CN114580159A - Deep space measurement and control antenna array expandable scale layout optimization design method - Google Patents

Deep space measurement and control antenna array expandable scale layout optimization design method Download PDF

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CN114580159A
CN114580159A CN202210169334.6A CN202210169334A CN114580159A CN 114580159 A CN114580159 A CN 114580159A CN 202210169334 A CN202210169334 A CN 202210169334A CN 114580159 A CN114580159 A CN 114580159A
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antenna array
antenna
antennas
layout
iteration
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夏双志
郑巧娜
耿虎军
张旭旺
杨伟军
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CETC 54 Research Institute
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    • G06F30/20—Design optimisation, verification or simulation
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01Q—ANTENNAS, i.e. RADIO AERIALS
    • H01Q21/00—Antenna arrays or systems
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Abstract

The invention relates to a layout optimization design method for an expandable scale of a deep space measurement and control antenna array, which adopts a step-by-step iteration intelligent optimization algorithm aiming at a deep space target detection layout constraint condition, wherein the position of an antenna to be added needs to be optimized one by one in each iteration until an optimization function tends to be stable. The invention realizes the array scale expansion and the function improvement by adding the antenna on the basis of the original array. Compared with the traditional antenna array optimization design method, the method has the characteristic of expandability, is more flexible in array arrangement, and can be more suitable for the antenna array layout constraint conditions required by actual engineering.

Description

Deep space measurement and control antenna array expandable scale layout optimization design method
Technical Field
The invention relates to the field of deep space target measurement and control, in particular to an extensible scale layout optimization design method for a deep space measurement and control antenna array.
Background
The antenna array technology is gradually developed along with the deep exploration of outer space by human beings, the existing large antenna technology reaches the performance limit, the equivalent aperture of the antenna can be improved through the antenna array, the receiving performance exceeds the existing maximum aperture antenna, and a path is provided for receiving signals with extremely low signal-to-noise ratio. The antenna array has a stable and scientific working mode, is more reliable and flexible to maintain, and saves the construction cost of ground equipment. As a flexible technical means for supporting deep space exploration, the antenna array technology has important significance for further developing deep space exploration.
Under the condition that the radiation power, the antenna gain and the number of antennas of a single antenna are determined, the far-field combined power gain is improved to the maximum extent, the ground layout of the antenna array is reasonably designed, wherein in the aspect of the expandability of the array, due to technical conditions and actual requirements, the number of array elements in the initial construction stage of the antenna array system is small, and the number of antennas is increased along with the increase of tasks. Most of the existing antenna array optimization is based on the fixed number of antennas, and the layout is not flexible enough. Therefore, when the number of the antennas is changed, the layout optimization algorithm is still based on all the antennas, the calculation amount is large, the solution efficiency is low, and the actual requirements cannot be better met.
Disclosure of Invention
The invention aims to avoid the defects in the background technology and provides a scalable design method for the deep space measurement and control antenna array scale. The invention comprehensively considers the constraint condition of the deep space measurement and control antenna array layout, increases the number of antennas on the basis of the original array, utilizes the step-by-step iterative intelligent optimization algorithm to realize the array scale expansion and improve the function, and can better adapt to the actual engineering requirements.
The purpose of the invention is realized as follows:
a deep space measurement and control antenna array expandable scale layout optimization design method comprises the following steps:
randomly generating an antenna array layout, wherein the antenna array comprises N antennas, the antenna aperture is D, and the position of the nth antenna is Pn＝(xn,yn) N is 1,2, N, the antenna array remains fixed and is marked as CN＝{P1,P2...PN}；
Determining the number of antennas to be increased:
Figure BDA0003516862540000021
in the formula, M is the number of antennas to be increased, and W is the equivalent aperture of the expanded antenna array;
setting an optimization function:
Figure BDA0003516862540000022
in the formula, F represents a score value of a deep space measurement and control antenna array directional diagram, P is 1, 2. w is aspRepresenting the weight, SPLR, of the p-th side lobepDenotes the ratio of the amplitude of the p-th side lobe to the amplitude of the main lobe, ΩspThe size of a solid angle corresponding to the beam range of the p < th > sidelobe 3dB is shown;
and fourthly, specifying constraint conditions: f (P)i,Pj)＝f1(Pi,Pj)·f2(Pi,Pj)·f3(Pi,Pj)·f4(Pi,Pj)
Wherein, f (P)i,Pj) Overall decision function, f, representing constraints1(Pi,Pj),f2(Pi,Pj),f3(Pi,Pj),f4(Pi,Pj) Respectively representing four constraint functions of antenna shielding, interference angle measurement, field deployment and compact layout; if the antenna array satisfies the constraint condition, f (P)i,Pj) If the antenna array does not satisfy the constraint condition, f (P) is defined as 1i,Pj)＝0；
Original antenna array CNKeeping the same, randomly distributing M antennas on the ground, wherein the antenna position meets the constraint condition, and the position of the mth antenna is
Figure BDA0003516862540000023
M1, 2.. M, thus constituting an antenna array after the initial expansion scale
Figure BDA0003516862540000031
Setting a threshold epsilon as a condition of iterative convergence;
sixthly, the positions of the M antennas are Q after the scale is expandedmM1, 2.., M, the optimal layout of the antenna array is CN+M(ii) a Starting iteration, and optimizing the positions of the M antennas one by one in each iteration; at the beginning, order
Figure BDA0003516862540000032
M1, 2, M, iteration k 1;
seventhly, in the kth iteration, when the position of the mth antenna is optimized, the positions of the rest M-1 antennas are fixed and unchanged
Figure BDA0003516862540000033
Randomly generating a series of positions in an area with radius r as a center, judging whether a constraint condition is met or not when generating a position, reserving if the constraint condition is met, and discarding if the constraint condition is not met until 1000 positions meeting the constraint condition are generated and recorded as
Figure BDA0003516862540000034
Eight calculates 1000 antenna array respectively
Figure BDA0003516862540000035
1, 2.., 1000, which corresponds to the maximum of the optimization function F
Figure BDA0003516862540000036
The optimal position of the current iteration of the mth antenna is recorded as
Figure BDA0003516862540000037
Ninthly, repeating the step (c) and the step (b) until the M antennas are optimized to obtain the positions of the M antennas; optimizing function at this time
Figure BDA0003516862540000038
Is marked as
Figure BDA0003516862540000039
The optimal layout for updating the extended-scale post-antenna array is
Figure BDA00035168625400000310
C, c +1, repeating the steps c to c until the optimization function is stable, and stopping iteration, where K is K, i.e.,
Figure BDA00035168625400000311
taking the result of the Kth iteration as the final result of the layout optimization of the expandable scale of the deep space measurement and control antenna array, wherein the optimal layout is
Figure BDA00035168625400000312
Figure BDA00035168625400000313
And finally, finishing the expandable scale layout optimization design method of the deep space measurement and control antenna array.
Further, the threshold ε is 10-3The radius r is 100 m.
Compared with the background technology, the invention has the following advantages:
1. the invention increases the number of antennas on the basis of the original array, and realizes the array scale expansion by utilizing a gradual iterative intelligent optimization algorithm.
2. The invention gives consideration to the layout constraint condition of the deep space measurement and control antenna array, can be suitable for different requirements in actual detection and improves the function.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings:
referring to fig. 1, a deep space measurement and control antenna array scalable scale layout optimization design method mainly includes the following steps:
randomly generating an antenna array layout, wherein the antenna array comprises N antennas, the antenna aperture is D, and the position of the nth antenna is Pn＝(xn,yn) N, the antenna array remains fixed, denoted as CN＝{P1,P2...PN}；
Determining the number of antennas to be increased:
Figure BDA0003516862540000041
in the formula, M is the number of antennas to be increased, and W is the equivalent aperture of the expanded antenna array;
setting an optimization function:
Figure BDA0003516862540000042
in the formula, F represents a score value of a deep space measurement and control antenna array directional diagram, P is 1, 2. w is aspRepresenting the weight, SPLR, of the p-th side lobepRepresents the ratio of the amplitude of the p-th sidelobe to the amplitude of the main lobe, ΩspThe size of a solid angle corresponding to the beam range of the p < th > sidelobe 3dB is shown;
and fourthly, specifying constraint conditions: f (P)i,Pj)＝f1(Pi,Pj)·f2(Pi,Pj)·f3(Pi,Pj)·f4(Pi,Pj)
Wherein, f (P)i,Pj) Overall decision function, f, representing constraints1(Pi,Pj),f2(Pi,Pj),f3(Pi,Pj),f4(Pi,Pj) Respectively representing four constraint functions of antenna shielding, interference angle measurement, field deployment and compact layout; if the antenna array satisfies the constraint condition, f (P)i,Pj) If the antenna array does not satisfy the constraint condition, f (P) is defined as 1i,Pj)＝0；
Original antenna array CNKeeping the same, randomly distributing M antennas on the ground, wherein the antenna position meets the constraint condition, and the position of the mth antenna is
Figure BDA0003516862540000051
M1, 2.. M, thus constituting an antenna array after the initial expansion scale
Figure BDA0003516862540000052
Setting a threshold epsilon as a condition for iterative convergence, wherein the threshold epsilon can be 10-3；
Sixthly, the positions of the M antennas are Q after the scale is expandedmM is 1,2, M, the antenna array is optimally arranged as CN+M(ii) a Starting iteration, and optimizing the positions of the M antennas one by one in each iteration; at the beginning, order
Figure BDA0003516862540000053
M1, 2, M, the number of iterations k 1;
seventhly, in the kth iteration, when the position of the mth antenna is optimized, the positions of the rest M-1 antennas are fixed and unchanged
Figure BDA0003516862540000054
As a center, randomly generating a series of positions in an area with radius r, judging whether a constraint condition is met or not when generating a position, reserving the position if the constraint condition is met, and discarding the position if the constraint condition is not met until generating 1000 positions meeting the constraint condition, and recording the positions as
Figure BDA0003516862540000055
The radius r can be 100 m;
respectively countingCalculating 1000 antenna array
Figure BDA0003516862540000056
1, 2.., 1000, which corresponds to the maximum of the optimization function F
Figure BDA0003516862540000057
The optimal position of the current iteration of the mth antenna is recorded as
Figure BDA0003516862540000058
Ninthly, repeating the step (c) and the step (b) until the M antennas are optimized to obtain the positions of the M antennas; optimizing function at this time
Figure BDA0003516862540000059
Is marked as
Figure BDA00035168625400000510
The optimal layout for updating the extended-scale post-antenna array is
Figure BDA0003516862540000061
C, c +1, repeating the steps c to c until the optimization function is stable, and stopping iteration, where K is K, i.e.,
Figure BDA0003516862540000062
taking the result of the Kth iteration as the final result of the layout optimization of the expandable scale of the deep space measurement and control antenna array, wherein the optimal layout is
Figure BDA0003516862540000063
Figure BDA0003516862540000064
And finally, finishing the expandable scale layout optimization design method of the deep space measurement and control antenna array.
Through the specific implementation of the invention, the method fully utilizes the information of the original antenna array, adopts a step-by-step iterative intelligent optimization algorithm, and can support the upgrading of the array scale by simply adding antennas on the basis of the prior antenna array layout.

Claims (2)

1. A deep space measurement and control antenna array expandable scale layout optimization design method is characterized by comprising the following steps:
firstly, randomly generating an antenna array layout, wherein the antenna array comprises N antennas, the aperture of each antenna is D, and the position of the nth antenna is Pn＝(xn,yn) N, the antenna array remains fixed, denoted as CN＝{P1,P2...PN}；
Determining the number of antennas to be increased:
Figure FDA0003516862530000011
in the formula, M is the number of the antennas to be increased, and W is the equivalent aperture of the antenna array after expansion;
setting an optimization function:
Figure FDA0003516862530000012
in the formula, F represents a score value of a deep space measurement and control antenna array directional diagram, P is 1, 2. w is aspWeight, SPLR, representing the p-th sidelobepDenotes the ratio of the amplitude of the p-th side lobe to the amplitude of the main lobe, ΩspThe size of a solid angle corresponding to the p < th > sidelobe 3dB beam range is shown;
and fourthly, specifying constraint conditions: f (P)i,Pj)＝f1(Pi,Pj)·f2(Pi,Pj)·f3(Pi,Pj)·f4(Pi,Pj)
Wherein, f (P)i,Pj) Overall decision function representing constraints, f1(Pi,Pj),f2(Pi,Pj),f3(Pi,Pj),f4(Pi,Pj) Respectively representing four constraint functions of antenna shielding, interference angle measurement, field deployment and compact layout; if the antenna array satisfies the constraint condition, f (P)i,Pj) If the antenna array does not satisfy the constraint condition, f (P) is defined as 1i,Pj)＝0；
Original antenna array CNKeeping unchanged, randomly laying M antennas on the ground, wherein the antenna position meets the constraint condition, and the position of the mth antenna is
Figure FDA0003516862530000013
Thus, the antenna array after the initial expansion scale is formed
Figure FDA0003516862530000014
Setting a threshold epsilon as a condition of iterative convergence;
sixthly, the positions of the M antennas are Q after the scale is expandedmM1, 2.., M, the optimal layout of the antenna array is CN+M(ii) a Starting iteration, and optimizing the positions of the M antennas one by one in each iteration; at the beginning, order
Figure FDA0003516862530000021
The iteration number k is 1;
seventhly, in the kth iteration, when the position of the mth antenna is optimized, the positions of the rest M-1 antennas are fixed and unchanged
Figure FDA0003516862530000022
As a center, randomly generating a series of positions in an area with radius r, judging whether a constraint condition is met or not when generating a position, reserving the position if the constraint condition is met, and discarding the position if the constraint condition is not met until generating 1000 positions meeting the constraint condition, and recording the positions as
Figure FDA0003516862530000023
Respectively calculating 1000 antenna array
Figure FDA0003516862530000024
1, 2.., 1000, which corresponds to the maximum of the optimization function F
Figure FDA0003516862530000025
The optimal position of the current iteration of the mth antenna is recorded as
Figure FDA0003516862530000026
Ninthly, repeating the step (c) and the step (b) until the M antennas are optimized to obtain the positions of the M antennas; optimizing function at this time
Figure FDA0003516862530000027
Is marked as
Figure FDA0003516862530000028
The optimal layout for updating the extended-scale post-antenna array is
Figure FDA0003516862530000029
C, c +1, repeating the steps c to c until the optimization function is stable, and stopping iteration, where K is K, i.e.,
Figure FDA00035168625300000210
taking the result of the K iteration as the final result of the layout optimization of the scalable scale of the deep space measurement and control antenna array, wherein the optimal layout is
Figure FDA00035168625300000211
Figure FDA00035168625300000212
And finally, finishing the expandable scale layout optimization design method of the deep space measurement and control antenna array.
2. The method of claim 1, wherein the threshold epsilon is 10-3The radius r is 100 m.
CN202210169334.6A 2022-02-23 2022-02-23 Deep space measurement and control antenna array expandable scale layout optimization design method Pending CN114580159A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116192222A (en) * 2023-04-27 2023-05-30 中国西安卫星测控中心 Resource scheduling method and device for antenna array demand and computer equipment

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116192222A (en) * 2023-04-27 2023-05-30 中国西安卫星测控中心 Resource scheduling method and device for antenna array demand and computer equipment
CN116192222B (en) * 2023-04-27 2023-08-29 中国西安卫星测控中心 Resource scheduling method and device for antenna array demand and computer equipment

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