Radiation source direct positioning method based on global narrowband model under sparse Bayesian framework

A technology of sparse Bayesian and positioning method, which is applied in the direct positioning of radiation source and the field of radiation source positioning, and can solve the problem of low probability of successful positioning

Active Publication Date: 2020-04-03
HARBIN INST OF TECH
View PDF4 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The main limitation of existing sparse positioning algorithms is that the probability of successful positioning is not high

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
  • Radiation source direct positioning method based on global narrowband model under sparse Bayesian framework
  • Radiation source direct positioning method based on global narrowband model under sparse Bayesian framework
  • Radiation source direct positioning method based on global narrowband model under sparse Bayesian framework

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0073] A direct localization method for radiation sources based on a global narrowband model under a sparse Bayesian framework, such as figure 1 As shown, the direct positioning method of the radiation source includes:

[0074] Step 1: For L discrete base stations and N narrowband radiation sources in the plane, model the received data of the global array under the condition that the radiation source signal has narrowband characteristics for the global array composed of all base stations, where each base station Linearly configure M sensors, and have M≥2, L≥2, 1≤N≤ML-1; then perform block sparse Bayesian extension on the received data model of the global array to obtain the received data of the global array sparse model;

[0075] Step 2: Obtain the posterior update of the signal statistical parameters according to the Gaussian statistical characteristics of the signal;

[0076] Step 3: Use the marginal probability density integral to obtain the parameter estimation cost func...

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 radiation source direct positioning method based on a global narrowband model under a sparse Bayesian framework, and belongs to the technical field of radiation source positioning. The radiation source direct positioning method comprises the following steps of 1, carrying out sparse modeling on the global array reception data; 2, carrying out posterior updating on the signal statistical parameters; and 3, solving the model parameters. The method is suitable for the condition that a radiation source signal has a narrowband characteristic for a global array composed of all base stations, only the angle information of the signal is needed in processing, and the reception synchronization does not need to be carried out on all the stations. Compared with a traditional positioning method, the radiation source direct positioning method provided by the invention does not need to carry out data association and does not need to know the number of information sources, andcompared with a sparse positioning method, the method provided by the invention can obtain a higher positioning success probability.

Description

technical field [0001] The invention relates to a radiation source direct positioning method based on a global narrowband model under a sparse Bayesian framework, and belongs to the technical field of radiation source positioning technology. Background technique [0002] Radiation source location technology is an important research topic in the fields of radar, sonar and wireless communication. The traditional radiation source localization method is divided into two steps: measurement quantity estimation (including angle of arrival, time difference of arrival, etc.) and target position calculation. Its main disadvantage is that an additional data association step is required. Therefore, a class of algorithms that directly use the received data to obtain target position estimates has gradually emerged. Most of the existing direct localization algorithms use the classic spectrum estimation technique, and its limitation is that the number of targets needs to be known. The mai...

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): G01S5/02
CPCG01S5/0278
Inventor 毛兴鹏陈敏求赵春雷
Owner HARBIN INST OF TECH
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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap