Wave beam space direction finding method under impact noise environment

A technology of shock noise and beam, applied in the field of beam space direction finding, which can solve the problems of complex calculation, local convergence, quantization error, etc.

Pending Publication Date: 2019-04-23
CHINA ELECTRONIC TECH GRP CORP NO 38 RES INST
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the traditional rotation projection transformation method of the maximum likelihood direction finding equation not only has quantization errors, but also has the disadvantages of complex calculation and easy to fall into local convergence

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Wave beam space direction finding method under impact noise environment
  • Wave beam space direction finding method under impact noise environment
  • Wave beam space direction finding method under impact noise environment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0088] Such as figure 1 as shown, figure 1 It is a flow chart of the beam space direction finding method under the impact noise environment of the present invention, and the beam space direction finding method under the impact noise environment of the present invention specifically includes steps;

[0089] S1. Acquire signal sampling data, perform beam space processing on the signal sampling data, and obtain an objective equation of beam space maximum likelihood estimation;

[0090] S2, initialize the dolphin group and initialize the belief space;

[0091] S3, calculate the fitness, and record the global optimal position of the dolphin group;

[0092] S4, divide the group of dolphins into different teams of equal size, each dolphin in the team obtains the temporary position of the individual dolphin according to information sharing; calculate the fitness according to the temporary position of the individual dolphin, and update the local optimum of each dolphin Location;

...

Embodiment 2

[0101] Specifically, in the step S1, assuming that N far-field narrowband signals are incident on a uniform linear array with M array elements, the k-th snapshot data is written in vector form; the k-th snapshot The expression of the data is:

[0102]

[0103] Among them, E(k) is the snapshot data vector, is the impact noise data vector, S(k) is the space signal vector, A(θ) is the M×N dimensional array flow pattern matrix; θ is the arrival angle vector.

[0104] The arrival angle vector θ=[θ 1 , θ 2 ,...,θ N ],

[0105] Among them, θ i is the angle between the incident direction of the i-th signal and the normal line of the line array, i=1, 2,...,N.

[0106] The expression of the M * N-dimensional array flow pattern matrix A (θ) is:

[0107] A(θ)=[a 1 (ω 0 ), a 2 (ω 0 ),...,a N (ω 0 )],

[0108] Among them, the steering vector of the i-th signal is:

[0109]

[0110] Among them, τ li Indicates the time delay when the i-th signal arrives at the l-th arra...

Embodiment 3

[0170] The method to be compared is the maximum likelihood direction finding method based on the particle swarm algorithm in the prior art. In the direction finding system, the distance between array elements is 1 / 2 wavelength, the number of antennas M=8, the number of beams B=4, the number of information sources N=2, and the number of snapshot samples K=100. The population size of the particle swarm optimization algorithm is the same as that of the cultural dolphin swarm, the number of termination iterations is set to be twice that of the cultural dolphin swarm, and other parameters are the same as those of the classical particle swarm optimization algorithm. The simulation parameters of the designed culture-based dolphin group are: z max =60, η=0.06, c 1 =c 2 = 2,

[0171] figure 2 In , two independent signal sources are injected from {-5°, 5°} directions, the characteristic index is 1.7, the generalized signal-to-noise ratio is 10dB, and the number of Monte Carlo...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a wave beam space direction finding method under an impact noise environment. The wave beam space direction finding method comprises the steps: signal sampling data are obtained and subjected to wave beam space processing, and a target equation of maximum likelihood estimation of a wave beam space is obtained; a dolphin group is initialized, and a belief space is initialized; the adaptability degree is calculated, and the global optimal position of the dolphin group is recorded; the dolphin group is divided into different equal-scale teams, and each dolphin in the teamsobtains the temporary position according to information sharing; the temporary adaptability degree is calculated, the local optimal position of each dolphin is updated; the positions of the dolphinsare updated according to a cultural mechanism; the adaptability degree is calculated, the local optimal position of each dolphin is updated, the global optimal position of the dolphin group is updated, and according to part of the local optimal positions, the belief space is updated; and whether the maximum number of iteration times is reached or not is judged, and the direction finding result isobtained and output. Coherent information sources are subjected to effective direction finding under the impact noise environment, and the advantages of high convergence speed and high convergence accuracy are achieved.

Description

technical field [0001] The invention relates to the field of array signal processing, in particular to a beam space direction finding method in an impact noise environment. Background technique [0002] Direction finding is an important research direction in the field of array signal processing, which has attracted the attention of many researchers. Beam space processing technology can synthesize a certain number of beam channels as data receiving channels, and the spatial spectrum estimation method of beam space has the advantages of reducing the amount of calculation, improving robustness and reducing the complexity of the system, which has important research significance. However, the existing eigen-decomposition beam space direction finding methods cannot directly estimate the coherent sources effectively without special processing because the steering vectors of some coherent sources are not completely orthogonal to the noise subspace. Direction-of-arrival estimation c...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G01S3/12
CPCG01S3/12
Inventor 杜亚男李武查月波
Owner CHINA ELECTRONIC TECH GRP CORP NO 38 RES INST
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products