scholarly journals Bathtub-Shaped Failure Rate of Sensors for Distributed Detection and Fusion

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Junhai Luo ◽  
Tao Li
Keyword(s):  
Failure Rate ◽  
Fusion Rule ◽  
Distributed Detection ◽  
Fusion Center ◽  
Ratio Test ◽  
Failure Model ◽  
Sensor Failure ◽  
Robust Performance ◽  
Random Failure ◽  
Local Observation

We study distributed detection and fusion in sensor networks with bathtub-shaped failure (BSF) rate of the sensors which may or not send data to the Fusion Center (FC). The reliability of semiconductor devices is usually represented by the failure rate curve (called the “bathtub curve”), which can be divided into the three following regions: initial failure period, random failure period, and wear-out failure period. Considering the possibility of the failed sensors which still work but in a bad situation, it is unreasonable to trust the data from these sensors. Based on the above situation, we bring in new characteristics to failed sensors. Each sensor quantizes its local observation into one bit of information which is sent to the FC for overall fusion because of power, communication, and bandwidth constraints. Under this sensor failure model, the Extension Log-likelihood Ratio Test (ELRT) rule is derived. Finally, the ROC curve for this model is presented. The simulation results show that the ELRT rule improves the robust performance of the system, compared with the traditional fusion rule without considering sensor failures.

scholarly journals Distributed detection basis on using soft decision scheme both in local sensors and in fusion center

2021 ◽  
pp. 49-56
Author(s):  
V. I. Parfenov ◽  
V. D. Le
Keyword(s):  
Signal To Noise Ratio ◽  
Energy Parameter ◽  
Fusion Rule ◽  
Decision Fusion ◽  
Distributed Detection ◽  
Fusion Center ◽  
Soft Decision ◽  
Signal To Noise ◽  
Decision Scheme ◽  
Noise Ratio

The paper considers distributed detection problem basis on using soft decision scheme both in the local sensors and in the fusion center (FC). The algorithm for making soft decisions when receiving data from local sensors in the fusion center and its performance characteristics, which are necessary for the formation decision fusion rule, are presented. The dependencies of the total error probability on the energy parameter taking into account signal-to-noise ratio at the level of local sensors and the channel’s signal-to-noise ratio are given. The gain of the fusion rule basis on the aggregation of soft decisions in the FC when receiving data about soft local decisions, in efficiency compared to hard fusion rule.

scholarly journals Typical Set Cognitive Sensing

2011 ◽  
Vol 2011 ◽  
pp. 1-10
Author(s):  
Oussama Souihli ◽  
Tomoaki Ohtsuki
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Fusion Rule ◽  
Decision Fusion ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fusion Center ◽  
Cooperative Sensing ◽  
Wireless Sensor Nodes ◽  
Detection Probabilities

In cognitive radio (CR) cooperative sensing schemes, wireless sensor nodes deployed in the network sense the licensed spectrum and send their local sensing decisions to a fusion center (FC) that makes a global decision on whether to allow the unlicensed user transmit on the licensed spectrum, based on a decision (fusion) rule. k-out-of-N is widely used in the literature owing to its practical simplicity. Regrettably, it exhibits a tradeoff between the achievable probabilities of false alarm and miss detection, which could have consequent effects on the performance of CR. In this paper, based on the notion of typical sequences, we propose a novel fusion rule in which the false alarm and miss detection probabilities can be simultaneously made as small as desired (asymptotically zero as the number of sensors goes to infinity).

Receiver Diversity for Distributed Detection in Wireless Sensor Networks

2012 ◽  
Vol 2 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Mohammad A. Al-Jarrah ◽  
Mohammad M. Al-Ibrahim
Keyword(s):  
Detection System ◽  
Block Codes ◽  
Distributed Detection ◽  
Wireless Sensor ◽  
Fusion Center ◽  
Receiver Diversity ◽  
Space Time Block Codes ◽  
Optimal Fusion ◽  
Central Device

In this paper, parallel distributed detection in wireless sensor network (WSN) is considered where the sensors process the observations to make local decisions and send these decisions to a central device called fusion center. Receiver diversity technique is proposed here for the distributed detection system in order to enhance the system reliability by improving the detection performance. The fusion center is assumed to be multiple antennas device in order to imply the idea of receiver diversity. Different combining schemes at the fusion center side are used to reduce the fading effects in the case of receiver diversity. Transmitter diversity is also considered in this paper. Cooperative sensors are assumed in order to obtain Alamouti space time block codes. Optimal and sub-optimal fusion rules are derived for each case study. Simulation results show the performance improvement obtained as compared to the conventional distributed detection system in which no diversity is used.

scholarly journals Two Types of Distributed CFAR Detection Based on Weighting Functions in Fusion Center for Weibull Clutter

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Amir Zaimbashi
Keyword(s):  
Fusion Center ◽  
Test Statistics ◽  
Constant False Alarm Rate ◽  
Robust Performance ◽  
Global Test ◽  
Weighting Functions ◽  
Cfar Detection ◽  
Local Detectors ◽  
Detection Schemes ◽  
Maximum Minimum

Two types of distributed constant false alarm rate (CFAR) detection using binary and fuzzy weighting functions in fusion center are developed. In the two types of distributed detectors, it was assumed that the clutter parameters at the local sensors are unknown and each local detector performs CFAR processing based on ML and OS CFAR processors before transmitting data to the fusion center. At the fusion center, received data is weighted either by a binary or a fuzzy weighting functions and combined according to deterministic rules, constructing global test statistics. Moreover, for the Weibull clutter, the expression of the weighting functions, based on ML and OS CFAR processors in local detectors, is obtained. In the binary type, we analyzed various distributed detection schemes based on maximum, minimum, and summation rules in fusion center. In the fuzzy type, we consider the various distributed detectors based on algebraic product, algebraic sum, probabilistic OR, and Lukasiewicz t-conorm fuzzy rules in fusion center. The performance of the two types of distributed detectors is analyzed and compared in the homogenous and nonhomogenous situations, multiple targets, or clutter edge. The simulation results indicate the superiority and robust performance of fuzzy type in homogenous and non homogenous situations.

Reliable filter synthesis for a class of stochastic systems under nonhomogeneous Markovian switching

2017 ◽  
Vol 40 (4) ◽  
pp. 1375-1385
Author(s):  
Yue Long ◽  
Chao Xu ◽  
Zhenyu Zhou
Keyword(s):  
Optimization Problem ◽  
Stochastic Systems ◽  
Aircraft Engine ◽  
Markovian Switching ◽  
Failure Model ◽  
Sensor Failure ◽  
Convex Optimization Problem ◽  
Normal Case ◽  
Filter Synthesis ◽  
Theoretical Results

This paper is concerned with the problem of reliable filter synthesis for a class of stochastic systems with random occurring nonlinearities and mode-dependent delays under nonhomogeneous Markovian switching. By considering a new sensor failure model, which is valid to describe the drift faults, the loss of effectiveness, the stuck as well as the outage faults besides the normal case, a procedure of filter synthesis is proposed. Further, the filter gains are characterized in terms of solutions to a convex optimization problem with less conservativeness. Finally, the theoretical results are illustrated through an example of the aircraft engine.

scholarly journals Fast Detection Method in Cooperative Cognitive Radio Networks

2010 ◽  
Vol 2010 ◽  
pp. 1-8 ◽  
Author(s):  
Zhengyi Li ◽  
Lin Liu ◽  
Chi Zhou
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sharing ◽  
Fusion Rule ◽  
Detection Accuracy ◽  
Ratio Test ◽  
Central Control ◽  
Spectrum Utilization ◽  
Observation Window ◽  
Detection Scheme ◽  
Fast Detection

Cognitive Radio (CR) technology improves the utilization of spectrum highly via opportunistic spectrum sharing, which requests fast detection as the spectrum utilization is dynamic. Taking into consideration the characteristic of wireless channels, we propose a fast detection scheme for a cooperative cognitive radio network, which consists of multiple CRs and a central control office. Specifically, each CR makes individual detection decision using the sequential probability ratio test combined with Neyman Pearson detection with respect to a specific observation window length. The proposed method upper bounds the detection delay. In addition, a weightedKout ofNfusion rule is also proposed for the central control office to reach fast global decision based on the information collected from CRs, with more weights assigned for CRs with good channel conditions. Simulation results show that the proposed scheme can achieve fast detection while maintaining the detection accuracy.

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