CN114518562A - Target identification method and device, electronic equipment and storage medium - Google Patents
Target identification method and device, electronic equipment and storage medium Download PDFInfo
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- CN114518562A CN114518562A CN202011306791.2A CN202011306791A CN114518562A CN 114518562 A CN114518562 A CN 114518562A CN 202011306791 A CN202011306791 A CN 202011306791A CN 114518562 A CN114518562 A CN 114518562A
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- 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
- G01S7/411—Identification of targets based on measurements of radar reflectivity
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Abstract
The present disclosure relates to the field of radar signal processing technologies, and in particular, to a method and an apparatus for identifying a target, an electronic device, and a storage medium. And extracting reflection point data of the detection object through a sliding window, and determining at least one candidate effective target point set according to the reflection point data in the sliding window, wherein a target corresponding to the candidate effective target point set is a candidate effective target. The sliding window is a time window for sampling reflection point data, and one time window corresponds to one time period; therefore, the method and the device for determining the effective target point set can acquire the reflection point data appearing in a period of time, and determine the candidate effective target point set according to the reflection point data appearing in the period of time. Compared with a mode of determining an effective target through reflection point data appearing at a certain moment, the method and the device for determining the effective target have the advantage that the accuracy of the candidate effective target identified through the mode of determining the candidate effective target through the reflection point data in a period of time is higher.
Description
Technical Field
The present invention relates to the field of radar signal processing technologies, and in particular, to a target identification method and apparatus, an electronic device, and a storage medium.
Background
Millimeter waves are electromagnetic waves between the infrared and microwave frequency bands. The wavelength of the millimeter wave is between 1 mm and 10mm, and the corresponding frequency range is 30 GHz to 300 GHz. A millimeter-wave radar is an electronic device that detects an object using millimeter waves. When the millimeter wave radar works, the radar antenna radiates millimeter waves in the atmosphere in a directional mode, the millimeter waves are transmitted in the atmosphere at a speed close to the speed of light, if a target is located in a millimeter wave beam radiated by the radar antenna, the target intercepts a part of millimeter waves and scatters the intercepted millimeter waves to all directions to form reflection signals, and after the radar antenna receives the reflection signals, the radar antenna processes the received reflection signals to obtain information of a detected object.
In the related art, as the millimeter waves radiated by the radar antenna may be reflected by other objects except for the target, the reflected signals of the millimeter waves are divided into a plurality of paths to be transmitted; when reflected signals propagated by different paths reach a receiving end of the millimeter wave radar, the reflected signals are mutually superposed according to respective phases to cause interference, namely multipath interference is generated. The multipath interference causes the received reflected signal of the target to change in amplitude and phase when the millimeter wave radar detects the target, thereby causing detection errors.
Disclosure of Invention
In order to overcome detection errors caused by multipath interference when a millimeter wave radar detects a target, embodiments of the present invention provide a method, an apparatus, an electronic device, and a storage medium for identifying a target, which can extract reflection point data occurring within a period of time through a sliding window, and determine a candidate effective target point set according to the reflection point data occurring within the period of time, thereby improving accuracy of target identification.
In order to solve the technical problem, the following technical solutions are provided in the embodiments of the present invention:
in a first aspect, an embodiment of the present invention provides a method for identifying an object, which is applied to an electronic device, and the method includes:
extracting reflection point data of a detection object through a sliding window, wherein the sliding window is a time window for sampling the reflection point data;
and determining at least one candidate effective target point set according to the reflection point data in the sliding window, wherein the target corresponding to the candidate effective target point set is a candidate effective target.
In a second aspect, an embodiment of the present invention provides an apparatus for identifying an object, which is applied to a femto electronic device, and the apparatus includes:
the extraction module is used for extracting the reflection point data according to a sliding window, and the sliding window is a time window for sampling the reflection point data;
and the determining module is used for determining at least one candidate effective target point set according to the reflection point data in the sliding window, and the target corresponding to the candidate effective target point set is a candidate effective target.
In a third aspect, an embodiment of the present invention provides an electronic device, where the electronic device includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method of identifying an object according to the first aspect of the invention.
In a fourth aspect, the embodiments of the present invention further provide a non-transitory computer-readable storage medium, where computer-executable instructions are stored, and when the computer-executable instructions are executed, the method for identifying an object according to the first aspect of the present invention can be performed.
The beneficial effects of the embodiment of the application are that: different from the situation in the prior art, embodiments of the present application provide a method, an apparatus, an electronic device, and a storage medium for identifying a target, which are capable of extracting reflection point data of a detection object through a sliding window, and determining at least one candidate effective target point set according to the reflection point data in the sliding window, where a target corresponding to the candidate effective target point set is a candidate effective target. The sliding window is a time window for sampling reflection point data, and one time window corresponds to one time period; therefore, the method and the device for determining the effective target point set can acquire the reflection point data appearing in a period of time, and determine the candidate effective target point set according to the reflection point data appearing in the period of time. Compared with a mode of determining an effective target through reflection point data appearing at a certain moment, the method and the device for determining the effective target have the advantage that the accuracy of the candidate effective target identified through the mode of determining the candidate effective target through the reflection point data in a period of time is higher.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below. It is obvious that the drawings described below are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is an application scenario provided by an embodiment of the present application;
fig. 2 is a hardware configuration of a millimeter wave radar apparatus provided in an embodiment of the present application;
FIG. 3a is a schematic flow chart diagram of a method for identifying objects provided by an embodiment of the present application;
FIG. 3b is a schematic flow chart diagram illustrating a method for identifying objects according to another embodiment of the present application;
FIG. 4 is a flowchart illustrating a method for determining whether a reflection point in a target cluster is a set of candidate valid target points according to an embodiment of the present application;
FIG. 5 is a schematic view of a sliding window provided by an embodiment of the present application;
FIG. 6 is a schematic diagram of a target recognition device according to an embodiment of the present application;
FIG. 7 is a schematic diagram of an object recognition device according to another embodiment of the present application;
fig. 8 is a hardware configuration of an electronic device that executes a target identification method according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
In the description of the present invention, it is to be understood that the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Furthermore, the references to "horizontal" and "vertical" etc. indicate that the orientation or positional relationship is based on that shown in the drawings for the purpose of describing the invention or facilitating the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore should not be construed as limiting the invention.
In the embodiment of the present application, the electronic device for executing the target identification method exists in various forms, including but not limited to a mobile communication device, a server, or other electronic devices with computing and processing functions. The electronic device may specifically be a radar.
The wave radar related to the embodiment of the application can be called a detector or a detection device, and the working principle of the wave radar is that a radar antenna emits radar signals and a target in a detection object is detected by receiving reflected signals, wherein the reflected signals are electromagnetic waves obtained by the radar signals after the radar signals are reflected by the detection object. Radar signals may also be referred to as radio signals or electromagnetic wave signals; for convenience of explanation, the embodiments of the present application are collectively referred to as radar signals. The transmission of the radar signal is periodic. For example, for a sawtooth radar signal, the duration of a complete sawtooth waveform is understood to be the transmission period of the radar signal; as another example, for a triangular wave radar signal, the duration of a complete triangular waveform may be understood as the transmission period of the triangular wave radar signal.
The radar related to the embodiments of the present application may be a millimeter wave radar. The millimeter wave has the following characteristics: 1) the bandwidth is large: the frequency domain resources are rich, the antenna side lobe is low, and the imaging or quasi-imaging is favorably realized; 2) the wavelength is short: the volume and the antenna aperture of the radar equipment are reduced, and the weight is reduced; 3) narrow beam: the wave beam of millimeter waves is much narrower than that of micron waves under the same antenna size, the radar resolution is high, and the measurement precision can reach millimeter level; 4) the penetration is strong: compared with a laser radar and an optical system, the laser radar has better capability of penetrating smoke, dust and clothes, and can work all the day. The millimeter wave related characteristics are very suitable for being applied to indoor human body detection, such as positioning, tracking or vital sign detection of a human body.
The millimeter wave radar can generate multipath effect in the process of detecting the target, which causes the fading and phase shift of radar signals. The multipath effect means that the time for each component field to reach a receiving end is different after the electromagnetic waves are propagated through different paths, and interference is caused by mutual superposition according to respective phases, so that signals received by a radar are distorted or errors are generated. Therefore, the multipath effect makes it difficult for the radar to accurately determine the position of the reflection point corresponding to the reflection signal, thereby affecting the efficiency and accuracy of identifying the detection object. Because the indoor environment is relatively complex, walls, floors, ceilings and various furniture may have reflection effects on millimeter waves; therefore, when the millimeter wave radar is applied to detection of an indoor detection object, the multipath interference phenomenon is more significant.
Referring to fig. 1, fig. 1 schematically shows an application scenario of the embodiment of the present application, as shown in fig. 1, a millimeter wave radar 10 is disposed indoors, and the millimeter wave radar 10 may be an independent detection device or may be integrated into other products, for example, the millimeter wave radar 10 may be integrated into a household appliance, and the household appliance may be an intelligent robot, for example. The detected target 20 is a human body or an object, and the target 20 is exemplified as a human body in fig. 1. As shown in fig. 1, the millimeter wave radar 10 may transmit a radar signal to a detection area where the target 20 is located, and receive a reflected signal of the radar signal. The reflected signal of the target 20 may directly reach the millimeter-wave radar 10 along the path a, may reach the radar after being reflected by the wall 30 along the path b, or may reach the millimeter-wave radar 10 after being reflected by the wall painting 40 provided on the wall 30 along the path c. The millimeter wave radar 10 receives the reflected signals including the reflected signals returned along the path a, the path b and the path c; among them, the reflected signals that reach the millimeter wave radar 10 along the path b and the path c are interference signals generated by the multipath effect. If the target 20 is detected directly by using the reflected signal containing the interference signal, the accuracy and efficiency of the millimeter wave radar 10 in identifying the target 20 may be affected.
In order to reduce the influence of multipath effect on the accuracy and efficiency of target identification, the embodiment of the application provides a target identification method, which can acquire reflection points according to reflection signals of radar signals, extract the reflection points according to a sliding window, and determine a candidate effective target point set in the reflection points, thereby filtering false points in the reflection points except the candidate effective target point set; screening out second effective points in the candidate effective target point set according to the number of the sliding windows extracting the same candidate effective target point set so as to filter out false points in the candidate effective target point set; and the detection object corresponding to the second effective point is an effective target. To facilitate the reader's understanding of the invention, reference will now be made to specific examples.
Fig. 2 schematically shows a hardware structure of the millimeter wave radar. Millimeter-wave radar 200 in fig. 2 may generate and transmit radar signals into an area that millimeter-wave radar 200 is monitoring. The radar signal transmitted by the millimeter Wave radar 200 is divided into a pulse Wave (chirp) signal and a frequency modulated Continuous Wave (CW) signal, which are distinguished by waveforms. If the radar signal is a pulse wave, when the target distance is very short, the time difference between the emission pulse wave and the reception pulse wave is very small, the radar is required to adopt a high-speed signal processing technology, the structure of the short-distance pulse radar becomes very complicated, and the cost is greatly increased. Therefore, the millimeter wave radar generally adopts frequency modulation continuous waves which have simple structure and lower cost and are suitable for short-distance detection. The embodiments of the present application take radar signals as frequency modulated continuous waves as an example for explanation.
As shown in fig. 2, the millimeter wave radar 200 includes: an oscillator 201, a directional coupler 202, a transmit antenna 203, a receive antenna 204, a mixer 205, a processor 206, and a memory 207. Those skilled in the art will appreciate that the configuration shown in fig. 2 is not intended to be limiting of the terminal, which may include more or fewer components than shown, or some components may be combined, some components may be split, or a different arrangement of components.
The oscillator 201 is used to generate a Frequency Modulated Continuous Wave (FMCW) and output the Frequency modulated continuous wave to the directional coupler 202. In some embodiments, the frequency modulated continuous wave may be a chirped continuous wave. The frequency of the chirp continuous wave increases or decreases linearly along with time, namely the frequency of the chirp continuous wave is in a linear relation with time in unit time, or the absolute value of the frequency variation of the chirp continuous wave is the same. The waveform of the frequency modulated continuous wave is generally a sawtooth wave or a triangular wave; for a sawtooth wave, the frequency variation is the same; for a triangular wave, the absolute value of the amount of frequency change is the same for the rising and falling edges.
On one hand, the directional coupler 202 outputs the frequency-modulated continuous wave to the mixer 205 as a local oscillation signal; on the other hand, the frequency-modulated continuous wave is output to the transmitting antenna 203 and is transmitted through the transmitting antenna 203. The frequency modulation continuous wave becomes a reflection wave of the frequency modulation continuous wave after being reflected by the detection object.
The receiving antenna 204 receives the reflected frequency-modulated continuous wave and outputs the received frequency-modulated continuous wave to the mixer 205.
The mixer 205 mixes the frequency modulated continuous wave with a reflected wave of the frequency modulated continuous wave to obtain an Intermediate Frequency (IF) signal, where the IF signal is a signal formed by a difference between frequencies of the frequency modulated continuous wave and the reflected wave of the frequency modulated continuous wave at the same time, that is, the frequency of the IF signal is a difference between frequencies of the frequency modulated continuous wave and the reflected wave at the same time.
The mixer 205 filters the intermediate frequency signal obtained by mixing through a low pass filter, amplifies the filtered intermediate frequency signal, and outputs the amplified intermediate frequency signal to the processor 206, and the processor 206 processes the intermediate frequency signal (for example, performs fast fourier transform, spectrum analysis, and the like on the intermediate frequency signal) to obtain at least one of distance information, velocity information, and angle information of the detection object.
In the embodiment of the present application, distance information, speed information, and angle information of a detection object, or a distance, a speed, and an angle of a detection object are all specific names for a millimeter wave radar that transmits a frequency modulated continuous wave, and the present application is not limited to the specific names.
The working principle of the millimeter wave radar will be described in detail below by taking the waveform of the frequency modulated continuous wave as a triangular wave.
The period of the frequency modulation continuous wave (triangular wave) is T, the frequency of the frequency modulation continuous wave linearly increases by delta F along with the time increase in a time unit [0, T/2], and the frequency of the frequency modulation continuous wave linearly decreases by delta F along with the time increase in a time unit [ T/2, T ], wherein the delta F is the maximum variation range of the frequency modulation continuous wave.
If the detection object is in a relative stationary position with respect to the millimeter wave radar, the frequency modulated continuous wave has the same shape as the reflected wave of the frequency modulated continuous wave, but with a time delay Δ t in time.
Frequency modulated continuous wave x1Comprises the following steps:
reflected wave x of frequency modulated continuous wave2Comprises the following steps:
wherein, ω is1(t) is a frequency-modulated continuous wave x1The angular velocity of (a) of (b),
for frequency-modulated continuous waves x1The initial phase of (2); omega2(t) is a frequency-modulated continuous wave x2The angular velocity of (a) of (b),
for frequency-modulated continuous waves x2The initial phase of (1).
Frequency modulated continuous wave x1Reflected wave x of frequency modulated continuous wave2The time delay delta t between the two and the distance R of the detection object satisfy:
Δt＝2R/c (3)
where c is the speed of light.
Frequency modulated continuous wave x1And a reflected wave x of the frequency modulated continuous wave2Mixing in a mixer to obtain an intermediate frequency signal xoutComprises the following steps:
the frequency IF of the intermediate frequency signal is the product of the slope s of the frequency modulated continuous wave and the time delay Δ t, namely:
wherein T is the period of the triangular wave, and Delta F is the maximum variation range of the frequency modulation continuous wave.
Therefore, the distance R of the detection object is:
as can be seen from the above derivation, for a detection object which is relatively stationary with respect to the millimeter wave radar, the frequency difference between the frequency modulated continuous wave and the reflected wave of the frequency modulated continuous wave at the same time (the frequency IF of the intermediate frequency signal) and the time delay Δ t between the frequency modulated continuous wave and the reflected wave of the frequency modulated continuous wave are in a linear relationship, that is, the longer the distance of the target object is, the later the time the reflected wave of the frequency modulated continuous wave is received by the millimeter wave radar, and the larger the frequency difference between the frequency modulated continuous wave and the reflected wave of the frequency modulated continuous wave at the same time (the frequency IF of the intermediate frequency signal) is, so that the distance of the detection object can be obtained by determining the magnitude of the frequency IF of the intermediate frequency signal.
If the detection object is in relative motion with respect to the radar, the frequency of the reflected wave of the frequency modulated continuous wave includes a Soplerian frequency shift f caused by the relative motion of the target objectd。
Therefore, the frequency f of the intermediate frequency signal corresponding to the rising edge of the triangular waveb+Comprises the following steps:
fb+＝IF-fd (7)
frequency f of intermediate frequency signal corresponding to falling edge of triangular waveb-Comprises the following steps:
fb-＝IF+fd (8)
wherein IF isFrequency of the intermediate-frequency signal when the target object is relatively stationary with respect to the radar, fdAnd 2fv/c is Doppler frequency shift, and the sign of the Doppler frequency shift is related to the direction of relative movement of the target object relative to the radar, wherein f is the center frequency of the frequency modulated continuous wave, and v is the speed of the detected object.
From the above equations (7), (8) and (5), the distance R of the detection object in relative motion with respect to the radar can be obtained as:
from the above equations (7) and (8) and the doppler shift, it can also be obtained that the velocity of the detection object that can move relative to the radar is:
as can be seen from the above equation (9) and equation (10), for a detection object that is in relative motion with respect to the radar, the distance and speed of the detection object with respect to the radar can be obtained by detecting the frequency of the intermediate frequency signal at the rising edge and the frequency of the intermediate frequency signal at the falling edge of the triangular wave.
The working principle of the millimeter wave radar is described below by taking a frequency modulated continuous wave as a sawtooth wave.
For a sawtooth wave, the principle of ranging is similar to a triangular wave. Let the time delay between the frequency modulated continuous wave and the reflected wave of the frequency modulated continuous wave be tau, and the period of the sawtooth wave be Tc。
Frequency modulated continuous wave x1Comprises the following steps:
reflected wave x of frequency modulated continuous wave2Comprises the following steps:
wherein, ω is1For frequency-modulated continuous waves x1The angular velocity of (a) of (b),
for frequency-modulated continuous waves x1The initial phase of (1).
Initial phase of intermediate frequency signal
For frequency-modulated continuous waves x1Phase of and frequency modulated continuous wave x2The phase difference of (2):
since τ is 2R/c, the initial phase of the intermediate frequency signal can be further obtained
Distance of the target object:
wherein λ ═ c/fcIs the wavelength of the frequency-modulated continuous wave, R is the distance of the target object, fcIs the center frequency of the frequency modulated continuous wave.
It can be seen from the above derivation that the relative distance between the target object and the radar can be obtained by detecting the phase of the intermediate frequency signal.
For measuring the speed of an object, the radar measures the time interval TcTwo frequency-modulated continuous waves are transmitted and the reflected waves of the two frequency-modulated continuous waves are respectively received, so that two intermediate-frequency signals are obtainedSubject matter at time TcMoved by Δ R ═ vTcWhere v is the moving speed of the target object, so that the phase difference of the two intermediate frequency signals obtained according to equation (14) is
Comprises the following steps:
wherein λ is the wavelength of the frequency modulated continuous wave. The velocity v of the target object is therefore:
the angle measurement principle of the radar is an extension of the distance measurement principle, and the receiving antenna of the millimeter wave radar for receiving an electromagnetic wave signal may specifically include a first antenna and a second antenna, where a reflected wave of a detection object received by the first antenna is a first reflected wave, and a reflected wave of the detection object received by the second antenna is a second reflected wave. Since the first antenna and the second antenna are close to each other, the distance from the detection object to the millimeter wave radar is much greater than the distance between the first antenna and the second antenna. The first reflected wave and the second-day reflected wave travel directions are approximately parallel. The angle of the detection object can be calculated from the difference between the phases of the intermediate frequency signals of the first reflected wave and the second reflected wave.
For example, assuming that the angles between the two reflected signals and the first and second antennas are both θ and the distance between the first and second receiving antennas is d, the difference Δ R between the reflected signals and the two antennas is dsin θ, and the phase difference between the two intermediate frequency signals is due to the difference between the two intermediate frequency signals
The angle θ of the target object is obtained as:
in the embodiment of the present application, the same millimeter wave radar may be used to transmit two frequency modulated continuous waves in different frequency bands, and accordingly receive reflected waves of the two frequency modulated continuous waves, respectively, and the method described above is adopted to obtain intermediate frequency signals corresponding to the two frequency modulated continuous waves, so as to obtain at least one of a distance, a speed, and an angle of the target object relative to the millimeter wave radar.
Specifically, the position of the detection object with respect to the millimeter wave radar can be determined in accordance with the distance and angle of the detection object with respect to the radar. For example, the angle of the target object includes a horizontal azimuth and a vertical azimuth, and the millimeter wave radar may calculate a horizontal two-dimensional rectangular coordinate of the reflection point from the horizontal angle and the distance of the detection object, or calculate a three-dimensional rectangular coordinate of the reflection point from the vertical angle and the distance of the detection object.
The embodiment of the application further provides a target identification method, which is applied to electronic equipment, for example, the millimeter wave radar 200 in fig. 2. Fig. 3 schematically shows a flow of a method of identifying an object. As shown in fig. 3a, the method for identifying an object in the embodiment of the present application includes the following steps:
s31, extracting the reflection point data of the detection object through a sliding window; the sliding window in the embodiment of the present application is a time window for sampling reflection point data. The reflection points occurring within the sliding window can be sampled each time the sliding window is slid forward one time unit. The size of each sliding window is equal, and the time interval of the starting time of two adjacent sliding windows is equal. In the embodiment of the application, the number and the size of the sliding windows can be controlled according to actual conditions. For example, if the size of the sliding window is 2s and the sliding window slides forward by a time unit with a size of 1s, a 5s period includes 4 sliding windows; if the size of the sliding window is 1s and the sliding window is slid forward by one time unit with a size of 1s, a 5s period comprises 5 sliding windows.
In some embodiments, the reflection point data of the detection object includes rectangular coordinates of the reflection point and a signal-to-noise ratio of the reflection point. The processor may arrange the position coordinates of the reflection points in an order of positioning time to form a time series of position coordinates. The processor may determine a time period corresponding to the sliding window. The processor can obtain the reflection point data of the reflection point positioned in the time period corresponding to each time window according to the time sequence and the time period corresponding to each sliding window; thus, the processor may sample the reflection point data in accordance with the sliding window.
In some embodiments, the method of acquiring the reflection point data of the detection object specifically includes:
in the embodiment of the application, the radar antenna transmits the transmitting antenna of the radar signal, the oscillator in the millimeter wave radar generates the radar signal, and then the radar signal is transmitted to the area monitored by the millimeter wave radar through the transmitting antenna. The transmitted radar signal is typically a chirp signal with a carrier frequency. The radar antenna further comprises a receiving antenna. And the radar signal sent by the transmitting antenna is reflected by the detection object and then received by the receiving antenna. The reflected signal received by the receiving antenna is a delay signal of the radar signal transmitted by the transmitting antenna. The reflected signals received by the receiving antenna comprise direct reflected signals and indirect reflected signals, wherein the direct reflected signals are signals which are transmitted to a positioning target by the transmitting antenna and are directly received by the receiving antenna after being reflected by the positioning target; the indirect reflected signal is a signal reflected by other obstacles except the effective target and then received by the receiving antenna.
In this embodiment, the processor may mix the radar signal transmitted by the transmitting antenna and the reflected signal received by the receiving antenna through the mixer to obtain an intermediate frequency signal. The processor can sample the intermediate frequency signal and perform Fourier transform on the sampled intermediate frequency signal so as to convert the intermediate frequency signal in a time domain into an intermediate frequency signal in a frequency domain; the processor can obtain the frequency and the phase difference of the intermediate frequency signal according to the frequency spectrum of the intermediate frequency signal after Fourier transformation, and calculate the reflection point data of the reflection point of the detection object. The reflection point data may specifically be one or more of a polar coordinate system distance, an angle, a velocity, and a signal-to-noise ratio of the reflection point.
In some embodiments, the processor may sample the intermediate frequency signal in the fast time dimension or the slow time dimension. For example, if the radar signal transmitted by the transmitting antenna is a periodic triangular wave, the reflected wave of each triangular wave may be stored by row. For example, the reflected signal of the first triangular wave is placed in the first row, and the reflected signal of the second triangular wave is placed in the second row … … and the reflected signal of the nth triangular wave is placed in the n rows. The dimension in which the row direction is located is a fast time dimension, and the dimension in which the column direction is located is a slow time dimension.
In some embodiments, the processor samples the intermediate frequency signal obtained in the fast time dimension into a fast time signal; the processor samples the resulting intermediate frequency signal in the slow time dimension as a slow time signal. The fast time signal is a transverse one-dimensional signal. A plurality of one-dimensional signals are arranged in the longitudinal direction to form a two-dimensional signal, which is slow-time accumulation.
In some embodiments, the processor may perform fourier transform on each fast time signal to obtain a polar coordinate system distance of the detection object; then, slow time accumulation is carried out on the fast time signals to obtain speed information of the detection object; and obtaining the angle information of the target through the phase difference of the two-dimensional signals accumulated by the plurality of receiving antenna arrays after the slow time. The processor can also perform Fourier transform on the two-dimensional signals obtained by slow time accumulation to obtain a frequency spectrum, then extract the signal intensity of the detection object from the frequency spectrum, and average the noise signals to obtain the noise signal intensity, so that the signal-to-noise ratio of the detection object can be calculated. And converting the distance and angle information of the polar coordinate system of the detection object into rectangular coordinates to obtain the information of each detection object including spatial rectangular coordinates. The rectangular coordinates in this embodiment may be two-dimensional rectangular coordinates or three-dimensional rectangular coordinates.
S32, determining at least one candidate effective target point set according to the reflection point data in the sliding window;
in this embodiment, the processor may filter out false points in each sliding window from the reflection point data in each sliding window, and screen out a candidate effective target point set. The processor may specifically determine a characteristic quantity of the reflection point data, which may specifically be the coordinates and/or velocity of the reflection point. The processor can perform clustering processing on the reflection point data extracted from the same sliding window based on the characteristic quantity, divide the reflection points with the similar characteristic quantity into the same target cluster, determine candidate effective target points in the target cluster according to the number of the reflection points in the target cluster and the signal-to-noise ratio of each reflection point, and add the candidate effective target points into a candidate effective target point set.
The processor may specifically perform clustering processing on the rectangular coordinates of the plurality of reflection points extracted according to the same sliding window through a clustering algorithm based on the rectangular coordinates of the reflection points, so as to scribe the reflection points whose coordinate values are close to each other into the same target cluster. The rectangular coordinates of the reflection points may specifically be two-dimensional rectangular coordinates or three-dimensional rectangular coordinates. For example, two-dimensional coordinates may be represented by [ x, y ], and three-dimensional coordinates may be represented by [ x, y, z ], where x, y are horizontal coordinates; z is a vertical coordinate; the processor may extract [ x, y ] or [ x, y, z ] as a feature quantity of the individual reflection point data, and perform clustering based on the feature quantity, clustering reflection point data whose position coordinates are close into one class. The reflecting points corresponding to one or more detection objects can be obtained by clustering the reflecting point data. In some embodiments, the processor may select a reflection point for which target cluster division is not performed as a target reflection point, and acquire a reflection point for which a difference between coordinates of the target reflection point is within a preset threshold as one target cluster.
The clustering algorithm in the embodiment of the present application may be a K-means clustering algorithm, a Density-based clustering with noise (DBSCAN) algorithm, a Balanced iterative reduction and clustering with hierarchical approach (BIRCH) algorithm, a STING algorithm model, a GMM gaussian mixture model, and the like. The embodiment of the present application does not set any limit to this. In particular, the DBSCAN clustering algorithm is directed to a key parameter field value E of the algorithm may be equal to 1.0, a minimum number MinPts of core object sample points may be equal to 10, and when a plurality of human objects exist in a detection range and the mutual distance between the human objects is large, the clustering algorithm may sense the plurality of detection objects.
In some embodiments, as shown in fig. 4, the method for determining candidate valid target points in a target cluster specifically includes the following steps:
s321, determining the number of the reflection points in the target cluster;
s322, if the number of the reflection points in the target cluster is larger than a first preset number threshold, determining the reflection points in the target cluster as candidate effective target points.
S323, if the number of the reflection points in the target cluster is smaller than a second preset number threshold, determining that the reflection points in the target cluster are false points, wherein the first preset number threshold is larger than the second preset number threshold.
S324, if the number of the reflection points in the target cluster is not greater than a first preset number threshold and not less than a second preset number threshold, determining the signal-to-noise ratio of each reflection point in the target cluster, and determining whether the reflection point is a candidate target point according to the signal-to-noise ratio of each reflection point;
if the signal-to-noise ratio of the reflection point is greater than a preset signal-to-noise ratio threshold, and the preset signal-to-noise ratio threshold is the third threshold in fig. 4, the reflection point is a candidate effective target point set; and if the signal-to-noise ratio of the reflection point is not greater than the preset signal-to-noise ratio threshold value, the reflection point is the false point.
In this embodiment, the processor may determine whether the number of reflection points in each target cluster is greater than a first preset number threshold; if the number of the reflection points in the target cluster is larger than a first preset number threshold, determining that all the reflection points in the target cluster are candidate effective target point sets; if the number of the reflection points in the target cluster is smaller than a second preset number threshold, determining that all the reflection points in the target cluster are false points, wherein the second preset number threshold is smaller than the first preset number threshold; and if the number of the reflection points in the target cluster is not greater than the first preset number threshold and not smaller than the second preset number threshold, determining whether each reflection point in the target cluster is a candidate effective target point set or not according to the signal-to-noise ratio of each reflection point in the target cluster. For example, the snr of each reflection point may be compared with a preset snr threshold, and if the snr of a reflection point is greater than the preset snr threshold, the reflection point is determined as a candidate valid target point set, and if the snr of the reflection point is less than or equal to the preset snr threshold, the reflection point is determined as a false point.
Since the number of reflection points in the target cluster where the dummy point is located is usually small, and the signal-to-noise ratio of the dummy point is low. Therefore, the embodiment of the application can determine whether the reflection points in the target cluster are candidate effective target points according to the number of all the reflection points in the target cluster and the signal-to-noise ratio of each reflection point in the target cluster, so as to preliminarily filter the false points in the reflection points. And a set formed by candidate effective target points in the same target cluster is a candidate effective target point set, and the candidate effective targets can be determined through the candidate effective target point set.
In some embodiments, the first preset number threshold, the second preset number threshold, and the preset signal-to-noise ratio threshold are preset thresholds; in other embodiments, the processor may extract feature quantities of a target cluster corresponding to the designated false target, and determine a first preset number threshold, a second preset number threshold, and a preset signal-to-noise ratio threshold according to the extracted feature quantities. For example, the number of reflection points in the target cluster where the dummy point is located is usually not greater than 3, so the second preset number threshold may be set to 3; the signal-to-noise ratio of the false point is usually less than-50 dB, so that the preset signal-to-noise ratio threshold value can be set to-50 dB; in addition, the first preset number threshold may be specifically set to 5.
As shown in fig. 3b, in some embodiments, in order to more accurately screen out the effective targets, the method further comprises:
s33, obtaining a candidate effective target point set of each sliding window in a specified time window, wherein the specified time window comprises at least one sliding window;
and S34, if the cumulative frequency of the same target appearing in each candidate effective target point set is greater than a preset frequency threshold value, determining that the target is an effective target.
In this embodiment, the time length of the designated time window is greater than the time length of one sliding window, and the time length of the designated time window may be a preset length, which may be set by a person skilled in the art according to actual requirements. The processor can determine sliding windows in the designated time window, determine a candidate effective target point set extracted from each sliding window, and determine a candidate effective target as an effective target if the number of times that the same candidate effective target is extracted by the sliding windows is greater than a preset number threshold; and if the times of extracting the same candidate effective target through the sliding window are not more than a preset time threshold, determining that the candidate effective target point set is a false point.
Referring to fig. 5, fig. 5 schematically shows a schematic diagram of sampling data through a sliding window. The time window 500 is specified to be 5T in duration, and each sliding window is specified to be T in duration. Moving the sliding window one time unit T forward to form a new time window; for example, the sliding window 501 is moved forward by one time unit T to form a sliding window 502, and the sliding window 502 is moved forward by one time unit T to form a sliding window 503. In the designated time window 500, a sliding window forms a new sliding window one time unit T ahead, and 5 sliding windows, namely a sliding window 501, a sliding window 502, a sliding window 503, a sliding window 504 and a sliding window 505, are included in the designated time window; accordingly, the sets of the targets extracted according to the 5 sliding windows are set a, set B, set C, set D, and set E, respectively. Wherein, the set a is { a, B, C, E, f }, the set B is { a, C, E, f, D }, the set C is { a, E, f, D, g }, the set D is { a, f, D, g, m }, and the set E is { a, E, f, D, g }.
As shown in table one, the candidate effective targets in the reflection points collected according to the sliding window 501 are a, c, and f; according to the candidate effective targets a, e and f in the reflection points collected by the sliding window 502; the candidate effective targets in the reflection points collected according to the sliding window 503 are a, f, d and g; the candidate valid targets collected according to the sliding window 504 are a, f, d, g, and m; candidate valid targets f, d, and g are collected according to the sliding window 505. The processor may determine that the sliding windows where the target a is sampled and the target a is the candidate valid target are the sliding window 501, the sliding window 502, the sliding window 503 and the sliding window 504, and therefore, the processor may calculate that the number of the sliding windows where the target a appears and the target a is the candidate valid target is 4, that is, the cumulative number of occurrences of the candidate valid target point set is 4. If the preset number threshold in this embodiment is 3, the point a is the second valid point. The processor may also determine that a sliding window where target c is sampled and is a candidate valid target point set is a sliding window 501; therefore, the processor may calculate the number of times that the target c is taken through the sliding window and is a candidate valid target point set to be 1, and the target c is a false target because 1 is smaller than a preset number threshold 3.
Table one: sliding the window and extracting the target from the sliding window.
The embodiment of the invention also provides a target identification device, which is applied to electronic equipment, such as the millimeter wave radar 200 in fig. 2. Fig. 6 schematically shows the structure of the object recognition apparatus, and as shown in fig. 6, the object recognition apparatus 700 includes:
an extraction module 701, where the extraction module 701 is configured to extract reflection point data of a detection object through a sliding window, where the sliding window is a time window for sampling the reflection point data;
a determining module 702, configured to determine at least one candidate effective target point set according to the reflection point data in the sliding window, where a target corresponding to the candidate effective target point set is a candidate effective target.
In some embodiments, the reflection point data includes a signal-to-noise ratio of the reflection point, and the determining module 702 is specifically configured to: clustering the reflection point data extracted according to the same sliding window so as to divide the reflection point data into at least one target cluster;
determining candidate effective target points in the reflecting points according to the number of the reflecting points in the target cluster and the signal-to-noise ratio of each reflecting point;
and adding the candidate effective target points into the candidate effective target point set, wherein the target corresponding to the candidate effective target point set is a candidate effective target.
In some embodiments, the determining the candidate effective target point in the reflection points according to the number of reflection points in the target cluster and the signal-to-noise ratio of each reflection point specifically includes:
if the number of the reflection points in the target cluster is greater than a first preset number threshold, determining that the reflection points in the target cluster are the candidate effective target points.
In some embodiments, the determining the candidate effective target point in the reflection points according to the number of reflection points in the target cluster and the signal-to-noise ratio of each reflection point specifically further includes:
if the number of the reflection points in the target cluster is smaller than a second preset number threshold, determining that the reflection points in the target cluster are false points, wherein the first preset number threshold is larger than the second preset number threshold.
In some embodiments, the determining the candidate effective target point in the reflection points according to the number of reflection points in the target cluster and the signal-to-noise ratio of each reflection point specifically further includes:
if the number of the reflection points in the target cluster is not greater than the first preset number threshold and not less than the second preset number threshold, determining candidate effective target points in the reflection points according to the signal-to-noise ratio of each reflection point in the target cluster;
the determining a candidate effective target point in the reflection points according to the signal-to-noise ratio of each reflection point in the cluster specifically includes:
if the signal-to-noise ratio of the reflection point is greater than a preset signal-to-noise ratio threshold value, the reflection point is a candidate effective target point;
and if the signal-to-noise ratio of the reflection point is not greater than the preset signal-to-noise ratio threshold value, the reflection point is the false point.
Referring to fig. 7, in some embodiments, the apparatus 700 for identifying a target further includes:
an obtaining module 703, where the obtaining module 703 is configured to obtain a candidate valid target point set of each sliding window in a specified time window, where the specified time window includes at least one sliding window;
a determining module 704, where the determining module 704 is configured to determine that the target is an effective target if the cumulative number of times that the same target appears in each candidate effective target point set is greater than a preset number threshold.
A determining module 705, where the determining module 705 is configured to determine that the target is a false target if the cumulative number of times that the same target appears in each candidate valid target point set is less than or equal to the preset number threshold.
In some embodiments, the reflection point data includes rectangular coordinates and/or speed of the reflection point, and the clustering processing of the reflection point data extracted according to the same sliding window specifically includes:
and clustering the reflection point data extracted from the same sliding window based on the rectangular coordinate and/or the speed of the reflection point.
The embodiment of the application provides a target identification method and a target identification device, which can acquire reflection point data of a detection object according to a received reflection signal, determine at least one candidate effective target point set according to the reflection point data extracted according to a sliding window, and filter out false points in reflection points for the first time by acquiring the candidate effective target point set; if the accumulated times of the same target appearing in each candidate effective target point set are more, the target is a candidate target, and the time for the candidate target to appear is longer. Therefore, the invention can screen the candidate target ineffective target with longer occurrence time according to the accumulated times of the same target appearing in each candidate effective target point set, thereby filtering the candidate target with shorter occurrence time and improving the accuracy and efficiency of target identification.
Fig. 8 schematically shows a hardware configuration of an electronic device that executes the identification method of the object of the present application. As shown in fig. 8, in some embodiments electronic device 800 comprises: one or more processors 81 and a memory 82, with one processor 81 being an example in fig. 2.
The processor 81 and the memory 82 may be connected by a bus or other means, and the bus connection is exemplified in fig. 8.
The memory 82, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The processor 81 executes various functional applications and data processing of the millimeter wave radar, that is, the identification method of the object of the above-described method embodiment, by executing nonvolatile software programs, instructions, and modules stored in the memory 82.
The memory 82 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the instant message alert device, and the like. Further, the memory 82 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 82 may optionally include memory located remotely from the processor 81, which may be connected to the instant message reminder device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory 82 and, when executed by the one or more processors 81, perform the method of identifying objects in any of the above-described method embodiments, e.g., performing the above-described method steps S31-S32 in fig. 3a, S31-S34 in fig. 3 b; the functions of the modules 701 and 702 in fig. 6 and the functions of the modules 701 and 705 in fig. 7 are realized.
The millimeter wave radar can execute the method provided by the embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method. For technical details that are not described in detail in this embodiment, reference may be made to the method provided by the embodiment of the present invention.
Embodiments of the present application also provide a non-transitory computer-readable storage medium storing computer-executable instructions, which when executed by one or more processors 81, perform the method for identifying targets in any of the above-described method embodiments, for example, performing the above-described method steps S31 to S32 in fig. 3a, and S31 to S34 in fig. 3 b; the functions of the modules 701-702 in fig. 6 and the modules 701-705 in fig. 7 are realized.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a general hardware platform, and certainly can also be implemented by hardware. It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a computer readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; within the idea of the invention, also technical features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for identifying an object, applied to an electronic device, is characterized in that the method comprises the following steps:
extracting reflection point data of a detection object through a sliding window, wherein the sliding window is a time window for sampling the reflection point data;
and determining at least one candidate effective target point set according to the reflection point data in the sliding window, wherein the target corresponding to the candidate effective target point set is a candidate effective target.
2. The method of identifying an object of claim 1, wherein the reflection point data comprises a signal-to-noise ratio of the reflection points, and wherein determining at least one set of candidate valid object points from the reflection point data within the sliding window comprises:
clustering the reflection point data extracted according to the same sliding window so as to divide the reflection point data into at least one target cluster;
determining candidate effective target points in the reflecting points according to the number of the reflecting points in the target cluster and the signal-to-noise ratio of each reflecting point;
and adding the candidate effective target points into the candidate effective target point set, wherein the target corresponding to the candidate effective target point set is a candidate effective target.
3. The method for identifying a target according to claim 2, wherein the determining the candidate valid target points from the number of reflection points in the target cluster and the signal-to-noise ratio of each reflection point comprises:
if the number of the reflection points in the target cluster is greater than a first preset number threshold, determining that the reflection points in the target cluster are the candidate effective target points.
4. The method for identifying a target according to claim 3, wherein the determining the candidate valid target points of the reflection points according to the number of reflection points in the target cluster and the signal-to-noise ratio of each reflection point further comprises:
if the number of the reflection points in the target cluster is smaller than a second preset number threshold, determining that the reflection points in the target cluster are false points, wherein the first preset number threshold is larger than the second preset number threshold.
5. The method for identifying a target according to claim 4, wherein the determining the candidate valid target points of the reflection points according to the number of reflection points in the target cluster and the signal-to-noise ratio of each reflection point further comprises:
if the number of the reflection points in the target cluster is not greater than the first preset number threshold and not less than the second preset number threshold, determining candidate effective target points in the reflection points according to the signal-to-noise ratio of each reflection point in the target cluster;
the determining candidate effective target points in the reflection points according to the signal-to-noise ratio of each reflection point in the target cluster includes:
if the signal-to-noise ratio of the reflection point is greater than a preset signal-to-noise ratio threshold value, the reflection point is a candidate effective target point;
and if the signal-to-noise ratio of the reflection point is not greater than the preset signal-to-noise ratio threshold value, the reflection point is the false point.
6. The method of identifying objects according to any one of claims 1 to 5, wherein the method further comprises:
obtaining a candidate effective target point set of each sliding window in a specified time window, wherein the specified time window comprises at least one sliding window;
and if the cumulative frequency of the same target appearing in each candidate effective target point set is greater than a preset frequency threshold value, determining that the target is an effective target.
7. The method for identifying objects according to claims 1-5, wherein the reflection point data comprises rectangular coordinates and/or velocity of the reflection point, and the clustering the reflection point data extracted according to the same sliding window comprises:
and clustering the reflection point data extracted from the same sliding window based on the rectangular coordinate and/or the speed of the reflection point.
8. An apparatus for identifying an object, applied to an electronic device, the apparatus comprising:
the extraction module is used for extracting reflection point data of a detection object through a sliding window, and the sliding window is a time window for sampling the reflection point data;
and the determining module is used for determining at least one candidate effective target point set according to the reflection point data in the sliding window, and the target corresponding to the candidate effective target point set is a candidate effective target.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the first and the second end of the pipe are connected with each other,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method of identifying an object as claimed in any one of claims 1 to 7.
10. A non-transitory computer-readable storage medium storing computer-executable instructions capable, when executed, of performing the method of identifying an object of any one of claims 1-7.
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