CN113109798B

CN113109798B - Target detection method, device, computer equipment and storage medium

Info

Publication number: CN113109798B
Application number: CN202110224360.XA
Authority: CN
Inventors: 于晓爽; 晁淑媛
Original assignee: Freetech Intelligent Systems Co Ltd
Current assignee: Freetech Intelligent Systems Co Ltd
Priority date: 2021-03-01
Filing date: 2021-03-01
Publication date: 2024-07-12
Anticipated expiration: 2041-03-01
Also published as: CN113109798A

Abstract

The application relates to a target detection method, a device, a computer device and a storage medium, wherein the method comprises the following steps: acquiring predicted motion information of a current motion point trace and a radar tracking target, and determining a target motion point trace corresponding to the radar tracking target based on the predicted motion information and the current motion point trace, wherein the predicted motion information comprises a predicted distance, a predicted speed and a predicted azimuth; acquiring a target range-Doppler position corresponding to a target motion trace, and acquiring an adjacent range-Doppler position corresponding to the target range-Doppler position; and acquiring interference suppression coefficients based on the adjacent range-Doppler positions, and acquiring current position information of the radar tracking target based on the interference suppression coefficients, the target range-Doppler positions and the predicted azimuth angles. The method solves the problem that the motion point trace of the same-distance same-speed weak target cannot be accurately detected in the related art.

Description

Target detection method, device, computer equipment and storage medium

Technical Field

The present application relates to the field of intelligent driving technologies, and in particular, to a target detection method, apparatus, computer device, and storage medium.

Background

With the development of intelligent driving technology, blind spot monitoring (BSD) and Lane Change Assist (LCA) based on millimeter wave radar have become essential functions that Advanced Driving Assist Systems (ADAS) must possess. The method is characterized in that the continuous and stable target motion track is obtained on the premise of realizing the blind spot monitoring alarm function and the lane change auxiliary alarm function, and the radar signal processing end is required to be capable of stably detecting the target.

In the related art, a peak detection method is adopted to detect the target, however, due to the working principle of the millimeter wave radar, two targets with the same distance and the same speed usually appear, if the echo energy of one target is far stronger than that of the other target, the target with weak echo energy cannot be normally detected, so that the problems of trace loss and trace interruption of the weak target point are caused, and the problems of alarm leakage, alarm delay or alarm interruption are further caused.

At present, aiming at the problem that the motion points of the same-distance same-speed weak targets cannot be accurately detected in the related art, no effective solution is proposed yet.

Disclosure of Invention

The embodiment of the application provides a target detection method, a target detection device, computer equipment and a storage medium, which at least solve the problem that in the related art, the motion trail of a same-distance same-speed weak target cannot be accurately detected.

In a first aspect, an embodiment of the present application provides a target detection method, where the method includes:

Acquiring predicted motion information of a current motion point trace and a radar tracking target, and determining a target motion point trace corresponding to the radar tracking target based on the predicted motion information and the current motion point trace, wherein the predicted motion information comprises a predicted distance, a predicted speed and a predicted azimuth angle;

Acquiring a target range-Doppler position corresponding to the target motion point trace, and acquiring an adjacent range-Doppler position corresponding to the target range-Doppler position, wherein the target range-Doppler position comprises the position of the target motion point trace in a range-Doppler matrix, and the range-Doppler matrix is constructed based on radar echo data;

and acquiring an interference suppression coefficient based on the adjacent range-Doppler position, and acquiring current position information of the radar tracking target based on the interference suppression coefficient, the target range-Doppler position and the predicted azimuth angle.

In some of these embodiments, the obtaining the predicted motion information of the radar tracking target includes:

acquiring a motion point trace prediction result of the current radar tracking target under a rectangular coordinate system, wherein the motion point trace prediction result comprises a current position prediction result and a current speed prediction result;

Acquiring current vehicle speed, vehicle radar installation information and conversion relation between a polar coordinate system and a rectangular coordinate system, wherein the vehicle radar installation information comprises a vehicle radar installation angle and a vehicle radar installation position;

And converting the motion point track prediction result from a rectangular coordinate system to a polar coordinate system based on the conversion relation, the current vehicle speed and the vehicle radar installation information to obtain the predicted motion information.

In some embodiments, the determining the target motion trajectory corresponding to the radar tracking target based on the predicted motion information and the current motion trajectory includes:

acquiring preset range-doppler parameters, wherein the preset range-doppler parameters comprise a preset range value and a preset doppler velocity;

Determining a current trace point search area based on the predicted distance, the predicted speed and the preset distance Doppler parameter;

And determining the target movement track from the current movement track based on the current track searching area and the predicted azimuth angle.

In some of these embodiments, the determining the target motion profile from the current motion profile based on the current profile search area and the predicted azimuth comprises:

Acquiring a point track azimuth corresponding to the current movement point track, and acquiring an azimuth difference between the point track azimuth and the predicted azimuth;

Judging whether the current motion track is in the current track searching area or not, and judging whether an azimuth angle difference value corresponding to the current motion track is larger than a preset difference value threshold value or not;

and if the current motion track is in the current track searching area and the azimuth angle difference value corresponding to the current motion track is larger than the preset difference value threshold, determining that the current motion track is the target motion track.

In some of these embodiments, the number of adjacent range-doppler locations is a plurality; the obtaining the interference suppression coefficient based on the adjacent range-doppler locations, and the obtaining the current location information of the radar tracking target based on the interference suppression coefficient, the target range-doppler location, and the predicted azimuth angle includes:

Acquiring an interference suppression coefficient corresponding to each adjacent range-Doppler position based on the guide vector and each adjacent range-Doppler position; the adjacent range-Doppler position comprises an adjacent position of the target motion trace in a range-Doppler matrix, an adjacent range value corresponding to the adjacent position and an adjacent Doppler speed;

Acquiring a target azimuth spectrum corresponding to the target distance Doppler position according to the target distance Doppler position and each interference suppression coefficient, and obtaining a plurality of target azimuth spectrums; the target range-Doppler position also comprises a target range value and a target Doppler speed corresponding to the position of the target motion point trace in a range-Doppler matrix;

And acquiring current position information of the radar tracking target based on a plurality of target azimuth spectrums and the predicted azimuth angles, wherein the current position information comprises the current azimuth angle of the radar tracking target.

In some of these embodiments, the obtaining current location information of the radar tracking target based on a plurality of the target azimuth spectra and the predicted azimuth comprises:

acquiring a first peak value and a second peak value in each target azimuth spectrum and a first peak azimuth corresponding to the first peak value;

Acquiring a peak energy ratio corresponding to the first peak value and the second peak value, and judging whether the peak energy ratio is larger than a preset energy ratio threshold value or not to obtain a first judgment result;

acquiring an absolute value of a difference value of the azimuth angles corresponding to the first peak azimuth angle and the predicted azimuth angle, and judging whether the absolute value of the difference value is smaller than a preset absolute value threshold value or not to obtain a second judging result;

and acquiring the current azimuth angle of the radar tracking target based on the first judgment result and the second judgment result.

In some of these embodiments, prior to the acquiring the predicted motion information of the radar tracking target, the method further comprises:

acquiring a historical motion point trace of the radar tracking target, and determining a current frame point trace prediction range of the radar tracking target based on the historical motion point trace;

Searching whether a motion point exists in the current frame point prediction range, and if the motion point exists in the current frame point prediction range, determining the current motion point successfully related to the radar tracking target;

And if the motion point trace does not exist in the current frame point trace prediction range, determining the current motion point trace which is not related to the radar tracking target, and acquiring the predicted motion information of the current radar tracking target based on the historical motion point trace.

In a second aspect, an embodiment of the present application provides an object detection apparatus, including:

the target point trace determining module is used for obtaining the current motion trace and the predicted motion information of the radar tracking target, and determining the target motion trace corresponding to the radar tracking target based on the predicted motion information and the current motion trace, wherein the predicted motion information comprises a predicted distance, a predicted speed and a predicted azimuth angle;

The adjacent position acquisition module is used for acquiring a target range-Doppler position corresponding to the target motion point trace and acquiring an adjacent range-Doppler position corresponding to the target range-Doppler position, wherein the target range-Doppler position comprises the position of the target motion point trace in a range-Doppler matrix, and the range-Doppler matrix is constructed based on radar echo data;

And the target position detection module is used for acquiring an interference suppression coefficient based on the adjacent range-Doppler position and acquiring the current position information of the radar tracking target based on the interference suppression coefficient, the target range-Doppler position and the predicted azimuth angle.

In a third aspect, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the object detection method according to the first aspect.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the object detection method according to the first aspect described above.

Compared with the related art, the target detection method, the device, the computer equipment and the storage medium provided by the embodiment of the application have the advantages that the predicted motion information of the current motion point trace and the radar tracking target is obtained, the target motion point trace corresponding to the radar tracking target is determined based on the predicted motion information and the current motion point trace, and the predicted motion information comprises the predicted distance, the predicted speed and the predicted azimuth angle; acquiring a target distance Doppler position corresponding to a target motion point trace, and acquiring an adjacent distance Doppler position corresponding to the target distance Doppler position, wherein the target distance Doppler position comprises the position of the target motion point trace in a distance Doppler matrix, and the distance Doppler matrix is constructed based on radar echo data; and acquiring interference suppression coefficients based on the adjacent range-Doppler positions, and acquiring current position information of the radar tracking target based on the interference suppression coefficients, the target range-Doppler positions and the predicted azimuth angles. According to the method, the interference suppression coefficient is obtained through the adjacent distance Doppler position, and the strong target is suppressed based on the interference suppression coefficient, so that the detection of the same-distance same-speed weak target is realized, and the problem that the motion trail of the same-distance same-speed weak target cannot be accurately detected in the related art is solved.

The details of one or more embodiments of the application are set forth in the accompanying drawings and the description below to provide a more thorough understanding of the other features, objects, and advantages of the application.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:

FIG. 1 is a flow chart of a target detection method according to an embodiment of the application;

FIG. 2a is a flowchart of obtaining predicted motion information of a radar tracking target according to an embodiment of the present application;

FIG. 2b is a schematic diagram of obtaining predicted motion information of a radar tracking target according to an embodiment of the present application;

FIG. 3 is a flow chart of determining a target motion profile based on predicted motion information and a current motion profile in an embodiment of the present application;

FIG. 4 is a flowchart of determining a target motion trajectory based on a current trajectory search region and a predicted azimuth in an embodiment of the present application;

FIG. 5 is a flowchart of acquiring current position information of a radar tracking target based on an interference suppression coefficient, a target range-Doppler position and a predicted azimuth angle in an embodiment of the present application;

FIG. 6 is a flowchart of acquiring current position information of a radar tracking target based on a plurality of target azimuth spectrums and predicted azimuth angles in an embodiment of the present application;

FIG. 7 is a flow chart of a current motion trace of an associated radar tracking target in an embodiment of the present application;

FIG. 8 is a schematic diagram of a related art application scenario;

fig. 9a is a schematic diagram of an application scenario of a target detection method according to an embodiment of the present application;

figure 9b is a schematic diagram of a range-doppler position versus azimuth spectrum for a target vehicle in accordance with an embodiment of the present application;

FIGS. 10 a-10 h are schematic diagrams of target azimuth spectra after interference suppression processing in an embodiment of the present application;

FIG. 11 is a block diagram of an object detection device according to an embodiment of the present application;

Fig. 12 is a schematic hardware structure of a computer device according to an embodiment of the present application.

Detailed Description

The present application will be described and illustrated with reference to the accompanying drawings and examples in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application. All other embodiments, which can be made by a person of ordinary skill in the art based on the embodiments provided by the present application without making any inventive effort, are intended to fall within the scope of the present application.

It is apparent that the drawings in the following description are only some examples or embodiments of the present application, and it is possible for those of ordinary skill in the art to apply the present application to other similar situations according to these drawings without inventive effort. Moreover, it should be appreciated that while such a development effort might be complex and lengthy, it would nevertheless be a routine undertaking of design, fabrication, or manufacture for those of ordinary skill having the benefit of this disclosure, and thus should not be construed as having the benefit of this disclosure.

Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is to be expressly and implicitly understood by those of ordinary skill in the art that the described embodiments of the application can be combined with other embodiments without conflict.

Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs. The terms "a," "an," "the," and similar referents in the context of the application are not to be construed as limiting the quantity, but rather as singular or plural. The terms "comprising," "including," "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to only those steps or elements but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. The terms "connected," "coupled," and the like in connection with the present application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The term "plurality" as used herein means two or more. "and/or" describes an association relationship of an association object, meaning that there may be three relationships, e.g., "a and/or B" may mean: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. The terms "first," "second," "third," and the like, as used herein, are merely distinguishing between similar objects and not representing a particular ordering of objects.

The various techniques described in this disclosure may be applied to MIMO (Multiple Input Multiple Output ) based radar and various vehicle object detection systems and devices to implement object detection functions during driving.

Fig. 1 is a flowchart of a target detection method according to an embodiment of the application, as shown in fig. 1, the flowchart includes the following steps.

Step S110, obtaining the current motion point trace and the predicted motion information of the radar tracking target, and determining the target motion point trace corresponding to the radar tracking target based on the predicted motion information and the current motion point trace, wherein the predicted motion information comprises a predicted distance, a predicted speed and a predicted azimuth angle.

The current motion point represents the current frame motion point acquired by the processor. The predicted motion information represents a predicted result of the current motion state of the radar tracking target.

Step S120, obtaining a target range-Doppler position corresponding to the target motion trace, and obtaining an adjacent range-Doppler position corresponding to the target range-Doppler position, wherein the target range-Doppler position comprises the position of the target motion trace in a range-Doppler matrix, and the range-Doppler matrix is constructed based on radar echo data.

The adjacent range-doppler locations represent the range-doppler locations in the range-doppler matrix that are adjacent to the location where the target motion trace is located. The range-doppler matrix is based on a two-dimensional fast fourier transform (Fast Fourier transform, FFT) process of the radar echo data.

Before the target distance Doppler position corresponding to the target motion point trace is acquired, a distance Doppler matrix is constructed according to the acquired current motion point trace, then the position of the target motion point trace in the distance Doppler matrix is found according to the coordinate information corresponding to the target motion point trace, and the adjacent position around the position of the target motion point trace in the distance Doppler matrix is used as the adjacent distance Doppler position.

Step S130, obtaining interference suppression coefficients based on the adjacent range-Doppler positions, and obtaining current position information of the radar tracking target based on the interference suppression coefficients, the target range-Doppler positions and the predicted azimuth angles.

The target range-Doppler position also comprises target range-Doppler data corresponding to the position of the target motion trace in the range-Doppler matrix. The adjacent range-doppler locations include adjacent locations of the target motion trace locations in the range-doppler matrix and adjacent range-doppler data corresponding to the adjacent locations.

It should be noted that, based on the adjacent range-doppler positions, an interference suppression coefficient may be calculated, where the interference suppression coefficient is used to cancel the strong target echo energy radiated onto the adjacent positions of the target range-doppler positions, so as to implement the suppression processing on the strong target.

Through the steps S110 to S130, obtaining the current motion trail and the predicted motion information of the radar tracking target, and determining the target motion trail corresponding to the radar tracking target based on the predicted motion information and the current motion trail; acquiring a target range-Doppler position corresponding to a target motion trace, and acquiring an adjacent range-Doppler position corresponding to the target range-Doppler position; and acquiring interference suppression coefficients based on the adjacent range-Doppler positions, and acquiring current position information of the radar tracking target based on the interference suppression coefficients, the target range-Doppler positions and the predicted azimuth angles. Aiming at the problem that in the prior art, two targets with the same distance and the same speed are detected by a radar, the echo energy of one target is far stronger than that of the other target, and then the target with weaker echo energy cannot be normally detected generally, the method and the device solve the problem that in the related art, the moving point trace of the target with the same distance and the same speed cannot be accurately detected by acquiring the adjacent distance Doppler position corresponding to the distance Doppler position of the current target of the radar tracking target (namely, the target with weaker echo energy) and calculating the interference suppression coefficient based on the adjacent distance Doppler position so as to suppress the strong target based on the interference suppression coefficient, thereby eliminating the influence of the echo energy of the strong target on the detection of the radar tracking target, and further realizing the detection of the target with the same distance and the same speed (namely, the radar tracking target).

In some embodiments, fig. 2a is a flowchart of acquiring predicted motion information of a radar tracking target according to an embodiment of the present application, and as shown in fig. 2a, the flowchart includes the following steps.

Step S210, a motion point trace prediction result of the current radar tracking target under a rectangular coordinate system is obtained, wherein the motion point trace prediction result comprises a current position prediction result and a current speed prediction result.

The current position prediction result is a current position prediction coordinate (x, y), and the current speed prediction result is a current speed prediction coordinate (v _x,v_y).

Step S220, obtaining the current vehicle speed, vehicle radar installation information and conversion relation between a polar coordinate system and a rectangular coordinate system, wherein the vehicle radar installation information comprises a vehicle radar installation angle and a vehicle radar installation position.

Wherein, the vehicle radar installation angle may be denoted as M _angle, and the vehicle radar installation position may be denoted as (M _x,M_y).

And step S230, converting the motion point track prediction result from a rectangular coordinate system to a polar coordinate system based on the conversion relation, the current vehicle speed and the vehicle radar installation information to obtain the predicted motion information.

It should be noted that, the track processing process of the radar tracking target is generally performed in a rectangular coordinate system, the echo data received by the radar is information of a polar coordinate system, and the coordinates of the current moving point track obtained from the echo data are also in the polar coordinate system, so that the moving point track prediction result needs to be converted from the rectangular coordinate system to the polar coordinate system, so that the subsequent step of determining the target moving point track from the current moving point track can be performed.

Through the steps S210 to S230, the motion trail prediction result is down-converted from the rectangular coordinate system to the polar coordinate system based on the conversion relation, the current vehicle speed and the vehicle radar installation information, so as to obtain the predicted motion information, so that the target motion trail can be conveniently determined from the current motion trail.

In some embodiments, fig. 2b is a schematic azimuth diagram of obtaining predicted motion information of a radar tracking target in the embodiment of the present application, as shown in fig. 2b, the predicted coordinates (x, y) of the current position in a rectangular coordinate system are converted into positions in the radar coordinate system, that is, a predicted distance R _idx, a predicted velocity (that is, a predicted doppler velocity) Dop _iax, and a predicted azimuth angle θ _pre, and specific conversion formulas are as follows:

Wherein Δr and Δv are a distance resolution unit and a speed resolution unit, respectively, and ROUND represents rounding the values. Doppler velocity (Doppler velocity) represents the radial velocity of a target relative to radar measured based on Doppler principles.

It should be noted that, after performing two-dimensional fast fourier transform processing on the acquired echo original ADC data, the radar processing end may obtain a two-dimensional matrix (i.e. a range-doppler matrix), where one dimension of the two-dimensional matrix corresponds to a distance, and the other dimension corresponds to a doppler velocity, and the two-dimensional matrix is called RV graph (R represents a distance, V represents a velocity). Each element in the two-dimensional matrix corresponds to a range-doppler position, and different range-doppler positions correspond to different range-doppler velocities. For example, the two-dimensional matrix has a size of n×m, i.e., N distance cells, M doppler cells. One distance unit corresponds to distance Δr and one doppler unit corresponds to velocity Δv, and assuming that the range-doppler position of the target is (m, n), the distance and doppler velocity corresponding to the target are m×Δr and n×Δv, respectively.

In some embodiments, fig. 3 is a flowchart of determining a target motion profile based on predicted motion information and a current motion profile according to an embodiment of the present application, and the flowchart includes the following steps as shown in fig. 3.

In step S310, a preset range-doppler parameter is obtained, where the preset range-doppler parameter includes a preset range value and a preset doppler velocity.

The preset distance value may be denoted Rwidth and the preset doppler velocity may be denoted Dop _width.

Step S320, determining the current trace search area based on the predicted distance, the predicted speed and the preset distance Doppler parameter.

The predicted velocity is a predicted doppler velocity, the predicted distance may be represented as R _idx, and the predicted doppler velocity may be represented as Dop _idx, that is, the predicted distance doppler position of the radar tracking target is (R _idx,Dop_idx).

Specifically, the current trace search area is divided based on the predicted distance, the predicted speed and the preset distance doppler parameter, that is, the distance doppler position corresponding to the current trace search area is (R _idx±R_width,Dop_idx±Dop_width), that is, the current trace search area is a rectangular area formed by two vertices with (R _idx-R_width,Dop_iax-Dop_width) and (R _idx+R_width,Dop_idx+Dop_width) as diagonal lines.

Step S330, determining the target movement track from the current movement track based on the current track searching area and the predicted azimuth angle.

In some embodiments, fig. 4 is a flowchart of determining a target motion track based on a current track search area and a predicted azimuth, and the flowchart includes the following steps in the embodiment of the application, as shown in fig. 4.

Step S410, a track azimuth corresponding to the current motion track is obtained, and an azimuth difference between the track azimuth and the predicted azimuth is obtained.

Step S420, judging whether the current motion track is in the current track searching area, and judging whether the azimuth angle difference value corresponding to the current motion track is larger than a preset difference value threshold value.

Step S430, if the current motion track is in the current track search area and the azimuth angle difference corresponding to the current motion track is greater than the preset difference threshold, determining the current motion track as the target motion track.

It should be noted that, the pre-selected current motion point track in the current point track searching area may be screened first, and then the target motion point track may be determined from the pre-selected current motion point track according to the difference threshold. Or firstly, judging and screening a preselected current motion point trace from the current motion point traces according to the difference threshold value, and then determining a target motion point trace from the preselected current motion point trace according to the current point trace searching area. Or traversing all the current motion points to judge the current point searching area and the difference threshold value, and determining the target motion point from the current motion points according to the two judgment results. The application is not limited to the execution sequence of the two judgments, and can be executed successively or simultaneously, as long as the target movement track can be determined from the current movement track without error.

In the prior art, in order to improve the resolution of the angle measurement, a vehicle-mounted millimeter wave radar mostly adopts sparse array, so that the side lobe of the azimuth spectrum is higher. When two targets with the same distance and the same speed are present, if the echo energy of one target is far stronger than that of the other target, the peak value of the azimuth spectrum of the weak target is usually lower than the side lobe of the azimuth spectrum of the strong target, and cannot be effectively detected.

In some of these embodiments, the number of adjacent range-doppler locations is a plurality; fig. 5 is a flowchart of acquiring current position information of a radar tracking target based on an interference suppression coefficient, a target range-doppler position and a predicted azimuth angle according to an embodiment of the present application, and as shown in fig. 5, the flowchart includes the following steps.

Step S510, based on the guiding vector and each adjacent distance Doppler position, obtaining an interference suppression coefficient corresponding to each adjacent distance Doppler position; the adjacent range-doppler locations include adjacent locations of the target motion trace locations in the range-doppler matrix and adjacent range values and adjacent doppler velocities corresponding to the adjacent locations.

The interference suppression coefficient may be expressed as w (θ), and a (θ) is a steering vector (column vector) in the azimuth θ direction. Steering vectors are responses of all array elements of an array antenna to a narrowband source with unit energy, and are an azimuthal function.

It should be noted that, after the radar receives the echo data, two-dimensional fast fourier transform processing is performed on the echo data, so as to obtain a two-dimensional matrix. If the radar has N channels, N two-dimensional matrices are obtained in one frame, and the range-doppler position data corresponding to the N two-dimensional matrices form an azimuth signal corresponding to the range-doppler position, that is, the same range-doppler position in the range-doppler matrix corresponds to multiple sets of range-doppler position data, and multiple sets of range-doppler position data form an azimuth signal corresponding to the range-doppler position.

Specifically, a target azimuth dimension signal corresponding to the adjacent range-doppler position is acquired and denoted as s. And acquiring adjacent azimuth dimension signals corresponding to each adjacent range-Doppler position, and recording the signals as s _ref, wherein s and s _ref are column vectors. Based on the steering vector and the adjacent azimuth dimension signal corresponding to each adjacent range-doppler position, obtaining an interference suppression coefficient corresponding to each adjacent range-doppler position, namely, an interference suppression coefficient w (θ) is:

w (θ) = (s _ref*s_ref ^H)^-1 a (θ) formula (4)

Where w (θ) represents an interference suppression coefficient, s _ref represents an adjacent azimuth dimension signal, s _ref ^H represents a conjugate transpose of the adjacent azimuth dimension signal s _ref, and a (θ) represents a steering vector.

Step S520, obtaining a target azimuth spectrum corresponding to the target distance Doppler position according to the target distance Doppler position and each interference suppression coefficient, and obtaining a plurality of target azimuth spectrums; the target range-doppler location also includes a target range value and a target doppler velocity corresponding to the location of the target motion trace in the range-doppler matrix.

Specifically, a target azimuth spectrum corresponding to the target range-doppler position is obtained according to a target azimuth dimension signal s corresponding to the target range-doppler position and each interference suppression coefficient w (θ), namely the target azimuth spectrum is P (θ):

p (θ) =w (θ) ^H s formula (5)

Where P (θ) represents the target azimuth spectrum, w (θ) ^H represents the conjugate transpose of the interference suppression coefficient w (θ), and s represents the target azimuth dimension signal.

In step S530, current location information of the radar tracking target is obtained based on the plurality of target azimuth spectrums and the predicted azimuth angles, the current location information including the current azimuth angle of the radar tracking target.

Through the steps S510 to S530, the interference suppression coefficient is calculated based on the steering vector and the adjacent azimuth dimension signal corresponding to each adjacent distance doppler position, so as to eliminate the signal of the adjacent distance doppler position as the interference source signal, thereby implementing the suppression processing on the strong target signal, avoiding the influence of the side lobe energy of the strong target azimuth spectrum on the weak target detection, and further implementing the detection on the same-distance same-speed weak target (i.e. radar tracking target).

Meanwhile, the embodiment utilizes the predicted motion information fed back by the tracking end to perform interference suppression processing in a small range (namely, in a rectangular window taking the Doppler position of the target distance corresponding to the target motion predicted track as the center), thereby realizing accurate suppression processing of the energy of the strong target side lobe, avoiding the problem of overlarge operand and improving the data processing efficiency.

In some embodiments, fig. 6 is a flowchart of acquiring current position information of a radar tracking target based on a plurality of target azimuth spectrums and predicted azimuth angles according to an embodiment of the present application, and the flowchart includes the following steps as shown in fig. 6.

Step S610, a first peak value, a second peak value and a first peak value azimuth angle corresponding to the first peak value in each target azimuth spectrum are obtained.

Wherein the first peak azimuth may be denoted as θ _peak and the predicted azimuth may be denoted as θ _pre.

Specifically, the first peak and the second peak are searched for in the target azimuth spectrum P (θ) obtained after the interference suppression processing, and the first peak, the second peak, and the first peak azimuth angle θ _peak corresponding to the first peak are recorded.

Step S620, a peak energy ratio corresponding to the first peak value and the second peak value is obtained, and whether the peak energy ratio is larger than a preset energy ratio threshold value is judged, so that a first judgment result is obtained.

Step S630, the absolute value of the difference between the azimuth angles corresponding to the first peak azimuth angle and the predicted azimuth angle is obtained, and whether the absolute value of the difference is smaller than a preset absolute value threshold is judged, so that a second judgment result is obtained.

Step S640, acquiring the current azimuth of the radar tracking target based on the first determination result and the second determination result.

It should be noted that, since the number of target azimuth spectrums is plural, that is, the number of adjacent range-doppler positions is plural, the above-mentioned determination process needs to be performed plural times, and the current azimuth angle of the radar tracking target needs to be determined according to the first determination result and the second determination result obtained in the plural determination processes.

In some of these embodiments, the determination of the current neighboring range-doppler position: judging whether the peak energy ratio corresponding to the first peak and the second peak is larger than a preset energy ratio threshold value, and judging whether the absolute value of the difference value between the azimuth angles corresponding to the first peak azimuth angle theta _peak and the predicted azimuth angle theta _pre is smaller than a preset absolute value threshold value; if the peak energy ratio is greater than a preset energy ratio threshold and the absolute value of the difference is less than a preset absolute value threshold, storing the first peak azimuth angle theta _peak; otherwise, discarding the first peak azimuth angle θ _peak, and turning to the judgment of the next adjacent distance Doppler position until the judgment process of all adjacent distance Doppler positions is completed, obtaining the stored azimuth angle number of the first peak azimuth angle θ _peak, and judging whether the azimuth angle number is larger than a preset number threshold.

If the azimuth number is greater than a preset number threshold, calculating azimuth averages of all stored first peak azimuth angles theta _peak, and taking the azimuth averages as the current azimuth of the radar tracking target (namely the current azimuth of the same-distance same-speed weak target point trace); if the azimuth number is smaller than the preset number threshold, the processing result is not credible and is not output, so that other problems caused by outputting false trace azimuth angles are prevented.

In some embodiments, fig. 7 is a flowchart of associating current motion trails of a radar tracking target according to an embodiment of the present application, and the flowchart includes the following steps as shown in fig. 7.

Step S710, acquiring a historical motion point trace of the radar tracking target, and determining a current frame point trace prediction range of the radar tracking target based on the historical motion point trace.

The current frame track prediction range represents the track distribution range of the radar tracking target predicted according to the historical motion track in the current frame.

The track processing flow of the radar tracking target comprises the processes of track initiation, track association/maintenance, track termination and the like, and each step can carry out smoothing, prediction and the like according to the historical motion point track information (generally realized through Kalman filtering). The prediction process is to estimate the position, speed and other information of the radar tracking target in the current frame to obtain the point track distribution range (i.e. the point track prediction range or the association window of the current frame) of the radar tracking target in the current frame.

Step S720, searching whether a motion point exists in the current frame point prediction range, and if the motion point exists in the current frame point prediction range, determining that the current motion point is successfully related to the radar tracking target.

Step S730, if there is no motion track in the current frame track prediction range, determining a current motion track not associated with the radar tracking target, and acquiring the predicted motion information of the current radar tracking target based on the historical motion track.

Further, if the current frame trace is in the trace distribution range, the current frame motion trace successfully related to the radar tracking target is considered; and if the current frame track does not exist in the track distribution range, the current frame motion track which is not related to the radar tracking target is considered. When a certain frame is not associated with the motion point trace in the prediction range, the track is not interrupted immediately, and normally, the motion point trace which is not associated with the prediction range in M frames (N > M) in continuous N frames is considered to be lost, and the track of the radar tracking target is not output.

In the application scene, because the motion trail of the weak target cannot be normally and continuously output under the influence of the strong targets with the same distance and the same speed, when the weak target trail is associated, multiple frames cannot be associated with the effective motion trail, and therefore the weak target trail is interrupted.

In the related art, two targets with the same distance and the same speed can be generally distinguished in an angle dimension, a DBF (Digital Beam Forming digital beam forming) angle measuring technology can be utilized, a peak is formed by angle units where the two targets are located in an azimuth spectrum, and whether a weak target is output or not is judged according to a comparison result by comparing a second peak with a preset threshold. Fig. 8 is a schematic diagram of an application scenario of the related art, as shown in fig. 8, in which a target vehicle is located in a BSD/LCA alert area. When the speed of the own vehicle and the target vehicle (namely the radar tracking target in the application) meet certain conditions, the distance and the radial speed (namely the Doppler speed) of the target point 1 and the target point 2 relative to the radar of the own vehicle are the same, namely the same distance and the same speed are the same. At this time, if the energy of the target point 2 is far stronger than that of the target point 1, the target point 1 cannot be detected normally, so that the problems of track loss and track interruption of the target vehicle are caused, and the situations of alarm missing, alarm delay or alarm interruption are further caused.

The embodiments of the application are described and illustrated below by means of two specific examples.

In the specific embodiment 1, (1) obtaining a motion point prediction result of a current motion point and a current radar tracking target under a rectangular coordinate system, wherein the motion point prediction result comprises a current position prediction result and a current speed prediction result; acquiring the current vehicle speed, vehicle radar installation information and conversion relation between a polar coordinate system and a rectangular coordinate system, wherein the vehicle radar installation information comprises a vehicle radar installation angle and a vehicle radar installation position; and converting the motion point trace prediction result from a rectangular coordinate system to a polar coordinate system based on the conversion relation, the current vehicle speed and the vehicle radar installation information to obtain the predicted motion information of the radar tracking target, wherein the predicted motion information comprises a predicted distance, a predicted speed and a predicted azimuth angle.

(2) Acquiring preset range-doppler parameters, wherein the preset range-doppler parameters comprise preset range values and preset doppler speeds; determining a current trace point search area based on the predicted distance, the predicted speed and the preset distance Doppler parameter; acquiring a point track azimuth corresponding to the current movement point track, and acquiring an azimuth angle difference between the point track azimuth and a predicted azimuth angle; judging whether the current movement track is in the current track searching area or not, and judging whether an azimuth angle difference value corresponding to the current movement track is larger than a preset difference value threshold value or not; and if the current motion track is in the current track searching area and the azimuth angle difference value corresponding to the current motion track is larger than the preset difference value threshold, determining the current motion track as the target motion track.

(3) Acquiring a target distance Doppler position corresponding to a target motion point trace, and acquiring an adjacent distance Doppler position corresponding to the target distance Doppler position, wherein the target distance Doppler position comprises the position of the target motion point trace in a distance Doppler matrix, and the distance Doppler matrix is constructed based on radar echo data; the number of adjacent range-doppler locations is multiple (typically 8).

(4) Acquiring an interference suppression coefficient corresponding to each adjacent range-Doppler position based on the guide vector and each adjacent range-Doppler position; the adjacent range-Doppler positions comprise adjacent positions of the target motion trace in the range-Doppler matrix, adjacent range values corresponding to the adjacent positions and adjacent Doppler speeds; acquiring a target azimuth spectrum corresponding to the target distance Doppler position according to the target distance Doppler position and each interference suppression coefficient, and obtaining a plurality of target azimuth spectrums; the target range-doppler location also includes a target range value and a target doppler velocity corresponding to the location of the target motion trace in the range-doppler matrix.

(5) Acquiring a first peak value and a second peak value in each target azimuth spectrum and a first peak azimuth corresponding to the first peak value; obtaining a peak energy ratio corresponding to the first peak value and the second peak value, and judging whether the peak energy ratio is larger than a preset energy ratio threshold value or not to obtain a first judging result; acquiring an absolute value of a difference value of azimuth angles corresponding to the first peak azimuth angle and the predicted azimuth angle, and judging whether the absolute value of the difference value is smaller than a preset absolute value threshold value or not to obtain a second judging result; and acquiring the current azimuth angle of the radar tracking target based on the first judgment result and the second judgment result.

In embodiment 2, fig. 9a is a schematic diagram of an application scenario of a target detection method according to an embodiment of the present application, taking an urban road scenario as an example, as shown in fig. 9a, a plurality of stationary objects such as trees, stationary vehicles, fences, etc. exist on a roadside, and a target vehicle (electric bicycle) is located in an adjacent lane of a self-vehicle driving lane. The speed of the self-vehicle is about 25KM/H KM/H, the speed of the target vehicle is about 15KM/H KM/H, the radial distance between the target vehicle and the radar on the right side of the self-vehicle is about 10m, and the azimuth angle of the target vehicle is about 50 degrees. The radar installation angle is 98 degrees, so that the radial speed of the target vehicle relative to the radar on the right side of the vehicle can be calculated to be:

The roadside stationary object distribution range is wide, and in the azimuth direction of 12 degrees, a stationary object with a radial distance of about 10m from the radar on the right side of the vehicle exists, and the radial speed of the stationary object relative to the radar on the right side of the vehicle is as follows:

the object vehicle and the static object in the 12-degree azimuth direction have the same distance and same speed, and the effective scattering sectional area of the static object is larger, and the azimuth of the static object is closer to the normal direction of the radar, so that the echo energy of the static object is stronger. Figure 9b is a schematic diagram of a range-doppler position correspondence azimuth spectrum of a target vehicle according to an embodiment of the present application, in which a significantly strong spike is formed only in a 12 ° azimuth, and a 50 ° azimuth target vehicle has been submerged by a side lobe of a spike of a stationary object.

Fig. 10a to fig. 10h are schematic diagrams of target azimuth spectrums after interference suppression processing in the specific embodiment of the present application, obtain target range-doppler positions corresponding to a target vehicle, obtain 8 adjacent range-doppler positions corresponding to the target range-doppler positions and adjacent azimuth dimension signals corresponding to each adjacent range-doppler position, calculate interference suppression coefficients according to the adjacent azimuth dimension signals corresponding to the 8 adjacent range-doppler positions, and obtain target azimuth spectrums (as shown in fig. 10a to fig. 10 h) obtained after interference suppression processing according to the interference suppression coefficients and the azimuth dimension signals corresponding to the target range-doppler positions, where the target azimuth spectrums obtained by processing the 2,3, 4, and 5 adjacent range-doppler positions all form peaks near the true target azimuth, and the average value is 52.5 °, so that it can be seen that the target detection method provided by the present application can realize detection of the same-distance same-speed weak target.

The 8 adjacent range-doppler positions refer to four range-doppler positions adjacent to the target range-doppler position in the up-down, left-right, and four range-doppler positions adjacent to the target range-doppler position in the diagonal direction in the range-doppler matrix.

It should be noted that the steps illustrated in the above-described flow or flow diagrams of the figures may be performed in a computer system, such as a set of computer-executable instructions, and that, although a logical order is illustrated in the flow diagrams, in some cases, the steps illustrated or described may be performed in an order other than that illustrated herein. For example, with reference to fig. 2, the execution sequence of step S210 and step S220 may be interchanged, i.e., step S210 may be executed first, and then step S220 may be executed; step S120 may be performed first, and then step S110 may be performed. For another example, in connection with fig. 6, the order of step S620 and step S630 may also be interchanged.

The present embodiment also provides an object detection device, which is used to implement the foregoing embodiments and preferred embodiments, and will not be described in detail. As used below, the terms "module," "unit," "sub-unit," and the like may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

Fig. 11 is a block diagram of an object detection apparatus according to an embodiment of the present application, and as shown in fig. 11, the apparatus includes.

The target point trace determining module 110 is configured to obtain predicted motion information of a current motion trace and a radar tracking target, and determine a target motion trace corresponding to the radar tracking target based on the predicted motion information and the current motion trace, where the predicted motion information includes a predicted distance, a predicted speed, and a predicted azimuth.

The adjacent position obtaining module 120 is configured to obtain a target range-doppler position corresponding to a target motion trace, and obtain an adjacent range-doppler position corresponding to the target range-doppler position, where the target range-doppler position includes a position of the target motion trace in a range-doppler matrix, and the range-doppler matrix is constructed based on radar echo data.

The target position detection module 130 is configured to obtain an interference suppression coefficient based on the adjacent range-doppler position, and obtain current position information of the radar tracking target based on the interference suppression coefficient, the target range-doppler position, and the predicted azimuth angle.

In some of these embodiments, the target trace determination module 110 includes a prediction information acquisition unit including a first data acquisition subunit, a second data acquisition subunit, and a coordinate conversion subunit.

The first data acquisition subunit is used for acquiring a motion point trace prediction result of the current radar tracking target in a rectangular coordinate system, wherein the motion point trace prediction result comprises a current position prediction result and a current speed prediction result.

The second data acquisition subunit is used for acquiring the current vehicle speed, the vehicle radar installation information and the conversion relation between the polar coordinate system and the rectangular coordinate system, wherein the vehicle radar installation information comprises a vehicle radar installation angle and a vehicle radar installation position;

And the coordinate conversion subunit is used for converting the motion point track prediction result from a rectangular coordinate system to a polar coordinate system based on the conversion relation, the current vehicle speed and the vehicle radar installation information to obtain the predicted motion information.

In some of these embodiments, the target point trace determination module 110 further includes a target point trace determination unit including a doppler parameter acquisition subunit, a search area determination subunit, and a target point trace determination subunit, wherein.

The Doppler parameter acquisition subunit is used for acquiring preset range Doppler parameters, wherein the preset range Doppler parameters comprise preset range values and preset Doppler speeds.

And the search area determining subunit is used for determining the current trace search area based on the predicted distance, the predicted speed and the preset distance Doppler parameter.

And the target point trace determining subunit is used for determining a target movement point trace from the current movement point trace based on the current point trace searching area and the predicted azimuth angle.

In some embodiments, the target track determining subunit is further configured to obtain a track azimuth corresponding to the current motion track, and obtain an azimuth difference between the track azimuth and the predicted azimuth; judging whether the current movement track is in the current track searching area or not, and judging whether an azimuth angle difference value corresponding to the current movement track is larger than a preset difference value threshold value or not; and if the current motion track is in the current track searching area and the azimuth angle difference value corresponding to the current motion track is larger than the preset difference value threshold, determining the current motion track as the target motion track.

In some of these embodiments, the number of adjacent range-doppler locations is a plurality, and the target location detection module 130 includes a suppression coefficient acquisition unit, a target azimuth spectrum acquisition unit, and a current location acquisition unit, among others.

The suppression coefficient acquisition unit is used for acquiring an interference suppression coefficient corresponding to each adjacent range-Doppler position based on the guide vector and each adjacent range-Doppler position; the adjacent range-doppler locations include adjacent locations of the target motion trace locations in the range-doppler matrix and adjacent range values and adjacent doppler velocities corresponding to the adjacent locations.

The target azimuth spectrum acquisition unit is used for acquiring a target azimuth spectrum corresponding to the target distance Doppler position according to the target distance Doppler position and each interference suppression coefficient to obtain a plurality of target azimuth spectrums; the target range-doppler location also includes a target range value and a target doppler velocity corresponding to the location of the target motion trace in the range-doppler matrix.

The current position acquisition unit is used for acquiring current position information of the radar tracking target based on the target azimuth spectrums and the predicted azimuth angles, wherein the current position information comprises the current azimuth angle of the radar tracking target.

In some of these embodiments, the current position acquisition unit includes a peak acquisition subunit, a first determination subunit, a second determination subunit, and an azimuth acquisition subunit, wherein.

The peak value acquisition subunit is used for acquiring a first peak value, a second peak value and a first peak value azimuth angle corresponding to the first peak value in each target azimuth spectrum.

The first judging subunit is configured to obtain a peak energy ratio corresponding to the first peak value and the second peak value, and judge whether the peak energy ratio is greater than a preset energy ratio threshold value, so as to obtain a first judging result.

The second judging subunit is configured to obtain an absolute value of a difference between the azimuth angle of the first peak and the azimuth angle corresponding to the predicted azimuth angle, and judge whether the absolute value of the difference is smaller than a preset absolute value threshold, so as to obtain a second judging result.

And the azimuth angle acquisition subunit is used for acquiring the current azimuth angle of the radar tracking target based on the first judgment result and the second judgment result.

In some embodiments, the target detection device further comprises a target association detection module, wherein the target association detection module comprises a history trace acquisition unit, a first association detection unit and a second association detection unit.

The historical movement track acquisition unit is used for acquiring the historical movement track of the radar tracking target and determining the current frame track prediction range of the radar tracking target based on the historical movement track.

The first association detection unit is used for searching whether motion points exist in the current frame point prediction range, and if the motion points exist in the current frame point prediction range, determining the current motion points successfully associated with the radar tracking target.

And the second association detection unit is used for determining the current motion point trace which is not associated with the radar tracking target if the motion point trace does not exist in the current frame point trace prediction range, and acquiring the predicted motion information of the current radar tracking target based on the historical motion point trace.

The above-described respective modules may be functional modules or program modules, and may be implemented by software or hardware. For modules implemented in hardware, the various modules described above may be located in the same processor; or the above modules may be located in different processors in any combination.

In addition, the object detection method of the embodiment of the present application described in connection with fig. 1 may be implemented by a computer device. Fig. 12 is a schematic hardware structure of a computer device according to an embodiment of the present application.

The computer device may include a processor 121 and a memory 122 storing computer program instructions.

In particular, the processor 121 may include a Central Processing Unit (CPU), or an Application SPECIFIC INTEGRATED Circuit (ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present application.

Memory 122 may include, among other things, mass storage for data or instructions. By way of example, and not limitation, memory 122 may comprise a hard disk drive (HARD DISK DRIVE, abbreviated HDD), floppy disk drive, solid state drive (Solid STATE DRIVE, abbreviated SSD), flash memory, optical disk, magneto-optical disk, magnetic tape, or universal serial bus (Universal Serial Bus, abbreviated USB) drive, or a combination of two or more of these. Memory 122 may include removable or non-removable (or fixed) media, where appropriate. The memory 122 may be internal or external to the data processing apparatus, where appropriate. In a particular embodiment, the memory 122 is a Non-Volatile (Non-Volatile) memory. In particular embodiments, memory 122 includes Read-Only Memory (ROM) and random access Memory (Random Access Memory, RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, abbreviated PROM), an erasable PROM (Erasable Programmable Read-Only Memory, abbreviated EPROM), an electrically erasable PROM (ELECTRICALLY ERASABLE PROGRAMMABLE READ-Only Memory, abbreviated EEPROM), an electrically rewritable ROM (ELECTRICALLY ALTERABLE READ-Only Memory, abbreviated EAROM), or a FLASH Memory (FLASH), or a combination of two or more of these. The RAM may be a Static Random-Access Memory (SRAM) or a dynamic Random-Access Memory (Dynamic Random Access Memory DRAM), where the DRAM may be a fast page mode dynamic Random-Access Memory (Fast Page Mode Dynamic Random Access Memory, FPMDRAM), an extended data output dynamic Random-Access Memory (Extended Date Out Dynamic Random Access Memory, EDODRAM), a synchronous dynamic Random-Access Memory (Synchronous Dynamic Random-Access Memory, SDRAM), or the like, as appropriate.

Memory 122 may be used to store or cache various data files that need to be processed and/or communicated for use, as well as possible computer program instructions for execution by processor 121.

The processor 121 implements any one of the target detection methods of the above embodiments by reading and executing the computer program instructions stored in the memory 122.

In some of these embodiments, the computer device may also include a communication interface 123 and a bus 120. As shown in fig. 12, the processor 121, the memory 122, and the communication interface 123 are connected to each other through the bus 120 and perform communication with each other.

The communication interface 123 is used to implement communication between modules, devices, units, and/or units in embodiments of the application. Communication interface 123 may also enable communication with other components such as: and the external equipment, the image/data acquisition equipment, the database, the external storage, the image/data processing workstation and the like are used for data communication.

Bus 120 includes hardware, software, or both, coupling components of a computer device to each other. Bus 120 includes, but is not limited to, at least one of: data Bus (Data Bus), address Bus (Address Bus), control Bus (Control Bus), expansion Bus (Expansion Bus), local Bus (Local Bus). By way of example, and not limitation, bus 120 may include a graphics acceleration interface (ACCELERATED GRAPHICS Port, abbreviated as AGP) or other graphics Bus, an enhanced industry standard architecture (Extended Industry Standard Architecture, abbreviated as EISA) Bus, a Front Side Bus (Front Side Bus, abbreviated as FSB), a HyperTransport (abbreviated as HT) interconnect, an industry standard architecture (Industry Standard Architecture, abbreviated as ISA) Bus, a wireless bandwidth (InfiniBand) interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a micro channel architecture (Micro Channel Architecture, abbreviated as MCA) Bus, a peripheral component interconnect (PERIPHERAL COMPONENT INTERCONNECT, abbreviated as PCI) Bus, a PCI-Express (PCI-X) Bus, a serial advanced technology attachment (SERIAL ADVANCED Technology Attachment, abbreviated as SATA) Bus, a video electronics standards Association local (Video Electronics Standards Association Local Bus, abbreviated as VLB) Bus, or other suitable Bus, or a combination of two or more of these. Bus 120 may include one or more buses, where appropriate. Although embodiments of the application have been described and illustrated with respect to a particular bus, the application contemplates any suitable bus or interconnect.

The computer device may execute the target detection method in the embodiment of the present application based on the obtained predicted motion information of the obtained current motion point track and the radar tracking target, thereby implementing the target detection method described in connection with fig. 1.

In addition, in combination with the target detection method in the above embodiment, the embodiment of the present application may be implemented by providing a computer readable storage medium. The computer readable storage medium has stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement any of the object detection methods of the above embodiments.

The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.

Claims

1. A method of target detection, the method comprising:

Acquiring an interference suppression coefficient based on the adjacent range-Doppler position, and acquiring current position information of the radar tracking target based on the interference suppression coefficient, the target range-Doppler position and the predicted azimuth angle;

Wherein the number of adjacent range-doppler locations is a plurality, the obtaining an interference suppression coefficient based on the adjacent range-doppler locations, and obtaining current location information of the radar tracking target based on the interference suppression coefficient, the target range-doppler locations, and the predicted azimuth angle comprises:

2. The method of claim 1, wherein the obtaining predicted motion information for the radar tracking target comprises:

3. The method of claim 1, wherein the determining a target motion profile corresponding to the radar tracking target based on the predicted motion information and the current motion profile comprises:

4. The method of claim 3, wherein the determining the target motion profile from the current motion profile based on the current profile search area and the predicted azimuth comprises:

5. The method of claim 1, wherein the obtaining current location information of the radar tracking target based on the plurality of target azimuth spectra and the predicted azimuth angle comprises:

6. The method of claim 1, wherein prior to the obtaining the predicted motion information for the radar tracking target, the method further comprises:

7. An object detection device, the device comprising:

the target position detection module is used for acquiring an interference suppression coefficient based on the adjacent range-Doppler position and acquiring the current position information of the radar tracking target based on the interference suppression coefficient, the target range-Doppler position and the predicted azimuth angle;

the target position detection module comprises a suppression coefficient acquisition unit, a target azimuth spectrum acquisition unit and a current position acquisition unit, wherein:

the suppression coefficient acquisition unit is used for acquiring an interference suppression coefficient corresponding to each adjacent distance Doppler position based on the guide vector and each adjacent distance Doppler position; the adjacent range-Doppler position comprises an adjacent position of the target motion trace in a range-Doppler matrix, an adjacent range value corresponding to the adjacent position and an adjacent Doppler speed;

the target azimuth spectrum acquisition unit is used for acquiring a target azimuth spectrum corresponding to the target range-Doppler position according to the target range-Doppler position and each interference suppression coefficient to obtain a plurality of target azimuth spectrums; the target range-Doppler position also comprises a target range value and a target Doppler speed corresponding to the position of the target motion point trace in a range-Doppler matrix;

the current position obtaining unit is used for obtaining current position information of the radar tracking target based on a plurality of target azimuth spectrums and the predicted azimuth angles, and the current position information comprises the current azimuth angle of the radar tracking target.

8. The apparatus of claim 7, wherein the target trace determination module comprises a prediction information acquisition unit comprising a first data acquisition subunit, a second data acquisition subunit, and a coordinate conversion subunit, wherein:

The first data acquisition subunit is used for acquiring a motion point trace prediction result of the current radar tracking target under a rectangular coordinate system, wherein the motion point trace prediction result comprises a current position prediction result and a current speed prediction result;

the coordinate conversion subunit is configured to down-convert the motion point track prediction result from a rectangular coordinate system to a polar coordinate system based on the conversion relation, the current vehicle speed and the vehicle radar installation information, so as to obtain the predicted motion information.

9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the object detection method according to any of claims 1 to 6 when executing the computer program.

10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when executed by a processor, implements the object detection method according to any one of claims 1 to 6.