An Intelligent Maritime Communication Signal Recognition Algorithm based on ACWGAN

2020 ◽  
Author(s):  
Zhao Caidan ◽  
He Zeping ◽  
Luo Gege ◽  
Chen Caiyun
Keyword(s):  
Recognition Algorithm ◽  
Signal Recognition ◽  
Communication Signal ◽  
Maritime Communication

The algorithm of the color signal recognition at landing an unmanned aerial vehicle on an aircraft carrier in autonomous mode

2020 ◽  
pp. 78
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Treatment Method ◽  
Recognition Algorithm ◽  
Connected Components ◽  
Preliminary Treatment ◽  
Signal Recognition ◽  
Aircraft Carrier ◽  
Halftone Image ◽  
Glide Path ◽  
Aerial Vehicle

The movement along the glide path of an unmanned aerial vehicle during landing on an aircraft carrier is investigated. The implementation of this task is realized in the conditions of radio silence of the aircraft carrier. The algorithm for treatment information from an optical landing system installed on an aircraft carrier is developed. The algorithm of the color signal recognition assumes the usage of the image frame preliminary treatment method via a downsample function, that performs the decimation process, the HSV model, the Otsu’s method for calculating the binarization threshold for a halftone image, and the method of separating the connected Two-Pass components. Keywords unmanned aerial vehicle; aircraft carrier; approach; glide path; optical landing system; color signal recognition algorithm; decimation; connected components; halftone image binarization

Research on Modulation Recognition Algorithm of Digital Communication Signal Based on Wavelet Denoising

2014 ◽  
Vol 608-609 ◽  
pp. 459-467 ◽  
Author(s):  
Xiao Yu Gu
Keyword(s):  
Pattern Recognition ◽  
Feature Extraction ◽  
Decision Theory ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
Modulation Recognition ◽  
The Core ◽  
Feature Parameters ◽  
Communication Signal ◽  
Modulation Signal

The paper researches a recognition algorithm of modulation signal and modulation modes. The modulation modes to be recognized include 2ASK, 2FSK, 2PSK, 4ASK, 4FSK and 4PSK modulation. There are two methods recognizing modulation modes of digital signal, method based on decision theory and pattern-recognition method based on feature extraction. The method based on decision theory is not suitable for recognition with multiple modulation modes. The core of pattern recognition based on feature extraction is selection of feature parameters. So the paper uses the feature parameters with simple calculation, easy to be implemented and high recognition rate as the core. The extraction of feature parameters is based on instant feature of modulation signal after Hilbert transformation.

Fiber Intrusion Signal Recognition Algorithm Based on Stochastic Configuration Network

2019 ◽  
Vol 56 (14) ◽  
pp. 140602 ◽  
Author(s):  
盛智勇 Zhiyong Sheng ◽  
曾志强 Zhiqiang Zeng ◽  
曲洪权 Hongquan Qu ◽  
李伟 Wei Li
Keyword(s):  
Recognition Algorithm ◽  
Signal Recognition

scholarly journals A RASPBERRY PI SELF-DRIVING CART BASED ON OPENCV AND DEEP LEARNING .

2021 ◽  
Vol 10 (3) ◽  
pp. 61-67
Keyword(s):  
Deep Learning ◽  
Obstacle Avoidance ◽  
Target Recognition ◽  
Recognition Algorithm ◽  
Traffic Signal ◽  
The Self ◽  
Raspberry Pi ◽  
Signal Recognition ◽  
Ultrasonic Sensors ◽  
Better Than

The self-driving trolley created in this thesis uses cameras and ultrasonic sensors to obtain roadway information, and a deep learning based target recognition algorithm to find out which are the targets in the data obtained, so that the trolley can drive itself on a simulated roadway with functions such as obstacle avoidance and traffic signal recognition. Originally the car used a Raspberry Pi 3b+, but here the jetson nano, which is better than the Raspberry Pi 3b+, is used to implement it.

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