CN115618166B - Time resource scheduling method and device based on multi-task radar - Google Patents
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Abstract
The embodiment of the invention provides a time resource scheduling method and device based on a multi-task radar, which are applied to the technical field of radar. The method comprises the following steps: determining total time resources for the radar to complete a search task in a target search mode of a low-frequency single beam; multiplying the time of the identification task allocated to the target farthest from the radar by the total number of the targets identified in the time resource allocation period to obtain the total time resource for the radar to complete the identification task; determining the total time resource of the radar for completing the tracking task according to the total time resource of the radar for completing the searching task, the total time resource for completing the identification task and the total time resource corresponding to the time resource allocation period; according to the total time resource of the radar completed tracking task, and based on a preset resource scheduling model, adopting an optimization algorithm to solve and obtain revisit time of the radar; and controlling the radar to transmit radar signals to different wave positions according to the revisit time.
Description
Technical Field
The present invention relates to the field of radar technologies, and in particular, to a time resource scheduling method and apparatus based on a multi-task radar.
Background
The ballistic missile has the advantages of long range, high power, strong maneuverability and high precision, and is incomparable with other weapons. Ballistic missiles and ballistic missile defense are current research hotspots.
The ballistic missile defense system mainly relates to key technologies such as detection, tracking, identification and interception, and can be generally divided into three stages of early warning, tracking and interception. As a core detector of a ballistic missile defense system, a radar plays an important role in detection, tracking and guidance of ballistic missile defense. Therefore, the method combines a ballistic target motion model and a nonlinear filtering algorithm to research the tracking of the ballistic target and the resource allocation technology of the radar, and has important significance for a ballistic missile defense system.
For radar, the task of searching, identifying and tracking targets needs to be completed in a limited time resource, but the performance evaluation method of each task is different. In the case of multiple tasks where the radar needs to complete searching, identifying and tracking, if only completion of the tracking task and scheduling of resources are considered, performance of the searching task and the identifying task may be affected.
Therefore, for the multi-task radar, a more reasonable and fine resource scheduling scheme is needed, an effective resource allocation model is established and solved, and the improvement of radar performance is very critical.
Disclosure of Invention
The invention provides a time resource scheduling method and device based on a multi-task radar. The technical proposal is as follows:
in a first aspect, an embodiment of the present invention provides a time resource scheduling method based on a multi-task radar, including:
determining total time resources for the radar to complete a search task in a target search mode of a low-frequency single beam;
multiplying the time of the identification task allocated to the target farthest from the radar by the total number of the targets identified in the time resource allocation period to obtain the total time resource for the radar to complete the identification task;
determining the total time resource of the radar for completing the tracking task according to the total time resource of the radar for completing the searching task, the total time resource for completing the identification task and the total time resource corresponding to the time resource allocation period;
according to the total time resource of the radar completed tracking task, and based on a preset resource scheduling model, adopting an optimization algorithm to solve and obtain revisit time of the radar;
and controlling the radar to transmit radar signals to different wave positions according to the revisit time.
Optionally, in the target search mode of the low-frequency band single beam, determining a total time resource for the radar to complete the search task includes:
Using the formulaObtaining the number N of wave bits covering the whole searching area S, wherein θk For searching the opening angle theta of the sector area at the current moment s Is the beam opening angle, and theta s ＜＜θ k ；
Using the formulaObtaining total time resource of the radar for completing searching task under the target searching mode of low-frequency band single beam> wherein ts ＝max[t 1 ，t 2 ，…t n ]t n The search time of a single wave bit is that n is the current wave bit and n is a positive integer.
Optionally, multiplying the time of the identification task allocated to the target farthest from the radar by the total number of targets identified in the time resource allocation period to obtain a total time resource for the radar to complete the identification task, including:
determining the time resource of the identification task allocated to the target farthest from the radar in the current scene
Using the formulaObtaining the total time resource of the radar for completing the identification task +.> wherein Nr The total number of targets identified in the time resource allocation period is determined.
Optionally, in determining the current scenario, the time resource of the identification task allocated to the target furthest from the radarPreviously, the method further comprises:
for each target, determining whether the target is a key target or not through the narrow-band characteristics of the target;
if the target is not the key target, determining the target as a general target;
If the target is a key target, further mobilizing a broadband one-dimensional image of the target to determine whether the target is a suspected target;
if the target is not a suspected target, determining that the target is an important target;
if the target is a suspected target, determining whether the target is a threat target or not through micro-motion detection;
if the target is not a threat target, determining that the target is a suspected target;
if the target is a threat target, determining that the target is a threat target;
wherein the threat target is the target furthest from the radar.
Optionally, the method further comprises:
after determining the target types of the targets, determining threat degree scores of the targets according to different target types; wherein the object types include the general object, the key object, the suspected object, and the threat object.
Optionally, the method further comprises:
and judging whether each target has interference.
Optionally, determining the total time resource for the radar to complete the tracking task according to the total time resource for the radar to complete the searching task, the total time resource for the radar to complete the identifying task, and the total time resource corresponding to the time resource allocation period includes:
using the formulaObtaining the total time resource of the radar for completing the tracking task +. >
wherein The total time resource corresponding to the kth time resource allocation period is allocated, k is a positive number, and +.>Total time resource for the radar to complete a search task, < >>And (5) completing the total time resource of the identification task for the radar.
Optionally, the preset resource scheduling model is:
wherein the radar works in an X wave band and an S wave band, w q，k Is threat degree weight of target q in kth tracking, T k Time resource allocation week for kth traceIn the period of time, the time period,dwell time of irradiation once of S-band wave position i for kth tracking, +.>For the dwell time of one irradiation of the X-band wave position i in kth tracking, +.>For revisiting time of S-band wave position i in kth tracking,/for the k-th tracking>For revisiting time of X-band wave position i in kth tracking,/for the k-th tracking>Is the minimum value of revisit time of S band, < ->Is the minimum value of revisit time of X wave band, < >>For maximum value of revisit time of S-band, < ->Maximum value of revisit time for X-band, < ->Time resource for radar for target tracking recognition for kth tracking, < >>η k Radar tracking time proportion for kth tracking, < >>N L In the wave position LTarget number, B of L For the L th wave position +.>Λ is a matrix of usages, F q And (t) is the sum of diagonal elements of the Kramer boundary matrix and is an evolution value for reflecting the error magnitude of target tracking, and B (t) is an error lower boundary factor.
Optionally, the B (t) includes an error lower bound factor in the absence of interference and an error lower bound factor in the presence of interference; wherein,
the error lower bound factor B (t) in the absence of interference is:
the error lower bound factor B (t) in the presence of interference is:
wherein ,information matrix attenuation factor, Q, representing target in case of receiving mth measurement value by utilizing band i tracking at current moment q，k For and track time interval T q，k Correlated process noise, J P (x q，k )＝[Q q，k +F q，k J -1 (x q，k-1 )(F q，k ) T ] -1 ，J -1 (x q，k-1 ) Clamerlo world, Y, representing the last time instant q，k For the remainder of the target covariance matrix, P q，k Average power allocated to target q when target q is allocated for kth time, τ q，k The residence time allocated to target q for the kth allocation, +.>Indicated at kthAnd tracking an Jacobian matrix of the mth target state data to be fused in the moment, wherein m, i and k are positive numbers.
In a second aspect, an embodiment of the present invention provides a time resource scheduling apparatus based on a multi-task radar, including: the system comprises a memory, a processor and a computer program stored on the memory and running on the processor, wherein the processor realizes the time resource scheduling method based on the multi-task radar as provided in the first aspect when executing the computer program.
The technical scheme of the invention has the beneficial effects that:
the time resource scheduling method and the time resource scheduling device based on the multi-task radar, provided by the embodiment of the invention, complete the time scheduling of the radar multi-task under a multi-target scene and the optimal allocation of the time resource under the tracking task. Meanwhile, under the background of multi-task time scheduling, the time resource of the radar can be optimally allocated by optimizing revisit time, so that the target tracking precision is improved, the threat score of the target is reduced, and a foundation is laid for subsequent further research.
Drawings
FIG. 1 is a diagram of radar resource allocation provided in an embodiment of the present invention;
fig. 2 is a flowchart of a time resource scheduling method based on a multi-task radar according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an optimization problem solving method according to an embodiment of the present invention;
FIG. 4 is a flow chart of radar single-task periodic scheduling provided by an embodiment of the present invention;
FIG. 5 is a target scenario and task allocation diagram provided by an embodiment of the present invention;
FIG. 6 is a graph of average target scores for average allocation and optimized allocation provided by an embodiment of the present invention;
FIG. 7 is a graph of average target score improvement ratio provided by an embodiment of the present invention;
FIG. 8 is a diagram of a target wave position change provided by an embodiment of the present invention;
fig. 9 is a schematic structural diagram of a time resource scheduling device based on a multi-task radar according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages to be solved more apparent, the following detailed description will be given with reference to the accompanying drawings and specific embodiments. In the following description, specific details such as specific configurations and components are provided merely to facilitate a thorough understanding of embodiments of the invention. It will therefore be apparent to those skilled in the art that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
In various embodiments of the present invention, it should be understood that the sequence numbers of the following processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
Aiming at the research of radar resource scheduling and unfolding, the embodiment of the invention designs an integral time resource allocation scheme aiming at a multi-task radar to finish the searching, identifying and tracking tasks of the radar, and provides corresponding model modeling and solution for key technologies of a multi-band radar beam level integrated scheduling optimization algorithm. The specific content comprises scheduling modeling from single task to multi-task, establishing a related tracking resource allocation model by taking revisit time as an optimization variable, and providing a performance evaluation method under non-sequential tracking and interference.
In particular, embodiments of the present invention relate generally to improvements in three aspects:
1. performance evaluation
For optimization of revisit time, an assessment is made of state estimates after a period of time. In view of simplifying the model and improving the evaluation efficiency, a performance evaluation method of non-sequential tracking is used in performance evaluation, meanwhile, in view of interference existing in the current target environment, the performance evaluation method of interference is adopted in tracking, so that tracking evaluation is more accurate.
2. Resource on-demand scheduling
The radar resource allocation diagram is shown in fig. 1, and the resource scheduling and allocation is a dynamic process in a plurality of task periods, and the resource is influenced by search time and identification time for the optimized tracking time. In a specific resource scheduling assignment model,indicating the total time resource which can be allocated in the kth time resource allocation period, +.>Representing time resources for target search, +.>Representing time resources for object recognition, +.>Representing the time resources for target tracking.
3. Intelligent optimization solution
For the non-convex and constrained nonlinear optimization problem presented by the embodiments of the present invention, a suitable optimization algorithm is required to solve the optimization problem.
Specifically, referring to fig. 2, the embodiment of the invention provides a time resource scheduling method based on a multi-task radar, and particularly provides a resource scheduling allocation model of the radar under the conditions of searching, identifying and tracking the multi-task. The method comprises the following steps:
step 201, determining total time resources for the radar to complete the search task in the target search mode of the low-frequency single beam.
Firstly, the embodiment of the invention utilizes the low frequency band to complete the search task on the time resource allocation of the search task. Assume that the search sector area at the current time is S k Its opening angle is theta k Beam angle θ s And θ is as follows s ＜＜θ k The entire search area requires a search of multiple bins to cover the entire airspace.
Thus, the formula can be used in particularObtaining the number N of wave bits covering the whole searching area S 。
In the same wave position, the search time mainly depends on the time of receiving the echo of the farthest target, and the search time t in one wave position can be obtained n The method comprises the following steps: wherein Rn Is the distance of the furthest target in the wave position of the current wave beam, and n is the current wave position. Because the conditions of the targets in each wave position are different, the search time t of a single wave position is taken from the consideration of simplifying the search time model s ＝max[t 1 ，t 2 ，…t n ]t n The search time of a single wave bit is that n is the current wave bit and n is a positive integer. Then in the target search mode of the low-frequency band single beam, the radar completes the total time resource of the search task at the current moment
Step 202, multiplying the time of the identification task allocated to the target farthest from the radar by the total number of targets identified in the time resource allocation period to obtain the total time resource for the radar to complete the identification task.
Specifically, the embodiment of the invention determines the time resource of the identification task allocated to the target farthest from the radar in the current scene And further utilize the formula +.>Obtaining the total time resource of the radar for completing the identification task +.> wherein Nr The total number of targets identified in the time resource allocation period is determined.
In the actual application process of the embodiment of the invention, targets with various different target types are included in the current scene, and the target types can include general targets, key targets, suspected targets and threat targets. The embodiment of the invention can sequentially classify all targets in the searched scene, specifically for example:
for each target, determining whether the target is a key target or not through the narrow-band characteristics of the target;
if the target is not the key target, determining the target as a general target;
if the target is a key target, further mobilizing a broadband one-dimensional image of the target to determine whether the target is a suspected target;
if the target is not a suspected target, determining that the target is an important target;
if the target is a suspected target, determining whether the target is a threat target or not through micro-motion detection;
if the target is not a threat target, determining that the target is a suspected target;
if the target is a threat target, determining that the target is a threat target;
wherein the threat target in the embodiment of the invention is the target farthest from the radar.
After tracking a target for T seconds, the embodiment of the invention firstly determines whether the target is an important target through the narrow-band characteristics of the target, then the important target can mobilize the broadband one-dimensional image of the target to determine whether the target is a suspected target, and finally determines whether the suspected target is a threat target through micro-motion detection. It is further preferred that after determining the target type of each target, the threat level score of each target may also be determined according to different target types. For example, the threat level score corresponding to a general target is 0.5, the threat level score corresponding to a key target is 5, the threat level score corresponding to a suspected target is 10, and the threat level score corresponding to a threat target is 25. And in the whole identification process, whether each target has interference can be judged at the same time.
Assume that the recognition time resources required for the above-mentioned different types of targets are respectively T N 、T B 、T F. wherein TN To mobilize the time consumption of narrowband identification, T B To mobilize the time resource consumption of the broadband one-dimensional image, T F Time resource consumption for fine motion detection is mobilized. The total time resources required for identification are marked as T R General target and key target T R ＝T N Suspected target T R ＝T N +T B Threat target T R ＝T N +T B +T F (T F ＞T B ). It can be seen that identifying a target consumes T as the longest time resource and T as the shortest time resource R and TN . When multiple targets are identified, the time resources consumed by the threat targets furthest from the radar are the greatest, noted asThe time resource consumed by the general target closest to the radar is minimal, noted +.>
In consideration of simplifying the model and simultaneously ensuring that each target in a multi-target scene can be accurately identified, the target furthest from the radar in the scene is set as a threat target, and the threat target corresponds to the targetAs the time resources allocated for each target in the identified task.
Thus, the total consumption of time resources for identification in the current time resource allocation periodN r Is the number of targets identifiable for the current time resource allocation period.
Step 203, determining the total time resource of the radar for completing the tracking task according to the total time resource of the radar for completing the searching task, the total time resource of the identification task and the total time resource corresponding to the time resource allocation period.
In the embodiment of the invention, after target searching and identifying, the method can be used for dominant tracking time resources whereinThe total time resource corresponding to the kth time resource allocation period is allocated, k is a positive number,total time resource for the radar to complete a search task, < >>And (5) completing the total time resource of the identification task for the radar.
And 204, according to the total time resource of the radar completed tracking task, and based on a preset resource scheduling model, solving by adopting an optimization algorithm to obtain the revisit time of the radar.
The resource scheduling model preset in the embodiment of the invention specifically comprises the following steps:
wherein the radar works in an X wave band and an S wave band, w q，k Is threat degree weight of target q in kth tracking, T k A period is allocated for the time resource at the kth trace,dwell time of irradiation once of S-band wave position i for kth tracking, +.>For the dwell time of one irradiation of the X-band wave position i in kth tracking, +.>For revisiting time of S-band wave position i in kth tracking,/for the k-th tracking>For revisiting time of X-band wave position i in kth tracking,/for the k-th tracking>Is the minimum value of revisit time of S band, < ->Is the minimum value of revisit time of X wave band, < >>For maximum value of revisit time of S-band, < - >Maximum value of revisit time for X-band, < ->Time resource for radar for target tracking recognition for kth tracking, < >>η k Radar tracking time proportion for kth tracking, < >>N L B is the number of targets in the wave position L L For the L th wave position +.>Λ is a matrix of usages, F q And (t) is the sum of diagonal elements of the Kramer boundary matrix and is an evolution value for reflecting the error magnitude of target tracking, and B (t) is an error lower boundary factor.
And further, B (t) in the embodiment of the present invention further includes: the error floor factor in the absence of interference and the error floor factor in the presence of interference. Wherein:
the error lower bound factor B (t) in the absence of interference is:
the error lower bound factor B (t) in the presence of interference is:
wherein ,information matrix attenuation factor, Q, representing target in case of receiving mth measurement value by utilizing band i tracking at current moment q，k For and track time interval T q，k Correlated process noise, J P (x q，k )＝[Q q，k +F q，k J -1 (x q，k-1 )(F q，k ) T ] -1 ，，J -1 (x q，k-1 ) Clamerlo world, Y, representing the last time instant q,k For the remainder of the target covariance matrix, P q,k Average power allocated to target q when target q is allocated for kth time, τ q,k The residence time allocated to target q for the kth allocation, +. >Jacobian matrix representing the mth target state data to be fused in the kth tracking moment, m, i and k are positive numbers.
The following detailed description is provided for the resource scheduling model, the error lower bound factor B (t) under the condition of no interference, the error lower bound factor B (t) under the condition of interference and the intelligent optimization solution related to the embodiment of the present invention.
First, the applicant introduces an error lower bound factor B (t) in the absence of interference and an error lower bound factor B (t) in the presence of interference.
It is known that Q targets exist in a scene and are in a two-dimensional motion state, the motion state accords with a discretized first-order correlation time Singer model, and a discrete state equation of the discretized Singer model is as follows: x is x q，k+1 ＝F q x q，k +w q，k wherein Corresponding to the position, speed and acceleration of the target q at the moment k.
State transition matrix
Noise w q，k Has the following covariance matrix:
q 12 ＝q 21 ＝(e -2αT +1-2e -αT +2αTe -αT -2αT+α 2 T 2 )/(2α 4 )
q 13 ＝q 31 ＝(1-e -2αT -2αTe -αT )/(2α 3 )
q 22 ＝(4e -αT -3-e -2αT +2αT)/(2α 3 )
q 23 ＝q 32 ＝(e -2αT +1-2e -αT )/(2α 2 )
q 33 ＝(1-e -2αT )/(2α)
where T is the tracking time interval, α is the inverse of the maneuver time constant, and the variance of the acceleration is
The above process is that the motion state of the target in one-dimensional state is expanded to two-dimensional state wherein ,I2 Is an identity matrix. The covariance of the corresponding noise is: / >
The target state vector is expanded toThe corresponding measurement model is:
z q，k ＝h(x q，k )+v q，k
where (x, y) is the position of the radar in the coordinate system, (x) q，k ，y q，k ) Location information of targetAnd (5) extinguishing. v q，k Is the mean value is 0 and the covariance is sigma q，k White gaussian noise of (c):
covariance matrix Σ q，k Can be simplified into:
Y q，k for the remainder of the target covariance matrix, P q，k Average power allocated to target q when target q is allocated for kth time, τ q，k For the residence time allocated to target q at the kth allocation, R q，k Representing the radial distance of the target q from the radar at the kth tracking,c is the speed of light, < >> Representing the reflectivity of the target q at the kth dispense, beta q，k Effective bandwidth of signal for kth allocation, beta q，NN For receiving the beamwidth.
In order to simplify the model, non-sequential tracking is adopted, and the motion states of a plurality of targets are assumed to be unchanged from the measurement model, Z q，k Representing a vector consisting of M metrology information:
processing a fusion of a plurality of radar data using maximum likelihood function (ML) estimation:
solving the state estimation by using least square iteration:
h q，k () Representing a nonlinear measurement function vector, Σ q，k Is Z q，k Corresponding noise covariance matrix, H q，k，j Jacobian matrices representing how much transition state information is fused are expressed as follows:
jacobian matrix representing the mth object state data to be fused in the kth tracking moment.
The clemerol bound fused with a plurality of state data is:
through calculation and reduction and from the consideration of real-time iteration, it is possible to obtain:
simultaneous a priori information matrix:
J P (x q，k )＝[Q q，k +F q，k J -1 (x q，k-1 )(F q，k ) T ] -1
wherein ,J-1 (x q，k-1 ) Clamerro world, Q representing the last time instant q，k Is the tracking time interval T q，k Correlated process noise.
The final fused error lower bound factor is:
from the analysis and the deduction, the mixed measurement can reduce the operation amount, improve the timeliness of the state estimation, and has important significance for optimizing the revisit time.
For the multiband radar, under the condition of no interference, the measurement information of one target can come from different wavebands, in the resource allocation period of the whole target, the radar receives the measurement information of M targets in total, the data information matrix of the target corresponding to each measurement information cannot be attenuated, and the target can be tracked normally. In the presence of interference in a certain band, the data information matrix of the target will be lost.
Here, assuming that the radar operates in two bands, namely 1 band and 2 band, the attenuation factors of the target data information matrix are defined as follows, taking into consideration the influence of the power of interference on the information matrix attenuation of the target:
IRF1＝1/(r 1 +1)
IRF2＝1/(r 2 +1)
wherein r1 ，r 2 The interference ratio is expressed as follows:
r 1 ＝P/P 1
r 2 ＝P/P 2
p is interference power, P 1 and P2 Is the reference interference power, which reflects the magnitude of the affected degree in the state of interference of a certain band, the smaller the value thereof, the larger the influence of the target in the band, that is, the larger the interference ratio, the more the information is attenuated.
Under the condition that the target is interfered by the wave band, the error lower bound under specific fused state estimation can be obtained through the introduction of an interference attenuation factor:
in the above-mentioned method, the step of,and the information matrix attenuation factor of the target is represented under the condition that the mth measured value is tracked and received by utilizing the wave band i at the current moment. It can be seen that the stronger the disturbance, the smaller the attenuation factor, and the larger the lower error bound.
Next, the applicant further introduces a resource scheduling model in the embodiment of the present invention.
On the distribution of tracking time resources, after target searching and identification, the tracking time resources can be used for dominance
At this time, a variable eta is introduced k ，
Recording device
By using the F q (t) as a criterion function of the accuracy of the measurement target, where Λ is a matrix of the generalization, F q And (t) is the sum of the diagonal elements of the Kramer boundary matrix, which is squared to reflect the magnitude of the error in target tracking.
According to the embodiment of the invention, for a scene of a plurality of targets, the radar needs to be manually divided into a plurality of wave positions, and each wave position is scanned by means of a single wave beam, namely, one wave beam simultaneously tracks a plurality of targets, and targets in the same wave position use the same time resource. In the embodiment of the invention, the revisit time is taken as an optimization variable, the radar works in an X-band and an S-band, and the obtained resource scheduling model is as follows:
it should be noted that, the above-mentioned resource allocation model reflects the relationship between optimization of revisit time under the interference-free condition and improvement of tracking effect of the target, and if the target has interference, performance evaluation under the interference condition is used in tracking evaluation of the target. The resource allocation model used in the presence and absence of interference in a particular embodiment of the present invention is the same, except that it depends on whether the target is interfered, i.e., in the aboveIs calculated in a different manner.
Finally, the intelligent optimization solution in the embodiment of the invention.
In embodiments of the present invention, the resource allocation problem generally requires that optimal task performance be sought under resource or logic constraints, generally represented as a constrained optimization problem, and some methods that may be used to solve the optimization problem are shown in FIG. 3.
According to the whole scheme design, intelligent algorithms such as a genetic algorithm, a simulated annealing algorithm and the like can be used, and after nonlinear constraint of constraint problems is changed into linear constraint, optimization algorithms such as a gradient projection method, a near-end ADMM algorithm and the like can be adopted.
Regarding the resource allocation model provided by the embodiment of the invention, the objective function and the constraint are nonlinear and non-convex, if some intelligent solving algorithms are used, the time consumption is huge, and the problem is simplified by converting the variable substitution into linear constraint according to the specificity of the constraint function, the method for solving the problem is more diversified, a method with higher solving efficiency is selected, and the real-time scheduling of the corresponding time resource is improved.
And step 205, controlling the radar to transmit radar signals to different wave positions according to the revisit time.
The time resource scheduling method based on the multi-task radar provided by the embodiment of the invention completes the time scheduling of the radar multi-task in a multi-target scene and the optimal allocation of the time resource in the tracking task. Meanwhile, under the background of multi-task time scheduling, the time resource of the radar can be optimally allocated by optimizing revisit time, so that the target tracking precision is improved, the threat score of the target is reduced, and a foundation is laid for subsequent further research.
The applicant further verifies and describes the realization effect of the invention through simulation experiments.
Simulation conditions
The simulation running system of the embodiment of the invention is, for example, an Inter (R) Core (TM) i5-4590 CPU@3.30GHZ,64 bit Windows 10 operating system, and the simulation software adopts MATLAB (R2016 b).
(II) simulation content and result analysis
In the simulation scene, after one ballistic target enters a warning airspace of a radar, the ballistic target is subjected to monomer splitting to gradually form 100 targets such as a warhead, a decoy bomb, a false target, rocket debris and the like, wherein the warhead, the false target and the like can continue to move, and the protection system of the ballistic target in the my is continuously pressurized, in particular: one target (namely a ballistic target) exists at the 1 st, the target splits for the first time at the 5 th, and two targets exist in the guard space of the radar. The missiles at 13s and 25s are split again, and the target number is gradually changed from 2 to 100 targets which are preset. Wherein table 1 is initial state information of the first 10 targets. The warning time of the my radar is 100S, the single fusion period is 4S, and the total number of the radar warning time is 25 task allocation periods, and an S-band and X-band double-band working mode is adopted. Table 2 shows radar band information. The interference setting during the alert process is as follows: when the target is interfered by one wave band, the interference ratio of the two wave bands is set to be 3 and 0.6, and when the target is interfered by the two wave bands, the interference ratio is 3. Table 3 sets for specific interference information.
TABLE 1
| Target object | Location (km) | Speed (m/s) |
| 1 | (1200,1600) | (-3000,3000) |
| 2 | (1190,1590) | (-2850,3100) |
| 3 | (1210,1610) | (-3150,2900) |
| 4 | (1170,1590) | (-2900,3150) |
| 5 | (1160,1600) | (-2850,2900) |
| 6 | (1180,1590) | (-2700,3000) |
| 7 | (1170,1610) | (-3100,3100) |
| 8 | (1160,1590) | (-2880,2900) |
| 9 | (1180,1610) | (-2950,3150) |
| 10 | (1170,1590) | (-2900,2900) |
TABLE 2
| Wave band | bandwidth/MHz | Beam width/degree |
| X-band | 10 | 1 |
| S-band | 5 | 1 |
TABLE 3 Table 3
Further as shown in fig. 4, fig. 4 is a flow chart of radar single-task cycle scheduling provided by an embodiment of the present invention. In the above-mentioned 100-objective scenario, the false alarm time needs to be divided into a plurality of task periods, each task period is required to complete searching, identifying and tracking, and threat level evaluation, four tasks are performed sequentially, and considering that the time is not required to be allocated to the identification in the previous task periods, it is preferable to add the judgment of whether to schedule the identification in the flow.
Referring to fig. 5, fig. 5 is a target scenario and task allocation diagram provided by an embodiment of the present invention. The searching task, the tracking task penetrates through the whole warning time, in simulation, the searching time distribution of the targets is determined according to the existence condition of the targets in a well-defined fusion period, the wave positions are divided by the targets, and the detection time of the farthest targets is selected to be determined as a scheme of the detection time of each target. The identification of the target requires at least two integration periods (8 s) of information accumulation, the broadband one-dimensional image requires 4 echo times, and the micro-motion detection time is consumed to be fixed 0.06s. In one fusion task period, 10 targets can be identified simultaneously, the first 10 targets in the first batch can be identified in 21s, then the identification of the rest targets is started in 33s, and 10 targets are selected randomly in each fusion period until all targets are identified. After recognition, a score of threat level is given to the recognition target, the threat target score is set to 25, the suspected target is set to 10, the key target is set to 5, the general target is set to 0.5, and once the target is recognized, the threat level score of the target is determined. Table 4 below is threat attribute settings for each target. The tracking time allocation of the target is an optimization problem, the allocable tracking time resource is dynamically changed, the minimum revisit time requirement of the double wave bands is more than or equal to the resident time resource, the resident time resource is set to be 0.01s, the maximum revisit time is set to be 0.8s, and the measurement data of more than two times are ensured to be acquired in the tracking process.
TABLE 4 Table 4
Referring to fig. 6, fig. 6 is a graph of average target scores for average allocation and optimization allocation provided by an embodiment of the present invention. From the figure, it can be seen that optimizing revisit time can well reduce threat score of the target of the current fusion period.
Referring to fig. 7, fig. 7 is a graph showing the average target score improvement ratio provided by the embodiment of the present invention. At the initial moment, the optimization result and the lifting ratio are not obvious, because the initial moment has less targets and more concentrated wave position division, the targets with large threat degree and the targets with small threat degree can use the same revisit time resource, the targets with small threat degree can also obtain a large amount of resources, the resource waste is caused, the optimization result is not obvious, in addition, the wave position is less, the resources which are evenly distributed to each wave position are more, the revisit time is close to the constraint lower bound, the change space of the optimization variable is reduced, and the optimization space of the objective function is reduced; optimizing allocation can reduce the target threat score by approximately 10% -15% at most times.
Referring to fig. 8, fig. 8 is a target wave position change chart provided by an embodiment of the present invention. According to the motion state and process of the target, the target is gradually dispersed, and the wave position division of the target is also gradually increased.
At the 16 th fusion time, the embodiment of the invention mainly concentrates the 4,5,6 wave bits of the wave bit division area in the area with high target threat degree, and the optimized scheme distributes more resources to the 4,5,6 wave bits compared with the average distribution scheme, and the wave bits on two sides of the area are distributed with less resources, so that the following conclusion can be reached: compared with an average allocation scheme, the optimized allocation reduces the resources of the wave positions with small threat, allocates the wave positions with higher threat degree to some wave positions, and reduces the target threat score by using the mechanism.
The embodiment of the invention is at the 16 th fusion time, and the threat score proportion distribution of the wave position at the time is the same as the total threat degree variation trend: the threat score of the threat is high, the optimization allocation leads the wave position threat score proportion with high threat score to be reduced, the proportion with low threat degree to be increased, and the total threat score to be reduced.
In summary, the above simulation experiment verifies the correctness, effectiveness and reliability of the embodiment of the present invention.
Based on the time resource scheduling method based on the multi-task radar provided by the foregoing text embodiment of the present invention, the embodiment of the present invention further provides a time resource scheduling device based on the multi-task radar, as shown in fig. 9, including:
The first determining module 100 is configured to determine, in a target search mode of a low-frequency band single beam, a total time resource for the radar to complete a search task;
a second determining module 200, configured to multiply the time of the identification task allocated to the target farthest from the radar by the total number of targets identified in the time resource allocation period, to obtain a total time resource for the radar to complete the identification task;
a third determining module 300, configured to determine a total time resource for the radar to complete the tracking task according to the total time resource for the radar to complete the searching task, the total time resource for the radar to complete the identifying task, and the total time resource corresponding to the time resource allocation period;
the solving module 400 is configured to obtain revisit time of the radar by adopting an optimization algorithm based on a preset resource scheduling model according to total time resources of the radar for completing tracking tasks;
and the control module 500 is used for controlling the radar to transmit radar signals to different wave positions according to the revisit time.
Wherein the first determining module 100 may include:
a first determining sub-module for using the formulaObtaining the number N of wave bits covering the whole searching area S, wherein θk For searching the opening angle theta of the sector area at the current moment s Is the beam opening angle, and theta s ＜＜θ k ；
A second determining sub-module for using the formulaObtaining total time resource of the radar for completing searching task under the target searching mode of low-frequency band single beam> wherein ts ＝max[t 1 ，t 2 ，…t n ]，t n The search time of a single wave bit is that n is the current wave bit and n is a positive integer.
Wherein the second determining module 200 may include:
a third determination submodule, configured to determine a time resource of an identification task allocated to a target farthest from the radar in the current scenario
A fourth determination sub-module for using the formulaObtaining the total time resource of the radar for completing the identification task +.> wherein Nr The total number of targets identified in the time resource allocation period is determined.
And, optionally, the second determining module 200 may be further configured to:
in determining the current scenario, the time resource of the identification task allocated to the target furthest from the radarPreviously, for each target, determining whether the target is a key target through the narrow-band characteristics of the target;
if the target is not the key target, determining the target as a general target;
if the target is a key target, further mobilizing a broadband one-dimensional image of the target to determine whether the target is a suspected target;
If the target is not a suspected target, determining that the target is an important target;
if the target is a suspected target, determining whether the target is a threat target or not through micro-motion detection;
if the target is not a threat target, determining that the target is a suspected target;
if the target is a threat target, determining that the target is a threat target;
wherein the threat target is the target furthest from the radar.
And, further optionally, the second determining module 200 may be further configured to: after determining the target types of the targets, determining threat degree scores of the targets according to different target types; wherein the object types include the general object, the key object, the suspected object, and the threat object.
Optionally, the time resource scheduling device based on the multi-task radar provided by the embodiment of the invention further includes: and the judging module is used for judging whether each target has interference.
Wherein, the third determining module 300 may be specifically configured to:
using the formulaObtaining the total time resource for the radar to complete the tracking task
wherein The total time resource corresponding to the kth time resource allocation period is allocated, k is a positive number, and +.>Total time resource for the radar to complete a search task, < > >And (5) completing the total time resource of the identification task for the radar.
In the embodiment of the present invention, the preset resource scheduling model may be:
wherein the radar operates in an X-band and an S-band,is threat degree weight of target q in kth tracking, T k Time resource allocation period for kth trace,/->Dwell time of irradiation once of S-band wave position i for kth tracking, +.>For the dwell time of one irradiation of the X-band wave position i in kth tracking, +.>For revisiting time of S-band wave position i in kth tracking,/for the k-th tracking>For revisiting time of X-band wave position i in kth tracking,/for the k-th tracking>Is the minimum value of revisit time of S band, < ->Is the minimum value of revisit time of X wave band, < >>For maximum value of revisit time of S-band, < ->Maximum value of revisit time for X-band, < ->Time resource for radar for target tracking recognition for kth tracking, < >>η k Radar tracking time proportion for kth tracking, < >>N L B is the number of targets in the wave position L L For the L th wave position +.>Λ is a matrix of usages, F q And (t) is the sum of diagonal elements of the Kramer boundary matrix and is an evolution value for reflecting the error magnitude of target tracking, and B (t) is an error lower boundary factor.
Further B (t) may comprise an error lower bound factor in the absence of interference and an error lower bound factor in the presence of interference; wherein,
The error lower bound factor B (t) in the absence of interference is:
the error lower bound factor B (t) in the presence of interference is:
wherein ,information matrix attenuation factor, Q, representing target in case of receiving mth measurement value by utilizing band i tracking at current moment q，k For and track time interval T q，k Correlated process noise, J P (x q，k )＝[Q q，k +F q，k J -1 (x q，k-1 )(F q，k ) T ] -1 ，J -1 (x q，k-1 ) Clamerlo world, Y, representing the last time instant q，k For the remainder of the target covariance matrix, P q，k Average power allocated to target q when target q is allocated for kth time, τ q，k The residence time allocated to target q for the kth allocation, +.>Jacobian matrix representing the mth target state data to be fused in the kth tracking moment, m, i and k are positive numbers.
It should be noted that, the time resource scheduling control device based on the multi-task radar is a device corresponding to the time resource scheduling method based on the multi-task radar in the foregoing embodiment, and all implementation means in the foregoing method embodiments are applicable to the embodiment of the time resource scheduling device based on the multi-task radar, so that the same technical effects can be achieved.
In addition, the embodiment of the invention also provides a time resource scheduling device based on the multi-task radar, which comprises the following steps: the system comprises a memory, a processor and a computer program stored on the memory and running on the processor, wherein the processor realizes the time resource scheduling method based on the multi-task radar according to the previous embodiment when executing the computer program.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the present invention.
Claims (9)
1. A time resource scheduling method based on a multi-task radar, comprising:
determining total time resources for the radar to complete a search task in a target search mode of a low-frequency single beam;
multiplying the time of the identification task allocated to the target farthest from the radar by the total number of the targets identified in the time resource allocation period to obtain the total time resource for the radar to complete the identification task;
determining the total time resource of the radar for completing the tracking task according to the total time resource of the radar for completing the searching task, the total time resource for completing the identification task and the total time resource corresponding to the time resource allocation period;
according to the total time resource of the radar completed tracking task, and based on a preset resource scheduling model, adopting an optimization algorithm to solve and obtain revisit time of the radar;
according to the revisit time, controlling the radar to transmit radar signals to different wave positions;
The preset resource scheduling model is as follows:
wherein the radar works in an X wave band and an S wave band, w q,k Is threat degree weight of target q in kth tracking, T k A period is allocated for the time resource at the kth trace,dwell time of irradiation once of S-band wave position i for kth tracking, +.>For the dwell time of one irradiation of the X-band wave position i in kth tracking, +.>For revisiting time of S band wave position i in kth tracking,for revisiting time of X-band wave position i in kth tracking,/for the k-th tracking>Is the minimum value of revisit time of S band, < ->Is the minimum value of revisit time of X wave band, < >>For maximum value of revisit time of S-band, < ->Maximum value of revisit time for X-band, < ->Time resource for radar for target tracking recognition for kth tracking, < >>η k Radar tracking time proportion for kth tracking, < >>N L B is the number of targets in the wave position L L For the L th wave position +.>Λ is a matrix of usages, F q (t) is the sum of diagonal elements of the Kelmer-Row matrix and is the squared value to reflect the magnitude of the error in target tracking, B (t) isError lower bound factor.
2. The method according to claim 1, wherein determining the total time resource for the radar to complete the search task in the target search mode of the low-band single beam comprises:
Using the formulaObtaining the number N of wave bits covering the whole searching area s, wherein θk For searching the opening angle theta of the sector area at the current moment s Is the beam opening angle, and theta s ＜＜θ k ；
Using the formulaObtaining total time resource of the radar for completing searching task under the target searching mode of low-frequency band single beam> wherein ts ＝max[t 1 ,t 2 ,…t n ]，t n The search time of a single wave bit is that n is the current wave bit and n is a positive integer.
3. The method of claim 1, wherein multiplying the time of the identified task assigned to the target furthest from the radar by the total number of targets identified in the time resource assignment period yields the total time resource for the radar to complete the identified task, comprising:
determining the time resource of the identification task allocated to the target farthest from the radar in the current scene
Using the formulaObtaining the total time resource of the radar for completing the identification task +.> wherein Nr The total number of targets identified in the time resource allocation period is determined.
4. A method according to claim 3, characterized in that in determining the current scenario, the target furthest from the radar is allocated time resources of the recognition taskPreviously, the method further comprises:
For each target, determining whether the target is a key target or not through the narrow-band characteristics of the target;
if the target is not the key target, determining the target as a general target;
if the target is a key target, further mobilizing a broadband one-dimensional image of the target to determine whether the target is a suspected target;
if the target is not a suspected target, determining that the target is an important target;
if the target is a suspected target, determining whether the target is a threat target or not through micro-motion detection;
if the target is not a threat target, determining that the target is a suspected target;
if the target is a threat target, determining that the target is a threat target;
wherein the threat target is the target furthest from the radar.
5. The method according to claim 4, wherein the method further comprises:
after determining the target types of the targets, determining threat degree scores of the targets according to different target types; wherein the object types include the general object, the key object, the suspected object, and the threat object.
6. The method according to any one of claims 3-5, further comprising:
and judging whether each target has interference.
7. The method of claim 1, wherein determining the total time resources for the radar to complete the tracking task based on the total time resources for the radar to complete the search task, the total time resources for the completion of the identification task, and the total time resources corresponding to the time resource allocation period comprises:
Using the formulaObtaining the total time resource for the radar to complete the tracking task
wherein The total time resource corresponding to the kth time resource allocation period is allocated, k is a positive number, and +.>Total time resource for the radar to complete a search task, < >>And (5) completing the total time resource of the identification task for the radar.
8. The method of claim 1, wherein B (t) comprises a lower error bound factor in the absence of interference and a lower error bound factor in the presence of interference; wherein,
the error lower bound factor B (t) in the absence of interference is:
the error lower bound factor B (t) in the presence of interference is:
wherein ,information matrix attenuation factor, Q, representing target in case of receiving mth measurement value by utilizing band i tracking at current moment q,k For and track time interval T q,k Correlated process noise, J P (x q,k )＝[Q q,k +F q,k J -1 (x q,k-1 )(F q,k ) T ] -1 ，J -1 (x q,k-1 ) Clamerlo world, Y, representing the last time instant q,k For the remainder of the target covariance matrix, P q,k Average power allocated to target q when target q is allocated for kth time, τ q,k The residence time allocated to target q for the kth allocation, +.>Jacobian matrix representing the mth target state data to be fused in the kth tracking moment, m, i and k are positive numbers.
9. A time resource scheduling apparatus based on a multi-task radar, comprising: memory, a processor and a computer program stored on the memory and running on the processor, the processor implementing the multi-tasking radar based time resource scheduling method according to any of the claims 1 to 8 when the computer program is executed.
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| CN108376105A (en) * | 2018-03-26 | 2018-08-07 | 电子科技大学 | A kind of radar fence method for allocating tasks constraining combination Double Auction based on timeliness |
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| CN108376105A (en) * | 2018-03-26 | 2018-08-07 | 电子科技大学 | A kind of radar fence method for allocating tasks constraining combination Double Auction based on timeliness |
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