Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Distributed source center direction-of-arrival estimation method based on Bayesian compressed perception

A technology of direction of arrival estimation and Bayesian compression, which is applied in directions such as radio wave director components and direction finders using radio waves, and can solve the problem of few estimation methods.

Inactive Publication Date: 2015-10-14
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF2 Cites 37 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, there are few methods for applying compressive sensing methods to distributed source-centered DOA estimation.

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
  • Distributed source center direction-of-arrival estimation method based on Bayesian compressed perception
  • Distributed source center direction-of-arrival estimation method based on Bayesian compressed perception
  • Distributed source center direction-of-arrival estimation method based on Bayesian compressed perception

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0059] according to figure 1 , the steps of the estimation method of distributed source center DOA based on Bayesian compressed sensing of the present invention are as follows:

[0060] Step 1. Set up the antenna array as figure 2 As shown, the array is an M=8-element uniform linear array set on the x-axis, and the distance between each array element and the array is the same as d, considering that K far-field narrowband signal sources are incident on the array, where , K=2, d=λ / 2, λ is the wavelength of the signal carrier;

[0061] Step 2. Since the signal source propagates in a multipath environment, the data vector x(t) received by the array can be expressed as:

[0062]

[0063] in, θ k is the central DOA of the incident source, The value range of is 0°~10°, and obey Gaussian distribution, β kl (t) is a random complex gain that obeys a Gaussian distribution, L k =200 is the total number of multipath signals of the kth distributed source, s k (t) is the kth ...

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 provides a distributed source center direction-of-arrival estimation method based on Bayesian compressed perception, and belongs to the technical field of wireless mobile communication. The invention mainly aims to solve the problem concerning inherent error of center direction-of-arrival estimation when the center angle of arrival of an information source is not on an angle sampling grid. According to the invention, an antenna array composed of parallel uniform linear arrays is arranged; an approximate array data reception model of a distribution source is established; the space-domain angle is sampled; a parameterized over-complete redundant dictionary is constructed by using an array steering vector so as to make the problem of distributed source center direction-of-arrival estimation converted into the problem of sparse matrix equation solving; a Bayesian compressed perception method is adopted to solve the equation set and obtain the most sparse solution of an unknown sparse vector; and the estimated value of the center direction of arrival is obtained according to the one-to-one correspondence relationship between sparse solutions and space-domain angles. The method of the invention is low in computing complexity, and has the characteristics of high resolution and accuracy under the condition of a small number of snapshots.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a method for estimating direction of arrival of distributed sources based on Bayesian compressed sensing. Background technique [0002] With the increasing demand for communication capabilities of wireless communication systems, the use of adaptive beamforming technology for wireless transceivers can effectively improve the efficiency of communication systems. Wherein, the direction of arrival (DOA for short) of the wireless signal source is an indispensable parameter of the beamforming technology. Therefore, DOA estimation is a fundamental and very important research problem in modern wireless communication systems. In addition, the estimation accuracy of DOA parameters has a crucial impact on the performance of wireless communication systems. [0003] Due to the multipath propagation phenomenon of wireless mobile communication, the traditional DOA e...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G01S3/12
CPCG01S3/12
Inventor 杨学敏郑植葛琰杨雨轩
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com