CN111060871A - Five-element array positioning method and device based on improved genetic algorithm - Google Patents

Five-element array positioning method and device based on improved genetic algorithm Download PDF

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CN111060871A
CN111060871A CN201911366383.3A CN201911366383A CN111060871A CN 111060871 A CN111060871 A CN 111060871A CN 201911366383 A CN201911366383 A CN 201911366383A CN 111060871 A CN111060871 A CN 111060871A
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尹光
汪大康
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Nanjing Changfeng Space Electronics Technology Co Ltd
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Abstract

The invention discloses a five-element array positioning method and a device based on an improved genetic algorithm, wherein the method comprises the following steps: determining a solving baseline based on the position of the quintuple array receiving antenna, taking the solving baseline as an array element channel, and determining phase difference information between the array element channels; setting the distance from the target array element to each receiving antenna of the quintuple array; constructing a target function for solving the azimuth angle and the pitch angle of the target signal source according to the phase difference information between the array element channels and the set distance from the target array element to each receiving antenna of the quinary array; and solving the target function to obtain the azimuth angle and the pitch angle of the target signal source. The invention realizes a fast and accurate five-element array signal source azimuth pitch angle estimation method.

Description

Five-element array positioning method and device based on improved genetic algorithm
Technical Field
The invention relates to a five-element array positioning method and a five-element array positioning device based on an improved genetic algorithm, and belongs to the technical field of passive positioning.
Background
With the development of electronic information technology and the wide application of mobile communication technology in various fields, people are more and more interested in various information services based on advanced communication technology. In military and civil applications of mobile and wireless communication, direction finding technology and radio positioning are also generally required, for example, the smart antenna technology in mobile communication needs to obtain the orientation of a terminal connected to a base station, seismic source positioning in seismic exploration, interference source positioning in military communication, and the like, and the related technical requirements often require that a system is simple and practical, high in real-time performance and measurement accuracy, and strong in anti-interference capability. Conventional positioning systems and radar direction finding are not adaptable to such applications. In this case, passive direction finding techniques have been rapidly developed.
In civil communication, passive positioning technology is a method for determining the physical position of a radio signal transmitting terminal within a certain radius range by using radio signals. The passive positioning method can provide position information for users in the mobile communication network, and brings great convenience to people. The positioning service provided by the civil communication network has huge application prospect. First, it can serve community utilities such as city traffic guidance, emergency services, mobile terminal theft prevention, vehicle tracking dispatch, etc. Secondly, it can bring huge economic benefits to trades such as car and mobile communication. Compared with the GPS positioning, the radio positioning does not need any change to a huge number of mobile terminals, and a certain number of devices are added to a base station to provide good service for users. Therefore, passive direction finding technology based on array antennas is widely used.
In military affairs, passive direction finding technology is a quite important reconnaissance means, and aims to know the movement and configuration of enemy command centers and troops. The development of radio direction finding technology is greatly accelerated by improving direction finding equipment, particularly airborne equipment, by both parties of the battle. Due to military requirements, direction-finding technologies, direction-finding equipment and the like are well developed. In peace construction period, the passive direction finding technology is widely applied, and is used in astronomy, traffic, weather, disaster relief and environmental protection; for monitoring the whereabouts of animals, both onshore and offshore, in order to protect rare animals; the method is used for checking the porcelain insulator leakage in the high-voltage distribution system. After the 'China No. 7' manned spacecraft reentry capsule launched falls to the ground, the reentry spacecraft capsule continuously launches radio signals, and aerospace scientific research personnel also need to find the reentry spacecraft capsule by using a direction-finding positioning technology.
Passive positioning is also of great importance in emerging fields such as radio identification, cognitive radio and the like. The core content of software radio cognition under a software communication system structure is the description and identification of a space complex radio state, and radio cognition related theory, concept, system structure and implementation technology have important significance on the research and development of a civil communication system and related equipment, and have great influence on the fields of military radio countermeasure, radio reconnaissance and the like. The radio identification is embodied as a vector structure of radio states of an electronic battlefield space, and the mapping relation between the radio state vector and an end user has possible time variation and reconstruction, namely, a communication frequency band and a communication mode can be appointed before communication and can be reconstructed in the communication process. However, for the identification and description of spatially complex radio conditions, the first task is to obtain physical entity information of the radio signal including the direction of the radio frequency beam, i.e. to obtain an accurate direction of arrival.
The rapid development of modern information technology requires more effective calculation to be completed in a shorter time, and the traditional DOA estimation algorithm is large in calculation amount, difficult to realize in real time and poor in adaptation to the actual application environment, so that most of theoretically good algorithms are retained in experimental simulation, and are greatly limited in application in actual engineering.
Since the advent of interferometer direction finding technology, the interferometer direction finding technology has been widely used in the fields of electromagnetic environment monitoring, electronic countermeasure, radar, sonar, navigation, etc. due to its high direction finding sensitivity, high accuracy and high speed. With the advent of digital signal processors, it became possible to achieve high precision real-time direction finding by means of digital signal processors. Currently, for quinary arrays, the commonly used positioning parameter estimation methods mainly include three types: conventional methods, FFT interferometers, correlation interferometry. The conventional method needs to calculate the maximum non-fuzzy phase difference according to the arrangement of the array element baselines, then verifies the phase difference of each baseline one by one, and screens the non-fuzzy azimuth, and the method has the disadvantages of complicated calculation process, long time, low precision, capability of only calculating the azimuth angle and incapability of acting as force for calculating the pitch angle; the FFT interferometer method adopts a space FFT algorithm to calculate a space spectrum of a signal, the method obtains the arrival angle of a target signal source by searching the maximum value of the corresponding angle of the space spectrum, the calculation amount of the method is large, and meanwhile, the method can only calculate a one-dimensional angle and cannot calculate the azimuth angle and the pitch angle at the same time; the correlation interferometry establishes a relational database of the phase difference between the azimuth angle and each base line through system calibration, and determines the true value of the angle by comparing the correlation between the actually measured data and the database data. The method is fastest, can evaluate the direction-finding effect, but has the problems of long working time of early test, large error and fuzzy phase.
The following table shows a group of results of calculating the five-element array positioning error precision by using an FFT interferometer method
TABLE 1FFT interferometer method for analyzing direction-finding performance
Figure BDA0002338538460000041
Figure BDA0002338538460000051
In the table above, the direction-finding performance is simulated by using the FFT interferometer, and the improvement of the signal-to-noise ratio by the correlation accumulation is verified. As can be seen from the above table, the FFT interferometer method has large test errors and needs to accumulate for a long time, and the method can only provide one-dimensional angle calculation, has a narrow application range, and cannot meet the requirements of two-dimensional measurement, real-time performance and high precision of practical problems in practical application.
In summary, although the methods for estimating the angle of arrival of a signal are mature, how to estimate the angle of arrival of the signal quickly and effectively in a complex environment remains a big hotspot and difficulty in the field, and the conventional estimation algorithm cannot be applied to a practical positioning system because of some disadvantages.
Disclosure of Invention
The technical problem to be solved by the invention is that the method for estimating the signal arrival angle in the prior art is mature day by day, but the signal arrival angle cannot be quickly and effectively estimated in a complex environment, and a quick and effective signal arrival angle estimation algorithm based on an improved genetic algorithm is provided.
The invention adopts the following technical scheme.
In one aspect, the invention provides a quintuple array positioning method based on an improved genetic algorithm, which is characterized by comprising the following steps:
determining a solving baseline based on the position of the quintuple array receiving antenna, taking the solving baseline as an array element channel, and determining phase difference information between the array element channels; setting the distance from the target array element to each receiving antenna of the quintuple array;
constructing a target function for solving the azimuth angle and the pitch angle of the target signal source according to the phase difference information between the array element channels and the set distance from the target array element to each receiving antenna of the quinary array;
and solving the target function to obtain the azimuth angle and the pitch angle of the target signal source.
Further, the constructed objective function is as follows:
Figure BDA0002338538460000061
where α is the azimuth and elevation angles of the target signal source to be estimated,
Figure BDA0002338538460000062
representing phase difference information extracted from signals of an ith array element channel and a jth array element channel in the quinary array; subscripts i and j represent the number of corresponding array element channels, the wavelength of working signals of the lambda quinary array detection system, r12＝r1-r2r23＝r2-r3，r34＝r3-r4,r45＝r4-r5,r51＝r5-r1(ii) a Wherein r is1、r2、r3、r4And r5And setting the distance from the target array element to each receiving antenna of the quintuple array.
Further, the air conditioner is provided with a fan,
Figure BDA0002338538460000063
Figure BDA0002338538460000064
Figure BDA0002338538460000065
Figure BDA0002338538460000066
Figure BDA0002338538460000067
wherein (x)i,yi) The position of the antenna number corresponding to the array element is i-1, 2,3,4, 5; r is0To set a distance parameter value.
Still further, a genetic algorithm is adopted to solve the objective function, and the specific method comprises the following steps:
(1) and setting parameters required by solving, including subscript of a reference channel, the maximum genetic algebra, the size of a population, the length of an individual, the probability of a gully, the probability of intersection, the probability of variation and the number of genetic iterations. Initializing a population;
(2) calculating a fitness function value according to the determined fitness function;
(3) selecting, crossing and mutating;
(4) if the genetic calculation times are less than the given times, switching to the step (2), and calculating a new optimal population until the specified calculation times are met; turning to the step (5);
(4) selecting the optimal output to obtain the azimuth angle and pitch angle information of the target signal source to be solved as follows:
azi＝α×180/π
pit＝β×180/π
wherein azi is the original azimuth angle of the target signal; and pit is the pitch angle of the target signal source.
Still further, step (3) and step (4) are preceded by a non-linear optimization step: and (3) taking the population corresponding to the optimal fitness obtained in the step (2) as an iteration initial value of a nonlinear estimation function fmincon, searching an optimal value near a local next-to-optimal value to obtain a global optimal point as an optimal value of parameter estimation, and inserting the obtained optimal value into the original population to replace the original population with the worst fitness.
In another aspect, the present invention provides a quintuple array positioning apparatus based on an improved genetic algorithm, comprising:
the system comprises a system initialization module, an objective function construction module and an objective function solving module;
the system initialization module is used for determining a solving baseline based on the position of the quintuple array receiving antenna, using the solving baseline as an array element channel and determining phase difference information between the array element channels; setting the distance from the target array element to each receiving antenna of the quintuple array;
the target function construction module is used for constructing a target function for solving the azimuth angle and the pitch angle of the target signal source according to the phase difference information between the array element channels and the set distance from the target array element to each receiving antenna of the quinary array;
and the objective function solving module is used for solving the objective function to obtain the azimuth angle and the pitch angle of the target signal source.
The beneficial technical effects are as follows:
the invention provides a quinary array high-precision positioning algorithm based on an improved genetic algorithm based on the requirements of instantaneity and high precision of the quinary array positioning algorithm, and the azimuth pitch angle of a target position in the quinary array positioning problem is obtained by solving based on an established target function; the method is used for calculating the azimuth pitch angle of the target position in the quinary array positioning problem, has good real-time performance and higher precision, and can effectively solve the existing problems.
The method combines the advantages of the GA algorithm and the nonlinear solving algorithm, adopts the idea that the nonlinear solving algorithm accelerates the GA algorithm convergence calculation, and quickly and accurately solves to obtain the azimuth pitch angle of the target position in the quinary array positioning problem;
simulation results and experimental results show that by adopting the estimation algorithm, the solving time is greatly shortened, the instability of the estimation result is improved, and the optimal estimation value can be obtained by each estimation.
Drawings
FIG. 1 is a schematic diagram of a quintuple array receiving antenna according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of an objective function solving method of a five-tuple array positioning algorithm according to an embodiment of the present invention.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
The contents and effects of the present invention will be described in detail below with reference to the accompanying drawings.
The invention constructs a positioning angle estimation method with fast calculation and accuracy, and solves the problem of solving the problem of fast and accurately extracting the azimuth pitch angle of a target signal source from the phase difference of quintuple array echo data. The method combines the advantages of the GA algorithm and the nonlinear solving algorithm, adopts the idea that the nonlinear solving algorithm accelerates the GA algorithm convergence calculation, and quickly and accurately solves the azimuth pitch angle of the target position in the quinary array positioning problem.
The embodiment provides a quintuple array positioning method based on an improved genetic algorithm, which comprises the following steps
(1) Constructing solution objective function
And constructing an objective function according to the baseline selection and algorithm of the five-element array positioning. The position of the quinary matrix is shown in figure 1.
And selecting a base line combination according to the position of the quinary array to construct an objective function. In the invention, the selected quinary matrix solving base lines are the base line 12, the base line 23, the base line 34, the base line 45 and the base line 51, and in the using process, a user can also set other solving base lines according to the problem solving requirement.
According to the solution baseline, the target model is constructed as follows:
Figure BDA0002338538460000091
α is the target signal source to be estimatedThe azimuth angle and the pitch angle of the rotor,
Figure BDA0002338538460000101
phase difference information extracted from signals of a first array element channel and a second array element channel in the quintuple array,
Figure BDA0002338538460000102
and phase difference information extracted from corresponding array element channel signals is also included, and subscripts represent the number of corresponding array element channels.
The assumed distances from the target array element to each receiving antenna of the quintuple array are as follows:
Figure BDA0002338538460000103
Figure BDA0002338538460000104
Figure BDA0002338538460000105
Figure BDA0002338538460000106
Figure BDA0002338538460000107
in the formula (x)i,yi) For the position of the corresponding array element receiving antenna number, r0The precise distance from the source of the guided target to the quinary array is not required for a hypothetical distance that satisfies the far field condition, and in the present invention r is05000 m α is the azimuth angle and the pitch angle of the target signal source to be solved to reach the quintuple array12＝r1-r2The remaining parameters are defined the same.
According to the method, the target function is actually established according to the problem, and the phase difference is converted into a cosine function mode in consideration of the fact that the phase has ambiguity with a period of 2 pi, so that the influence of ambiguity is avoided.
The invention adopts an improved genetic algorithm to solve an objective function, and a solving flow schematic diagram is shown in figure 2 and comprises the following steps:
(2) solving parameter settings
Parameters required by the solution are set, and the parameters mainly comprise the following parameters: subscript of reference channel, algebra of maximum inheritance, size of population, length of individual, probability of gully, probability of cross, probability of mutation, and number of genetic iterations.
(3) Initializing a population
Genetic algorithms perform iterative searches within a given initialization population. In the invention, a binary coding method is adopted, a generating population generates the value of each chromosome by adopting a method for generating random numbers, and the initialized population is converted into decimal numbers by a coding function.
(4) Fitness calculation
And writing a fitness calculation function. The evaluation function is determined according to the optimization objective of the problem. In the invention, because the solved problem is the parameter corresponding to the minimum value of the objective function, the objective function is used as a fitness calculation function, the smaller the value of the objective function is, the better the fitness is, and the fitness of each population is ranked through the ranking function.
(5) Selection, crossing, mutation
And selecting excellent individuals from the old population with a given gully probability to form a new population so as to breed to obtain next generation individuals, wherein the selected probability of the individuals is obtained by the fitness, and the higher the fitness is, the higher the selected probability is.
The selection operation adopts a roulette selection algorithm, and the probability of the individual being selected is calculated by the following formula
Figure BDA0002338538460000111
Wherein FjThe fitness of the individual j is obtained by the calculation of the previous step, and N is the number of population individuals.
The crossover operation is a random selection of two individuals from the population, with each chromosome crossing or not being determined by a given crossover probability. The process is as follows: generating a random number between 0 and 1 for each chromosome, if the value is less than the specified cross probability, crossing the selected chromosomes, otherwise, directly copying the chromosomes into a new population without participating in crossing, and performing the crossing operation as shown in the following
Figure BDA0002338538460000121
Every two individuals are crossed according to the cross probability, and two new filial generations are generated after respective partial gene exchange. The specific operation is to randomly generate an effective mating position, and chromosome exchange is carried out on all genes positioned after the mating position.
And the mutation operation is to determine whether each gene of the chromosomes in the crossed new population is mutated according to the mutation probability. The process is as follows: generating random numbers between 0 and 1, and if the value is less than the designated mutation probability, mutating the selected gene to generate new chromosomes, wherein the mutation operation is as follows:
Figure BDA0002338538460000122
after the operations are completed, the fitness of the generated new population is recalculated, the generated new population is inserted into the old population according to the fitness, and the optimal chromosome is updated.
And calculating the fitness of the individuals in the newly generated population, and recombining the new individuals and the old population according to the fitness to obtain a new population.
(6) Non-linear optimization
If the generation number of the inheritance is integral multiple of 10, such as 10 generation, 20 generation and the like, the nonlinear optimization calculation is carried out once. And (3) taking the population corresponding to the optimal fitness obtained in the step (5) as an iteration initial value of a nonlinear estimation function fmincon, searching an optimal value near a local next-to-optimal value to obtain a global optimal point as an optimal value of parameter estimation, and inserting the obtained optimal value into the original population to replace the original population with the worst fitness. fmincon is a matlab function used to solve the nonlinear multivariate function minimum, and the optimization toolset provides fmincon functions for solving constrained optimization problems.
(7) Determination of termination condition
And (4) if the genetic calculation times are less than the given times, switching to the step (4) to calculate a new optimal population until the specified calculation times are met. And (7) switching to the step.
(8) Selecting an optimal output
And transforming the optimal value output by genetic calculation, wherein the output angle is in radian as a unit, and the optimal value is converted into angle as a unit through the following formula to be output, so as to obtain the azimuth angle and pitch angle information of the signal source to be solved:
azi＝α×180/π
pit＝β×180/π。
wherein azi is the original azimuth angle of the target signal; and pit is the pitch angle of the target signal source.
In the simulation experiment of this embodiment, the azimuth angle and pitch angle information of a plurality of groups of signal sources with different arrival angles are calculated, the related set angles are given in the error analysis table, and the calculation parameters of other genetic algorithms are as follows:
the population size NIND is 100;
genetic algebra MAXGEN is 50;
the crossover probability pcross is 0.7;
variation probability pmutation is 0.01;
signal frequency f0 ═ 1000e6 Hz;
diameter of quinary matrix: d is 1 meter;
solving an angle setting range bound ═ 0-pi; 0 to pi/2 ]; wherein the corresponding azimuth angle range is 0-180 degrees, and the pitching angle range is 0-90 degrees.
The specific set angle and the experimentally calculated angle are shown in table 1 below:
table 1 table for comparing the angle specifically set in the embodiment with the angle calculated in the experiment
Figure BDA0002338538460000141
Figure BDA0002338538460000151
Figure BDA0002338538460000161
Computer configuration for experimental parameter calculation
A processor: intel (R) Xeon (R) CPU E3-1270V 2@3.50GHz
Install memory (RAM): 16.0GB
The system type is as follows: 64-bit operating system
The simulation result and the experimental result show that the estimation algorithm of the invention has high calculation precision and short calculation time, can obtain accurate results within a few tenths of a second, and effectively solves the calculation precision requirement and the real-time requirement.
The invention combines the advantages and the disadvantages of the GA algorithm and the traditional nonlinear estimation algorithm, develops a fast and accurate five-element array signal source azimuth pitch angle estimation method, overcomes the defects of weak local optimization capability of the GA and weak global optimization capability of the traditional nonlinear estimation algorithm, fully utilizes the global optimization capability of the GA and the local optimization capability of the traditional nonlinear estimation algorithm, considers the characteristic of the randomness of the GA, adopts the nonlinear solving algorithm to accelerate the concept of the convergence calculation of the GA algorithm, and fast and accurately solves to obtain the azimuth pitch angle of the target position in the five-element array positioning problem.
The method is used for calculating the azimuth pitch angle of the target position in the quinary array positioning problem, has good real-time performance and higher precision, and can effectively solve the existing problems. Simulation results and experimental results show that by adopting the estimation algorithm, the solving time is greatly shortened, the instability of the estimation result is improved, and the optimal estimation value can be obtained by each estimation.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (6)

1. A five-element array positioning method based on an improved genetic algorithm is characterized by comprising the following steps:
determining a solving baseline based on the position of the quintuple array receiving antenna, taking the solving baseline as an array element channel, and determining phase difference information between the array element channels; setting the distance from the target array element to each receiving antenna of the quintuple array;
constructing a target function for solving the azimuth angle and the pitch angle of the target signal source according to the phase difference information between the array element channels and the set distance from the target array element to each receiving antenna of the quinary array;
and solving the target function to obtain the azimuth angle and the pitch angle of the target signal source.
2. The quintuple array positioning method based on the improved genetic algorithm according to claim 1, wherein the constructed objective function is as follows:
Figure FDA0002338538450000011
where α is the azimuth and elevation angles of the target signal source to be estimated,
Figure FDA0002338538450000012
representing phase difference information extracted from signals of an ith array element channel and a jth array element channel in the quinary array; subscripts i and j represent the number of corresponding array element channels, the wavelength of working signals of the lambda quinary array detection system, r12＝r1-r2，r23＝r2-r3，r34＝r3-r4,r45＝r4-r5,r51＝r5-r1(ii) a Wherein r is1、r2、r3、r4And r5And setting the distance from the target array element to each receiving antenna of the quintuple array.
3. The quintuple array mapping method based on the improved genetic algorithm according to claim 2,
Figure FDA0002338538450000021
Figure FDA0002338538450000022
Figure FDA0002338538450000023
Figure FDA0002338538450000024
Figure FDA0002338538450000025
wherein (x)i,yi) The position of the antenna number corresponding to the array element is i-1, 2,3,4, 5; r is0To set a distance parameter value.
4. The quinary array positioning method based on the improved genetic algorithm as claimed in claim 2, wherein the genetic algorithm is adopted to solve the objective function, and the specific method comprises the following steps:
(1) setting parameters required by solving, including subscript of a reference channel, the number of generations of the maximum inheritance, the size of a population, the length of an individual, the probability of generation ditches, the probability of intersection, the probability of variation and the number of times of genetic iteration, and initializing the population;
(2) calculating a fitness function value according to the determined fitness function;
(3) selecting, crossing and mutating;
(4) if the genetic calculation times are less than the given times, switching to the step (2), and calculating a new optimal population until the specified calculation times are met; turning to the step (5);
(4) selecting the optimal output to obtain the azimuth angle and pitch angle information of the target signal source to be solved as follows:
azi＝α×180/π
pit＝β×180/π
wherein azi is the original azimuth angle of the target signal; and pit is the pitch angle of the target signal source.
5. The quintuple array positioning method based on the improved genetic algorithm according to claim 4, wherein the steps (3) and (4) are preceded by a nonlinear optimization step: and (3) taking the population corresponding to the optimal fitness obtained in the step (2) as an iteration initial value of a nonlinear estimation function fmincon, searching an optimal value near a local next-to-optimal value to obtain a global optimal point as an optimal value of parameter estimation, and inserting the obtained optimal value into the original population to replace the original population with the worst fitness.
6. A quinary array positioning device based on improved genetic algorithm is characterized by comprising:
the system comprises a system initialization module, an objective function construction module and an objective function solving module;
the system initialization module is used for determining a solving baseline based on the position of the quintuple array receiving antenna, using the solving baseline as an array element channel and determining phase difference information between the array element channels; setting the distance from the target array element to each receiving antenna of the quintuple array;
the target function construction module is used for constructing a target function for solving the azimuth angle and the pitch angle of the target signal source according to the phase difference information between the array element channels and the set distance from the target array element to each receiving antenna of the quinary array;
and the objective function solving module is used for solving the objective function to obtain the azimuth angle and the pitch angle of the target signal source.
CN201911366383.3A 2019-12-26 2019-12-26 Five-element array positioning method and device based on improved genetic algorithm Pending CN111060871A (en)

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