Maneuvering target tracking system based on nerve network data fusion
A mobile target tracking and data fusion technology, applied in the field of multi-sensor data fusion and neural network, can solve problems such as reducing the accuracy of target tracking, and achieve the effects of eliminating limitations, weakening faults, and improving parameter measurement accuracy
Inactive Publication Date: 2012-09-12
CHANGSHU RES INSTITUE OF NANJING UNIV OF SCI & TECH
View PDF4 Cites 4 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0008] In the process of multi-sensor fusion, the sensor output is not a value. For example, the sensor outputs target attribute data and target state data at the same time, or the output of the sensor changes during the observation time interval, and the precise value is used for the neural network. Judgment, which reduces the accuracy of target tracking
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 moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment
[0027] Among many real-time sensors, the sensor that acquires the graphical object is a charge-coupled device.
[0028] The data preprocessing unit filters out the interference and noise introduced in the data collection process through methods such as averaging, filtering, eliminating trend items, and eliminating wild points.
[0029] In step B of the processing method for data fusion by the coarse neural network data fusion unit, the transfer function between the coarse neurons where f u (x) is the upper transfer function, f l (x) is the lower transfer function.
[0030] In step D of the processing method of data fusion by the coarse neural network data fusion unit, the error in the error transfer function in the traditional neural network learning method is the mean value of the variance of the upper and lower layers,
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
Login to view more Abstract
The invention belongs to a technical field of multi-sensor data fusion and nerve network, and discloses a maneuvering target tracking system based on nerve network data fusion. The system comprises sensors, an A/D converter, a data preprocessing unit, a feature extraction unit, a rough neural network data fusion unit and an output unit. Target data obtained by the sensors is converted into digital quantities through the A/D converter; interferences and noises are filtered through the data preprocessing unit, and then feature extraction is carried out on filtered target data; fusion calculations are carried out on the feature data through the rough neural network data fusion unit; and finally, a result is outputted by the output unit. Data information combination is carried out by processing with the rough neural network data fusion unit, a best synergy is obtained, validity of the multi-sensor system is improved, limitations of the single sensor and a few sensors are eliminated, and accuracy of target tracking positioning is improved.
Description
technical field [0001] The invention belongs to the technical field of multi-sensor data fusion and neural network, and more specifically relates to a maneuvering target tracking system based on neural network data fusion. Background technique [0002] In the fields of military ballistic missile defense, air early warning, and air attack, the application of target tracking has been widely valued by various countries. [0003] Multi-sensor tracking produces multi-source signals, and reducing signal uncertainty to give a more complete description of the signal source is a key technical issue, resulting in the concept of multi-sensor data fusion, which originates from the human nervous system for multiple senses The survival ability of organs is called neural network in the field of modern research. Neural network imitates human reasoning and imitation ability, and better links multi-sensor data fusion and neural network. Due to the similarity of the observations, a certain al...
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
Login to view more Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/02
Inventor 马小云
Owner CHANGSHU RES INSTITUE OF NANJING UNIV OF SCI & 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
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