scholarly journals Laser Remote Sensing Method of Carbon Monoxide Emissions Detection

2020 ◽  
pp. 20-34
Author(s):  
M. L. Belov ◽  
Ya. E. Drachennikova ◽  
V. A. Gorodnichev
Keyword(s):  
Remote Sensing ◽  
Carbon Monoxide ◽  
False Alarm ◽  
Detection Probability ◽  
False Alarm Probability ◽  
Correct Detection ◽  
Gas Analyzer ◽  
Gas Concentration ◽  
Information Parameter ◽  
Laser Remote Sensing

Monitoring of atmospheric gas pollution is one of the most important environmental target. Laser methods are the most effective for remote operational monitoring of atmospheric pollution.One of the most important air pollutants is carbon monoxide.The article analyzes the possibility of laser remote sensing method of carbon monoxide emissions detection in atmosphere.The information parameter measured by the remote sensing laser gas analyzer was assessed for absorption band of carbon monoxide near 2,3 μm.The information parameter that can be used for monitoring monoxide emissions is the ratio of the power of laser signals at the wavelengths 4295 cm-1 and 4370 cm-1.Results of calculations of the information parameter for different sizes of emissions (from 1 m to 100 m) and different content of carbon monoxide in the emission (from 0.01 % to 10 %) were showed.Comparing the information parameter R with its background value shows that carbon monoxide emissions can be monitored.Mathematical modeling was performed for quantitative estimation the reliability of detecting carbon monoxide emissions.The probability of correctly emission detecting (emission detecting when there is one) and the probability of false alarms (emission detecting when there is none) were calculated.Mathematical modelling shows that a laser gas analyzer allows us to detect the carbon monoxide emissions with correct detection probability not less 0,845 and false alarm probability no more 0,243 for carbon monoxide emissions with gas concentration not less  0,1 %  and dimension of emissions cloud not less 10 m. For carbon monoxide emissions with gas concentration not less 1 % and dimension of emissions cloud not less 5 m a laser gas analyzer allows us to detect the carbon monoxide emissions with correct detection probability not less  0,999 and false alarm probability no more 0,001.

scholarly journals A Novel Sensing Strategy Based on Energy Detector for Spectrum Sensing

2019 ◽  
Vol 9 (21) ◽  
pp. 4634 ◽  
Author(s):  
Hai Huang ◽  
Jia Zhu ◽  
Junsheng Mu
Keyword(s):  
False Alarm ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
False Alarm Probability ◽  
Energy Detector ◽  
Accuracy Improvement ◽  
Classical Scheme ◽  
Sensing Performance

Sensing strategy directly influences the sensing accuracy of a spectrum sensing scheme. As a result, the optimization of a sensing strategy appears to be of great significance for accuracy improvement in spectrum sensing. Motivated by this, a novel sensing strategy is proposed in this paper, where an improved tradeoff among detection probability, false-alarm probability and available throughput is obtained based on the energy detector. We provide the optimal sensing performance and exhibit its superiority in theory compared with the classical scheme. Finally, simulations validate the conclusions drawn in this paper.

Multi-Sensor N-P Criterion Fusion Detection Based on Weighting by SNR

2014 ◽  
Vol 1044-1045 ◽  
pp. 818-824
Author(s):  
Bo Fan Yang ◽  
Rui Wang ◽  
Gang Wang ◽  
Li Zhao
Keyword(s):  
Signal Detection ◽  
False Alarm ◽  
Sensor Fusion ◽  
Detection Probability ◽  
Detection System ◽  
False Alarm Probability ◽  
Radar Target ◽  
Low Snr ◽  
Simulation Results ◽  
Fusion Detection

Aiming at signal detection of radar target, concerning about on the basis of the influence of SNR on detection probability when false alarm probability is given based on N-P criterion, a kind of multi-sensor fusion detection based on SNR is put forward. It can improve system’s detection probability under the condition of required false alarm probability in the detection of low SNR signal. The simulation results show that the detection performance is significantly increased, no matter fusion detection system is composed of same sensors working in the same working point or different sensors.

scholarly journals A PRACH Preamble Generation and Detection Model for 5GNR Systems

2021 ◽  
pp. 98-105
Author(s):  
Puneeth K M ◽  
Poornima M S
Keyword(s):  
False Alarm ◽  
Detection Probability ◽  
Additive White Gaussian Noise ◽  
Random Access ◽  
False Alarm Probability ◽  
Probability Of Detection ◽  
Detection Model ◽  
High Data ◽  
Access Channel ◽  
New Radio

The basic idea of 5th generation New Radio (5GNR) is to have very high data rate and to make it work efficiently for all Internet of Things (IOT) applications like healthcare, Automotive, Industrial etc. applications. This paper provides the Orthogonal Frequency Division Multiple Access (OFDM) baseband signal generation and detection method for Physical Random-Access Channel (PRACH). The proposed model provides four scenarios of preamble detection i.e., Preamble detection probability, Miss-detection probability, False alarm probability and null. We achieved the target of 99% of Probability of Detection and less than 0.1% of False-alarm probability at certain SNR as specified according to 3gpp standard requirements when tested in Additive White Gaussian Noise (AWGN) channel and Extended Typical Urban (ETU) channel.

scholarly journals An analysis of energy detector based on improved approximations of the chi-square distributions

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Felipe G. M. Elias ◽  
Evelio M. G. Fernández
Keyword(s):  
False Alarm ◽  
Detection Probability ◽  
Total Error ◽  
Detection Threshold ◽  
False Alarm Probability ◽  
Optimal Number ◽  
Energy Detector ◽  
Chi Square ◽  
Total Error Rate ◽  
Wide Range

AbstractClosed-form expressions for the detection probability, the false alarm probability and the energy detector constant threshold are derived using approximations of the central chi-square and non-central chi-square distributions. The approximations used show closer proximity to the original functions when compared to the expressions used in the literature. The novel expressions allow gains up to 6% and 16% in terms of measured false alarm and miss-detection probability, respectively, if compared to the Central Limit Theorem approach. The throughput of cognitive network is also enhanced when these novel expressions are implemented, providing gains up to 9%. New equations are also presented that minimize the total error rate to obtain the detection threshold and the optimal number of samples. The analytical results match the results of the simulation for a wide range of SNR values.

Cepstrum-Based Spectrum Hole Search in Different Fading Scenario in Cognitive Radio Network

2017 ◽  
pp. 49-62
Author(s):  
Srijibendu Bagchi
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Detection Probability ◽  
False Alarm Probability ◽  
Channel Fading ◽  
Spectral Density Estimation ◽  
Power Spectral ◽  
Detection Probabilities ◽  
Spectrum Scarcity ◽  
Spectrum Hole

Cognitive radio is now acknowledged as a potential solution to meet the spectrum scarcity problem in radio frequency range. To achieve this objective proper identification of vacant frequency band is necessary. In this article a detection methodology based on cepstrum estimation has been proposed that can be done through power spectral density estimation of the received signal. The detection has been studied under different channel fading conditions along with Gaussian noise. Two figures of merit are considered here; false alarm probability and detection probability. For a specific false alarm probability, the detection probabilities are calculated for different sample size and it has been established through numerical results that the proposed detector performs quite well in different channel impairments.

scholarly journals Robust Spectrum Sensing Demonstration Using a Low-Cost Front-End Receiver

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Daniele Borio ◽  
Emanuele Angiuli ◽  
Raimondo Giuliani ◽  
Gianmarco Baldini
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Spectrum Sensing ◽  
High Frequency ◽  
Detection Probability ◽  
Low Cost ◽  
False Alarm Probability ◽  
Primary Users ◽  
Front End ◽  
Challenging Tasks

Spectrum Sensing (SS) is an important function in Cognitive Radio (CR) to detect primary users. The design of SS algorithms is one of the most challenging tasks in CR and requires innovative hardware and software solutions to enhance detection probability and minimize low false alarm probability. Although several SS algorithms have been developed in the specialized literature, limited work has been done to practically demonstrate the feasibility of this function on platforms with significant computational and hardware constraints. In this paper, SS is demonstrated using a low cost TV tuner as agile front-end for sensing a large portion of the Ultra-High Frequency (UHF) spectrum. The problems encountered and the limitations imposed by the front-end are analysed along with the solutions adopted. Finally, the spectrum sensor developed is implemented on an Android device and SS implementation is demonstrated using a smartphone.

A Reliable Spectrum Sensing Strategy Based on Multiple-Antenna Technique

2013 ◽  
Vol 765-767 ◽  
pp. 2305-2308
Author(s):  
Shou Tao Lv ◽  
Ze Yang Dai ◽  
Jian Liu
Keyword(s):  
Performance Analysis ◽  
False Alarm ◽  
Closed Form ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
False Alarm Probability ◽  
Multiple Antenna ◽  
Single Antenna ◽  
Simulation Results ◽  
Present Simulation

In this paper, we propose a reliable spectrum sensing strategy based on multiple-antenna technique, called RSS-MAT, to combat the channel uncertainties. We derive the closed-form expressions of the false alarm probability and detection probability for RSS-MAT. Finally, we present simulation results to validate our performance analysis. As expected, the simulation results show that RSS-MAT outperforms the spectrum sensing strategy with single antenna.

scholarly journals Feasibility of Using a MEMS Microphone Array for Pedestrian Detection in an Autonomous Emergency Braking System

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4162
Author(s):  
Alberto Izquierdo ◽  
Lara del Val ◽  
Juan J. Villacorta
Keyword(s):  
False Alarm ◽  
Detection Probability ◽  
Light Propagation ◽  
Microphone Array ◽  
Pedestrian Detection ◽  
False Alarm Probability ◽  
Constant False Alarm Rate ◽  
Sound System ◽  
Emergency Braking ◽  
Mems Microphone

Pedestrian detection by a car is typically performed using camera, LIDAR, or RADAR-based systems. The first two systems, based on the propagation of light, do not work in foggy or poor visibility environments, and the latter are expensive and the probability associated with their ability to detect people is low. It is necessary to develop systems that are not based on light propagation, with reduced cost and with a high detection probability for pedestrians. This work presents a new sensor that satisfies these three requirements. An active sound system, with a sensor based on a 2D array of MEMS microphones, working in the 14 kHz to 21 kHz band, has been developed. The architecture of the system is based on an FPGA and a multicore processor that allow the system to operate in real time. The algorithms developed are based on a beamformer, range and lane filters, and a CFAR (Constant False Alarm Rate) detector. In this work, tests have been carried out with different people and in different ranges, calculating, in each case and globally, the Detection Probability and the False Alarm Probability of the system. The results obtained verify that the developed system allows the detection and estimation of the position of pedestrians, ensuring that a vehicle travelling at up to 50 km/h can stop and avoid a collision.

Decision Analysis of Statistically Detecting Distributed Denial-of-Service Flooding Attacks

2003 ◽  
Vol 02 (03) ◽  
pp. 397-405 ◽  
Author(s):  
Ming Li ◽  
Chi-Hung Chi ◽  
Weijia Jia ◽  
Wei Zhao ◽  
Wanlei Zhou ◽  
...  
Keyword(s):  
False Alarm ◽  
Detection Probability ◽  
Denial Of Service ◽  
False Alarm Probability ◽  
Statistical Decision ◽  
Flooding Attacks ◽  
Decision Region ◽  
High Detection ◽  
Statistical Decision Making

There are two statistical decision making questions regarding statistically detecting sings of denial-of-service flooding attacks. One is how to represent the distributions of detection probability, false alarm probability and miss probability. The other is how to quantitatively express a decision region within which one may make a decision that has high detection probability, low false alarm probability and low miss probability. This paper gives the answers to the above questions. In addition, a case study is demonstrated.

Sensing Confidence Level-Based Cooperative Spectrum Sensing Algorithm

2013 ◽  
Vol 380-384 ◽  
pp. 1499-1504
Author(s):  
Shi Ding Zhang ◽  
Hai Lian Wang ◽  
Jing Ping Mei
Keyword(s):  
False Alarm ◽  
Spectrum Sensing ◽  
Confidence Level ◽  
Detection Probability ◽  
Cooperative Spectrum Sensing ◽  
False Alarm Probability ◽  
Control Channel ◽  
Fusion Center ◽  
Local Spectrum ◽  
Secondary Users

Cooperative spectrum sensing is a key technology to tackle the challenges such as fading or hidden terminal problem in local spectrum sensing of cognitive radio system. Conventional cooperative method can improve the detection performance in some sense, but increase overhead of control channel. In order to reduce the overhead, a new cooperative spectrum sensing algorithm based on confidence level is proposed. In this algorithm, the maximum-eigenvalue-based detection scheme is carried out to obtain the local spectrum detection and the detection probability and false alarm probability of each secondary user are used to estimate the reliability of the sensing decision. The test statistic of the secondary users with high reliability are chosen and sent to fusion center. Then weighted factors of chosen secondary users are derived from creditability values, and the global decision is made by weighted fusion at fusion center. The simulation results show that the proposed algorithm improves the detection probability in the guarantee of the false-alarm probability close to 0 and saves half of the overhead in the control channel.

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