Method for improving EIRP efficiency of array feed reflector antenna

Abstract

The invention discloses a method for improving EIRP efficiency of an array-fed reflector antenna, and belongs to the field of array-fed reflector antennas. The method comprises the following steps: S1, randomly initializing a binary weed population; s2, weed fitness evaluation; s3, breeding and diffusing the weed population based on a probability selection mechanism; s4, evaluating the fitness of newly generated weeds; s5, competitive exclusion of weed populations; and S6, judging whether the maximum evolution algebra is reached or not, and outputting a final solution or returning to S3. According to the method, a classic invasive weed algorithm is improved, reproduction and diffusion of weed populations are not based on a normal distribution mechanism any more, but based on a probability selection mechanism, the improved algorithm can be suitable for rapid optimization of binary variables, and an obtained feed source array feed power scheme can effectively improve the EIRP efficiency of a reflector antenna.

Description

Technical Field

[0001] The present invention belongs to the field of array-fed reflector antennas, and in particular relates to an optimization of a feeding power scheme of a feed source array of a reflector antenna, and specifically relates to a binary invasive weed algorithm for improving the EIRP efficiency of an array-fed reflector antenna. Background Art

[0002] Reflector antennas are widely used in satellite communications, space radar and other fields due to their advantages of high gain and high efficiency. In order to achieve beam scanning, phased array antennas are used as feed sources for reflector antennas. Among the comprehensive methods for pencil scanning beams of array-fed reflector antennas, the conjugate field matching method is the most commonly used one. Although it can synthesize the highest efficiency, due to the focusing characteristics of the focal field, this method can only obtain a strongly tapered feed power distribution. This will cause the power amplifier to operate in a low-efficiency state, resulting in a decrease in EIRP when the system power consumption is constant, that is, a decrease in EIRP efficiency. In the transmitting antenna system, EIRP efficiency is more important than antenna efficiency because EIRP represents the maximum communication or monitoring distance under a given signal-to-noise ratio requirement. Therefore, it is necessary to adjust the feed power distribution of the feed array to improve the efficiency of the power amplifier while minimizing the sacrifice of efficiency, thereby achieving higher EIRP efficiency. Summary of the invention

[0003] Aiming at the problem of low EIRP efficiency of array-fed reflector antennas designed by pencil beam synthesis method in the prior art, the present invention proposes a method for improving the EIRP efficiency of array-fed reflector antennas.

[0004] The technical solution adopted by the present invention is as follows:

[0005] A method for improving the EIRP efficiency of an array-fed reflector antenna comprises the following steps:

[0006] S1. Randomly initialize the binary weed population;

[0007] Randomly generate P in the search space ini weeds to form an initial population; among them, P ini is the initial population size, and one weed represents a set of feed array feeding power schemes. The feeding power of each array element in the feed array feeding power scheme only contains power values ​​of 0 and 1, which respectively indicate that the power amplifier is turned off and on, and the turned-on power amplifier operates at the highest efficiency state.

[0008] S2. Weed fitness evaluation;

[0009] Calculate the fitness value of each weed in the current weed population:

[0010] fitness=η a ×ηpa

[0011] Among them, the fitness value fitness represents the EIRP efficiency of the array-fed reflector antenna corresponding to the feeding power scheme represented by the current weeds;

[0012] η a It indicates the array-fed reflector antenna efficiency corresponding to the feeding power scheme represented by the current weeds, which is calculated as follows:

[0013]

[0014] Among them, G is the gain of the array-fed reflector antenna corresponding to the feeding power scheme represented by the current weeds, and D is the directivity coefficient calculated according to the aperture size of the reflector;

[0015] η pa It represents the average power amplifier efficiency corresponding to the feeding power scheme represented by the current weeds, which is calculated as follows:

[0016]

[0017] Among them, P i is the output power of the power amplifier connected to the i-th array element, η i is the efficiency of the power amplifier connected to the ith array element, and N is the number of array elements of the feed array antenna.

[0018] S3. Weed populations reproduce and spread based on a probabilistic selection mechanism;

[0019] Each weed in the current weed population will serve as a parent weed and produce a number of offspring weeds. The better the fitness value of the parent weed, the more offspring weeds it will produce, and vice versa. The number of offspring weeds produced by each parent weed is determined by the following formula:

[0020]

[0021] Among them, floor(·) means rounding down, F is the fitness value of the current parent weed, and F max and F min are the maximum and minimum fitness values ​​of the parent weeds in the current population, s max and min are the maximum and minimum number of seeds that can be generated, respectively.

[0022] The propagation and diffusion of the weed population is based on a probabilistic selection mechanism, in which the feed power value of each array element in the parent generation of weeds is reversed with a certain probability during the propagation and diffusion process;

[0023] Specifically, a parent weed undergoes the following process when breeding a daughter weed:

[0024]

[0025] in, Represents the nth feature of the current parent weed, represents the nth feature of the offspring weeds, where the nth feature is the feed power of the nth element of the feed array, rand is a random number, Prob I is the probability that the feeding power value of the first generation weed population is reversed during the reproduction and diffusion process, Prob ini and Prob final are the initial and final probabilities, I and I max are the current and maximum evolutionary generations respectively, and w is the nonlinear adjustment factor.

[0026] The resulting offspring weeds together with the parent weeds constitute a new population.

[0027] S4. Weed fitness evaluation;

[0028] According to step S2, the fitness value of the newly generated offspring weeds in the current weed population is calculated.

[0029] S5. Competitive exclusion of weed populations;

[0030] Determine whether the current weed population size exceeds the maximum population size P max If it exceeds, sort all weeds according to their fitness values ​​from high to low, and select the top P from the sorted population. max The weeds are the population that survived this evolution.

[0031] S6. Determine whether the maximum evolutionary number has been reached, output the final solution or return to step S3;

[0032] It is determined whether the evolutionary generation of the weed population has reached the maximum evolutionary generation. If so, the feeding power scheme represented by the weed with the highest fitness value in the current population is output; otherwise, the process returns to step S3 to continue iterative calculation.

[0033] Preferably, in step S3, Prob ini The value range is Prob final The value range is [1 / N, 2 / N].

[0034] The beneficial effects of the present invention are:

[0035] First, the present invention improves the classic invasive weed algorithm. The propagation and diffusion of weed populations is no longer based on a normal distribution mechanism, but on a probability selection mechanism. The improved algorithm can be applied to the rapid optimization of binary variables.

[0036] Second, the feed array feeding power scheme obtained by optimizing the binary invasive weed algorithm proposed in the present invention can maximize the EIRP efficiency of the reflector antenna. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 The figure is a flowchart of the method of the present invention.

[0038] Figure 2 Schematic diagram of the structure of the array-fed reflector antenna in the embodiment.

[0039] Figure 3 This is a typical efficiency curve for a power amplifier.

[0040] Figure 4 Normalized feeding power of the feed array designed for the present invention.

[0041] Figure 5 Normalized feed power of the feed array designed for the conjugate field matching method.

[0042] Figure 6 The figure shows the EIRP efficiency comparison between the present invention and the conjugate field matching method when the array-fed reflector antenna performs beam scanning. DETAILED DESCRIPTION

[0043] In order to better illustrate the embodiments of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The embodiments described in this part are only partial examples of the implementation of the present invention and not all. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0044] This embodiment provides a method for improving the EIRP efficiency of an array-fed reflector antenna. Figure 1 As shown, the following steps are included:

[0045] Step 1: Consider Figure 2 The array-fed reflector antenna shown in the figure has parameters of D=30λ, F=30λ, H=5λ, d=3λ, θ=3°, and λ is the wavelength. The feed array is a 14×14 patch antenna array with an array element spacing of 0.5λ.

[0046] Randomly generate P in the search space ini The weeds form the initial population, where P ini is the initial population size, which is 5. A weed represents a set of feed power schemes for the feed array, in which the feed power only contains 0 / 1 power values, which represent the power amplifier being turned off and on, respectively, and the turned-on power amplifier works at the highest efficiency state. Therefore, each weed is a 0 / 1 vector with a dimension of 196×1.

[0047] Step 2: The product of the array-fed reflector antenna efficiency and the average power amplifier efficiency is used as the fitness value of each weed in the weed population. This fitness value is the EIRP efficiency of the array-fed reflector antenna when the feeding power scheme represented by the current weed is adopted. The feeding phase still adopts the phase obtained by the conjugate field matching method.

[0048] Here, the efficiency of the array-fed reflector antenna is defined as the ratio of the antenna gain to the directivity coefficient; the average power amplifier efficiency is defined as follows:

[0049]

[0050] Among them, P i is the output power of the power amplifier connected to the i-th array element, η i is the efficiency of the power amplifier connected to the i-th array element, which is taken from Figure 3 The typical efficiency curve of the power amplifier is shown; N is the number of feed array elements, which is 196 in this embodiment.

[0051] Step 3: Each weed in the current weed population will serve as a parent weed and produce a number of offspring weeds. The better the fitness value of the parent weed, the more offspring weeds it will produce, and vice versa. The number of offspring weeds produced by each parent weed is determined by the following formula:

[0052]

[0053] Among them, floor(·) means rounding down, F is the fitness value of the current parent weed, and F max and F min are the maximum and minimum fitness values ​​of the parent weeds in the current population, s max and min are the preset maximum and minimum seed numbers respectively. In this embodiment, s max =5,s min =1.

[0054] The propagation and diffusion of weed populations is based on a probabilistic selection mechanism, that is, each feed power value represented by the parent weed is reversed with a certain probability during the propagation and diffusion process; a parent weed undergoes the following process when propagating a child weed:

[0055]

[0056] in, Represents the nth feature of the current parent weed, represents the nth feature of the offspring weeds, where the nth feature represents the feed power of the nth antenna element of the feed array, rand is a random number, Prob IIt represents the probability that the feeding power value of the first generation weed population is reversed during the reproduction and diffusion process, Prob ini and Prob final Denote the initial and final probabilities, I and I respectively max Respectively represent the current and maximum evolution generations, and w is a nonlinear adjustment factor. In this embodiment, Prob ini =0.06, Prob final =0.005, I max =1000,w=3.

[0057] The resulting offspring weeds together with the parent weeds constitute a new population.

[0058] Step 4: Calculate the fitness value of the newly generated offspring weeds in the current weed population. The calculation method of this fitness value is the same as that in step 2.

[0059] Step 5: Determine whether the current weed population size exceeds the maximum population size P max If it exceeds, sort all weeds according to their fitness values ​​from best to worst, and select the top P from the sorted population in turn. max Weeds are the population that finally survives this evolution. max =20.

[0060] Step 6: Determine whether the evolutionary generation of the weed population has reached the maximum evolutionary generation. If so, output the feeding power scheme represented by the weed with the best fitness value in the current population; otherwise, return to step 3 and continue to execute the algorithm.

[0061] Figure 4 The normalized feed power of the feed source array of the array-fed reflector antenna of this embodiment is given when the azimuth plane is scanned to 0°, 1°, 2°, and 3°, where the blank indicates that the power amplifier is turned off.

[0062] Figure 5 The normalized feed power of the feed array of the array-fed reflector antenna designed by the conjugate field matching method is given when the azimuth plane is scanned to 0°, 1°, 2°, and 3°.

[0063] Figure 6 The EIRP efficiency comparison between the present invention and the conjugate field matching method when the array-fed reflector antenna performs beam scanning is given. It can be seen that the feeding power scheme obtained by the method of the present invention can increase the EIRP efficiency of the array-fed reflector antenna from 6% of the conjugate field matching method to 28%, corresponding to a 4.7-fold EIRP increase. This means that under the same signal-to-noise ratio requirement, the present invention can increase the communication or monitoring distance of the array-fed reflector antenna to 2.2 times the original.

Claims

1. A method for improving the EIRP efficiency of an array-fed reflector antenna, characterized in that: The following steps are involved: S1. Randomly initialize the binary weed population; Randomly generate P in the search space ini weeds to form an initial population; among them, P ini is the initial population size, one weed represents a set of feed array power schemes, and the feed power of each array element in the feed array power scheme only contains power values ​​of 0 and 1, which respectively represent that the power amplifier is turned off and on, and the turned-on power amplifier works at the highest efficiency state; S2. Weed fitness evaluation; Calculate the fitness value of each weed in the current weed population: fitness a ×n pa Among them, the fitness value fitness represents the EIRP efficiency of the array-fed reflector antenna corresponding to the feeding power scheme represented by the current weeds, η a represents the array-fed reflector antenna efficiency corresponding to the feeding power scheme represented by the current weeds, η pa represents the average power amplifier efficiency corresponding to the feeding power scheme represented by the current weeds; S3. Weed populations reproduce and spread based on a probabilistic selection mechanism; Each weed in the current weed population will serve as a parent weed and produce several offspring weeds. The better the fitness value of the parent weed, the more offspring weeds it will produce, and vice versa. The propagation and diffusion of the weed population is based on a probabilistic selection mechanism, in which the feed power value of each array element in the parent generation of weeds is reversed with a certain probability during the propagation and diffusion process; Specifically, a parent weed undergoes the following process when breeding a daughter weed: in, Represents the nth feature of the current parent weed, represents the nth feature of the offspring weeds, where the nth feature is the feed power of the nth element of the feed array, rand is a random number, Prob I is the probability that the feeding power value of the first generation weed population is reversed during the reproduction and diffusion process, Prob ini and Prob final are the initial and final probabilities, I and I max are the current and maximum evolution generations respectively, and w is the nonlinear adjustment factor; The resulting offspring weeds and the parent weeds together constitute a new population; S4. Weed fitness evaluation; Calculate the fitness value of the newly generated offspring weeds in the current weed population according to step S2; S5. Competitive exclusion of weed populations; Determine whether the current weed population size exceeds the maximum population size P max If it exceeds, sort all weeds according to their fitness values ​​from high to low, and select the top P from the sorted population. max The weeds are the populations that remain in this evolution; S6. Determine whether the maximum evolutionary number has been reached, output the final solution or return to step S3; It is determined whether the evolutionary generation of the weed population has reached the maximum evolutionary generation. If so, the feeding power scheme represented by the weed with the highest fitness value in the current population is output; otherwise, the process returns to step S3 to continue iterative calculation.

2. A method for improving the EIRP efficiency of an array-fed reflector antenna as claimed in claim 1, characterized in that: In step S2, the array-fed reflector antenna efficiency η corresponding to the feeding power scheme represented by the current weeds a The calculation method is: Among them, G is the gain of the array-fed reflector antenna corresponding to the feeding power scheme represented by the current weeds, and D is the directivity coefficient calculated according to the aperture size of the reflector.

3. A method for improving the EIRP efficiency of an array-fed reflector antenna as claimed in claim 1, characterized in that: In step S2, the average power amplifier efficiency η corresponding to the feeding power scheme represented by the current weeds pa The calculation method is: Among them, P i is the output power of the power amplifier connected to the i-th array element, η i is the efficiency of the power amplifier connected to the ith array element, and N is the number of array elements of the feed array antenna.

4. A method for improving the EIRP efficiency of an array-fed reflector antenna as claimed in claim 1, characterized in that: In step S3, the number of offspring weeds produced by each parent weed is determined by the following formula: Among them, floor(·) means rounding down, F is the fitness value of the current parent weed, and F max and F min are the maximum and minimum fitness values ​​of the parent weeds in the current population, s max and min are the maximum and minimum number of seeds that can be generated, respectively.

5. A method for improving the EIRP efficiency of an array-fed reflector antenna as claimed in claim 1, characterized in that: In step S3, Prob ini The value range is Prob final The value range is [1 / N, 2 / N].

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