reflection points indicated by the range-doppler spectrum; determining the speed boundary of the current reflection point according to the excluded speed dimension; determining the reference speed dimension of the current reflection point according to the speed boundary and the reference threshold value; and determining the screening condition of the current reflecting point according to the amplitude values of the echo signals of the reflecting points indicated in the reference speed dimension, and determining whether the current reflecting point is a candidate reflecting point according to the screening condition and the amplitude value of the echo signal of the current reflecting point.
Optionally, the fourth determining module 4062 is configured to determine a distance unit threshold according to the distance of the at least one candidate reflection point from the radar and the relative speed; determining a preliminary screening reflection point satisfying the distance unit threshold from the at least one candidate reflection point; and performing density clustering on the relative speed of the primary screening reflection points, determining the clustering result with the longest span as the static clutter clustering cluster, and taking the primary screening reflection points contained in the static clutter clustering cluster as the static reflection points.
Optionally, the third determining module 408 is configured to use a centroid algorithm for the stationary clutter clusters to determine an average speed of the stationary reflecting point relative to the mobile device according to the relative speed of the stationary reflecting point contained in the stationary clutter clusters as the driving speed of the mobile device relative to the earth.
Optionally, when the detection period is two or more, the apparatus further includes: and a filtering module 410, configured to perform kalman filtering processing according to the driving speed of the mobile device obtained in a plurality of consecutive detection cycles, and determine the driving speed of the mobile device relative to the ground according to a processing result.
The data processing apparatus of this embodiment is configured to implement the corresponding data processing method in the foregoing multiple method embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again. In addition, the functional implementation of each module in the data device of this embodiment can refer to the description of the corresponding part in the foregoing method embodiment, and is not described herein again.
EXAMPLE five
Referring to fig. 5, a schematic structural diagram of an electronic device according to a fifth embodiment of the present application is shown, and the specific embodiment of the present application does not limit a specific implementation of the electronic device.
As shown in fig. 5, the electronic device may include: a processor (processor)502, a Communications Interface (Communications Interface)504, a memory 506, and a communication bus 508.
Wherein:
the processor 502, communication interface 504, and memory 506 communicate with one another via a communication bus 508.
A communication interface 504 for communicating with other electronic devices or servers.
The processor 502 is configured to execute the program 510, and may specifically perform relevant steps in the above-described data processing method embodiments.
In particular, program 510 may include program code that includes computer operating instructions.
The processor 52 may be a central processing unit CPU or an application Specific Integrated circuit asic or one or more Integrated circuits configured to implement embodiments of the present application. The intelligent device comprises one or more processors which can be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.
And a memory 506 for storing a program 510. The memory 506 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 510 may be specifically configured to enable the processor 502 to execute operations corresponding to any one of the aforementioned data processing methods.
For specific implementation of each step in the program 510, reference may be made to corresponding steps and corresponding descriptions in units in the foregoing data processing method embodiments, which are not described herein again. It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described devices and modules may refer to the corresponding process descriptions in the foregoing method embodiments, and are not described herein again.
It should be noted that, according to the implementation requirement, each component/step described in the embodiment of the present application may be divided into more components/steps, and two or more components/steps or partial operations of the components/steps may also be combined into a new component/step to achieve the purpose of the embodiment of the present application.
The above-described methods according to embodiments of the present application may be implemented in hardware, firmware, or as software or computer code storable in a recording medium such as a CD ROM, a RAM, a floppy disk, a hard disk, or a magneto-optical disk, or as computer code originally stored in a remote recording medium or a non-transitory machine-readable medium downloaded through a network and to be stored in a local recording medium, so that the methods described herein may be stored in such software processes on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware such as an ASIC or FPGA. It will be appreciated that the computer, processor, microprocessor controller or programmable hardware includes memory components (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the data processing methods described herein. Further, when a general-purpose computer accesses code for implementing the data processing method shown herein, execution of the code converts the general-purpose computer into a special-purpose computer for executing the data processing method shown herein.
Those of ordinary skill in the art will appreciate that the various illustrative elements and method steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the embodiments of the present application.
The above embodiments are only used for illustrating the embodiments of the present application, and not for limiting the embodiments of the present application, and those skilled in the relevant art can make various changes and modifications without departing from the spirit and scope of the embodiments of the present application, so that all equivalent technical solutions also belong to the scope of the embodiments of the present application, and the scope of patent protection of the embodiments of the present application should be defined by the claims.
Claims (10)
1. A method of data processing, comprising:
periodically transmitting a detection signal through a radar carried by mobile equipment, and acquiring an echo signal generated by a reflection point of a target reflecting the detection signal when the detection signal irradiates a corresponding target;
determining a frame range Doppler spectrum according to the echo signals received in a detection period;
determining stationary clutter cluster formed by the reflecting points which are stationary relative to the ground according to the distance from the reflecting points indicated by the one-frame distance Doppler spectrum to the radar and the relative speed of the reflecting points relative to the radar;
and determining the driving speed of the mobile equipment relative to the ground according to the relative speed of the static reflection points included in the static clutter cluster.
2. The method according to claim 1, wherein the determining that relatively geodetic reflecting points constitute stationary clutter clusters from the range to the radar of reflecting points indicated by the range-doppler spectrum and the relative velocity of reflecting points with respect to the radar comprises:
screening out at least one candidate reflection point out of the noise reflection points from the plurality of reflection points indicated by the range-Doppler spectrum;
and determining a stationary clutter cluster consisting of stationary reflection points which are relatively geostationary from the at least one candidate reflection point according to the distance from the at least one candidate reflection point to the radar and the relative speed of the at least one candidate reflection point relative to the radar.
3. The method of claim 2, wherein said screening out at least one candidate reflection point other than a noise reflection point from the reflection points indicated by the range-doppler spectrum comprises:
acquiring a set protection threshold value and a reference threshold value according to the total number of velocity dimensions of the range-doppler spectrum, wherein the protection threshold value and the reference threshold value are used for determining screening conditions corresponding to the candidate reflecting points when the candidate reflecting points are determined;
and determining at least one candidate reflection point according to the protection threshold value, the reference threshold value and the amplitude of the echo signal corresponding to the plurality of reflection points indicated by the range-Doppler spectrum.
4. The method of claim 3, wherein the determining at least one candidate reflection point according to the guard threshold value, the reference threshold value and the amplitude of the echo signal corresponding to the plurality of reflection points indicated by the range-Doppler spectrum comprises:
aiming at a plurality of reflection points indicated by the range-Doppler spectrum, determining excluded speed dimensions according to the speed dimensions and the protection threshold values of the current reflection points;
determining the speed boundary of the current reflection point according to the excluded speed dimension;
determining the reference speed dimension of the current reflection point according to the speed boundary and the reference threshold value;
and determining the screening condition of the current reflecting point according to the amplitude values of the echo signals of the reflecting points indicated in the reference speed dimension, and determining whether the current reflecting point is a candidate reflecting point according to the screening condition and the amplitude value of the echo signal of the current reflecting point.
5. The method of claim 2, wherein the determining a cluster of stationary clutter clusters of relatively geodetic stationary refiection points from the at least one candidate refiection point based on a distance of the at least one candidate refiection point to the radar and a relative velocity of the at least one candidate refiection point with respect to the radar comprises:
determining a distance unit threshold according to the distance of the at least one candidate reflection point relative to the radar and the relative speed;
determining a preliminary screening reflection point satisfying the distance unit threshold from the at least one candidate reflection point;
and performing density clustering on the relative speed of the primary screening reflection points, determining the clustering result with the longest span as the static clutter clustering cluster, and taking the primary screening reflection points contained in the static clutter clustering cluster as the static reflection points.
6. The method according to claim 1, wherein said determining a travel speed of the mobile device relative to the earth from the relative speeds of stationary reflecting points comprised by the stationary clutter clusters comprises:
and using a centroid algorithm for the stationary clutter cluster to determine an average speed of the stationary reflection point relative to the mobile equipment according to the relative speed of the stationary reflection point contained in the stationary clutter cluster, wherein the average speed is used as the driving speed of the mobile equipment relative to the ground.
7. The method according to any one of claims 1-5, wherein when the detection period is two or more, the method further comprises:
and performing Kalman filtering processing according to the running speed of the mobile equipment obtained in a plurality of continuous detection periods, and determining the running speed of the mobile equipment relative to the ground according to a processing result.
8. A data processing apparatus comprising:
the acquisition module is used for periodically transmitting a detection signal through a radar carried by mobile equipment and acquiring an echo signal generated by a reflection point of a target reflecting the detection signal when the detection signal irradiates a corresponding target;
the first determining module is used for determining a frame distance Doppler spectrum according to the echo signal received in a detection period;
the second determination module is used for determining a stationary clutter cluster formed by reflecting points which are stationary relative to the ground according to the distance from the reflecting points indicated by the one-frame distance Doppler spectrum to the radar and the relative speed of the reflecting points relative to the radar;
and the third determination module is used for determining the driving speed of the mobile equipment relative to the ground according to the relative speed of the static reflection points included in the static clutter cluster.
9. An electronic device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the corresponding operation of the data processing method according to any one of claims 1-7.
10. A computer storage medium, on which a computer program is stored which, when being executed by a processor, carries out the data processing method of any one of claims 1 to 7.
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