scholarly journals On the Detection of a Non-Cooperative Beam Signal Based on Wireless Sensor Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Guofeng Wei ◽  
Bangning Zhang ◽  
Guoru Ding ◽  
Bing Zhao ◽  
Kefeng Guo ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Detection Probability ◽  
Communication Systems ◽  
Prior Information ◽  
Signal Strength ◽  
Energy Detection ◽  
Wireless Sensor ◽  
Fusion Algorithm ◽  
Beam Signal

With the extensive research of multiantenna technology, beamforming (BF) will play an important role in the future communication systems due to its high transmission gain and satisfying directivity. If we can detect the non-cooperative beams, it is of great significance in counter reconnaissance, beam tracking, and spectrum sensing of multiantenna transmitters. This paper investigates the wireless sensor networks (WSNs), which is used to detect the unknown non-cooperative beam signal. In order to perceive the presence of beam signals without the prior information, we first derive the detection probability based on the sensors’ received signal strength (RSS). Then, based on the strong directivity of the beam signal, we propose an improved “k rank” fusion algorithm by jointly exploiting the energy detection (ED) information and location information of the sensors. Finally, the beam detection performance of different fusion algorithms is compared in simulation, and we find that our proposed algorithm showed better detection probability and lower error probability. The simulation results verify the correctness and effectiveness of the proposed algorithm.

Path coverage enhancement in wireless sensor networks based on CVT model

2021 ◽  
pp. 1-13
Author(s):  
Guangxu Yu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Detection Probability ◽  
Coverage Rate ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Current Path ◽  
Coverage Model ◽  
Path Coverage ◽  
Low Coverage

In order to overcome the problems of low detection probability, low coverage uniformity and low coverage of current path coverage enhancement methods in wireless sensor networks, a new path coverage enhancement method based on CVT model is proposed in this paper. Firstly, the node perception model and network coverage model are constructed. On the basis of the node awareness model and network coverage model, CVT model is used to adjust the connection mode, density and location of nodes in wireless sensor networks, so as to improve the coverage performance of nodes in the detection area in wireless sensor networks, and realize the effective enhancement of path coverage in wireless sensor networks. Experimental results show that, compared with the traditional methods, the proposed method has high detection probability, high coverage uniformity and coverage rate, and the highest coverage rate reaches 97%, which has higher practical application performance.

Formal Probabilistic Analysis of Detection Properties in Wireless Sensor Networks

2015 ◽  
pp. 228-258
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Probabilistic Analysis ◽  
Detection Probability ◽  
Scheduling Algorithm ◽  
Wireless Sensor ◽  
Higher Order Logic ◽  
Security Monitoring ◽  
Detection Delay ◽  
Mission Critical

In the context of Wireless Sensor Networks (WSNs), the ability to detect an intrusion event is the most desired characteristic. Due to the randomness in nodes scheduling algorithm and sensor deployment, probabilistic techniques are used to analyze the detection properties of WSNs. However, traditional probabilistic analysis techniques, such as simulation and model checking, do not ensure accurate results, which is a severe limitation considering the mission-critical nature of most of the WSNs. In this chapter, the authors overcome these limitations by using higher-order-logic theorem proving to formally analyze the detection properties of randomly deployed WSNs using the randomized scheduling of nodes. Based on the probability theory, described in Chapters 5, they first formally reason about the intrusion period of any occurring event. This characteristic is then built upon to develop the fundamental formalizations of the key detection metrics: the detection probability and the detection delay. For illustration purposes, the authors formally analyze the detection performance of a WSN deployed for border security monitoring.

scholarly journals Opportunities and Challenges for Error Control Schemes for Wireless Sensor Networks: A Review

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 504
Author(s):  
Rajan Kadel ◽  
Krishna Paudel ◽  
Deepani B. Guruge ◽  
Sharly J. Halder
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Error Correction ◽  
Communication Systems ◽  
Research Work ◽  
Error Correcting Codes ◽  
Wireless Sensor ◽  
Future Research ◽  
Asymmetric Structure ◽  
Design And Implementation

Error Correction Schemes (ECSs) significantly contribute to enhancing reliability and energy efficiency of Wireless Sensor Networks (WSNs). This review paper offers an overview of the different types of ECS used in communication systems and a synopsis of the standards for WSN. We also discuss channels and network models for WSN as they are crucial for efficient ECS design and implementation. The literature review conducted on the proposed energy consumption and efficiency models for WSN indicates that existing research work has not considered Single Hop Asymmetric Structure (SHAS) with high performing Error Correcting Codes (ECCs). We present a review on proposed ECS for WSN based on three criteria: Forward Error Correction (FEC), adaptive error correction techniques, and other techniques. Based on our review work, we found that there are limited works on ECS design on a realistic network model i.e., a modified multi-hop WSN model. Finally, we offer future research challenges and opportunities on ECS design and implementation for WSN.

scholarly journals A Fusion Localization Method based on a Robust Extended Kalman Filter and Track-Quality for Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3638 ◽  
Author(s):  
Yan Wang ◽  
Huihui Jie ◽  
Long Cheng
Keyword(s):  
Wireless Sensor Networks ◽  
Kalman Filter ◽  
Sensor Networks ◽  
Extended Kalman Filter ◽  
Wireless Sensor ◽  
Multiple Model ◽  
Fusion Algorithm ◽  
Time Step ◽  
Localization Method ◽  
Track Quality

As one of the most essential technologies, wireless sensor networks (WSNs) integrate sensor technology, embedded computing technology, and modern network and communication technology, which have become research hotspots in recent years. The localization technique, one of the key techniques for WSN research, determines the application prospects of WSNs to a great extent. The positioning errors of wireless sensor networks are mainly caused by the non-line of sight (NLOS) propagation, occurring in complicated channel environments such as the indoor conditions. Traditional techniques such as the extended Kalman filter (EKF) perform unsatisfactorily in the case of NLOS. In contrast, the robust extended Kalman filter (REKF) acquires accurate position estimates by applying the robust techniques to the EKF in NLOS environments while losing efficiency in LOS. Therefore it is very hard to achieve high performance with a single filter in both LOS and NLOS environments. In this paper, a localization method using a robust extended Kalman filter and track-quality-based (REKF-TQ) fusion algorithm is proposed to mitigate the effect of NLOS errors. Firstly, the EKF and REKF are used in parallel to obtain the location estimates of mobile nodes. After that, we regard the position estimates as observation vectors, which can be implemented to calculate the residuals in the Kalman filter (KF) process. Then two KFs with a new observation vector and equation are used to further filter the estimates, respectively. At last, the acquired position estimates are combined by the fusion algorithm based on the track quality to get the final position vector of mobile node, which will serve as the state vector of both KFs at the next time step. Simulation results illustrate that the TQ-REKF algorithm yields better positioning accuracy than the EKF and REKF in the NLOS environment. Moreover, the proposed algorithm achieves higher accuracy than interacting multiple model algorithm (IMM) with EKF and REKF.

Testing the feasibility of wireless sensor networks and the use of radio signal strength indicator to track the movements of wild animals

2018 ◽  
Vol 45 (8) ◽  
pp. 659 ◽  
Author(s):  
C. R. Krull ◽  
L. F. McMillan ◽  
R. M. Fewster ◽  
R. van der Ree ◽  
R. Pech ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Signal Strength ◽  
The Body ◽  
Data Uncertainty ◽  
Wireless Sensor ◽  
Small Animals ◽  
Significant Difference

Context Wireless sensor networks (WSNs) are revolutionising areas of animal behaviour research and are advantageous based on their ability to be deployed remotely and unobtrusively, for long time periods in inaccessible areas. Aims We aimed to determine the feasibility of using a WSN to track detailed movement paths of small animals, e.g. rats (Rattus spp.) 100–400g, too small for current GPS technology, by calibrating active Radio Frequency Identification (RFID) tags and loggers using Radio Frequency Signal Strength Indicator (RSSI) as a proxy for distance. Active RFIDs are also called Wireless Identification (WID) tags. Methods Calibration tests were conducted using a grid of loggers (n=16) spaced at 45-m intervals in clear line-of-sight conditions. WID tags (n=16) were placed between the loggers at 45-m intervals. Eight ‘walks’ were also conducted through the grid using a single WID tag. This involved attaching the tag to a small bottle of water (to simulate the body of an animal), towed around the grid using a 1-m long tow line attached to a volunteer walker. The volunteer also held a GPS device that logged their track. Models were constructed to test the effects of distance, tag movement and individual differences in loggers and tags on the reliability of movement data. Key results Loggers were most successful at detecting tags at distances <50m. However, there was a significant difference in the detection probabilities of individual loggers and also the transmission performance of individual tags. Static tags were less likely to be detected than the mobile tag; and although RSSI was somewhat related to distance, the reliability of this parameter was highly variable. Implications We recommend caution in the future use of current radio frequency ID tags in wireless sensor networks to track the movement of small animals, and in the use of RSSI as an indicator of individual distance values, as extensive in situ calibration is required. ‘Off the shelf’ devices may vary in performance, rendering data unreliable. We emphasise the importance of calibrating all equipment in animal tracking studies to reduce data uncertainty and error.

scholarly journals A Real-Time Smooth Weighted Data Fusion Algorithm for Greenhouse Sensing Based on Wireless Sensor Networks

Sensors ◽  
2017 ◽  
Vol 17 (11) ◽  
pp. 2555 ◽  
Author(s):  
Tengyue Zou ◽  
Yuanxia Wang ◽  
Mengyi Wang ◽  
Shouying Lin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Fusion ◽  
Real Time ◽  
Wireless Sensor ◽  
Fusion Algorithm ◽  
Weighted Data
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