Method and system for optimizing sub-array position of distributed array

An optimization method and sub-array technology, applied to antenna arrays, antennas, instruments, etc., can solve the problems of less research on sub-array-level distributed arrays, and achieve the goal of improving optimization results, improving optimization results, and suppressing sidelobe levels Effect

Active Publication Date: 2022-03-18
CHINA ELECTRONIC TECH GRP CORP NO 38 RES INST
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

To date, little research has been done on subarray-level distributed arrays

Method used

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  • Method and system for optimizing sub-array position of distributed array
  • Method and system for optimizing sub-array position of distributed array
  • Method and system for optimizing sub-array position of distributed array

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Experimental program
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Embodiment 1

[0042] Such as figure 1 As shown, this embodiment provides a technical solution: a sub-array position optimization method for a distributed array, comprising the following steps:

[0043] S1: Setting optimization parameters and initializing the population

[0044] Set optimization parameters and randomly generate the position information of multiple sub-arrays as the initial population;

[0045] S2: Perform cross operation

[0046] Calculate the fitness value of each individual in the population, randomly select two individuals in the population for similarity detection, and use the discriminant formula of similarity to judge whether direct crossover operation is possible. The discriminant formula is as follows:

[0047] |AD(X i )-AD(X j )|≤γ

[0048] Among them, X i and x j Represent the two individuals to be crossed, AD(X i ) and AD(X j ) respectively represent the fitness values ​​of the two individuals to be crossed, and γ represents the similarity detection thresho...

Embodiment 2

[0074] Such as figure 2 As shown, the distributed array position optimization algorithm based on the improved genetic algorithm provided by this embodiment includes the following steps:

[0075] Step 1, in the crossover operation of the improved algorithm, perform similarity detection on two individuals;

[0076] Step two, in the mutation operation of the improved algorithm, adaptively change the value of the mutation probability VR.

[0077] In step 1, the specific content of similarity detection between two individuals in the crossover operation of the improved algorithm is as follows:

[0078] Before randomly selecting two different individuals for crossover operation, the similarity between the two individuals is first detected to determine whether the next crossover operation is "inbreeding". If the two individuals to be crossed have a high degree of similarity, it is considered "inbreeding", and the individual with a low fitness value among the two individuals needs t...

Embodiment 3

[0092] In order to evaluate the performance of the present invention, the following simulation experiments are done in this embodiment.

[0093] Such as image 3 As shown, the distributed array antenna is optimized by using the traditional genetic algorithm and the improved genetic algorithm respectively, so as to obtain the peak side lobe level change curve, the total aperture of the distributed array is L=100λ, the number of sub-arrays is M=5, The number of array elements in a single sub-array is N=10, the distance between adjacent array elements in the sub-array is d=λ / 2, and the wavelength λ=1. Population size NP = 100, the maximum number of iterations G max =500, crossover probability CR=0.9, mutation probability VR=0.1, single-point crossover method and similarity detection threshold γ=0.5 are used in the crossover operation. Next, the optimization method of the present invention optimizes and solves the sub-array positions of the distributed array.

[0094] To sum up...

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Abstract

The invention discloses a sub-array position optimization method and system of a distributed array, belonging to the technical field of distributed array antennas, comprising the following steps: S1: setting optimization parameters and initializing populations; S2: performing crossover operations; S3: performing mutations Operation; S4: end the optimization process. The present invention can judge the similarity of two individuals in a timely and effective manner by performing similarity detection on two individuals to be crossed, thereby effectively reducing the possibility of crossing similar or identical individuals, and improving the optimization effect; and according to Based on the fitness of individuals in the population, the dynamic adaptive adjustment of the mutation probability can effectively improve the position optimization results of the sub-array in the distributed array, so that the side lobe level of the distributed array antenna can be better suppressed, and the It improves the performance of distributed antennas and is worthy of promotion.

Description

technical field [0001] The invention relates to the technical field of distributed array antennas, in particular to a sub-array position optimization method and system of a distributed array. Background technique [0002] Today is the era of information technology, and human beings widely use the form of electromagnetic waves to realize the transmission and exchange of information. The working method of the radar is to transmit electromagnetic waves to the detection target, and then process the echoes reflected by the target to obtain the required information such as the parameters of the target. Radar itself is a modern electronic device with strong adaptability and long-distance detection capability. Because of its excellent characteristics, since its inception, it has been widely developed and applied in both military and civilian fields. With the continuous development and progress of society, human beings are constantly pursuing higher resolution and greater space radi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/00H01Q21/00
CPCG06N3/006H01Q21/00
Inventor 张正宇邹永庆胡树楷王昕李家干李进黄永华刘晨晨赵靓张世彬郑雨阳
Owner CHINA ELECTRONIC TECH GRP CORP NO 38 RES INST
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