scholarly journals Low-altitude protection technology of anti-UAVs based on multisource detection information fusion

2020 ◽  
Vol 17 (5) ◽  
pp. 172988142096290
Author(s):  
Shuai Chen ◽  
Yang Yin ◽  
Zheng Wang ◽  
Fan Gui
Keyword(s):  
Information Fusion ◽  
Single Shot ◽  
Personal Safety ◽  
Defense System ◽  
Correlation Filters ◽  
Stability Performance ◽  
Multisensor Information Fusion ◽  
Protection Technology ◽  
Low Altitude ◽  
Detector Model

Nowadays, unmanned aerial vehicles (UAVs) have achieved massive improvement, which brings great convenience and advantage. Meanwhile, threats posed by them may damage public security and personal safety. This article proposes an architecture of intelligent anti-UAVs low-altitude defense system. To address the key problem of discovering UAVs, research based on multisensor information fusion is carried out. Firstly, to solve the problem of probing suspicious targets, a fusion method is designed, which combines radar and photoelectric information. Subsequently, single shot multibox detector model is introduced to identify UAV from photoelectric images. Moreover, improved spatially regularized discriminative correlation filters algorithm is used to elevate real-time and stability performance of system. Finally, experimental platform is constructed to demonstrate the effectiveness of the method. Results show better performance in range, accuracy, and success rate of surveillance.

scholarly journals A Multi-Information Fusion Correlation Filters Tracker

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 162022-162040
Author(s):  
Junnan Wang ◽  
Zhenhong Jia ◽  
Huicheng Lai ◽  
Jie Yang ◽  
Nikola K. Kasabov
Keyword(s):  
Information Fusion ◽  
Correlation Filters

scholarly journals Object Detection Algorithm Based on Multiheaded Attention

2019 ◽  
Vol 9 (9) ◽  
pp. 1829 ◽  
Author(s):  
Jie Jiang ◽  
Hui Xu ◽  
Shichang Zhang ◽  
Yujie Fang
Keyword(s):  
Object Detection ◽  
Linear Interpolation ◽  
Detection Algorithm ◽  
Attention Mechanism ◽  
Visual Object ◽  
Single Shot ◽  
Object Class ◽  
Feature Information ◽  
Base Network ◽  
Detector Model

This study proposes a multiheaded object detection algorithm referred to as MANet. The main purpose of the study is to integrate feature layers of different scales based on the attention mechanism and to enhance contextual connections. To achieve this, we first replaced the feed-forward base network of the single-shot detector with the ResNet–101 (inspired by the Deconvolutional Single-Shot Detector) and then applied linear interpolation and the attention mechanism. The information of the feature layers at different scales was fused to improve the accuracy of target detection. The primary contributions of this study are the propositions of (a) a fusion attention mechanism, and (b) a multiheaded attention fusion method. Our final MANet detector model effectively unifies the feature information among the feature layers at different scales, thus enabling it to detect objects with different sizes and with higher precision. We used the 512 × 512 input MANet (the backbone is ResNet–101) to obtain a mean accuracy of 82.7% based on the PASCAL visual object class 2007 test. These results demonstrated that our proposed method yielded better accuracy than those provided by the conventional Single-shot detector (SSD) and other advanced detectors.

scholarly journals Monitoring and Analysis of Physical Exercise Effects Based on Multisensor Information Fusion

2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Xinliang Zhou ◽  
Shantian Wen
Keyword(s):  
Physical Exercise ◽  
Data Fusion ◽  
Information Fusion ◽  
Development Process ◽  
System Optimization ◽  
Physiological Parameters ◽  
Fusion Technology ◽  
Multisensor Data Fusion ◽  
Multiple Sensors ◽  
Multisensor Information Fusion

In this paper, multiple sensors are used to track human physiological parameters during physical exercise, and data information fusion technology is used to extract useful information for monitoring and analyzing the effects of physical exercise. This paper explores the interaction and developmental dynamics of multisensor information fusion technology and physical exercise data monitoring based on the interrelationship and interpenetration between the two. The design ideas and principles that should be followed for the software designed in this study are discussed from the perspective of the portable design of measurement instruments and the perspective of multisensor information fusion, and then, the overall architecture and each functional module are studied to propose a scientific and reasonable design model. The general methodological model to be followed for the development of this resource is designed, and the basic development process of the model is explained and discussed, especially the requirement analysis and structural design, and how to build the development environment are explained in detail; secondly, based on the course unit development process in this model, we clarify the limitations of the system through meticulous analysis of the measurement results, which provides a solid foundation for the next step of system optimization. Finally, with a focus on future development, we elaborate on the potential possible role and development trend of multisensor information fusion in the future period. In this paper, we propose to apply the multisensor data fusion algorithm to the monitoring, analysis, and evaluation of the effect of physical exercise, by collecting multiple human physiological parameters during physical exercise through multiple sensors and performing data fusion processing on the collected physiological parameters to finally evaluate the effect of physical exercise.

Multisensor information fusion scheme for particle filter

2015 ◽  
Vol 51 (6) ◽  
pp. 486-488 ◽  
Author(s):  
Wei Zhang ◽  
Junyi Zuo ◽  
Qing Guo ◽  
Zhigang Ling
Keyword(s):  
Particle Filter ◽  
Information Fusion ◽  
Multisensor Information Fusion ◽  
Fusion Scheme
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