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

Estimation method of co-prime array DOA (Direction Of Arrival) angle based on sparse reconstruction

A direction-of-arrival and sparse reconstruction technology, which is applied in the field of direction-of-arrival estimation based on coprime arrays based on sparse reconstruction, can solve the problems of unrecognizable number of targets, large amount of calculation, and inability to estimate the number of information sources. Achieve the effects of avoiding target reconnaissance errors, reducing the amount of signal data, and wide application value

Inactive Publication Date: 2015-07-01
XIDIAN UNIV
View PDF2 Cites 68 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing methods need to calculate the autocorrelation matrix and cross-correlation matrix when calculating the data received by the virtual array in the coprime array, and then extract and sort, and the selected dictionary is not optimal, so the maximum number of information sources cannot be estimated. In the process of construction, a good error distribution parameter is not given, resulting in a large DOA estimation error
However, in practical applications, the number of sources and the distribution of noise are generally unknown. The above-mentioned traditional methods have defects such as large amount of calculation and large estimation error, which will have a great impact on the speed and accuracy of target detection and passive positioning. : The target cannot be detected quickly in real time, and even when there are many targets, it cannot be recognized, resulting in the failure of target capture

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
  • Estimation method of co-prime array DOA (Direction Of Arrival) angle based on sparse reconstruction
  • Estimation method of co-prime array DOA (Direction Of Arrival) angle based on sparse reconstruction
  • Estimation method of co-prime array DOA (Direction Of Arrival) angle based on sparse reconstruction

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0030] In military reconnaissance, such as in the radar field, the detector does not know the number of targets and the direction of arrival of the target in advance, and this information is particularly important. In order to obtain this information, the usual method is to first estimate the number of targets , and then obtain the spatial spectrum of the target signal through methods such as subspace. The traditional spatial spectrum estimation is generally established when the number of targets is known, and the number of targets recognized by the traditional scheme is less than the number of array elements. If the target to be captured The number of targets is more than the number of array elements. The traditional method is to increase the number of array receivers, which increases the cost to a certain extent or cannot be realized on site. The defects of the traditional method, such as large amount of computation and estimation error, will greatly affect the detection of ta...

Embodiment 2

[0048] The method for estimating DOA of a coprime array based on sparse reconstruction is the same as in Embodiment 1, wherein step 3) calculates the virtual array receiving data vector y according to the actual array output signal Y(t), including the following steps:

[0049] 3a) The actual array position vector v is obtained from the position information of the coprime array. The value of v corresponds to the array element information of the coprime array starting from array element 0 at intervals d from the beginning to the end. If there is an array element, the array element information is 1. If there is no array element, the array element information is 0.

[0050] 3b) Calculate the virtual array element position set ω(n) from the actual array position vector v, ω(n)=(v*v - )(n), where * represents convolution, v - Represents the reverse order of v, n=-(2M-1)N,-(2M-1)N+1,...,(2M-1)N-1,(2M-1)N, n is coprime The possibility of multiples of d for the relative distance of e...

Embodiment 3

[0055] The method for estimating DOA of coprime arrays based on sparse reconstruction is the same as that of embodiment 1-2, wherein step 5) calculates the error distribution parameter η parameter, including the following steps:

[0056] 5a) Calculate the received data y at the virtual array element position w(0) 0 ,y 0 =Y 0 (t)×Y 0 H (t) / T,(·) H Represents the conjugate transpose operation of a matrix.

[0057] 5b) According to the formula Calculate the error distribution parameter η, where G is the length of the received data vector y, and T is the number of sampling snapshots, Represents the square of the second norm of the vector y.

[0058] The present invention does not need to know the number of targets in advance; the cross-correlation information of the array is used when calculating the received signal of the virtual array, and the autocorrelation information of the noise is not brought into or seldom brought into the received signal of the virtual array sel...

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 an estimation method of a co-prime array DOA (Direction Of Arrival) angle based on sparse reconstruction, and mainly solves the problems that a prior art is higher in operand, less in identification information source amount and large in passive location evaluated error, and needs more priori knowledge. The method comprises the realizing steps of forming a co-prime array by an antenna receiver; obtaining observation data to spatial signal sampling; receiving data vectors by a virtual array element obtained by observation data; dividing spatial grids to form over-complete bases; receiving a spare relationship between the data vectors and the over-complete bases by the virtual array element to build a spare restraint equation; resolving the spare restraint equation by adopting a convex optimization method to obtain sparest resolution; drawing a magnitude spectrogram by a relative relationship between the sparest resolution and the spatial angle to obtain a DOA angle value. According to the method provided by the invention, the passive direction-finding precision and operating speed can be improved under a condition of low priori knowledge, the number of the recognized information source can be improved, and the estimation precision of a signal direction angle can be improved in a low signal to noise ratio, therefore the estimation method can be used for target reconnaissance and passive location.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to an array signal processing technology of acoustic signals and electromagnetic signals, and specifically relates to a method for estimating the DOA of coprime arrays based on sparse reconstruction, which can be used for target reconnaissance and passive positioning. Background technique [0002] Signal DOA estimation is an important branch in the field of array signal processing. It refers to the use of antenna arrays to inductively receive spatial acoustic signals and electromagnetic signals, and then use modern signal processing methods to quickly and accurately estimate the direction of the signal source. , has important application value in radar, sonar, wireless communication and other fields. With the continuous advancement of science and technology, there are increasingly higher requirements for the accuracy and resolution of signal direction of arriva...

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 蔡晶晶鲍丹武斌刘高高秦国栋李鹏马亚东
Owner XIDIAN UNIV
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