CN118131213A

CN118131213A - Doppler blind area speed determining method, device and equipment

Info

Publication number: CN118131213A
Application number: CN202410244978.6A
Authority: CN
Inventors: 李坤乾; 徐世奇; 朱飞亚; 吴童
Original assignee: Jiangsu Hanrun Automobile Electronics Co ltd
Current assignee: Jiangsu Hanrun Automobile Electronics Co ltd
Priority date: 2024-03-04
Filing date: 2024-03-04
Publication date: 2024-06-04

Abstract

The application provides a Doppler blind zone speed determining method, a device and equipment, which are characterized in that the current relative azimuth angle between a sensor and a measured target and the current running information of the measured target are obtained; based on the current relative azimuth angle and the current running information, determining a blind area state of the measured target, wherein the blind area state is used for indicating whether the measured target is in a Doppler blind area of the sensor; under the condition that the blind area state indicates that the measured target is in the Doppler blind area of the sensor, acquiring a multi-frame real-time azimuth angle between the sensor and the measured target in the Doppler blind area of the measured target and multi-frame real-time sensor information measured by the sensor; and carrying out joint calculation on the multi-frame real-time azimuth angle and the multi-frame real-time sensor information to determine the target speed of the measured target in the Doppler blind zone. The method and the device can improve the accuracy of determining the speed of the target in the Doppler blind zone.

Description

Doppler blind area speed determining method, device and equipment

Technical Field

The present application relates to the field of sensor technologies, and in particular, to a method, an apparatus, and a device for determining a speed of a doppler blind area.

Background

In the field of target detection and target tracking data processing based on a Doppler sensor such as a millimeter wave radar, the detection principle of the Doppler sensor shows that in the process of relative movement between a target and the sensor, a Doppler blind area exists in the observation of the target by the sensor, namely, the Doppler velocity of the target detected by the sensor is approximately equal to zero in a certain range of an included angle of the relative movement direction, and the range is generally called as a zero Doppler area or a Doppler blind area. When the movement of the target relative to the sensor falls into the Doppler blind zone, the movement information of the target cannot be accurately detected, so that intermittent or continuous loss of target detection is easily caused, and the track interruption during target tracking processing is caused.

In conventional methods, velocity measurements of a target in a doppler blind zone are typically processed using multi-model hypotheses or multi-hypothesis methods. However, this method has a limitation in dealing with the problem of doppler blind zone, because it requires prediction and assumption of possible motion models of the target, which often differ from the actual target motion situation, resulting in lower accuracy of the travel speed estimation of the target in the doppler blind zone.

Disclosure of Invention

The method, the device and the equipment for determining the speed of the Doppler blind zone can improve the accuracy of determining the speed of the target in the Doppler blind zone.

In a first aspect, an embodiment of the present application provides a method for determining a speed of a doppler blind area, where the method includes:

acquiring a current relative azimuth angle between a sensor and a measured target and current running information of the measured target, wherein the current running information comprises a current transverse speed of the measured target and a current longitudinal speed of the measured target;

based on the current relative azimuth angle and the current running information, determining a blind area state of the measured target, wherein the blind area state is used for indicating whether the measured target is in a Doppler blind area of the sensor;

Under the condition that the blind area state indicates that the measured target is in the Doppler blind area of the sensor, acquiring a multi-frame real-time azimuth angle between the sensor and the measured target in the Doppler blind area of the measured target and multi-frame real-time sensor information measured by the sensor;

And carrying out joint calculation on the multi-frame real-time azimuth angle and the multi-frame real-time sensor information to determine the target speed of the measured target in the Doppler blind zone.

In a second aspect, the present application provides a doppler blind area speed determining apparatus, the apparatus comprising:

The first acquisition module is used for acquiring the current relative azimuth angle between the sensor and the measured target and the current running information of the measured target, wherein the current running information comprises the current transverse speed of the measured target and the current longitudinal speed of the measured target;

the first determining module is used for determining the blind area state of the detected target based on the current relative azimuth angle and the current running information, wherein the blind area state is used for indicating whether the detected target is in the Doppler blind area of the sensor;

the second acquisition module is used for acquiring a multi-frame real-time azimuth angle between the sensor and the measured target in the Doppler blind zone and multi-frame real-time sensor information of the measurement of the sensor under the condition that the blind zone state indicates that the measured target is in the Doppler blind zone of the sensor;

and the second determining module is used for carrying out joint calculation on the multi-frame real-time azimuth angle and the multi-frame real-time sensor information to determine the target speed of the measured target in the Doppler blind zone.

In a third aspect, an embodiment of the present application provides an electronic device, including: a processor and a memory storing computer program instructions;

The processor, when executing the computer program instructions, implements the doppler blind zone velocity determination method as in any one of the embodiments of the first aspect.

In a fourth aspect, an embodiment of the present application provides a computer storage medium, where computer program instructions are stored, which when executed by a processor implement a method for determining a doppler blind area velocity as in any one of the embodiments of the first aspect.

In a fifth aspect, an embodiment of the present application provides a computer program product, where instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform a method for determining a doppler blind area velocity according to any one of the embodiments of the first aspect.

In the method, the device and the equipment for determining the Doppler blind zone speed provided by the embodiment of the application, the current relative azimuth angle between the sensor and the measured target and the current running information of the measured target are obtained, wherein the current running information comprises the current transverse speed of the measured target and the current longitudinal speed of the measured target; based on the current relative azimuth angle and the current running information, determining a blind area state of the measured target, wherein the blind area state is used for indicating whether the measured target is in a Doppler blind area of the sensor; under the condition that the blind area state indicates that the measured target is in the Doppler blind area of the sensor, acquiring a multi-frame real-time azimuth angle between the sensor and the measured target in the Doppler blind area of the measured target and multi-frame real-time sensor information measured by the sensor; and carrying out joint calculation on the multi-frame real-time azimuth angle and the multi-frame real-time sensor information to determine the target speed of the measured target in the Doppler blind zone. By the mode, not only is the information of multi-frame real-time azimuth angle fully utilized, but also the multi-frame real-time sensor data measured by the sensor is combined for calculation, so that the problem of insufficient dependence of the traditional method on the target motion model is effectively solved. By the comprehensive data processing means, the accuracy of determining the target running speed in the Doppler blind zone is obviously improved.

Drawings

In order to more clearly illustrate the technical solution of the embodiments of the present application, the drawings that are needed to be used in the embodiments of the present application will be briefly described, and it is possible for a person skilled in the art to obtain other drawings according to these drawings without inventive effort.

FIG. 1 is a flow chart of a method for determining a velocity of a Doppler blind zone according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a geometrical relationship between a sensor and a measured target in a radar coordinate system according to an embodiment of the present application;

fig. 3 is a schematic view of a doppler blind zone 1 according to an embodiment of the present application;

FIG. 4 is a schematic diagram of a Doppler blind zone 2 provided by an embodiment of the present application;

fig. 5 is a schematic view of a doppler blind zone 3 according to an embodiment of the present application;

FIG. 6 is a schematic diagram of a trace comparison of a measured target generated using the Doppler blind zone velocity determination method of the present application and the prior art according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a doppler blind area speed determining device according to an embodiment of the present application;

Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the disclosure.

It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.

In the field of target detection and target tracking data processing based on a Doppler sensor such as a millimeter wave radar, the detection principle of the Doppler sensor shows that in the process of relative movement between a target and the sensor, a Doppler blind area exists in the observation of the target by the sensor, namely, the Doppler velocity of the target detected by the sensor is approximately equal to zero in a certain range of an included angle of the relative movement direction, and the range is generally called as a zero Doppler area or a Doppler blind area. Therefore, if the moving object has a doppler dead zone relative to the sensor, the doppler velocity detected by the sensor has a zero crossing phenomenon, that is, three processes of motion of the object relative to the sensor are respectively "motion-rest-motion". In addition, when the movement of the target relative to the sensor falls into the Doppler blind zone, the movement information of the target cannot be accurately detected, so that the intermittent or continuous loss of the target detection is easily caused, and the track interruption during the target tracking processing is caused, so that the track continuity and stability of the radar on the moving target detection tracking are seriously reduced. In the traditional processing algorithm, a data association method is often adopted for tracking the target in the Doppler blind zone, a limited time-varying number of state models are established based on random state variables, and the target tracking processing is often decomposed into a plurality of mutually independent sub-modules (such as track initiation, track maintenance, track management, track extinction and the like) for processing. However, due to the inherent complete combination characteristic of the complex data association algorithm, the traditional data processing algorithm has the problems of huge calculation amount and large occupied storage space. Therefore, the effective Doppler blind area judgment and the target tracking algorithm under the blind area are beneficial to the improvement of the continuity of target tracking and the stability of target detection.

In the process of detecting and tracking a target by a sensor such as a doppler radar, a measurement value in a polar coordinate system is generally obtained by the sensor. In the traditional Doppler radar data processing, regarding the judgment of a Doppler blind zone, a relatively fixed area is defined and identified as the Doppler blind zone only based on the position of a radar and the direction of an antenna beam, and targets entering the area are considered to enter the Doppler blind zone, and obviously, the judgment mode can only successfully identify the targets meeting a certain speed orientation as entering the Doppler blind zone.

For the target tracking processing in the Doppler blind zone, the target Doppler speed detected by the radar is approximately equal to zero, so that the motion attribute of the target cannot be accurately estimated. The traditional processing algorithm generally adopts a multi-constraint and multi-hypothesis mode to process and carry out multi-model hypothesis on the motion state of the target, so that the calculation amount of batch processing is increased, and the continuity and stability of the flight path are not facilitated.

In order to solve the problems in the prior art, the embodiment of the application provides a method, a device and equipment for determining the speed of a Doppler blind zone.

The embodiment of the application provides a Doppler blind zone speed determining method, device and equipment. The following first describes a method for determining a velocity of a doppler blind area according to an embodiment of the present application. As shown in fig. 1, the method specifically includes the following steps:

s100, acquiring a current relative azimuth angle between the sensor and the measured target and current running information of the measured target, wherein the current running information comprises a current transverse speed of the measured target and a current longitudinal speed of the measured target.

Alternatively, in the embodiment of the present application, the sensor may be a sensor having a doppler blind area such as a millimeter wave radar and a laser radar. The object to be measured can be any object with relative motion, such as a vehicle, a pedestrian, an unmanned aerial vehicle and the like, for example, a ship, a flying bird and the like, and can be the object to be measured.

Optionally, in a possible implementation manner of the present application, the relative azimuth information θ of the measured target detected by the sensor at the current moment is obtained, and the position information (x, y) of the measured target in the cartesian coordinate system.

In particular, millimeter wave radar or other radar devices may detect a target under test and provide relative azimuth information, in particular, the radar system transmits signals, receives signals reflected by the target under test, and calculates the azimuth of the target under test relative to the radar through signal processing. And then analyzing the relative azimuth information of the measured target from the original data acquired by the radar system through steps of signal processing, peak detection, target tracking and the like.

The radar measured relative azimuth information and distance information to the object being measured (also typically provided by the radar) are then converted into position information in a cartesian coordinate system. This conversion may be accomplished using trigonometric functions. If the mounting direction and coordinate system of the radar do not coincide with the coordinate system of the vehicle or sensor system, a coordinate system transformation is also required, in particular involving a rotation and translation transformation. After the coordinate transformation is completed, the position information of the target in the Cartesian coordinate system can be obtained, wherein the position information comprises an abscissa (X axis), an ordinate (Y axis) and the like.

Optionally, the following describes the principle of existence of a doppler blind area:

As shown in fig. 2, θ in fig. 2 is the azimuth angle, i.e. the relative position direction, of the measured object relative to the radar sensor; alpha is the included angle between the actual speed V _T of the measured object and the direction of the relative position, namely the direction of relative movement; l is a connecting line mark of the positions of the radar sensor and the measured target; v _r is the radial Doppler velocity of the measured object relative to the sensor; v _T is the actual velocity of the object under test, which in a cartesian coordinate system has an x-direction velocity component V _x and a y-direction velocity component V _y. From the basic detection principle of the doppler radar sensor, the doppler velocity detected by the radar can be expressed as the following formula 1:

v_r＝v_T·cosα (1)

furthermore, the doppler velocity detected by the radar can also be represented by velocity components in the cartesian coordinate system of the measured object, as shown in the following equation 2:

v_r＝v_y·cosθ+v_x·sinθ (2)

the position information of the target in the cartesian coordinate system is (x, y), and the sine and cosine values of the azimuth angle in the formula (2) can be expressed as follows:

thus, the above formula (2) can be further expressed as:

As can be seen from the above formula (1), when the actual velocity V _T of the measured target is approximately perpendicular to the straight line i, i.e. the included angle α≡90 degrees, the doppler velocity V _r＝v_T ·cos α≡0 detected by the radar sensor, i.e. under such relative position direction and relative movement direction conditions, no matter how large the actual movement velocity V _T of the target is, the target doppler velocity detected by the radar is approximately equal to 0, and the target is in the zero doppler region relative to the radar at this time, i.e. the range of a certain region relative to the target and the radar at this time is referred to as the doppler dead zone.

S200, determining a blind area state of the measured target based on the current relative azimuth angle and the current running information, wherein the blind area state is used for indicating whether the measured target is in a Doppler blind area of the sensor.

Alternatively, in one possible implementation of the present application, first, the relative azimuth information and the current traveling information of the detected target detected at the current time may be obtained from the sensor. The relative azimuth indicates the directional angle of the target with respect to the sensor, and the travel information may include the travel speed of the measured target, the position of the measured target, and the like. The acquired relative azimuth and travel information are then used to calculate a relative motion vector for the object under test, which vector describes the direction and speed of motion of the object under test relative to the sensor. Then, whether the target is in the Doppler blind zone or not can be judged by utilizing the characteristic of the Doppler blind zone, namely, the Doppler speed of the target detected by the sensor is approximately equal to zero in a certain range of an included angle of the relative motion direction, and particularly, the target is judged to be in the Doppler blind zone by setting a Doppler blind zone judging threshold when the included angle of the relative motion vector and the connecting line of the position exceeds the threshold. And determining the blind area state of the measured target according to the judging result. The blind state may be represented by a binary variable, e.g., 1 for a target that is in a blind region and 0 for a target that is not in a blind region.

Specifically, the determination of the blind area state can be achieved by comparing the relative motion vector with a set doppler blind area discrimination threshold. If the angle of the relative motion vector exceeds the threshold, the target is determined to be in a Doppler blind zone, otherwise, the target is not in a blind zone. The setting of this threshold can be adjusted according to the specific application scenario and sensor performance.

S300, under the condition that the blind area state indicates that the measured target is in the Doppler blind area of the sensor, acquiring a multi-frame real-time azimuth angle between the sensor and the measured target in the Doppler blind area of the measured target and multi-frame real-time sensor information measured by the sensor.

Optionally, in one possible implementation of the present application, when the blind zone status indicates that the target is in a doppler blind zone, a module specifically designed for monitoring and processing doppler blind zone is activated. And configures data acquisition parameters including the number of frames acquired and the time interval acquired, the setting of these parameters depends on the actual problem to be solved and the performance requirements of the system. The sensor is then used to obtain target relative azimuth information at multiple time points, in particular to radar, millimeter wave sensor and the like, and azimuth data can be obtained according to the characteristics and working principle of the sensor. Meanwhile, multiple frames of real-time sensor measurement information such as Doppler speed and the like are acquired. And storing the acquired multiframe azimuth information and sensor information in a temporary buffer or data structure for subsequent processing.

Through the steps, the multi-frame real-time azimuth angle and the sensor information of the target in the Doppler blind zone can be obtained, and necessary data support is provided for subsequent target speed calculation. These data can be used to more accurately infer the motion state of the target within the Doppler blind zone.

S400, carrying out joint calculation on the multi-frame real-time azimuth angle and the multi-frame real-time sensor information to determine the target speed of the measured target in the Doppler blind zone.

Optionally, in one embodiment of the present application, the stored multiframe real-time azimuth and sensor information may be preprocessed first to ensure consistency and accuracy of the data, and specific preprocessing operations may include data alignment, noise removal, error correction, and the like. The multi-frame real-time azimuth and sensor information are then jointly calculated, for example, a filter, a least square method and other mathematical methods can be used to obtain the speed information of the target in the Doppler blind zone. After the target speed information is obtained, speed calculation compensation is carried out, and specifically, the speed can be corrected according to actual conditions so as to improve the accuracy of the speed information. And outputting the calculated target speed information for subsequent target tracking and processing.

In the method for determining the Doppler blind zone speed provided by the embodiment of the application, the current relative azimuth angle between the sensor and the measured target and the current running information of the measured target are obtained; based on the current relative azimuth angle and the current running information, determining a blind area state of the measured target, wherein the blind area state is used for indicating whether the measured target is in a Doppler blind area of the sensor; under the condition that the blind area state indicates that the measured target is in the Doppler blind area of the sensor, acquiring a multi-frame real-time azimuth angle between the sensor and the measured target in the Doppler blind area of the measured target and multi-frame real-time sensor information measured by the sensor; and carrying out joint calculation on the multi-frame real-time azimuth angle and the multi-frame real-time sensor information to determine the target speed of the measured target in the Doppler blind zone. By the mode, not only is the information of multi-frame real-time azimuth angle fully utilized, but also the multi-frame real-time sensor data measured by the sensor is combined for calculation, so that the problem of insufficient dependence of the traditional method on the target motion model is effectively solved. By the comprehensive data processing means, the accuracy of determining the target running speed in the Doppler blind zone is obviously improved.

In an embodiment, the step S200 may specifically be performed as follows:

S210, determining a direction unit vector between a sensor and a measured target based on the current relative azimuth angle;

s220, determining a speed component vector of the measured object based on the current transverse speed of the measured object and the current longitudinal speed of the measured object;

S230, determining the blind area state of the measured object based on the direction unit vector and the speed component vector.

Alternatively, in the embodiment of the present application, the unit vector of the direction between the sensor and the measured object may be calculated according to the relative azimuth information of the object detected by the sensor, and the purpose of this step is to obtain the moving direction of the object relative to the sensor. The velocity component vector of the object can be determined by using the current transverse velocity and longitudinal velocity information of the object to be measured, and this step considers the transverse and longitudinal motion components of the object in a Cartesian coordinate system. By comparing the magnitude relation between the direction unit vector and the velocity component vector, it can be determined whether the measured target is located in the Doppler blind zone of the sensor. If the relative movement direction included angle is approximately vertical, namely in the Doppler blind zone, the target can be judged to be in the blind zone state.

In these alternative embodiments, by considering the lateral velocity and the longitudinal velocity, in combination with the relative azimuth information, the blind zone status of the target is determined more accurately and comprehensively. This helps to improve the accuracy and practicality of the doppler blind area discrimination.

In an embodiment, the step S230 may specifically be performed as follows:

s231, calculating an included angle cosine value of an included angle between the actual speed direction of the measured object and a relative position, wherein the relative position is the relative position between the sensor and the measured object, based on a first formula, and the first formula is as follows:

Wherein alpha is the included angle between the actual speed direction and the relative position of the measured object, n _l is the direction unit vector, Is a velocity component vector;

S232, determining the blind area state of the measured target as a first state when the cosine value of the included angle is smaller than or equal to a preset judging threshold value, wherein the first state is used for indicating that the measured target is in the Doppler blind area of the sensor, and the preset judging threshold value is determined according to the running state of the measured target;

S233, determining the blind area state of the measured target as a second state when the cosine value of the included angle is larger than a preset judging threshold value, wherein the second state is used for indicating that the measured target is not in the Doppler blind area of the sensor.

Optionally, in a specific implementation manner of the present application, a determination flow of the doppler blind area is as follows:

① Acquiring relative azimuth information theta of a detected target detected by a sensor at the current moment and position information (x, y) of the detected target under a Cartesian coordinate system;

② Based on the relative azimuth information theta of the measured target, a direction unit vector of a connecting line l of the radar sensor and the measured target can be obtained, wherein the direction unit vector is represented by the following formula 5:

n_l1＝(sinθ cosθ) (5)

In addition, based on the measured target position information obtained in step ①, the position information may be rewritten into a vector form as follows:

n_l2＝(x y) (6)

③ The estimated value of the velocity information component of the measured object at the current moment is obtained from the tracking list of the measured object, namely, the x-direction component in the rectangular coordinate system is v _x, the y-direction component is v _y, and then the vector expression form of the velocity component can be obtained, as shown in the following formula 7:

④ And judging Doppler blind areas.

Based on the direction unit vector n _l and the velocity component vector of the object to be measuredJudging whether the measured target is in a Doppler blind area relative to the radar sensor in real time, wherein a judging strategy is as follows:

Epsilon in the formula (8) is the discrimination threshold of the Doppler blind zone 1. In general, cosα=0, i.e., n _l, Strictly in a vertical state, namely a strict Doppler blind zone, but considering the influences of target size information, measurement errors and the like, the value of cos alpha is not strictly equal to zero, so a discrimination threshold epsilon is set. If cos alpha is less than or equal to epsilon, namely the Doppler blind area judging condition is met, the flag=1 (namely the first state) is marked, namely the current moving direction of the measured target is marked to be in the Doppler blind area relative to the radar sensor, otherwise the flag=0 (namely the second state) is marked, namely the non-Doppler blind area. Thus, the target satisfying the expression (8) can be expressed as the zero doppler blind area 1.

Optionally, in the embodiment of the present application, the tracking list of the measured target is obtained through a target tracking system or algorithm. The target tracking system is responsible for processing the target information detected by the sensor, maintaining the state of the target, including position, speed, etc., and recording the information in a tracking list. A sensor (such as a millimeter wave radar) detects the target at each instant and provides data on relative azimuth, position information, etc. The tracking algorithm tracks the target using data provided by the sensor. When the target tracking system determines the state of the target, it updates the information of the target into the tracking list. The list may contain information such as unique identifier of the target, location, velocity, acceleration, etc.

In these alternative embodiments, the direction unit vector and the velocity component vector of the measured target are used to determine whether the measured target is in a doppler blind zone relative to the radar sensor in real time. And adopting a discrimination strategy, if the Doppler blind zone discrimination condition is met, marking the state as a first state, wherein the current motion direction of the measured target is in a Doppler blind zone relative to the radar sensor, and otherwise marking the state as a second state, and indicating a non-Doppler blind zone.

By introducing the discrimination threshold, the implementation mode does not require that the target motion direction is completely perpendicular to the position connecting line, allows certain threshold constraint conditions, and improves the flexibility of Doppler blind zone discrimination. In addition, through the state identification, whether the target is in the Doppler blind zone or not is effectively distinguished, and important information is provided for subsequent processing. The method has the advantages of real-time performance and adaptability, and is beneficial to the performance of the target tracking system in the aspect of Doppler blind zone processing.

In an embodiment, the current driving information further includes a current lateral coordinate of the measured object and a current longitudinal coordinate of the measured object; the step S200 may specifically further include the following steps:

S240, determining the blind area state of the detected target as a first state under the condition that the current longitudinal coordinate y is smaller than or equal to a preset judging threshold epsilon and the current transverse speed v _x is in a first preset range.

In an embodiment, the above step 200 may specifically further include the following steps:

S250, determining the blind area state of the detected target as a first state under the condition that the current transverse coordinate x is smaller than or equal to a preset judging threshold epsilon and the current longitudinal speed v _y is in a first preset range.

Alternatively, in one embodiment of the present application, if the doppler measurement value is equal to 0, that is, v _r =0, it is only possible that the molecular portion of formula (4) is equal to zero, that is, the following molecular expression F is equal to zero, as shown in formula (4):

F＝y·v_y+x·v_x (9)

By analysis of equation (9), however, there are mainly two cases where F equals zero:

① Relative longitudinal travel of objects

If y is less than or equal to epsilon and v _x is about 0, then v _y of the measured target is a small value no matter how large, namely the Doppler speed measured by the radar is a small value, and the corresponding measured target is on the side of the radar and mainly runs longitudinally.

Corresponds to the Doppler blind zone 2 shown in fig. 4, so the Doppler blind zone 2 discrimination process is as follows: if y is less than or equal to epsilon and v _x is about 0, marking flag=A, namely marking that the current moving direction of the measured target is in a Doppler blind zone relative to the radar sensor, otherwise marking flag=0, namely a non-Doppler blind zone.

② Relative lateral travel of objects

If x is less than or equal to epsilon and v _y is about 0, v _x of the measured target is a small value no matter how large, i.e. the Doppler speed measured by the radar is a small value, and the corresponding measured target is in front of or behind the radar and mainly runs transversely.

Corresponds to the doppler blind area 3 shown in fig. 5, so the doppler blind area 3 discrimination process is: if x is less than or equal to epsilon and v _y is about 0, marking flag=B, namely marking that the current moving direction of the measured target is in a Doppler blind zone relative to the radar sensor, otherwise marking flag=0, namely a non-Doppler blind zone.

In these alternative embodiments, it is allowed to effectively determine whether the measured target is in a doppler blind zone with respect to the radar sensor by the case where the doppler measurement value is equal to zero. By analyzing the relative movement direction of the measured target, the type of the Doppler blind zone where the target is located can be identified more accurately, finer information is provided for subsequent speed calculation compensation, and the accuracy and reliability of the Doppler blind zone judgment are improved.

In one embodiment, each frame of real-time sensor information includes real-time Doppler velocity of the measured object measured by the sensor, the object velocity including an object lateral velocity and an object longitudinal velocity; the above step 400 may specifically be performed as follows:

S410, generating a second formula based on the multi-frame real-time azimuth angle and the multi-frame real-time sensor information, wherein the second formula is as follows:

Wherein v _x is the target transverse velocity of the measured target, v _y is the target longitudinal velocity of the measured target, θ _m is the real-time azimuth angle corresponding to the m-th frame, and v _rm is the real-time Doppler velocity corresponding to the m-th frame;

S420, carrying out speed solving on the second formula based on a least square method to obtain the target transverse speed of the measured target and the target longitudinal speed of the measured target.

Optionally, in a specific implementation manner of the application, the track with the Doppler blind zone pre-determined is subjected to velocity calculation compensation. For the detected target identified in steps S210-S250 as flag >0, or flag=a, or flag=b (i.e. in the first state), the detected target is identified as the detected target whose current movement direction is in the doppler blind area with respect to the radar sensor. Because the Doppler information detected by the sensor cannot accurately reflect the motion state of the detected target, based on the Doppler information detection basic principle represented by the formula (2), the Doppler measurement information of the detected target in the Doppler blind area can be combined for resolving the real motion velocity component of the detected target. M frames of measured values are usually stored, and the calculation of the real speed information of the measured object can be performed by adopting a least square method, as follows:

After the number of data storage frames is met, the real motion velocity component v _x、v_y of the target in the zero Doppler region can be obtained by carrying out least square solution on the above formula 10.

In these alternative embodiments, the accuracy of the velocity of the target in the Doppler blind zone is improved by combining multiple measurements to perform least squares solution. The method not only can effectively solve the problem of inaccurate speed information caused by the Doppler blind area, but also can provide more reliable speed information for subsequent target tracking processing, and enhances the performance of the system under the condition of the Doppler blind area.

In an embodiment, after the step S400, the method may further specifically perform the following steps:

s430, increasing the value of the preset judging threshold value under the condition that the target speed of the measured target in the Doppler blind zone is not obtained.

Optionally, in a specific implementation manner of the present application, after the target lateral velocity of the measured target and the target longitudinal velocity of the measured target are obtained, the target tracking process and velocity information in the doppler blind area are compensated and corrected. For the target in the doppler blind area, namely the target with flag=1, if the calculation of the real speed of the target is completed in S410-S420, the calculation value v _x、v_y is used for correcting the speed information in the target state, namely the speed component v _x、v_y of the target obtained by calculation replaces the speed information of the corresponding target in the target tracking list; if the solution is not completed, the search threshold associated with the target is enlarged (i.e. the value of epsilon is increased) to ensure that the track is not interrupted.

In these alternative embodiments, the system may take another strategy, i.e., expand the search threshold for target association, with incomplete resolution, i.e., no true velocity component is obtained. Therefore, under the condition that the target is in the Doppler blind zone, the system can still effectively carry out target association, and the interruption of the flight path is avoided. The operation of expanding the search threshold considers the inaccuracy of speed information caused by Doppler blind area, and the system can more easily re-associate the targets by increasing the search range, so as to keep the tracking continuity of the targets.

In the embodiment of the application, for the target with the real speed obtained by resolving, the accuracy of the target tracking state is improved by directly replacing the speed information; for the target which is not solved, the adaptability of the system to the target in the Doppler blind zone is enhanced by expanding the search threshold, so that the tracking continuity of the target is effectively maintained.

In an embodiment, after the step 400, the method may further specifically perform the following steps:

s440, obtaining a tracking record of a detected target in a preset database;

S450, acquiring the initial speed of the measured target in the Doppler blind zone from the tracking record;

s460, the initial speed is replaced with the target speed.

Alternatively, in a specific embodiment of the present application, first, the doppler blind area velocity determination method of the present application is exemplarily described with reference to an exemplary diagram. As shown in fig. 3, the unit direction vector of the measured target direction straight line l can be expressed as n _l = (sin theta cos theta) by the formula (5), and the vector expression of the measured target movement speed V _T can be expressed as the expression (7)Therefore, cos α≡0 when the relative motion vector of the object to be measured is perpendicular to the relative position line l. At this time, by the Doppler velocity measurement principle shown in the formula (2), it can be determined that the measured target is in a Doppler blind zone relative to the radar.

The Doppler blind zone discrimination algorithm of the application does not strictly require that the moving direction of the measured object is completely perpendicular to the position connecting line on the basis of considering the size information, measurement error and other influence factors of the measured object, namely, the moving direction is not in the same state as the moving directionAnd judging whether the measured target is in a Doppler blind zone or not on the basis of being strictly equal to zero, and allowing a certain threshold constraint condition, namely, as shown in a formula (8).

In the implementation process of the algorithm, based on the processed data characteristics, the Doppler blind area judgment threshold epsilon can be considered to be set to 0.1736, namely when the included angle between the moving direction of the measured target and the connecting line of the position is larger than 80 degrees, the algorithm can judge that the movement of the measured target relative to the radar is in the Doppler blind area. As shown in fig. 3, on the basis of obtaining the azimuth θ of the measured target relative to the radar, if the angle of the measured target in the relative movement speed direction α is located in the included angle area formed by the straight line l ₂₁、l₂₂ in the middle area enveloped by the straight line l ₁₁、l₁₂ in fig. 3, it can be determined that the measured target in the relative positional relationship is in the doppler blind area, that is, in the middle area enveloped by the straight line l ₁₁、l₁₂ in fig. 3, the target satisfying the formula (8) can be identified as the measured target in the doppler blind area, at this time, flag=1 is identified, and the subsequent tracking processing is performed.

For discriminating the measured target in the Doppler blind zone, m frames of measured value information can be stored, and then based on the formula (10), the formula (10) is rewritten into a matrix product form, and the following formula 11 is adopted:

And (3) solving the formula (11) by adopting a least square method to obtain the actual movement velocity component information v _x、v_y of the measured object. After the calculation is completed, the speed information compensation and correction are carried out on the measured target in the Doppler blind zone in the tracking algorithm processing process. The stored frame number can be determined according to the characteristics of the processed data, if the relative movement speed of the detected target in the tracking processing is higher, for example, 2-3 can be taken if the detected target is detected and tracked in a remote early warning way; if the relative movement speed of the detected target in the tracking process is slower, for example, the tracking process of the road vehicle-mounted radar sensor, 5-10 can be taken.

Optionally, in practical application, the zero doppler discrimination threshold and the setting of the storage frame number of the target measurement information in the doppler dead zone are both flexibly set based on the selected sensing and the processed data characteristics, for example, the processed data scene is a small target tracking problem with relatively clean background noise, and the constraint threshold met by doppler can be set smaller, namely, the relative included angle is required to be greater than 85 degrees, even greater; and for the number of stored frames of the target measurement values in the doppler dead zone, setting can be made based on the usage scenario of the speed magnitude of the relative motion.

Alternatively, in another implementation manner of the present application, as shown in fig. 6, an embodiment of a tracking process based on whether the measured target is in the condition of the doppler blind zone determination and the doppler blind zone based on the measured data is given herein. The Doppler blind area discrimination threshold epsilon= 0.0698 is set, namely the included angle between the relative motion direction of the measured target and the azimuth direction of the sensor is larger than 86 degrees, and the measured target in the example data is smaller in size; the measured value storage is performed for the measured object in the doppler blind area for the actual moving speed calculation, in which the data storage frame number m=10 is set, since the measured object in the example data is a relatively low-speed moving object on the road.

After the detected target is pre-determined to enter the Doppler blind zone, target tracking processing under the condition of the Doppler blind zone is started, as shown in fig. 6, the observed detected target transversely passes through the radar detection area from the right side, the area between two dotted lines in fig. 6 is the Doppler blind zone based on the parameter setting, and the detected target in the transverse passing movement can be determined as the Doppler blind zone. For a detected target entering a Doppler blind zone and traversing transversely, after 10 frames of measured values are stored, the true motion velocity component v _x、v_y of the detected target is calculated based on a formula (7), velocity compensation of the detected target is carried out after the calculation, as can be seen from comparison in fig. 6, three tracks with the numbers of 25, 31 and 14 are output after the processing of a traditional algorithm, the track is discontinuous and a false alarm (namely redundant tracks with the numbers of 31 and 14) exists in the traditional processing algorithm, the track number output by the processing result of the algorithm related by the application is 10, and as can be seen from the result analysis in fig. 6, the track is continuous and stable in the processing result, and the intermittent and false alarm of the track are effectively restrained.

In the embodiment of the application, whether the target is in a Doppler blind zone or not is judged in real time by combining the relative position direction and the relative movement direction included angle of the target; and (5) carrying out targeted speed estimation compensation on the target entering the Doppler blind zone. The measurement of the motion state of the target in the Doppler blind zone is inaccurate, and because the target in the Doppler blind zone is inaccurate, the target Doppler information detected by the sensor cannot accurately reflect the dynamic attribute of the target, and therefore the algorithm disclosed by the application carries out speed calculation compensation on the target in the Doppler blind zone. In addition, the dynamic attribute of the target is further judged based on the calculated result, and further special speed compensation is carried out on the track entering the Doppler blind zone, so that continuous, stable and stable tracking output of the track is realized.

In the optional embodiments, whether the target is in a Doppler blind zone relative to the radar sensor or not can be rapidly judged in the data processing process, and compared with the traditional Doppler blind zone setting algorithm method, the algorithm related to the application has great improvement on the real-time performance and the flexibility of the Doppler blind zone judgment; in addition, the algorithm disclosed by the application carries out speed resolving compensation on the target in the Doppler blind zone, effectively corrects the characteristic of inaccurate speed information of the Doppler blind zone, and has great improvement on the aspects of the traditional multi-hypothesis and multi-model processing strategies, because the algorithm disclosed by the application can effectively avoid unnecessary hypothesis and calculation amount investment. The adaptability of the algorithm related by the application is wider than that of the traditional algorithm.

Fig. 7 is a schematic structural diagram of a doppler blind area velocity determination apparatus according to another embodiment of the present application, and only a portion related to the embodiment of the present application is shown for convenience of explanation.

Referring to fig. 7, the doppler blind area velocity determination apparatus may include:

A first obtaining module 701, configured to obtain a current relative azimuth angle between the sensor and the measured target, and current running information of the measured target, where the current running information includes a current lateral speed of the measured target and a current longitudinal speed of the measured target;

A first determining module 702, configured to determine a blind area state of the measured target based on the current relative azimuth angle and the current driving information, where the blind area state is used to indicate whether the measured target is in a doppler blind area of the sensor;

A second obtaining module 703, configured to obtain, in a case where the blind area status indicates that the measured target is in a doppler blind area of the sensor, a multiframe real-time azimuth angle between the sensor and the measured target in the doppler blind area of the measured target, and multiframe real-time sensor information measured by the sensor;

and the second determining module 704 is configured to perform joint calculation on the multiframe real-time azimuth angle and multiframe real-time sensor information, and determine a target speed of the measured target in the doppler blind area.

In an embodiment, the current travel information includes a current lateral speed of the measured object and a current longitudinal speed of the measured object; the first determination module 702 may include:

the first determining submodule is used for determining a direction unit vector between the sensor and the measured target based on the current relative azimuth angle;

A second determining sub-module for determining a velocity component vector of the measured object based on the current lateral velocity of the measured object and the current longitudinal velocity of the measured object;

and the third determination submodule is used for determining the blind area state of the measured object based on the direction unit vector and the speed component vector.

In an embodiment, the third determination submodule may include:

The first calculation unit is used for calculating an included angle cosine value of an included angle between the actual speed direction of the measured target and the relative position based on a first formula, wherein the relative position is the relative position between the sensor and the measured target, and the first formula is as follows:

The first determining unit is used for determining the blind area state of the measured target to be a first state under the condition that the cosine value of the included angle is smaller than or equal to a preset judging threshold value, wherein the first state is used for indicating that the measured target is in the Doppler blind area of the sensor, and the preset judging threshold value is determined according to the running state of the measured target;

And the second determining unit is used for determining the blind area state of the measured target to be a second state under the condition that the cosine value of the included angle is larger than a preset judging threshold value, and the second state is used for indicating that the measured target is not in the Doppler blind area of the sensor.

In an embodiment, the current driving information further includes a current lateral coordinate of the measured object and a current longitudinal coordinate of the measured object; the first determination module 702 may further include:

and the fourth determining submodule is used for determining the blind area state of the measured target as a first state under the condition that the current longitudinal coordinate is smaller than or equal to a preset judging threshold value and the current transverse speed is in a first preset range.

In an embodiment, the first determining module 702 may further include:

And the fifth determining submodule is used for determining the blind area state of the measured target as a first state under the condition that the current transverse coordinate is smaller than or equal to a preset judging threshold value and the current longitudinal speed is in a first preset range.

In one embodiment, each frame of real-time sensor information includes real-time Doppler velocity of the measured object measured by the sensor, the object velocity including an object lateral velocity and an object longitudinal velocity; the second determining module 704 may include:

The generating submodule is used for generating a second formula based on the multi-frame real-time azimuth angle and the multi-frame real-time sensor information, wherein the second formula is as follows:

And the computing sub-module is used for carrying out speed solving on the second formula based on the least square method to obtain the target transverse speed of the measured target and the target longitudinal speed of the measured target.

In an embodiment, the doppler blind area speed determining device may further include:

And the increasing module is used for increasing the value of the preset judging threshold value under the condition that the target speed of the measured target in the Doppler blind zone is not obtained.

the third acquisition module is used for acquiring a tracking record of a detected target in a preset database;

the fourth acquisition module is used for acquiring the initial speed of the measured target in the Doppler blind zone from the tracking record;

and the replacing module is used for replacing the initial speed with the target speed.

It should be noted that, based on the same concept as the method embodiment of the present application, the information interaction and the execution process between the devices/units are devices corresponding to the battery thermal runaway warning method, and all implementation manners in the method embodiment are applicable to the device embodiment, and specific functions and technical effects thereof may be referred to the method embodiment section, and are not repeated herein.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.

Fig. 8 shows a schematic hardware structure of an electronic device according to an embodiment of the present application.

The device may include a processor 801 and a memory 802 storing program instructions.

The steps of any of the various method embodiments described above are implemented when the processor 801 executes a program.

By way of example, a program may be partitioned into one or more modules/units that are stored in the memory 802 and executed by the processor 801 to accomplish the present application. One or more of the modules/units may be a series of program instruction segments capable of performing specific functions to describe the execution of the program in the device.

In particular, the processor 801 may include a Central Processing Unit (CPU), or Application SPECIFIC INTEGRATED Circuit (ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present application.

Memory 802 may include mass storage for data or instructions. By way of example, and not limitation, memory 802 may include a hard disk drive (HARD DISK DRIVE, HDD), a floppy disk drive, flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (Universal Serial Bus, USB) drive, or a combination of two or more of these. Memory 802 may include removable or non-removable (or fixed) media, where appropriate. Memory 802 may be internal or external to the integrated gateway disaster recovery device, where appropriate. In a particular embodiment, the memory 802 is a non-volatile solid-state memory.

The memory may include Read Only Memory (ROM), random Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described with reference to methods in accordance with aspects of the present disclosure.

The processor 801 implements any of the methods of the above embodiments by reading and executing program instructions stored in the memory 802.

In one example, the electronic device may also include a communication interface 803 and a bus 810. The processor 801, the memory 802, and the communication interface 803 are connected to each other via a bus 810 and perform communication with each other.

Communication interface 803 is primarily used to implement communication between modules, devices, units, and/or apparatuses in an embodiment of the present application.

Bus 810 includes hardware, software, or both, coupling components of the online data flow billing device to each other. By way of example, and not limitation, the buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a micro channel architecture (MCa) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of the above. Bus 810 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.

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

The embodiment of the application further provides a chip, the chip comprises a processor and a communication interface, the communication interface is coupled with the processor, the processor is used for running programs or instructions, the processes of the embodiment of the method can be realized, the same technical effects can be achieved, and the repetition is avoided, and the description is omitted here.

It should be understood that the chips referred to in the embodiments of the present application may also be referred to as system-on-chip chips, chip systems, or system-on-chip chips, etc.

Embodiments of the present application provide a computer program product stored in a storage medium, where the program product is executed by at least one processor to implement the respective processes of the above method embodiments, and achieve the same technical effects, and for avoiding repetition, a detailed description is omitted herein.

It should be understood that the application is not limited to the particular arrangements and instrumentality described above and shown in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. The method processes of the present application are not limited to the specific steps described and shown, but various changes, modifications and additions, or the order between steps may be made by those skilled in the art after appreciating the spirit of the present application.

The functional blocks shown in the above block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer grids such as the internet, intranets, etc.

It should also be noted that the exemplary embodiments mentioned in this disclosure describe some methods or systems based on a series of steps or devices. The present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, or may be performed in a different order from the order in the embodiments, or several steps may be performed simultaneously.

Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In the foregoing, only the specific embodiments of the present application are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present application is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present application, and they should be included in the scope of the present application.

Claims

1. A method for determining a velocity of a doppler blind zone, the method comprising:

determining a blind area state of the detected target based on the current relative azimuth angle and the current running information, wherein the blind area state is used for indicating whether the detected target is in a Doppler blind area of the sensor;

Acquiring a multi-frame real-time azimuth angle between the sensor and the measured target in the Doppler blind zone and multi-frame real-time sensor information measured by the sensor under the condition that the blind zone state indicates that the measured target is in the Doppler blind zone of the sensor;

2. The method of claim 1, wherein determining the blind zone status of the measured object based on the current relative azimuth and the current travel information comprises:

Determining a direction unit vector between the sensor and the measured target based on the current relative azimuth;

Determining a velocity component vector of the measured object based on a current lateral velocity of the measured object and a current longitudinal velocity of the measured object;

and determining the blind area state of the measured object based on the direction unit vector and the speed component vector.

3. The method of claim 2, wherein the determining the blind zone state of the measured object based on the direction unit vector and the velocity component vector comprises:

calculating an included angle cosine value of an included angle between an actual speed direction of the measured target and a relative position based on a first formula, wherein the relative position is a relative position between the sensor and the measured target, and the first formula is as follows:

Wherein alpha is an included angle between the actual speed direction and the relative position of the measured object, n _l is the direction unit vector, and n _VT is the speed component vector;

under the condition that the cosine value of the included angle is smaller than or equal to a preset judging threshold value, determining the blind area state of the measured object as a first state, wherein the first state is used for indicating that the measured object is in the Doppler blind area of the sensor, and the preset judging threshold value is determined according to the running state of the measured object;

And under the condition that the cosine value of the included angle is larger than the preset judging threshold value, determining the blind area state of the measured target as a second state, wherein the second state is used for indicating that the measured target is not in the Doppler blind area of the sensor.

4. A method according to claim 3, wherein the current travel information further comprises current lateral coordinates of the object under test and current longitudinal coordinates of the object under test;

The determining the blind area state of the measured target based on the current relative azimuth angle and the current running information further comprises:

And determining the blind area state of the detected target as the first state under the condition that the current longitudinal coordinate is smaller than or equal to the preset judging threshold value and the current transverse speed is in a first preset range.

5. The method of claim 4, wherein determining the blind zone status of the measured object based on the current relative azimuth and current travel information further comprises:

And determining the blind area state of the detected target as the first state under the condition that the current transverse coordinate is smaller than or equal to the preset judging threshold value and the current longitudinal speed is in the first preset range.

6. The method of claim 1, wherein each frame of real-time sensor information comprises a real-time doppler velocity of the measured object measured by the sensor, the object velocity comprising an object lateral velocity and an object longitudinal velocity;

and the step of carrying out joint calculation on the multi-frame real-time azimuth angle and the multi-frame real-time sensor information to determine the target speed of the measured target in the Doppler blind zone, which comprises the following steps:

generating a second formula based on the multi-frame real-time azimuth angle and the multi-frame real-time sensor information, wherein the second formula is:

And carrying out speed solving on the second formula based on a least square method to obtain the target transverse speed of the tested target and the target longitudinal speed of the tested target.

7. The method of claim 3, wherein after jointly computing the multi-frame real-time azimuth angle, and the multi-frame real-time sensor information, determining a target velocity of the measured target within the doppler blind zone, the method further comprises:

and under the condition that the target speed of the measured target in the Doppler blind zone is not obtained, increasing the value of the preset judging threshold value.

8. The method of claim 1, wherein after jointly computing the multi-frame real-time azimuth angle, and the multi-frame real-time sensor information, determining a target velocity of the measured target within the doppler blind zone, the method further comprises:

Acquiring a tracking record of the detected target in a preset database;

acquiring the initial speed of the measured target in the Doppler blind zone from the tracking record;

And replacing the initial speed with the target speed.

9. A doppler blind zone velocity determination apparatus, the apparatus comprising:

the first acquisition module is used for acquiring a current relative azimuth angle between a sensor and a measured target and current running information of the measured target, wherein the current running information comprises a current transverse speed of the measured target and a current longitudinal speed of the measured target;

The first determining module is used for determining a blind area state of the measured target based on the current relative azimuth angle and the current running information, wherein the blind area state is used for indicating whether the measured target is in a Doppler blind area of the sensor;

A second obtaining module, configured to obtain, when the blind area state indicates that the measured target is in a doppler blind area of the sensor, a multiframe real-time azimuth angle between the sensor and the measured target in the doppler blind area of the measured target, and multiframe real-time sensor information measured by the sensor;

10. An electronic device, the device comprising: a processor and a memory storing computer program instructions;

The processor, when executing the computer program instructions, implements the doppler blind zone velocity determination method according to any one of claims 1-8.