CN106777679B - ISAR imaging radar resource adaptive scheduling method based on pulse interleaving - Google Patents

ISAR imaging radar resource adaptive scheduling method based on pulse interleaving Download PDF

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CN106777679B
CN106777679B CN201611152226.9A CN201611152226A CN106777679B CN 106777679 B CN106777679 B CN 106777679B CN 201611152226 A CN201611152226 A CN 201611152226A CN 106777679 B CN106777679 B CN 106777679B
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CN106777679A (en
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张群
孟迪
罗迎
陈怡君
李开明
张慧伟
李彬彬
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Air Force Engineering University of PLA
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/904—SAR modes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/904—SAR modes
    • G01S13/9064—Inverse SAR [ISAR]

Abstract

The ISAR imaging radar resource scheduling method based on pulse interleaving comprises the following steps: the first step is as follows: a small amount of pulses are sent to recognize the target characteristics; the second step is that: calculating parameters such as observation dimensions and the like by using the cognitive result; the third step: on the premise of meeting resource constraints, scheduling each radar imaging task by using a pulse interleaving technology; the fourth step: and observing and imaging the successfully scheduled tasks by using the sparse aperture. The scheduling success rate and the resource utilization rate of the system are greatly improved. After the imaging target characteristics are known, the saturated capacity of the system can be deduced through the change curve of the average interleaving degree, so that the scheduling method is more effective.

Description

ISAR imaging radar resource adaptive scheduling method based on pulse interleaving
Technical Field
The invention relates to an information processing technology and an optimized scheduling strategy, in particular to an ISAR imaging radar resource self-adaptive scheduling method based on pulse interleaving.
Background
In recent years, phased array radar technology has been developed and has been widely used. Compared with the conventional mechanical scanning radar, the phased array radar has incomparable advantages in the aspects of time and energy management due to the characteristics of microsecond-order beam agility, controllable space power, time resource allocation and the like.
The key point of whether the reasonable, flexible and efficient scheduling strategy can exert the advantages of the scheduling strategy is. Common scheduling methods can be mainly divided into two main categories: a template method and an adaptive scheduling method. The adaptive scheduling method can flexibly adjust the resource scheduling strategy according to the working environment and task requirements, and is the most effective and complex scheduling method.
The proposal of the pulse interleaving theory provides a new way for further improving the resource utilization rate of the system, and the basic idea is that the waiting period between the sending and receiving of the pulses can be used for interleaving and scheduling other tasks. And from the pulse angle, the utilization rate of radar resources is further improved.
An online pulse interleaving scheduling algorithm aiming at the phased array radar is provided by an improved phased array radar pulse interleaving algorithm (radar science and technology, 2013,4(2):185-191), so that the time utilization rate and the energy utilization rate are improved; a scheduling algorithm based on scheduling interval analysis is provided for digital array radar beam residence scheduling problem in digital array radar beam residence scheduling algorithm (information and electronic engineering, 2011,9(1):17-21) of Zhao Hong et al; and so on. However, most of the algorithms only perform resource scheduling on the searching and tracking tasks of the target, and do not take the imaging tasks into consideration. In practical situations, target imaging can provide important support information for target classification and identification, and is one of the important functions of the phased array radar. Most of the existing phased array radar resource scheduling strategies need to divide a part of continuous fixed resources to realize an imaging function, so that the resource utilization rate is low.
Under the framework of a compressive sensing theory, continuous observation imaging of a target can be converted into random sparse observation imaging, and a high-quality target ISAR image is obtained under the condition of sparse aperture, so that effective technical support is provided for bringing imaging task requirements into a phased array radar resource scheduling model.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides an ISAR imaging radar resource adaptive scheduling method based on pulse interleaving, which comprises the following steps:
the method comprises the following steps: establishing a radar imaging resident task model:
Figure GDA0002288721510000021
Figure GDA0002288721510000022
in the formula, txj，twj，trjRespectively representing a transmission period, a waiting period and a receiving period of the resident j (j ═ 1, 2); et aliAnd stiRespectively an expected scheduling starting time and an actual scheduling starting time of the ith task; t isciAccumulating time for azimuth coherence of the ith task; omegaiFor the time window of the ith task, the earliest scheduling starting time is defined as the expected scheduling starting time; the vector T represents the scheduling state of the discretized time interval; a isiNumbering the tasks of the ith task; q. q.s1,q2,q3,q4To adjust the coefficient; the first and second constraints represent time constraints to be satisfied by the task scheduling; the third to fifth constraints represent sparse aperture conditions and observation time ranges that the imaging task needs to satisfy; the sixth constraint represents an energy constraint that the task schedule needs to satisfy.
Step two: the radar imaging task scheduling method specifically comprises the following steps:
the first step is as follows: a small amount of pulses are sent to recognize the target characteristics; according to echo feedback information, calculating azimuth coherent accumulation time and observation dimension required by imaging of each target;
the specific process of the cognitive target characteristics is as follows: target distance
Figure GDA0002288721510000023
Speed of rotation
Figure GDA0002288721510000024
And course
Figure GDA0002288721510000025
Measuring by using a conventional radar method; sending a small quantity of continuous pulses to each target to obtain a coarse-resolution ISAR image; speed of rotation
Figure GDA0002288721510000026
And course
Figure GDA0002288721510000027
The measurement can be carried out using conventional radar methods; target size
Figure GDA0002288721510000028
Can be estimated from the coarse-resolution ISAR image of the target; degree of azimuth sparsity
Figure GDA0002288721510000029
The number of the distance units in each azimuth direction of the target coarse resolution ISAR image is greater than a set threshold value; observation time
Figure GDA00022887215100000210
Calculating by defining the standard azimuth resolution required by standard target imaging; relative priority PkWeighting according to parameters such as the distance, the speed and the course of the target;
the second step is that: calculating parameters such as observation dimensions and the like by using the cognitive result;
the third step: on the premise of meeting resource constraints, scheduling each radar imaging task by using a pulse interleaving technology;
the specific steps are P1: the latest scheduling starting time in the N imaging tasks is smaller than t0The sum of the earliest scheduling start time and the azimuth coherent accumulation time is more than tendAdding the task into a deletion linked list, sending the rest N-K tasks into an execution linked list from high to low according to the priority, initializing the energy state of each time slot in the scheduling interval, and setting i as 1;
p2: definition of tp_firstThe first transmit pulse directed to the ith imaging task, i.e. the desired scheduling start time, tp_endTo the last transmit pulse, then
Figure GDA0002288721510000032
P3: if at tp_firstAnd tp_endDefinite pulse-taking from head to tailIn the impact-pair interval, the M is successfully inserted according to the time and energy constraint conditions i2 transmit-receive pulse pairs, scheduling the imaging task in this manner and updating the energy state of each time slot, i ═ i +1, transition P4; otherwise, let tp_first＝tp_first+Δtp，tp_end＝tp_end+Δtp(ΔtpIs the minimum pointer slip step size); if tp_first＜eti+ωiReturning to P3, otherwise, considering that the task scheduling fails and adding the task scheduling failure into a deletion linked list, i is i +1, and returning to P2;
p4: if i is less than or equal to N-K, returning to P2, otherwise, turning to the fourth step.
The resource constraint premise comprises a time resource constraint condition and an energy resource constraint condition, and the time resource constraint condition is required to transmit or receive other resident tasks by using the time resource of the waiting period on the premise of not conflicting with the transmitting period and the receiving period of the original resident task; the pulse interleaving mode is divided into cross interleaving and internal interleaving, and the time constraint conditions required to be respectively met by the two interleaving modes are as follows:
(a)tw1≥tx2,tw2≥tr1,tx2+tw2≥tx1+tr1(2)
(b)tw1≥tx2+tw2+tr2(3)
the transient energy of the radar system at time t can be expressed as:
Figure GDA0002288721510000031
wherein, p (x) is the power parameter of the system, τ is the back-off parameter of the system, and the essence of the above formula is to perform exponential weighted summation on the power function, the energy weighting coefficient of the early-stage emission pulse is small, and the energy weighting coefficient of the near-stage emission pulse is large;
if the energy state of the system at the time t is close to the upper limit E of the transient energymaxThen the pulse cannot be transmitted continuously at this time, and a cooling time t is requiredcThe energy is restored to the normal value ElThat is to say thatAt [ t, t + tc]In the time period, the system does not transmit the pulse any more, but can normally receive the pulse; if the transient energy of the system at time t is E (t), then at t + tcAt the moment, the transient energy of the system is:
Figure GDA0002288721510000041
let E (t) become Emax，E(t+tc)＝ElThen the system cools for time tcThe expression of (a) is:
Figure GDA0002288721510000042
thereby obtaining the cooling rate v of the systemEThe expression of (a) is:
Figure GDA0002288721510000043
the decrease Δ E in the energy state of the system over the Δ t time may be expressed as:
Figure GDA0002288721510000044
in the process of pulse interleaving, the energy constraint condition of the system can be defined as that the system cannot exceed the maximum instantaneous energy threshold E at any time tmaxNamely:
E(t)≤Emax(9)
the fourth step: and observing and imaging the successfully scheduled tasks by using the sparse aperture.
The imaging accumulation time of the ith target obtained after feature recognition is assumed to be
Figure GDA0002288721510000045
Then the radar co-transmits
Figure GDA0002288721510000046
A pulse representing the discretization of the full aperture signal for the completion of the range-wise processing as sr(t,m),m1,2, N; transmitting only M (M < N) sub-pulses to the target, the sparse aperture signal may be represented as sr(t, M'), M ═ 1,2, …, M; if the estimated sparsity of the ith target is
Figure GDA0002288721510000047
The azimuth observation dimension after the ith target dimension reduction processing is as follows:
Figure GDA0002288721510000048
wherein c is a constant related to the recovery precision, a Fourier transform matrix is selected as a sparse transform matrix psi of the signal x, and an observation matrix phi is designed according to the sparse aperture distribution condition to meet the following requirements:
Figure GDA0002288721510000049
reconstructing the azimuth information by solving an optimization problem:
Figure GDA0002288721510000051
and performing azimuth imaging on each distance unit according to the method to obtain a matrix form, namely a target two-dimensional ISAR image.
The invention provides an ISAR imaging radar resource self-adaptive scheduling method based on pulse interleaving, establishes a reasonable pulse interleaving resident resource scheduling model, and designs an online pulse interleaving implementation method under the double constraints of time and energy resources. Compared with the traditional scheduling method, the method of the invention greatly improves the scheduling success rate and the resource utilization rate of the system by reasonably utilizing the resources of the pulse waiting period. After the imaging target characteristics are known, the saturated capacity of the system can be deduced through the change curve of the average interleaving degree, so that the scheduling method is more effective. By calculating the peak signal-to-noise ratio of the sparse aperture imaging result and the traditional full aperture imaging result, the method can obtain satisfactory imaging quality while obviously improving the utilization rate of radar resources.
Drawings
Fig. 1 shows a comparison of performance indexes of the method of the present invention and a conventional method, where fig. 1(a) is a comparison of scheduling success rates, fig. 1(b) is a comparison of time resource utilization rates, fig. 1(c) is a comparison of energy resource utilization rates, and fig. 1(d) is a comparison of average interleaving ratios;
FIG. 2 shows an imaging task resident pulse interlacing schematic of the present invention;
FIG. 3 illustrates an imaging task resource scheduling framework of the present invention;
FIG. 4 illustrates a flow chart of a scheduling method of the present invention;
Detailed Description
The invention is further described below with reference to the drawings and embodiments of the invention.
The specific implementation process of the invention is as follows: the first step is as follows: a small amount of pulses are sent to recognize the target characteristics; the second step is that: calculating parameters such as observation dimensions and the like by using the cognitive result; the third step: on the premise of meeting resource constraints, scheduling each radar imaging task by using a pulse interleaving technology; the fourth step: and observing and imaging the successfully scheduled tasks by using the sparse aperture.
Comprises the following steps:
the method comprises the following steps: establishing a radar imaging resident task model:
Figure GDA0002288721510000061
Figure GDA0002288721510000062
in the formula, txj，twj，trjRespectively representing a transmission period, a waiting period and a receiving period of the resident j (j ═ 1, 2); et aliAnd stiRespectively an expected scheduling starting time and an actual scheduling starting time of the ith task; t isciAccumulating time for azimuth coherence of the ith task; omegaiFor the time window of the ith task, the earliest scheduling starting time is defined as the expected scheduling starting time;the vector T represents the scheduling state of the discretized time interval; a isiNumbering the tasks of the ith task; q. q.s1,q2,q3,q4To adjust the coefficient; the first and second constraints represent time constraints to be satisfied by the task scheduling; the third to fifth constraints represent sparse aperture conditions and observation time ranges that the imaging task needs to satisfy; the sixth constraint condition represents an energy constraint condition which needs to be met by task scheduling;
step two: the radar imaging task scheduling method specifically comprises the following steps:
the first step is as follows: a small amount of pulses are sent to recognize the target characteristics; according to echo feedback information, calculating azimuth coherent accumulation time and observation dimension required by imaging of each target;
the specific process of the cognitive target characteristics is as follows: target distance
Figure GDA0002288721510000063
Speed of rotation
Figure GDA0002288721510000064
And course
Figure GDA0002288721510000065
Measuring by using a conventional radar method; sending a small quantity of continuous pulses to each target to obtain a coarse-resolution ISAR image; speed of rotation
Figure GDA0002288721510000066
And course
Figure GDA0002288721510000067
The measurement can be carried out using conventional radar methods; target size
Figure GDA0002288721510000068
Can be estimated from the coarse-resolution ISAR image of the target; degree of azimuth sparsity
Figure GDA0002288721510000069
Defined as directions of orientation of coarse resolution ISAR image of targetThe number of distance units with distance units larger than a set threshold value; observation time
Figure GDA00022887215100000610
Calculating by defining the standard azimuth resolution required by standard target imaging; relative priority PkWeighting according to parameters such as the distance, the speed and the course of the target;
the second step is that: calculating parameters such as observation dimensions and the like by using the cognitive result;
the third step: on the premise of meeting resource constraints, scheduling each radar imaging task by using a pulse interleaving technology;
the specific steps are P1: the latest scheduling starting time in the N imaging tasks is smaller than t0The sum of the earliest scheduling start time and the azimuth coherent accumulation time is more than tendAdding the task into a deletion linked list, sending the rest N-K tasks into an execution linked list from high to low according to the priority, initializing the energy state of each time slot in the scheduling interval, and setting i as 1;
p2: definition of tp_firstThe first transmit pulse directed to the ith imaging task, i.e. the desired scheduling start time, tp_endTo the last transmit pulse, then
Figure GDA0002288721510000072
P3: if at tp_firstAnd tp_endSuccessfully inserting M in the determined pulse pair interval for head and tail transmission and reception meeting the time and energy constraint conditions i2 transmit-receive pulse pairs, then the imaging task is scheduled in this manner and the time slot energy state is updated, i ═ i +1, to P4. Otherwise, let tp_first＝tp_first+Δtp，tp_end＝tp_end+Δtp(ΔtpIs the minimum pointer slip step size); if tp_first＜eti+ωiReturning to P3, otherwise, considering that the task scheduling fails and adding the task scheduling failure into a deletion linked list, i is i +1, and returning to P2;
p4: if i is less than or equal to N-K, returning to P2, otherwise, turning to the fourth step.
The resource constraint premise comprises a time resource constraint condition and an energy resource constraint condition, and the time resource constraint condition is required to transmit or receive other resident tasks by using the time resource of the waiting period on the premise of not conflicting with the transmitting period and the receiving period of the original resident task; the pulse interleaving mode is divided into cross interleaving and internal interleaving, and the time constraint conditions required to be respectively met by the two interleaving modes are as follows:
(a)tw1≥tx2,tw2≥tr1,tx2+tw2≥tx1+tr1(2)
(b)tw1≥tx2+tw2+tr2(3)
in the actual scheduling process, the number of pulse interlaces is limited by an energy constraint condition so as to avoid damage of the transmitter due to overlong continuous working time, the energy constraint of the radar system is divided into a steady-state energy constraint and a transient energy constraint, because a total energy consumption threshold set by the steady-state energy constraint is limited by the performance of the device, only the transient energy constraint is usually considered, and the transient energy of the system at the time t can be represented as:
Figure GDA0002288721510000071
wherein, p (x) is the power parameter of the system, τ is the back-off parameter of the system, and the essence of the above equation is to perform exponentially weighted summation on the power function, the energy weighting coefficient of the early-stage emission pulse is small, and the energy weighting coefficient of the near-stage emission pulse is large.
If the energy state of the system at the time t is close to the upper limit E of the transient energymaxThen the pulse cannot be transmitted continuously at this time, and a cooling time t is requiredcThe energy is restored to the normal value ElThat is, at [ t, t + t [ ]c]In the time period, the system does not transmit the pulse any more, but can normally receive the pulse; if the transient energy of the system at time t is E (t), then at t + tcAt the moment, the transient energy of the system is:
Figure GDA0002288721510000081
let E (t) become Emax，E(t+tc)＝ElThen the system cools for time tcThe expression of (a) is:
Figure GDA0002288721510000082
thereby obtaining the cooling rate v of the systemEThe expression of (a) is:
Figure GDA0002288721510000083
the decrease Δ E in the energy state of the system over the Δ t time may be expressed as:
Figure GDA0002288721510000084
in the process of pulse interleaving, the energy constraint condition of the system can be defined as that the system cannot exceed the maximum instantaneous energy threshold E at any time tmaxNamely:
E(t)≤Emax(9)
the fourth step: and observing and imaging the successfully scheduled tasks by using the sparse aperture.
The imaging accumulation time of the ith target obtained after feature recognition is assumed to be
Figure GDA0002288721510000085
Then the radar co-transmits
Figure GDA0002288721510000086
A pulse representing the discretization of the full aperture signal for the completion of the range-wise processing as sr(t, m), m ═ 1, 2.., N; transmitting only M (M < N) sub-pulses to the target, the sparse aperture signal may be represented as sr(t, M'), M ═ 1,2, …, M; if the estimated sparsity of the ith target is
Figure GDA0002288721510000087
The azimuth observation dimension after the ith target dimension reduction processing is as follows:
Figure GDA0002288721510000088
wherein c is a constant related to the recovery precision, a Fourier transform matrix is selected as a sparse transform matrix psi of the signal x, and an observation matrix phi is designed according to the sparse aperture distribution condition to meet the following requirements:
Figure GDA0002288721510000091
reconstructing the azimuth information by solving an optimization problem:
Figure GDA0002288721510000092
and performing azimuth imaging on each distance unit according to the method to obtain a matrix form, namely a target two-dimensional ISAR image.
Example (c): imaging task scheduling experiment
Simulation experiment: assuming that the radar transmits a linear frequency modulation signal, the transmission pulse width is 10 mus, the minimum pointer sliding step length is set to be 10 mus, the time window is 1ms, the simulation time is 1s, the pulse transmission power is 4KW, and the radar average power is 500W. The distance from each target to the radar is 10-30 Km.
It should be noted that, since the range size of the target may affect the arrival time of the radar echo, in order to ensure the imaging quality, the pulse receiving period needs to be widened appropriately. If the distance between the radar and the ith target is RiThe dimension of the ith target in the range direction is
Figure GDA0002288721510000093
The width of the actual received pulse for the ith target should be set to:
Figure GDA0002288721510000094
after multiple times of simulation, the time resource utilization rate of the system tends to be in a saturated state when the target number is 50. Taking 200ms as an observation window, the radar imaging resource scheduling graph based on pulse interleaving of the invention is shown in fig. 5. The absolute value of each pulse represents the imaging task number, with the transmit pulse number being positive and the receive pulse number being negative. Each pair of sending and receiving pulses and the waiting period between the sending and receiving pulses form a complete task residence, and the residence waiting period of different imaging tasks is determined by the distance from the radar to the target. And the imaging tasks with high priority are scheduled preferentially, and the imaging tasks with low priority are adjusted to meet the scheduling condition or are abandoned within the time window range until the resources are saturated. Therefore, the radar carries out staggered scheduling imaging on each target, and the time resource utilization rate of the system is greatly improved.
The scheduling method of the invention is compared with the scheduling method in the radar resource self-adaptive scheduling method based on sparse aperture ISAR imaging. The resource scheduling performance index is defined as follows:
scheduling Success Rate (SSR): the scheduling success rate is defined as the ratio of the number of imaging tasks applied for execution to the number of imaging tasks actually executed. The expression is as follows:
Figure GDA0002288721510000101
time resource utilization (TUR): the time resource utilization is defined as the ratio of the time occupied by all task resident pulses to the total scheduling time. The expression is as follows:
Figure GDA0002288721510000102
energy resource utilization (EUR): energy resource utilization is defined as the ratio of the energy consumed by all transmit pulses to the total energy provided by the system. The expression is as follows:
Figure GDA0002288721510000103
average degree of interleaving (AID): the invention provides an average interleaving degree as a performance index for measuring the interleaving degree of the pulses. And defining the interleaving degree as the number of the transmission pulses which are successfully inserted into other dwells in the waiting period of one task dwell. The average interleaving degree is the average value of all the resident interleaving degrees in the whole scheduling interval. Obviously, the average interleaving degree is related to the selection of parameters such as the number and the distance of radar imaging targets, the transmitting power of a system, the energy threshold of the system, the minimum sliding step length and the like. When other parameters are determined, the maximum resource tolerance of the system can be obtained by observing the variation trend of the average interleaving degree. The expression is as follows:
Figure GDA0002288721510000104
in the formula, N is the number of imaging tasks applied to be executed; n' is the number of imaging tasks actually performed; t is txiAnd triRespectively representing the transmitting time and the receiving time of the pulse in the ith task dwell; miThe azimuth observation dimension of the ith task is defined; t istotalThe total simulation time is; pavAverage power that can be provided for the radar; ptPeak power for each transmit pulse; numi,jThe number of other resident sending pulses in the jth sending and receiving pulse pair of the ith task is successfully staggered.
Fig. 1 is a comparison of performance index variation curves of two scheduling methods. As can be seen from fig. 1(a), when the number of tasks is small, both methods can successfully schedule all imaging tasks, and the scheduling success rate reaches 100%. When the number of tasks exceeds 6, the scheduling success rate of the traditional method starts to be greatly reduced, and the method of the invention can still successfully schedule all tasks until the number of tasks reaches 50. The method of the invention fully utilizes the idle time between task pulses to schedule other tasks, and can more fully utilize the time resource of the system compared with the traditional method.
The variation curves in fig. 1(b) and fig. 1(c) show that, because the method of the present invention fully utilizes the time resource of the pulse waiting period, the number of tasks successfully scheduled in the same scheduling time is large, so that the system time resource utilization rate and the energy resource utilization rate both reach about 80%, and after the number of imaging tasks exceeds 6, the method is much higher than the conventional method.
As can be seen from fig. 1(d), when there are fewer targets, the radar resources are sufficient, and the average degree of interleaving increases as the number of tasks increases. When the target reaches 50, the average degree of staggering tends to level off. This is because the pulse interleaving capability of the system is limited by both time resource constraints and energy resource constraints. When the average interleaving degree is not increased any more, the scheduling success rate of the system is saturated, and the resource utilization rate of the system reaches the highest.
Three targets are selected from the imaging tasks successfully scheduled based on the method of the invention to observe the imaging results. The results were compared with the results of conventional full aperture ISAR imaging, respectively, and are shown in Table 1.
TABLE 1 comparison of the imaging effect of the present invention with that of conventional full aperture imaging
Figure GDA0002288721510000111
The invention adopts peak signal-to-noise ratio (PSNR) to measure the imaging effect of the method, and the peak signal-to-noise ratio is defined as follows:
Figure GDA0002288721510000112
where the mean square error MSE is expressed as
Figure GDA0002288721510000121
Wherein
Figure GDA0002288721510000122
The sparse aperture imaging result of the invention is shown, sigma (i, j) shows the traditional full aperture imaging result, and m and n respectively show the row number and the column number of the ISAR image matrix. The larger the PSNR value, the better the imaging effect. Table 1 shows the peak snr and the mean square error of the conventional full aperture imaging results and the sparse aperture imaging results of the present invention. It can be seen that the invention isThe method can greatly improve the working efficiency of the radar on the premise of not obviously reducing the imaging quality.
TABLE 2 Peak SNR and mean squared error of imaging results
Object 1 Object 2 Target 3
PSNR/dB 43.89 39.44 40.81
MSE 2.653 7.391 5.235
In summary, the present invention provides a method for scheduling imaging radar resources based on pulse interleaving. According to the method, radar resources required by sparse aperture ISAR imaging are calculated according to a target characteristic cognitive result, on the basis, a reasonable pulse interleaving resident resource scheduling model is established, the radar resources are reasonably distributed under the double constraints of time and energy resources, a pulse interleaving implementation method is optimized, the average interleaving degree is provided as a performance index for measuring the radar imaging task resource scheduling, finally, a sparse aperture ISAR imaging method based on compressed sensing is adopted to image different targets respectively, and the radar resource utilization rate is remarkably improved on the premise that the target expected imaging resolution is met.

Claims (5)

1. An ISAR imaging radar resource adaptive scheduling method based on pulse interleaving comprises the following steps:
the method comprises the following steps: establishing a radar imaging resident task model:
Figure FDA0002288721500000011
Figure FDA0002288721500000012
in the formula, txι，twι，trιRespectively representing the transmitting period, the waiting period and the receiving period of the pulse in the ith task residence; et aliAnd stiRespectively an expected scheduling starting time and an actual scheduling starting time of the ith task; t isciAccumulating time for azimuth coherence of the ith task; omegaiFor the time window of the ith task, the earliest scheduling starting time is defined as the expected scheduling starting time; the vector T represents the scheduling state of the discretized time interval; a isiNumbering the tasks of the ith task; q. q.s1,q2,q3,q4To adjust the coefficient; the first and second constraints represent time constraints to be satisfied by the task scheduling; the third to fifth constraints represent sparse aperture conditions and observation time ranges that the imaging task needs to satisfy; the sixth constraint condition represents an energy constraint condition which needs to be met by task scheduling; wherein N is the number of imaging tasks required to be executed; n' is the number of imaging tasks actually performed; t is the simulation time, t0Is the simulation starting time; t is tendIs the simulation end time; ptPeak power for each transmit pulse; pavAverage power that can be provided for the radar; t istotalIs the total time of the simulation; miThe azimuth observation dimension of the ith task is defined; numi,jFor the ith task, the jth pulse pair is successfully staggered with other resident pulsesCounting; e (t) is the transient energy of the system at the time t; emaxApproaching the transient energy upper limit E for the energy state of the system at the time tmax；
Step two: the radar imaging task scheduling method specifically comprises the following steps:
the first step is as follows: a small amount of pulses are sent to recognize the target characteristics; according to echo feedback information, calculating azimuth coherent accumulation time and observation dimension required by imaging of each target;
the second step is that: calculating observation dimension parameters by using the cognitive result;
the third step: on the premise of meeting resource constraints, scheduling each radar imaging task by using a pulse interleaving technology;
the fourth step: and observing and imaging the successfully scheduled tasks by using the sparse aperture.
2. The method of claim 1, wherein a specific process of the cognitive target characteristics in the first step of the second step is as follows: target distance
Figure FDA0002288721500000021
Speed of rotation
Figure FDA0002288721500000022
And course
Figure FDA0002288721500000023
Measuring by using a conventional radar method; sending a small quantity of continuous pulses to each target to obtain a coarse-resolution ISAR image; target size
Figure FDA0002288721500000024
Estimating by the coarse resolution ISAR image of the target; degree of azimuth sparsity
Figure FDA0002288721500000025
The distance unit defined as the distance between the coarse resolution ISAR image of the target and each azimuth direction is larger than the set threshold valueNumber of off units; observation time
Figure FDA0002288721500000026
Calculating by defining the standard azimuth resolution required by standard target imaging; relative priority PkAnd weighting according to the distance, the speed and the course parameter of the target.
3. The method for adaptively scheduling ISAR imaging radar resources based on pulse interleaving as claimed in claim 1, wherein the third step of the second step specifically comprises:
p1: the latest scheduling starting time in the N imaging tasks is smaller than t0The sum of the earliest scheduling start time and the azimuth coherent accumulation time is more than tendAdding the tasks into a deletion linked list, and sending the rest N-K tasks into an execution linked list from high to low according to the priority, wherein K is: the latest scheduling starting time in the N imaging tasks is smaller than t0The sum of the earliest scheduling start time and the azimuth coherent accumulation time is more than tendInitializing the energy state of each time slot in the scheduling interval, and setting i as 1;
p2: definition of tp_firstThe first transmit pulse directed to the ith imaging task, i.e. the desired scheduling start time, tp_endTo the last transmit pulse, then
Figure FDA0002288721500000027
P3: if at tp_firstAnd tp_endSuccessfully inserting M in the determined pulse pair interval for head and tail transmission and reception meeting the time and energy constraint conditionsi2 transmit-receive pulse pairs, scheduling the imaging task in this manner and updating the energy state of each time slot, i ═ i +1, transition P4; otherwise, let tp_first＝tp_first+Δtp，tp_end＝tp_end+Δtp，ΔtpIs the minimum pointer sliding step length; if tp_first＜eti+ωiReturning to P3, otherwise, the task is considered to have failed scheduling and is processedAdding a deletion linked list, i is i +1, and returning to P2;
p4: if i is less than or equal to N-K, returning to P2, otherwise, turning to the fourth step.
4. The pulse-interleaving-based ISAR imaging radar resource adaptive scheduling method as claimed in claim 1, wherein the resource constraint conditions of the third step of the second step include time resource constraint conditions and energy resource constraint conditions, and the time resource constraint conditions are satisfied that other resident tasks are transmitted or received by using the time resources of the waiting period on the premise of not colliding with the transmission period and the receiving period of the original resident tasks; the pulse interleaving mode is divided into cross interleaving and internal interleaving, and the time constraint conditions required to be respectively met by the two interleaving modes are as follows:
(a)tw1≥tx2,tw2≥tr1,tx2+tw2≥tx1+tr1(2)
(b)tw1≥tx2+tw2+tr2(3)
the transient energy of the radar system at time t is represented as:
Figure FDA0002288721500000031
wherein, p (x) is a power parameter of the system, x is an integral variable of the power, and τ is a back-off parameter of the system, wherein the essence of the above formula is that the power function is subjected to exponential weighted summation, the energy weighting coefficient of an early-stage emission pulse is small, and the energy weighting coefficient of a recent emission pulse is large;
if the energy state of the system at the time t is close to the upper limit E of the transient energymaxThen the pulse cannot be transmitted continuously at this time, and a cooling time t is requiredcThe energy is restored to the normal value ElThat is, at [ t, t + t [ ]c]In the time period, the system does not transmit the pulse any more, but can normally receive the pulse; if the transient energy of the system at time t is E (t), then at t + tcAt the moment, the transient energy of the system is:
Figure FDA0002288721500000032
let E (t) become Emax，E(t+tc)＝ElThen the system cools for time tcThe expression of (a) is:
Figure FDA0002288721500000033
thereby obtaining the cooling rate v of the systemEThe expression of (a) is:
Figure FDA0002288721500000034
the decrease Δ E in the energy state of the system over the time Δ t is expressed as:
Figure FDA0002288721500000035
in the process of pulse interleaving, the energy constraint condition of the system is defined as that the system cannot exceed the maximum instantaneous energy threshold E at any time tmaxNamely:
E(t)≤Emax(9)。
5. the pulse-interleaving-based ISAR imaging radar resource adaptive scheduling method as claimed in claim 1, wherein a fourth step of the second step is specifically:
the imaging accumulation time of the ith target obtained after feature recognition is assumed to be
Figure FDA0002288721500000041
Then the radar co-transmits
Figure FDA0002288721500000042
A pulse, wherein PRF is the pulse repetition frequency, and discretizing the full aperture signal by sr(t, m), m ═ 1, 2.., N; emitting M (M < N) sub-pulses only to the target, sparse holesThe path signal can be represented as sr(t, M'), M ═ 1,2, …, M; if the estimated sparsity of the ith target is
Figure FDA0002288721500000043
The azimuth observation dimension after the ith target dimension reduction processing is as follows:
Figure FDA0002288721500000044
wherein c is a constant related to the recovery precision, a Fourier transform matrix is selected as a sparse transform matrix psi of the signal x, and an observation matrix phi is designed according to the sparse aperture distribution condition to meet the following requirements:
Figure FDA0002288721500000045
reconstructing the azimuth information by solving an optimization problem:
Figure FDA0002288721500000046
Sr(f,τm) In the form of a fourier transform of the sparse aperture signal,
and performing azimuth imaging on each distance unit according to the method to obtain a matrix form, namely a target two-dimensional ISAR image.
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