Low Altitude Target Detection Technology Based on 5G Base Station

2021 ◽  
pp. 381-389
Author(s):  
Yuxin Wu ◽  
Wenhao Guo ◽  
Jinlong Liu ◽  
Bo Yang ◽  
Lu Ba ◽  
...  
Keyword(s):  
Target Detection ◽  
Base Station ◽  
Detection Technology ◽  
Low Altitude

scholarly journals Implementation of a Modified Faster R-CNN for Target Detection Technology of Coastal Defense Radar

2021 ◽  
Vol 13 (9) ◽  
pp. 1703
Author(s):  
He Yan ◽  
Chao Chen ◽  
Guodong Jin ◽  
Jindong Zhang ◽  
Xudong Wang ◽  
...  
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Target Detection ◽  
Real Data ◽  
Detection Performance ◽  
Detection Accuracy ◽  
Constant False Alarm Rate ◽  
Data Set ◽  
Detection Technology ◽  
Coastal Defense

The traditional method of constant false-alarm rate detection is based on the assumption of an echo statistical model. The target recognition accuracy rate and the high false-alarm rate under the background of sea clutter and other interferences are very low. Therefore, computer vision technology is widely discussed to improve the detection performance. However, the majority of studies have focused on the synthetic aperture radar because of its high resolution. For the defense radar, the detection performance is not satisfactory because of its low resolution. To this end, we herein propose a novel target detection method for the coastal defense radar based on faster region-based convolutional neural network (Faster R-CNN). The main processing steps are as follows: (1) the Faster R-CNN is selected as the sea-surface target detector because of its high target detection accuracy; (2) a modified Faster R-CNN based on the characteristics of sparsity and small target size in the data set is employed; and (3) soft non-maximum suppression is exploited to eliminate the possible overlapped detection boxes. Furthermore, detailed comparative experiments based on a real data set of coastal defense radar are performed. The mean average precision of the proposed method is improved by 10.86% compared with that of the original Faster R-CNN.

scholarly journals Optimal Placement of Low-Altitude Aerial Base Station for Securing Communications

2019 ◽  
Vol 8 (3) ◽  
pp. 869-872 ◽  
Author(s):  
Dong Wang ◽  
Bo Bai ◽  
Guangzheng Zhang ◽  
Zhu Han
Keyword(s):  
Base Station ◽  
Optimal Placement ◽  
Low Altitude

scholarly journals A Probabilistic Target Search Algorithm Based on Hierarchical Collaboration for Improving Rapidity of Drones

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2535 ◽  
Author(s):  
Il-Kyu Ha ◽  
You-Ze Cho
Keyword(s):  
High Altitude ◽  
Target Detection ◽  
Information Transfer ◽  
Search Algorithm ◽  
Search Time ◽  
Previous Method ◽  
Target Search ◽  
Low Altitude ◽  
Military Facilities ◽  
Different Altitudes

Finding a target quickly is one of the most important tasks in drone operations. In particular, rapid target detection is a critical issue for tasks such as finding rescue victims during the golden period, environmental monitoring, locating military facilities, and monitoring natural disasters. Therefore, in this study, an improved hierarchical probabilistic target search algorithm based on the collaboration of drones at different altitudes is proposed. This is a method for reducing the search time and search distance by improving the information transfer methods between high-altitude and low-altitude drones. Specifically, to improve the speed of target detection, a high-altitude drone first performs a search of a wide area. Then, when the probability of existence of the target is higher than a certain threshold, the search information is transmitted to a low-altitude drone which then performs a more detailed search in the identified area. This method takes full advantage of fast searching capabilities at high altitudes. In other words, it reduces the total time and travel distance required for searching by quickly searching a wide search area. Several drone collaboration scenarios that can be performed by two drones at different altitudes are described and compared to the proposed algorithm. Through simulations, the performances of the proposed algorithm and the cooperation scenarios are analyzed. It is demonstrated that methods utilizing hierarchical searches with drones are comparatively excellent and that the proposed algorithm is approximately 13% more effective than a previous method and much better compared to other scenarios.

Application of Cellular Communications Models and Designs for Use in Disaster-Aftermath Related Scenarios

2015 ◽  
Vol 7 (3) ◽  
pp. 46-56
Author(s):  
Stephen J. Curran
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Ground Level ◽  
Base Station ◽  
Cellular Communications ◽  
Fixed Position ◽  
Above Ground Level ◽  
High Altitude Platforms ◽  
Major Disaster ◽  
Future Strategy ◽  
Low Altitude

This paper is a pilot study on the concept of an aerial base station as a future strategy for restoring cellular communications in the aftermath of a major disaster. The strategy being studied makes use of low altitude platforms (LAPs) or unmanned aerial vehicles (UAVs) that can hover or orbit in a relatively fixed position and can act as an aerial base station. Unlike High Altitude Platforms (HAP) operating in a layer of the atmosphere above any existing air traffic, the LAPs or UAVs will be able to operate a few hundred to some thousands of meters above ground level. This paper also describes the functionality of the components comprising the aerial base station.

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