Radar identification task scheduling method based on differential evolution algorithm

Abstract

The invention discloses a radar identification task scheduling method based on a differential evolution algorithm, and belongs to the technical field of radar identification, and the method specifically comprises the steps: introducing a radar-target assignment variable, and analyzing a constraint condition; according to the constraint condition, establishing a target identification sequence resource scheduling model; a constraint-based population initialization method and an information exchange-based differential evolution algorithm are designed to solve the target recognition sequence resource scheduling model, and a final radar-target-mode assignment result is obtained; and transmitting the final radar-target-mode assignment result to each radar to complete radar identification task scheduling. The radar identification task scheduling method based on the differential evolution algorithm has the advantages that under the condition of radar resource and time limitation, radar resources can be reasonably scheduled, and the target identification capacity of the whole task sequence is maximized.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar identification, and in particular relates to a radar identification task scheduling method based on a differential evolution algorithm. Background Art

[0002] The modern battlefield environment is becoming increasingly complex, and the number of tasks that radar systems need to perform is increasing, requiring radar systems to identify targets more robustly under limited resource conditions. The penetration speed of ballistic missiles is extremely fast. For example, a ballistic missile with a range of 3500km can reach a terminal penetration speed of 4800m / s. In order to increase the probability of successful penetration, some false targets such as debris and various decoys will be released, which brings great pressure to the interception mission. When using the terminal low stage for anti-missile interception, the reserved interception time window is less than 3s, so it is necessary to make combat decisions in a very short time to accurately identify the real target and effectively intercept it. However, radar resources are limited. How to reasonably dispatch radar resources in a very short time to maximize the target recognition capacity is a problem that needs to be solved urgently. Summary of the invention

[0003] The purpose of the present invention is to provide a radar identification task scheduling method based on a differential evolution algorithm, which has the characteristics of being able to reasonably schedule radar resources under the conditions of radar resource and time constraints to maximize the target identification capacity of the entire task sequence.

[0004] The technical solution adopted by the present invention is a radar identification task scheduling method based on a differential evolution algorithm, which specifically includes the following steps:

[0005] Step 1: Introduce radar-target assignment variables and analyze constraints;

[0006] Step 2: Establish a target recognition sequence resource scheduling model based on constraints;

[0007] Step 3: Design a constraint-based population initialization method and a differential evolution algorithm based on information exchange to solve the target recognition sequence resource scheduling model and obtain the radar-target-mode assignment result;

[0008] Step 4: Transmit the radar-target-mode assignment results to each radar to complete the radar identification task scheduling.

[0009] The present invention is also characterized in that:

[0010] In step 1, the radar-target assignment variable u is introduced and the following constraints are analyzed:

[0011] To assign variable constraints:

[0012]

[0013] In the formula, It means that at the kth moment, the qth target is identified using the jth recognition mode of the ith radar; Indicates that the target is not recognized;

[0014] Identify probability constraints:

[0015]

[0016] In the formula, p i,j represents the probability of the jth recognition mode of the i-th radar, represents the probability threshold of identifying target q at the kth moment; I represents the total number of radars;

[0017] Radar resource constraints:

[0018]

[0019] In the formula, Q represents the total number of targets, J represents the total number of radar identification methods, and T i,j,k It represents the dwell time consumed by the i-th radar using the j-th recognition mode within the tracking interval; represents the total dwell time consumed by the i-th radar in a time interval;

[0020] Identify the pattern completion constraints:

[0021]

[0022] In the formula, represents the total dwell time consumed by the i-th radar using the j-th recognition method, T s is the tracking interval, k 0 To identify the start time, k 1 To identify the termination moment;

[0023] Maximum window constraint for target recognition:

[0024]

[0025] In the formula, represents the initial recognition time of the qth target by the i-th radar, It indicates the termination recognition time of the qth target by the i-th radar.

[0026] The target recognition sequence resource scheduling model established in step 2 is as follows:

[0027]

[0028] In the formula, F(·) represents the function.

[0029] Step 3 specifically includes the following steps:

[0030] Step 3.1: Design a constraint-based population initialization method to generate an initialization population that satisfies the constraints;

[0031] Step 3.2: Based on step 3.1, increase the collaboration between networked radars, design a differential evolution algorithm based on information interaction, and assign recognition targets and recognition methods to each radar in the networked radar.

[0032] Step 3.1 specifically includes the following steps:

[0033] Step 3.11: Initialize the number of radars and targets, the type of identification method and the corresponding dwell time and identification probability, the start identification time and the end identification time;

[0034] Step 3.12: Identifiable target inspection;

[0035] Within the identifiable time range, determine whether the target q is within the radar's observable range. If it is within the radar's observable range and the target is not identified, that is, the identification matrix is_used[q] = 0, then perform a feasible method test;

[0036] Determine whether the radar can identify target q within the time required for the jth identification method; if target q can be identified, add the jth identification method to the method matrix choose_type[];

[0037] Determine whether choose_type[] is not empty. If it is not empty, add the target q to the target matrix choose_num[];

[0038] Step 3.13: Target assignment and identification method selection;

[0039] If there is an identifiable target, an identification method is assigned to it according to the radar resource constraints; if there is no identifiable target, the radar does not perform the identification task and waits for the next step of allocation;

[0040] Step 3.14: Output radar-target-mode assignment matrix;

[0041] In step 3.13, the identifiable targets and modes are screened, and the is_used[] matrix is ​​used to memorize the identified targets to generate the initial radar-target-mode assignment results, ensure that the generated radar-target-mode assignment meets the model constraints, and generate an initialized population that meets the constraints.

[0042] Step 3.2 specifically includes the following steps:

[0043] Assume that after the allocation of radar b is determined at time k-1, due to the continuity constraint of identification, radar b is allocated the same in the time slice from k-1 to k-1+t_type. Therefore, at the kth time, the allocation of radar b is determined, and the radars with undetermined allocation use the determined radar allocation information to select targets. The specific steps are as follows:

[0044] Step 3.21: When assigning the number of targets to radar a, determine whether there is interactive information between other radars before the assignment at the kth moment, that is, determine whether the element in the kth column of the individual code is 0. If the element in the kth column is not 0, there is interactive information, and information interactive selection is performed;

[0045] Step 3.22: Determine whether other radars need to cooperate, that is, determine whether the final probability of radar b selecting the identification method to identify target q is greater than the probability threshold of identifying the target. If it is greater than or equal to the probability threshold of identifying the target, then no cooperation is required and random allocation is performed; if it is less than the probability threshold of identifying the target, radar a and radar b cooperate to identify target q, that is, the kth column value in the individual code of radar a is the same as the kth column value of radar b;

[0046] Step 3.23: Set the recognition success matrix is_successed[] in the same way as step 3.12 to determine whether the target is successfully recognized. If it is successfully recognized, is_successed[q] = 1, and all radars no longer recognize the target;

[0047] Step 3.24: Until the recognition time is used up and the allocation is completed, the final radar-target-mode assignment result is output.

[0048] The beneficial effects of the present invention are:

[0049] The radar identification task scheduling method based on the differential evolution algorithm of the present invention designs an initialization population method based on information interaction according to the physical characteristics, detection capability and location distribution of the radar. The algorithm can more accurately allocate identification targets and select identification methods, make full use of the resources of each radar, and avoid resource waste and redundancy. Through the collaborative optimization method, the entire radar network can jointly optimize the target allocation and identification method, thereby achieving better global performance. Through the collective intelligence method, the local optimal solution is avoided and the overall performance of the system is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is an overall flow chart of the radar identification task scheduling method based on the differential evolution algorithm of the present invention;

[0051] Figure 2 It is a radar 1 recognition target allocation result diagram of the radar recognition task scheduling method based on the differential evolution algorithm of the present invention;

[0052] Figure 3 It is a radar 1 residence time allocation result diagram of the radar identification task scheduling method based on the differential evolution algorithm of the present invention;

[0053] Figure 4 It is a radar 1 recognition mode allocation result diagram of the radar recognition task scheduling method based on the differential evolution algorithm of the present invention;

[0054] Figure 5 It is a radar 2 recognition target allocation result diagram of the radar recognition task scheduling method based on the differential evolution algorithm of the present invention;

[0055] Figure 6 It is a radar 2 residence time allocation result diagram of the radar identification task scheduling method based on the differential evolution algorithm of the present invention;

[0056] Figure 7 It is a radar 2 recognition mode allocation result diagram of the radar recognition task scheduling method based on the differential evolution algorithm of the present invention;

[0057] Figure 8 It is a comparison chart of simulation results of the radar identification task scheduling method based on the differential evolution algorithm of the present invention. DETAILED DESCRIPTION

[0058] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0059] The radar recognition task scheduling method based on the differential evolution algorithm of the present invention is as follows: Figure 1 As shown, the specific steps include:

[0060] Step 1: Introduce radar-target assignment variables and analyze constraints.

[0061] Since radar system resources are limited, such as power, bandwidth, and dwell time, optimization technology needs to consider resource constraints. The radar system may need to process multiple targets at the same time, and these targets may have different characteristics and priorities. At the same time, missile targets present variable and differentiated target characteristics at different flight stages. A single identification method is difficult to robustly identify the entire process, which can easily cause the early warning mission to fail. For this reason, it is necessary to develop an appropriate identification method based on the characteristics of missiles at different stages. Radars of different bands have different recognition capabilities for targets, so the radar's recognition time window needs to be considered to make the radar recognition task scheduling sequence more reasonable.

[0062] First, introduce the radar-target assignment variable u and analyze the following constraints:

[0063] To assign variable constraints:

[0064]

[0065] In the formula, It means that at the kth moment, the qth target is identified using the jth recognition mode of the ith radar; Indicates that the target is not recognized;

[0066] Identify probability constraints:

[0067] Each recognition method of each radar corresponds to a recognition probability. Only when the recognition probability of the target is higher than a certain threshold does it mean that the target is successfully recognized. That is, the recognition probability constraint is:

[0068]

[0069] In the formula, p i,j represents the probability of the jth recognition mode of the i-th radar, represents the probability threshold of identifying target q at the kth moment; I represents the total number of radars;

[0070] Radar resource constraints:

[0071] When the radar identifies a target, it needs to determine whether the radar has enough resources to identify the target, that is, the radar resource constraint:

[0072]

[0073] In the formula, Q represents the total number of targets, J represents the total number of radar identification methods, and T i,j,k It represents the dwell time consumed by the i-th radar using the j-th recognition mode within the tracking interval; represents the total dwell time consumed by the i-th radar in a time interval;

[0074] Identify the pattern completion constraints:

[0075] Starting from a certain moment, the radar identifies a target within the time period constraint of target identification, that is, the constraint of identification completion is:

[0076]

[0077] In the formula, represents the total dwell time consumed by the i-th radar using the j-th recognition method, T s is the tracking interval, k 0 To identify the start time, k 1 To identify the termination moment;

[0078] Maximum window constraint for target recognition:

[0079] The radar needs to identify a target within a specified time, which is expressed as the maximum window constraint for target identification:

[0080]

[0081] In the formula, represents the initial recognition time of the qth target by the i-th radar, It indicates the termination recognition time of the qth target by the i-th radar.

[0082] Step 2: Establish a target recognition sequence resource scheduling model based on constraints;

[0083] In the process of multi-target recognition by networked radars, the recognition capability of each radar is limited. Now assume that the number of X-band radars is fixed. In the process of target recognition, the optimal target recognition sequence is output by reasonably scheduling radar resources. According to the constraint analysis of step 1, the resource scheduling model of target recognition sequence is established as follows:

[0084]

[0085] In the formula, F(·) represents the function.

[0086] On the basis of meeting the probability of successful identification, radar resources are scheduled to maximize the target identification capacity. Specifically, the assignment variable constraint and the identification probability constraint represent the range of variable values, that is, whether the jth identification mode of the i-th radar is selected to identify the qth target at the kth moment; the radar resource constraint, that is, when the radar identifies the target, it determines whether there is enough dwell time to identify it; the identification mode completion constraint means that the radar identifies a certain target within the time period constraint of target identification from a certain moment; the target identification maximum window constraint represents the constraint of the target identification time period, that is, a certain target needs to be successfully identified within the specified time period.

[0087] Step 3: Design a constraint-based population initialization method and a differential evolution algorithm based on information exchange to solve the target recognition sequence resource scheduling model and obtain the radar-target-mode assignment result.

[0088] The target recognition sequence resource scheduling model is an NP-hard problem that requires an optimized solution. Therefore, a constraint-based population initialization method and a differential evolution algorithm solution model based on information exchange are designed to complete the scheduling of radar recognition tasks.

[0089] The differential evolution algorithm is a population-based evolutionary algorithm that simulates the process of competition and cooperation among individuals in a population. First, the initial population is generated by coding, but its random method of generating the initial population makes most of the initial solutions unable to meet the constraints and cannot effectively solve the optimization problem with constraints. Therefore, a constrained population initialization method is designed. The mutation, crossover, selection and other operations in genetics are applied to individuals to generate a new generation of populations, calculate their fitness functions, and then according to the law of survival of the fittest, after the maximum number of iterations, the global optimal solution or an approximate global optimal solution is finally generated.

[0090] The encoding method of the population individuals is integer encoding. The integer encoding and the 0-1 encoding in the model can be converted to each other through the one-to-one correspondence between the integer encoding value and the 0-1 encoding index. The specific encoding form of each radar is a 2×K_max matrix, where K_max represents the maximum recognition window, the first row of the matrix represents the target index assigned to the radar, and the second row of the matrix represents the specific recognition method assigned by the radar. Therefore, the core of this initialization is to select reasonable targets for radar assignment based on constraints.

[0091] The model is solved according to the following steps:

[0092] Step 3.1: Design a constraint-based population initialization method to generate an initialization population that satisfies the constraints;

[0093] Step 3.11: Initialize the number of radars and targets, the type of identification method and the corresponding dwell time and identification probability, the start identification time and the end identification time;

[0094] Step 3.12: Identifiable target inspection;

[0095] Within the identifiable time range, determine whether the target q is within the radar's observable range. If it is within the radar's observable range and the target is not identified, that is, the identification matrix is_used[q] = 0, then perform a feasible method test;

[0096] Determine whether the radar can identify target q within the time required for the jth identification method; if target q can be identified, add the jth identification method to the method matrix choose_type[];

[0097] Determine whether choose_type[] is not empty. If it is not empty, add the target q to the target matrix choose_num[];

[0098] Step 3.13: Target assignment and identification method selection;

[0099] If there is an identifiable target, an identification method is assigned to it according to the radar resource constraints; if there is no identifiable target, the radar does not perform the identification task and waits for the next step of allocation;

[0100] Step 3.14: Output radar-target-mode assignment matrix;

[0101] In step 3.13, the identifiable targets and modes are screened, and the is_used[] matrix is ​​used to memorize the identified targets to generate the initial radar-target-mode assignment results, ensure that the generated radar-target-mode assignment meets the model constraints, and generate an initialized population that meets the constraints.

[0102] Step 3.2: Based on step 3.1, increase the collaboration between networked radars, design a differential evolution algorithm based on information interaction, and assign recognition targets and recognition methods to each radar in the networked radar.

[0103] Assume that after the allocation of radar b is determined at time k-1, due to the continuity constraint of identification, radar b is allocated the same in the time slice from k-1 to k-1+t_type. Therefore, at the kth time, the allocation of radar b is determined, and the radars with undetermined allocation use the determined radar allocation information to select targets. The specific steps are as follows:

[0104] Step 3.21: When assigning the number of targets to radar a, determine whether there is interactive information between other radars before the assignment at the kth moment, that is, determine whether the element in the kth column of the individual code is 0. If the element in the kth column is not 0, there is interactive information, and information interactive selection is performed;

[0105] Step 3.22: Determine whether other radars need to cooperate, that is, determine whether the final probability of radar b selecting the identification method to identify target q is greater than the probability threshold of identifying the target. If it is greater than or equal to the probability threshold of identifying the target, then no cooperation is required and random allocation is performed; if it is less than the probability threshold of identifying the target, radar a and radar b cooperate to identify target q, that is, the kth column value in the individual code of radar a is the same as the kth column value of radar b;

[0106] Step 3.23: Set the recognition success matrix is_successed[] in the same way as step 3.12 to determine whether the target is successfully recognized. If it is successfully recognized, is_successed[q] = 1, and all radars no longer recognize the target;

[0107] Step 3.24: Until the recognition time is used up and the allocation is completed, the final radar-target-mode assignment result is output.

[0108] Step 4: Transmit the radar-target-mode assignment results to each radar to complete the radar identification task scheduling.

[0109] Example 1

[0110] This embodiment provides a radar recognition task scheduling method based on a differential evolution algorithm, such as Figure 1 As shown, the specific steps include:

[0111] Step 1: Introduce radar-target assignment variables and analyze constraints;

[0112] Step 2: Establish a target recognition sequence resource scheduling model based on constraints;

[0113] Step 3: Design a constraint-based population initialization method and a differential evolution algorithm based on information exchange to solve the target recognition sequence resource scheduling model and obtain the radar-target-mode assignment result;

[0114] Step 4: Transmit the radar-target-mode assignment results to each radar to complete the radar identification task scheduling.

[0115] Example 2

[0116] This embodiment provides a radar recognition task scheduling method based on a differential evolution algorithm, such as Figure 1 As shown, the specific steps include:

[0117] Step 1: Introduce radar-target assignment variables and analyze constraints;

[0118] Introduce the radar-target assignment variable u and analyze the following constraints:

[0119] To assign variable constraints:

[0120]

[0121] In the formula, It means that at the kth moment, the qth target is identified using the jth recognition mode of the ith radar; Indicates that the target is not recognized;

[0122] Identify probability constraints:

[0123]

[0124] In the formula, p i,j represents the probability of the jth recognition mode of the i-th radar, represents the probability threshold of identifying target q at the kth moment; I represents the total number of radars;

[0125] Radar resource constraints:

[0126]

[0127] In the formula, Q represents the total number of targets, J represents the total number of radar identification methods, and T i,j,k It represents the dwell time consumed by the i-th radar using the j-th recognition mode within the tracking interval; represents the total dwell time consumed by the i-th radar in a time interval;

[0128] Identify the pattern completion constraints:

[0129]

[0130] In the formula, represents the total dwell time consumed by the i-th radar using the j-th recognition method, T s is the tracking interval, k 0 To identify the start time, k 1 To identify the termination moment;

[0131] Maximum window constraint for target recognition:

[0132]

[0133] In the formula, represents the initial recognition time of the qth target by the i-th radar, It indicates the termination recognition time of the qth target by the i-th radar.

[0134] Step 2: Establish a target recognition sequence resource scheduling model based on constraints;

[0135]

[0136] In the formula, F(·) represents the function.

[0137] Step 3: Design a constraint-based population initialization method and a differential evolution algorithm based on information exchange to solve the target recognition sequence resource scheduling model and obtain the radar-target-mode assignment result.

[0138] Step 3.1: Design a constraint-based population initialization method to generate an initialization population that satisfies the constraints;

[0139] Step 3.2: Based on step 3.1, increase the collaboration between networked radars, design a differential evolution algorithm based on information interaction, and assign recognition targets and recognition methods to each radar in the networked radar.

[0140] Step 4: Transmit the radar-target-mode assignment results to each radar to complete the radar identification task scheduling.

[0141] Example 3

[0142] This embodiment provides a radar recognition task scheduling method based on a differential evolution algorithm, such as Figure 1 As shown, the specific steps include:

[0143] Step 1: Introduce radar-target assignment variables and analyze constraints;

[0144] Introduce the radar-target assignment variable u and analyze the following constraints:

[0145] To assign variable constraints:

[0146]

[0147] In the formula, It means that at the kth moment, the qth target is identified using the jth recognition mode of the ith radar; Indicates that the target is not recognized;

[0148] Identify probability constraints:

[0149]

[0150] In the formula, p i,j represents the probability of the jth recognition mode of the i-th radar, represents the probability threshold of identifying target q at the kth moment; I represents the total number of radars;

[0151] Radar resource constraints:

[0152]

[0153] In the formula, Q represents the total number of targets, J represents the total number of radar identification methods, and T i,j,k It represents the dwell time consumed by the i-th radar using the j-th recognition mode within the tracking interval; represents the total dwell time consumed by the i-th radar in a time interval;

[0154] Identify the pattern completion constraints:

[0155]

[0156] In the formula, represents the total dwell time consumed by the i-th radar using the j-th recognition method, T s is the tracking interval, k 0 To identify the start time, k 1 To identify the termination moment;

[0157] Maximum window constraint for target recognition:

[0158]

[0159] In the formula, represents the initial recognition time of the qth target by the i-th radar, It indicates the termination recognition time of the qth target by the i-th radar.

[0160] Step 2: Establish a target recognition sequence resource scheduling model based on constraints;

[0161]

[0162] In the formula, F(·) represents the function.

[0163] Step 3: Design a constraint-based population initialization method and a differential evolution algorithm based on information exchange to solve the target recognition sequence resource scheduling model and obtain the radar-target-mode assignment result.

[0164] Step 3.1: Design a constraint-based population initialization method to generate an initialization population that satisfies the constraints;

[0165] Step 3.11: Initialize the number of radars and targets, the type of identification method and the corresponding dwell time and identification probability, the start identification time and the end identification time;

[0166] Step 3.12: Identifiable target inspection;

[0167] Within the identifiable time range, determine whether the target q is within the radar's observable range. If it is within the radar's observable range and the target is not identified, that is, the identification matrix is_used[q] = 0, then perform a feasible method test;

[0168] Determine whether the radar can identify target q within the time required for the jth identification method; if target q can be identified, add the jth identification method to the method matrix choose_type[];

[0169] Determine whether choose_type[] is not empty. If it is not empty, add the target q to the target matrix choose_num[];

[0170] Step 3.13: Target assignment and identification method selection;

[0171] If there is an identifiable target, an identification method is assigned to it according to the radar resource constraints; if there is no identifiable target, the radar does not perform the identification task and waits for the next step of allocation;

[0172] Step 3.14: Output radar-target-mode assignment matrix;

[0173] In step 3.13, the identifiable targets and modes are screened, and the is_used[] matrix is ​​used to memorize the identified targets to generate the initial radar-target-mode assignment results, ensure that the generated radar-target-mode assignment meets the model constraints, and generate an initialized population that meets the constraints.

[0174] Step 3.2: Based on step 3.1, increase the collaboration between networked radars, design a differential evolution algorithm based on information interaction, and assign recognition targets and recognition methods to each radar in the networked radar.

[0175] Assume that after the allocation of radar b is determined at time k-1, due to the continuity constraint of identification, radar b is allocated the same in the time slice from k-1 to k-1+t_type. Therefore, at the kth time, the allocation of radar b is determined, and the radars with undetermined allocation use the determined radar allocation information to select targets. The specific steps are as follows:

[0176] Step 3.21: When assigning the number of targets to radar a, determine whether there is interactive information between other radars before the assignment at the kth moment, that is, determine whether the element in the kth column of the individual code is 0. If the element in the kth column is not 0, there is interactive information, and information interactive selection is performed;

[0177] Step 3.22: Determine whether other radars need to cooperate, that is, determine whether the final probability of radar b selecting the identification method to identify target q is greater than the probability threshold of identifying the target. If it is greater than or equal to the probability threshold of identifying the target, then no cooperation is required and random allocation is performed; if it is less than the probability threshold of identifying the target, radar a and radar b cooperate to identify target q, that is, the kth column value in the individual code of radar a is the same as the kth column value of radar b;

[0178] Step 3.23: Set the recognition success matrix is_successed[] in the same way as step 3.12 to determine whether the target is successfully recognized. If it is successfully recognized, is_successed[q] = 1, and all radars no longer recognize the target;

[0179] Step 3.24: Until the recognition time is used up and the allocation is completed, the final radar-target-mode assignment result is output.

[0180] Step 4: Transmit the radar-target-mode assignment results to each radar to complete the radar identification task scheduling.

[0181] Simulation experiment

[0182] The effect of the present invention can be further illustrated by the following simulation results.

[0183] 1. Simulation conditions

[0184] In order to verify the effectiveness of differential evolution algorithm in optimizing the resource scheduling model of radar target recognition sequence, random selection recognition without optimization processing is used as a control. The random selection is in a non-interference state to verify the basic recognition ability of the radar network.

[0185] 2. Basic parameter settings

[0186] In the recognition stage, two X-band radars, three recognition methods, and 20 targets were used for simulation. When the dwell time of the two radars and the probability of successful recognition of the corresponding three recognition methods were known, as shown in Tables 1 to 3, the completion of the technical indicators was verified by simulation experiments.

[0187] Table 1 The radar's dwell time for each time slice in a certain recognition mode

[0188] Identification method 1 Identification method 2 Identification method 3 Radar 1 0.2s 0.3s 0.4s Radar 2 0.7s 0.8s 0.3s

[0189] Table 2 The total dwell time of the radar using a certain recognition method

[0190] Identification method 1 Identification method 2 Identification method 3 Radar 1 8s 10s 12s Radar 2 6s 8s 10s

[0191] Table 3 The probability of successful identification by radar using a certain identification method

[0192] Identification method 1 Identification method 2 Identification method 3 Radar 1 0.6 0.7 0.8 Radar 2 0.7 0.8 0.9

[0193] Due to the limited radar resources, it is necessary to reasonably schedule radar resources to ensure the maximum utilization of radar resources and improve the recognition accuracy and efficiency. A target recognition sequence resource scheduling model is constructed. Through simulation experiments, the target allocation of radar 1 and radar 2, the corresponding dwell time allocation, the corresponding recognition mode allocation, the number of successfully identified targets, and the earliest and latest recognition windows for identifying group targets are output, and the Monte Carlo method is used to output the recognition capacity of the target.

[0194] Monte Carlo experiment is a commonly used random simulation method that can be used to simulate the propagation of radar signals and the activity patterns of targets. Through this method, radar signals and target behaviors in different situations can be simulated to evaluate the performance and robustness of the recognition system. The differential evolution algorithm based on information exchange optimizes the model solution. After simulating the experiment with the Monte Carlo method 40 times, the target recognition capacity is improved compared with the random target recognition capacity of the radar. This method of improving recognition capacity can effectively improve the performance and efficiency of the radar system, thereby better meeting the needs of practical applications.

[0195] 3. Simulation Experiment Results

[0196] In the precise identification stage, radar resources are limited, so it is necessary to reasonably allocate radar resources. The experiment simulates two radars, three identification methods, and 20 targets, and outputs the target allocation of radar 1 and radar 2, the corresponding dwell time allocation, the corresponding identification method allocation, the number of successfully identified targets, and the identification capacity of the targets.

[0197] Figure 2-3 It's Radar 1, Figure 5-6 It is radar 2. Under the constraint of the target recognition time window, the dwell time allocation required for the radar to recognize 20 targets is output. From the perspective of a single radar, the same radar will not repeat the recognition; from the perspective of the radar system, a radar will adopt a scheme with a high probability of successful recognition, and the other radars will not recognize it again; when a radar adopts a low probability scheme to recognize a target, another radar can perform collaborative recognition.

[0198] Figure 4 , Figure 7 The results show that the radar can identify 20 targets by selecting the recognition mode within the range of the target recognition time period and under the premise of meeting the recognition success probability constraint. Figure 2-3 , Figure 5-6 , summarize the time occupied by a single radar using a certain recognition method, and then calculate the time proportion at 0 to 360 seconds. The results are shown in Tables 4 and 5:

[0199] Table 4 Radar 1 recognition time ratio

[0200] Identification probability Time occupied(s) Time Proportion Identification method 1 0.6 40-65、130-155、290-315 45 / 360 Identification method 2 0.7 230-290 60 / 360 Identification method 3 0.8 0-40、65-130、155-230 180 / 360

[0201] Table 5 Radar 2 recognition time ratio

[0202]

[0203] According to the objective function:

[0204] in

[0205] The calculation of the time proportion of joint identification of multiple radars is shown in Table 6:

[0206] Table 6: Time proportion of joint identification of multiple radars

[0207] Radar 1 identification method Radar 2 identification method Identification probability Time occupied(s) Time Proportion 3 3 0.98 35-40、120-130 15 / 360 1 3 0.96 40-60、130-155 45 / 360 1 1 0.88 60-65 5 / 360 3 1 0.94 65-70 5 / 360 3 2 0.96 70-12、155-230 125 / 360 2 2 0.94 230-250、285-290 35 / 360 2 3 0.97 250-285 35 / 360 1 2 0.92 290-315 25 / 360

[0208] From the joint probability in Table 6, it can be seen that the use of joint calculation between radars can greatly improve the probability of target recognition, thereby improving the target recognition capacity.

[0209] like Figure 8As shown in the figure, the evolutionary algorithm based on constrained construction and initialization population is used to optimize the model, and the target recognition capability is improved compared with the recognition capacity of randomly selected targets. In order to give full play to the synergy between networked radars, a differential evolution algorithm based on information exchange is proposed to further optimize the model, and the simulation experiment verifies that the target recognition capacity is significantly improved compared with random selection.

Claims

1. A radar identification task scheduling method based on differential evolution algorithm, characterized in that: The specific steps include: Step 1: Introduce radar-target assignment variables and analyze constraints; Step 2: Establish a target recognition sequence resource scheduling model based on constraints; Step 3: Design a constraint-based population initialization method and a differential evolution algorithm based on information exchange to solve the target recognition sequence resource scheduling model and obtain the radar-target-mode assignment result; Step 4: Transmit the radar-target-mode assignment results to each radar to complete the radar identification task scheduling.

2. The radar identification task scheduling method based on differential evolution algorithm according to claim 1 is characterized in that: In step 1, the radar-target assignment variable u is introduced and the following constraints are analyzed: To assign variable constraints: In the formula, It means that at the kth moment, the qth target is identified using the jth recognition mode of the ith radar; Indicates that the target is not recognized; Identify probability constraints: In the formula, p i,j represents the probability of the jth recognition mode of the i-th radar, represents the probability threshold of identifying target q at the kth moment; I represents the total number of radars; Radar resource constraints: In the formula, Q represents the total number of targets, J represents the total number of radar identification methods, and T i,j,k It represents the dwell time consumed by the i-th radar using the j-th recognition mode within the tracking interval; represents the total dwell time consumed by the i-th radar in a time interval; Identify the pattern completion constraints: In the formula, represents the total dwell time consumed by the i-th radar using the j-th recognition method, T s is the tracking interval, k0 is the recognition start time, and k1 is the recognition end time; Maximum window constraint for target recognition: In the formula, represents the initial recognition time of the qth target by the i-th radar, It indicates the termination recognition time of the qth target by the i-th radar.

3. The radar identification task scheduling method based on differential evolution algorithm according to claim 2 is characterized in that: The target recognition sequence resource scheduling model established in step 2 is as follows: In the formula, F(·) represents the function.

4. The radar identification task scheduling method based on differential evolution algorithm according to claim 3 is characterized in that: Step 3 specifically includes the following steps: Step 3.1: Design a constraint-based population initialization method to generate an initialization population that satisfies the constraints; Step 3.2: Based on step 3.1, increase the collaboration between networked radars, design a differential evolution algorithm based on information interaction, and assign recognition targets and recognition methods to each radar in the networked radar.

5. The radar identification task scheduling method based on differential evolution algorithm according to claim 4 is characterized in that: Step 3.1 specifically includes the following steps: Step 3.11: Initialize the number of radars and targets, the type of identification method and the corresponding dwell time and identification probability, the start identification time and the end identification time; Step 3.12: Identifiable target inspection; Within the identifiable time range, determine whether the target q is within the radar's observable range. If it is within the radar's observable range and the target is not identified, that is, the identification matrix is_used[q] = 0, then perform a feasible method test; Determine whether the radar can identify target q within the time required for the jth identification method; If the target q can be identified, the jth identification method is added to the method matrix choose_type[]; Determine whether choose_type[] is not empty. If it is not empty, add the target q to the target matrix choose_num[]; Step 3.13: Target assignment and identification method selection; If there is an identifiable target, an identification method is assigned to it according to the radar resource constraints; if there is no identifiable target, the radar does not perform the identification task and waits for the next step of allocation; Step 3.14: Output radar-target-mode assignment matrix; In step 3.13, the identifiable targets and modes are screened, and the is_used[] matrix is ​​used to memorize the identified targets to generate the initial radar-target-mode assignment results, ensure that the generated radar-target-mode assignment meets the model constraints, and generate an initialized population that meets the constraints.

6. The radar identification task scheduling method based on differential evolution algorithm according to claim 5 is characterized in that: Step 3.2 specifically includes the following steps: Assume that after the allocation of radar b is determined at time k-1, due to the continuity constraint of identification, radar b is allocated the same in the time slice from k-1 to k-1+t_type. Therefore, at the kth time, the allocation of radar b is determined, and the radars with undetermined allocation use the determined radar allocation information to select targets. The specific steps are as follows: Step 3.21: When assigning the number of targets to radar a, determine whether there is interactive information between other radars before the assignment at the kth moment, that is, determine whether the element in the kth column of the individual code is 0. If the element in the kth column is not 0, there is interactive information, and information interactive selection is performed; Step 3.22: Determine whether other radars need to cooperate, that is, determine whether the final probability of radar b selecting the identification method to identify target q is greater than the probability threshold of identifying the target. If it is greater than or equal to the probability threshold of identifying the target, then no cooperation is required and random allocation is performed; if it is less than the probability threshold of identifying the target, radar a and radar b cooperate to identify target q, that is, the kth column value in the individual code of radar a is the same as the kth column value of radar b; Step 3.23: Set the recognition success matrix is_successed[] in the same way as step 3.12 to determine whether the target is successfully recognized. If it is successfully recognized, is_successed[q] = 1, and all radars no longer recognize the target; Step 3.24: Until the recognition time is used up and the allocation is completed, the final radar-target-mode assignment result is output.

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