CN115755022A - Target tracking method, device, equipment and medium - Google Patents
Target tracking method, device, equipment and medium Download PDFInfo
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Abstract
The application discloses a target tracking method, a target tracking device, target tracking equipment and a target tracking medium. The method comprises the following steps: acquiring current measurement data of a target to be measured acquired by a radar and a last state vector estimation value of the target to be measured at a last execution moment; determining a current deviation vector according to current measurement data, a last state vector estimation value and set engineering parameter information; determining the current state vector of the target to be measured according to the current deviation vector and the last state vector estimation value; and determining the current position of the target to be measured according to the current state vector. Corresponding engineering parameters are introduced according to data characteristics of radar target tracking, original deviation vectors are corrected through the engineering parameters, current state vectors of the target to be detected are obtained through the extended Kalman filter, and the target to be detected is tracked. The problem of target position and state estimation divergence in the target tracking process is solved, the stability of the filter is ensured, and the continuity and the precision of target tracking are improved.
Description
Technical Field
The present application relates to the field of radar technologies, and in particular, to a target tracking method, apparatus, device, and medium.
Background
The measurement data acquired by the vehicle-mounted angle radar detection target comprises the position (radial distance), angle and speed (radial distance change rate) of the target relative to the radar. Usually, a simple newton linear prediction model is used to track a target, i.e. information such as a distance and a speed of the target to be measured in a cartesian coordinate system is obtained. However, since the measurement is in a radar polar coordinate system and the state tracking of the target is in a cartesian coordinate system, an extended kalman filter is required. However, errors existing in actual target detection can cause divergence of the filter, and finally obtained target state values are wrong, so that the target loses tracking or is in abnormal states (such as position jump, speed mutation and the like).
In the prior art, an Unscented Kalman Filter (UKF) is designed to reduce linearization errors, or a noise matrix Q in an adaptive filter adjustment process and a measurement noise matrix R are designed to suppress filter jitter caused by measurement errors, and the like. However, in practical applications, on one hand, the calculation is enlarged, on the other hand, the estimated Q and R do not necessarily conform to the reality, and even the instability of the filter is aggravated.
Content of application
The application provides a target tracking method, a target tracking device and a target tracking medium, which are used for accurately determining a current state vector of a target.
According to a first aspect of the present application, there is provided a target tracking method, including:
acquiring current measurement data of a target to be measured acquired by a radar and a last state vector estimation value of the target to be measured at a last execution moment;
determining the current deviation vector according to the current measurement data, the last state vector estimation value and set engineering parameter information;
determining the current state vector of the target to be detected according to the current deviation vector and the last state vector estimation value;
and determining the current position of the target to be detected according to the current state vector.
According to a second aspect of the present application, there is provided a target tracking apparatus comprising:
the acquisition module is used for acquiring current measurement data of a target to be measured acquired by a radar and a last state vector estimation value of the target to be measured at a last execution moment;
the first determining module is used for determining the current deviation vector according to the current measurement data, the last state vector estimation value and set engineering parameter information;
the second determining module is used for determining the current state vector of the target to be measured according to the current deviation vector and the last state vector estimation value;
and the position determining module is used for determining the current position of the target to be detected according to the current state vector.
According to a third aspect of the present application, there is provided an electronic apparatus comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the first and the second end of the pipe are connected with each other,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform a target tracking method as described in any of the embodiments of the present application.
According to another aspect of the present application, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the target tracking method according to any one of the embodiments of the present application when the computer instructions are executed.
According to the technical scheme of the embodiment of the application, the application discloses a target tracking method, a target tracking device, target tracking equipment and a target tracking medium. The method comprises the following steps: acquiring current measurement data of a target to be measured acquired by a radar and a last state vector estimation value of the target to be measured at a last execution moment; determining a current deviation vector according to the current measurement data, the last state vector estimation value and the set engineering parameter information; determining the current state vector of the target to be measured according to the current deviation vector and the last state vector estimation value; and determining the current position of the target to be detected according to the current state vector. Corresponding engineering parameters are introduced according to data characteristics of radar target tracking, original deviation vectors are corrected through the engineering parameters, current state vectors of the target to be detected are obtained through the extended Kalman filter, and the target to be detected is tracked. The problem of target position and state estimation divergence in the target tracking process is solved, the stability of the filter is ensured, and the continuity and the precision of target tracking are improved.
It should be understood that the statements in this section are not intended to identify key or critical features of the embodiments of the present application, nor are they intended to limit the scope of the present application. Other features of the present application will become apparent from the following description.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a target tracking method according to an embodiment of the present application;
FIG. 2 is a flowchart of a target tracking method according to a second embodiment of the present application;
FIG. 3 is a schematic structural diagram of a target tracking apparatus according to a third embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device implementing the target tracking method according to the embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example one
Fig. 1 is a flowchart of a target tracking method according to an embodiment of the present application, where the present embodiment is applicable to a target tracking situation based on an extended kalman filter, and the method may be performed by a target tracking device, where the target tracking device may be implemented in a form of hardware and/or software, and the target tracking device may be configured in an electronic device. As shown in fig. 1, the method includes:
s110, current measurement data of the target to be measured collected by the radar and a last state vector estimation value of the target to be measured at a last execution time are obtained.
It should be noted that the current measurement data acquired by the radar is measurement data of the target to be measured relative to the radar, which is current measurement data in a radar polar coordinate system, and the state tracking of the target to be measured is in a cartesian coordinate system, so that an extended kalman filter is required to convert the current measurement data in the cartesian coordinate system into a state vector in the cartesian coordinate system.
In the present embodiment, the radar is understood as a device having a plurality of transmitting antennas and receiving antennas, which transmits and receives radar signals. The target to be detected can be understood as a target needing to be tracked in the detection range of the radar. The current measurement data can be understood as data of the position, the angle, the speed and the like of the target to be measured relative to the radar obtained by converting the radar signal. The last execution time can be understood as the time when the target to be measured is detected in the last frame of the radar. The last state vector estimate may be understood as the current state vector estimate from the last time the prediction was performed.
Specifically, a radar can be arranged on the vehicle, the processor can control the radar, a linear frequency modulation continuous wave signal is transmitted through a transmitting antenna of the radar, if a target to be detected exists in a detection range of the radar, a receiving signal with relevant information of the target to be detected can be formed after the transmitting signal detects the target to be detected, the receiving signal is received by the receiving antenna, the received receiving signal can be subjected to frequency mixing, filtering, sampling and other processing, and current measurement data can be obtained, wherein the current measurement data can include the position (radial distance), the angle and the speed (radial distance change rate) of the target to be detected relative to the radar. When the target to be detected is detected at the last execution time of the radar, the state vector of the target to be detected at the last execution time can be calculated according to the extended kalman filter, the state transition matrix is multiplied by the state vector at the last execution time, the state vector value at the next execution time is calculated, namely, the moving track of the target to be detected at the next execution time is predicted, the last state vector estimation value is obtained, and the processor can obtain the last state vector estimation value of the target to be detected at the last execution time.
And S120, determining the current deviation vector according to the current measurement data, the last state vector estimation value and the set engineering parameter information.
In this embodiment, the engineering parameter information may be understood as a parameter that is not affected by the outside, i.e., more accurate parameter information. The current offset vector may be understood as the offset vector between the current measurement data and the measurement equation for the last state vector estimate.
Specifically, a measurement equation of a previous state vector can be calculated according to a recursion formula of the extended kalman filter, the current measurement data and the measurement equation of the previous state vector are subtracted from each other, a deviation value between the current measurement data and the measurement equation is determined, and the deviation value is corrected according to the set engineering parameter information, so that a more accurate corrected current deviation vector is obtained.
And S130, determining the current state vector of the target to be measured according to the current deviation vector and the last state vector estimation value.
In this embodiment, the current state vector may be understood as a state vector of the target to be measured at the current time in a cartesian coordinate system, where the state vector includes a position, a speed, and an acceleration of the target to be measured at the current time in the x-axis direction, and a position, a speed, and an acceleration in the y-axis direction.
Specifically, the last measured data estimated value may be calculated according to the recursion formula of the extended kalman filter and the measured data at the last execution time, the gain coefficient may be calculated according to the last measured data estimated value and the last state vector estimated value, and the current state vector of the target to be measured may be determined according to the last state vector estimated value, the gain coefficient, and the corrected current deviation vector.
And S140, determining the current position of the target to be detected according to the current state vector.
In the present embodiment, the current position may be understood as a position of the measurement target in a rectangular coordinate system centered on the radar.
Specifically, according to the current state vector, the position information of the target to be detected under the Cartesian coordinate system at the current moment can be determined, the position of the target to be detected in the x-axis direction and the position of the target to be detected in the y-axis direction can be determined, the radar can be used as the original point, the position information in the x-axis direction and the y-axis direction can be determined, the current position of the target to be detected can be determined, the information such as the distance of the target to be detected relative to the radar at the current time can be determined according to the position information in the x-axis direction and the y-axis direction, and the tracking of the target to be detected is achieved.
In the target tracking method provided by the embodiment, current measurement data of a target to be detected, which is acquired by a radar, and a last state vector estimation value of the target to be detected at a last execution time are acquired; determining a current deviation vector according to the current measurement data, the last state vector estimation value and the set engineering parameter information; determining the current state vector of the target to be measured according to the current deviation vector and the last state vector estimation value; and determining the current position of the target to be detected according to the current state vector. Corresponding engineering parameters are introduced according to data characteristics of radar target tracking, original deviation vectors are corrected through the engineering parameters, the current state vector of the target to be detected is obtained through the extended Kalman filter, and the target to be detected is tracked. The problem of target position and state estimation divergence in the target tracking process is solved, the stability of the filter is ensured, and the continuity and the precision of target tracking are improved.
Example two
Fig. 2 is a flowchart of a target tracking method provided in the second embodiment of the present application, and this embodiment is further refined based on the foregoing embodiments, as shown in fig. 2, the method includes:
s210, current measurement data of the target to be measured collected by the radar and a last state vector estimation value of the target to be measured at a last execution moment are obtained.
And S220, determining the current measurement vector of the target to be measured according to the current measurement data.
In the present embodiment, the current measurement vector may be understood as a vector formed by forming a plurality of data in the current measurement data in a prescribed order.
Specifically, the current measurement data of the target to be measured acquired by the radar may be acquired, the current measurement data may include a position (radial distance), an angle, and a speed (radial distance change rate) of the target to be measured with respect to the radar, and the current measurement data may be arranged according to the radial distance, the angle, and the radial speed sequence of the target to be measured with respect to the radar, so as to obtain a current measurement vector.
For example, the current time is n, the current measurement vector may be denoted as U (n), and the current measurement vector may be determined by the following formula:
where r (n) represents the radial distance of the target relative to the radar,
representing the angle of the target relative to the radar and r' (n) representing the radial velocity of the target relative to the radar.
And S230, determining the current measurement equation of the target to be measured according to the last state vector estimation value.
Specifically, the last state vector estimation value may include a position, a speed, and an acceleration of the target to be measured in the cartesian coordinate system in the x-axis direction, and a position, a speed, and an acceleration in the y-axis direction. The position information of the x axis and the position information of the y axis predicted by the target to be measured at the last execution time in the last state vector estimation value can be substituted into the measurement equation, and then the current measurement equation of the target to be measured is determined.
For example, if the last execution time is n-1, the state vector S (n-1) at the last execution time can be expressed as:
S(n-1)＝[x(n-1),y(n-1),x′(n-1),y′(n-1),x″(n-1),y″(n-1)]
wherein x (n-1), x' (n-1) respectively represent the position, the speed and the acceleration of the object to be measured in the x-axis direction at the moment of n-1. y (n-1), y' (n-1) respectively represent the position, the speed and the acceleration of the object to be measured in the y-axis direction at the moment of n-1.
The last state vector estimation value S can be calculated from the state vector at the last execution time by the following formula apr (n)：
S apr (n)＝F×S(n-1)
Where F is the state transition matrix.
Can be estimated from the last state vector S apr (n) calculating a measurement equation H (S) by the following formula apr (n))：
Wherein x is apr (n) can represent the position estimated value of the target to be measured in the x-axis direction at the moment n, y apr (n) can represent the object to be measured at the time nThe position estimate in the y-direction is plotted.
S240, determining a current intermediate deviation vector according to the current measurement equation and the current measurement vector.
Specifically, the current measurement equation obtained through calculation of the measurement equation includes a position value, an angle value, and a velocity value of the relative radar obtained through prediction, and the current measurement vector and the current measurement equation may be subtracted from each other to determine the current intermediate deviation vector.
Illustratively, following the above formula, the current measurement vector may be represented by U (n), and the current measurement equation may be represented by H (S) apr (n)), the current median deviation value y can be calculated by the following formula:
y＝U(n)-H(S apr (n))
and S250, determining the current deviation vector according to the current intermediate deviation vector and the engineering parameter information.
Specifically, the current measurement vector includes a radial distance value, an angle, and a radial velocity with respect to the radar, and the current measurement equation includes a position value, an angle value, and a velocity value with respect to the radar, which are obtained through prediction, and the current intermediate deviation vector obtained by subtracting the current measurement equation from the current measurement vector includes a position deviation value obtained by subtracting the measured radial distance value from the predicted position value, an angle deviation value obtained by subtracting the measured angle from the predicted angle, and a velocity deviation value obtained by subtracting the measured radial velocity from the predicted velocity. The engineering information parameters include maximum values of possible deviations of positions, angles and speeds obtained through engineering. Comparing each deviation value in the current intermediate deviation vector with each deviation maximum value in the engineering information parameters to ensure that the calculated current intermediate deviation vector is not greater than the engineering parameter information, and if the calculated current intermediate deviation vector is greater than the engineering parameter information, replacing the deviation value with the maximum deviation value, so as to determine the current deviation vector.
Further, the step of determining the current deviation vector according to the current intermediate deviation vector and the engineering parameter information may include:
a1, acquiring a middle position deviation value, a middle angle deviation value and a middle speed deviation value which are included by a current middle deviation vector, wherein the position, the angle and the speed are respectively the position, the angle and the speed of a target to be measured relative to a radar.
In this embodiment, the intermediate position offset value may be understood as a position offset value obtained by subtracting a measured radial distance value and a predicted position value. The intermediate angular deviation value can be understood as an angular deviation value resulting from the subtraction of the measured angle and the predicted angle. The intermediate speed deviation value may be understood as a speed deviation value resulting from the subtraction of the measured radial speed and the predicted speed.
Specifically, the current intermediate deviation vector may have three values arranged in a fixed order from left to right, and a value at the leftmost position in the current intermediate deviation vector may be extracted, that is, the intermediate position deviation value. The value at the middle position in the current middle deviation vector can be extracted, namely the value of the middle angle deviation. The value of the rightmost position in the current intermediate deviation vector can be extracted, i.e. the intermediate speed deviation value.
and a2, determining a position deviation value according to the intermediate position deviation value and the engineering parameter information.
Specifically, the intermediate position deviation value may be compared with a corresponding position value in the engineering parameter information, and the position deviation value may be determined according to the comparison result.
Further, the step of determining the position deviation value according to the intermediate position deviation value and the engineering parameter information may specifically include:
and a21, acquiring the maximum position deviation value included in the engineering parameter information.
In this embodiment, the maximum position deviation value may be understood as the maximum value of the position deviation determined according to the engineering method.
Specifically, since the intermediate deviation vector includes an intermediate position deviation, an intermediate angle deviation, and an intermediate speed deviation, and the engineering parameter information also includes a maximum deviation value of a position, an angle, and a speed, the maximum position deviation value included in the engineering parameter information can be obtained.
and a22, taking the minimum value of the maximum position deviation value and the middle position deviation value as the position deviation value.
Specifically, the maximum position deviation value may be compared with the middle position deviation value, and when the maximum position deviation value is greater than or equal to the middle position deviation value, the middle position deviation value may be used as the position deviation value; when the maximum position deviation value is smaller than the intermediate position deviation value, the intermediate position deviation value obtained through calculation at present may be considered to be inaccurate, and the maximum position deviation value may be used as the position deviation value.
For example, the maximum position deviation value may be [1,5], and if 4 is used as the maximum position deviation value, and the calculated middle position deviation value is 3, the middle position deviation value is the minimum value, and 3 is used as the position deviation value. And if 2 is taken as the maximum position deviation value and the calculated middle position deviation value is 3, the maximum position deviation value is the minimum value, and 2 is taken as the position deviation value.
and a3, determining the angle deviation value according to the intermediate angle deviation value and the engineering parameter information.
Specifically, the intermediate angle deviation value may be compared with a corresponding angle value in the engineering parameter information, and the angle deviation value may be determined according to the comparison result.
Further, the step of determining the angle deviation value according to the intermediate angle deviation value and the engineering parameter information may specifically include:
and a31, acquiring the maximum angle deviation value included in the engineering parameter information.
In this embodiment, the maximum angle deviation value may be understood as the maximum value of the angle deviation determined according to the engineering method.
Specifically, since the intermediate deviation vector includes an intermediate position deviation, an intermediate angle deviation, and an intermediate speed deviation, and the engineering parameter information also includes a maximum deviation value of a position, an angle, and a speed, the maximum angle deviation value included in the engineering parameter information can be obtained.
and a32, judging whether the middle angle deviation value is greater than or equal to zero.
Specifically, since the target to be measured may be on the left side of the radar or on the right side of the radar, in order to distinguish the target to be measured, the angle value of the target to be measured on the left side of the radar measured by the radar may be set to a negative value, and the angle value of the target to be measured on the right side of the radar measured by the radar may be set to a positive value. It is determined whether the intermediate angle deviation value is greater than or equal to zero.
and a33, if yes, taking the minimum value of the maximum angle deviation value and the middle angle deviation value as the angle deviation value.
Specifically, after the intermediate angle deviation value is judged to be greater than or equal to zero, the maximum angle value may be divided by 180 ° multiplied by pi to obtain an angle corresponding to the maximum angle value, the obtained angle is compared with the intermediate angle deviation value to determine a minimum value thereof, and the minimum value is used as the angle deviation value.
and a34, if not, taking the maximum value of the maximum angle deviation value and the middle angle deviation value as the angle deviation value.
Specifically, if the intermediate angle deviation value is smaller than zero, the angle corresponding to the maximum angle value can be obtained by dividing the maximum angle value by 180 ° and multiplying pi, the obtained angle is compared with the intermediate angle deviation value, the maximum value is determined, and the maximum value is used as the angle deviation value.
For example, the maximum angle deviation value may range from [1,10].
and a4, determining a speed deviation value according to the intermediate speed deviation value and the engineering parameter information.
Specifically, the intermediate speed deviation value may be compared with a corresponding speed value in the engineering parameter information, and the speed deviation value may be determined according to the comparison result.
Further, the step of determining the speed deviation value according to the intermediate speed deviation value and the engineering parameter information may specifically include:
and a41, acquiring the maximum speed deviation value included in the engineering parameter information.
In this embodiment, the maximum speed deviation value may be understood as the maximum value of the speed deviation determined according to the engineering method.
Specifically, since the intermediate deviation vector includes an intermediate position deviation, an intermediate angle deviation, and an intermediate speed deviation, and the engineering parameter information also includes a maximum deviation value of a position, an angle, and a speed, the maximum speed deviation value included in the engineering parameter information can be obtained.
and a42, taking the minimum value of the maximum speed deviation value and the middle speed deviation value as the speed deviation value.
Specifically, the maximum speed deviation value may be compared with the intermediate speed deviation value, and when the maximum speed deviation value is greater than or equal to the intermediate speed deviation value, the intermediate speed deviation value may be used as the speed deviation value; when the maximum speed deviation value is smaller than the intermediate speed deviation value, the intermediate speed deviation value obtained through calculation at present can be considered to be inaccurate, and the maximum speed deviation value can be used as the speed deviation value.
For example, the maximum position deviation value may range from [1,3].
and a5, determining a current deviation vector according to the position deviation value, the angle deviation value and the speed deviation value.
Specifically, the current intermediate deviation vector can be replaced according to the determined position deviation value, angle deviation value and speed deviation value to obtain the current deviation vector.
And S260, determining the current measurement matrix according to the last state vector estimation value.
Specifically, the current measurement matrix may be determined from the position in the x-axis direction and the position in the y-axis direction in the last state vector estimation value according to a measurement matrix formula in the recurrence formula of the extended kalman filter.
And S270, determining a current gain coefficient according to the current measurement matrix and the acquired measurement noise matrix.
Specifically, the measurement vector at the previous execution time is combined with the state transition matrix and the process noise matrix to calculate the measurement vector estimation value at the previous execution time, and the current gain coefficient can be calculated according to the gain coefficient formula of the extended kalman filter and according to the measurement vector estimation value, the measurement matrix, the previous state vector estimation value and the measurement noise matrix.
For example, the current gain factor K may be calculated by the following formula:
K＝P apr (n)×J H (S apr (n)) T (J H (S apr (n))×P apr (n)×J H (S apr (n))+R) -1
wherein, P apr (n) denotes the measurement vector estimate, J H (S apr (n)) represents the current metrology matrix, R represents the measurement noise matrix, S apr And (n) represents the last state vector estimate.
And S280, determining the current state vector of the target to be measured according to the current gain coefficient, the current deviation vector and the last state vector estimation value.
Specifically, the current state vector of the target to be measured can be determined according to a state vector calculation formula in the extended kalman filter and according to the current gain coefficient, the current deviation vector and the last state vector estimation value.
For example, the current time is n, and the current state vector S (n) of the target to be measured can be determined by the following formula:
S(n)＝S apr (n)+K×y′
wherein S is apr And (n) represents the last state vector estimated value, K is the current gain coefficient, and y' is the current deviation vector.
And S290, determining the current position of the target to be detected according to the current state vector.
In the target tracking method provided by the second embodiment, corresponding engineering parameter information is introduced for data characteristics of radar target tracking, the intermediate deviation vector obtained according to the extended kalman filter is corrected through the engineering parameter information, the intermediate deviation vector larger than the engineering parameter information is replaced by using a corresponding numerical value in the engineering parameter information to obtain a current intermediate deviation vector, and the current state vector of the target to be detected is obtained through the current intermediate deviation vector in combination with the extended kalman filter, so that the target to be detected is tracked. The problem of target position and state estimation divergence in the target tracking process is solved, the divergence of the filter can be restrained quickly, simply and efficiently, the stability of the filter is ensured, and the continuity and the precision of target tracking are improved.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a target tracking apparatus according to a third embodiment of the present application. As shown in fig. 3, the apparatus includes: an acquisition module 31, a first determination module 32, a second determination module 33, and a position determination module 34. Wherein, the first and the second end of the pipe are connected with each other,
the acquiring module 31 is configured to acquire current measurement data of a target to be measured, which is acquired by a radar, and a last state vector estimation value of the target to be measured at a last execution time;
a first determining module 32, configured to determine a current offset vector according to the current measurement data, a last state vector estimation value, and set engineering parameter information;
a second determining module 33, configured to determine a current state vector of the target to be measured according to the current deviation vector and the previous state vector estimation value;
and the position determining module 34 is configured to determine a current position of the target to be measured according to the current state vector.
The third embodiment provides a target tracking device. The original deviation vector is corrected through engineering parameters, the current state vector of the target to be detected is obtained through an extended Kalman filter, and the target to be detected is tracked. The problem of target position and state estimation divergence in the target tracking process is solved, the stability of the filter is ensured, and the continuity and the precision of target tracking are improved.
Optionally, the first determining module may include:
the first determining unit is used for determining the current measurement vector of the target to be measured according to the current measurement data;
the second determination unit is used for determining the current measurement equation of the target to be measured according to the last state vector estimation value;
the third determining unit is used for determining a current intermediate deviation vector according to the current measurement equation and the current measurement vector;
and the fourth determining unit is used for determining the current deviation vector according to the current intermediate deviation vector and the engineering parameter information.
Further, the fourth determining unit may include:
the acquisition subunit is configured to acquire a middle position deviation value, a middle angle deviation value and a middle speed deviation value included in the current middle deviation vector, where the position, the angle and the speed are respectively a position, an angle and a speed of the target to be detected relative to the radar;
the first determining subunit is used for determining a position deviation value according to the intermediate position deviation value and the engineering parameter information;
the second determining subunit is used for determining an angle deviation value according to the intermediate angle deviation value and the engineering parameter information;
the third determining subunit is used for determining a speed deviation value according to the intermediate speed deviation value and the engineering parameter information;
and the fourth determining subunit is used for determining the current deviation vector according to the position deviation value, the angle deviation value and the speed deviation value.
The first determining subunit is specifically used for determining the first time interval;
acquiring a maximum position deviation value included in the engineering parameter information;
and taking the minimum value of the maximum position deviation value and the middle position deviation value as the position deviation value.
Wherein the second determining subunit is specifically configured to:
acquiring a maximum angle deviation value included in the engineering parameter information;
judging whether the intermediate angle deviation value is greater than or equal to zero or not;
if so, taking the minimum value of the maximum angle deviation value and the middle angle deviation value as the angle deviation value;
and if not, taking the maximum value of the maximum angle deviation value and the middle angle deviation value as the angle deviation value.
The third determining subunit may be specifically configured to:
acquiring a maximum speed deviation value included in the engineering parameter information;
and taking the minimum value of the maximum speed deviation value and the intermediate speed deviation value as the speed deviation value.
Optionally, the second determining module may be specifically configured to:
determining a current measurement matrix according to the last state vector estimation value;
determining a current gain coefficient according to the current measurement matrix and the acquired measurement noise matrix;
and determining the current state vector of the target to be measured according to the current gain coefficient, the current deviation vector and the last state vector estimated value.
The target tracking device provided by the embodiment of the application can execute the target tracking method provided by any embodiment of the application, and has corresponding functional modules and beneficial effects of the execution method.
Example four
FIG. 4 shows a schematic structural diagram of an electronic device 10 that may be used to implement embodiments of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the applications described and/or claimed herein.
As shown in fig. 4, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data necessary for the operation of the electronic apparatus 10 may also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to the bus 14.
A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, or the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, microprocessor, or the like. The processor 11 performs the various methods and processes described above, such as the target tracking method.
In some embodiments, the target tracking method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the object tracking method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the target tracking method by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. A computer program can execute entirely on a machine, partly on a machine, as a stand-alone software package partly on a machine and partly on a remote machine or entirely on a remote machine or server.
In the context of this application, a computer readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a first component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, first, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.
It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solution of the present application can be achieved, and the present invention is not limited thereto.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A target tracking method, comprising:
acquiring current measurement data of a target to be measured acquired by a radar and a last state vector estimation value of the target to be measured at a last execution moment;
determining the current deviation vector according to the current measurement data, the last state vector estimation value and set engineering parameter information;
determining the current state vector of the target to be detected according to the current deviation vector and the last state vector estimation value;
and determining the current position of the target to be detected according to the current state vector.
2. The method of claim 1, wherein determining the current deviant vector based on the current measurement data, the last state vector estimate, and configured engineering parameter information comprises:
determining the current measurement vector of the target to be measured according to the current measurement data;
determining a current measurement equation of the target to be measured according to the last state vector estimation value;
determining a current intermediate deviation vector according to the current measurement equation and the current measurement vector;
and determining the current deviation vector according to the current intermediate deviation vector and the engineering parameter information.
3. The method of claim 2, wherein determining a current offset vector based on the current intermediate offset vector and the set engineering parameter information comprises:
acquiring a middle position deviation value, a middle angle deviation value and a middle speed deviation value which are included by the current middle deviation vector, wherein the position, the angle and the speed are respectively the position, the angle and the speed of the target to be detected relative to the radar;
determining a position deviation value according to the middle position deviation value and the engineering parameter information;
determining an angle deviation value according to the intermediate angle deviation value and the engineering parameter information;
determining a speed deviation value according to the intermediate speed deviation value and the engineering parameter information;
and determining a current deviation vector according to the position deviation value, the angle deviation value and the speed deviation value.
4. The method of claim 3, wherein determining a location offset value based on the intermediate location offset value and the engineering parameter information comprises:
acquiring a maximum position deviation value included in the engineering parameter information;
and taking the minimum value of the maximum position deviation value and the middle position deviation value as a position deviation value.
5. The method of claim 3, wherein determining an angular deviation value based on the intermediate angular deviation value and the engineering parameter information comprises:
acquiring a maximum angle deviation value included in the engineering parameter information;
judging whether the intermediate angle deviation value is greater than or equal to zero or not;
if so, taking the minimum value of the maximum angle deviation value and the middle angle deviation value as an angle deviation value;
and if not, taking the maximum value of the maximum angle deviation value and the middle angle deviation value as an angle deviation value.
6. The method of claim 3, wherein determining a speed deviation value based on the intermediate speed deviation value and the engineering parameter information comprises:
acquiring a maximum speed deviation value included in the engineering parameter information;
and taking the minimum value of the maximum speed deviation value and the middle speed deviation value as a speed deviation value.
7. The method of claim 1, wherein determining the current state vector of the target under test based on the current discrepancy vector and the last state vector estimate comprises:
determining a current measurement matrix according to the last state vector estimation value;
determining a current gain coefficient according to the current measurement matrix and the acquired measurement noise matrix;
and determining the current state vector of the target to be measured according to the current gain coefficient, the current deviation vector and the last state vector estimation value.
8. An object tracking device, comprising:
the acquisition module is used for acquiring current measurement data of a target to be measured acquired by a radar and a last state vector estimation value of the target to be measured at a last execution moment;
the first determining module is used for determining the current deviation vector according to the current measurement data, the last state vector estimation value and set engineering parameter information;
the second determining module is used for determining the current state vector of the target to be measured according to the current deviation vector and the last state vector estimation value;
and the position determining module is used for determining the current position of the target to be detected according to the current state vector.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the object tracking method of any one of claims 1-7.
10. A computer-readable storage medium having stored thereon computer instructions for causing a processor, when executed, to implement the object tracking method of any one of claims 1-7.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211378742.9A CN115755022A (en) | 2022-11-04 | 2022-11-04 | Target tracking method, device, equipment and medium |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211378742.9A CN115755022A (en) | 2022-11-04 | 2022-11-04 | Target tracking method, device, equipment and medium |
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| CN115755022A true CN115755022A (en) | 2023-03-07 |
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| CN202211378742.9A Pending CN115755022A (en) | 2022-11-04 | 2022-11-04 | Target tracking method, device, equipment and medium |
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