Average Detection Probability Research Articles

Near-Real Time Automatic Snow Avalanche Activity Monitoring System Using Sentinel-1 SAR Data in Norway

Knowledge of the spatio-temporal occurrence of avalanche activity is critical for avalanche forecasting. We present a near-real time automatic avalanche monitoring system that outputs detected avalanche polygons within roughly 10 min after Sentinel-1 SAR data are download. Our avalanche detection algorithm has an average probability of detection (POD) of 67.2% with a false alarm rate (FAR) averaging 45.9, with a maximum POD of over 85% and a minimum FAR of 24.9% compared to manual detection of avalanches. The high variability in performance stems from the dynamic nature of snow in the Sentinel-1 data. After tuning parameters of the detection algorithm, we processed five years of Sentinel-1 images acquired over a 150 × 100 km large area in Northern Norway, with the best setup. Compared to a dataset of field-observed avalanches, 77.3% were manually detectable. Using these manual detections as benchmark, the avalanche detection algorithm achieved an accuracy of 79% with high POD in cases of medium to large wet snow avalanches. For the first time, we present a dataset of spatio-temporal avalanche activity over several winters from a large region. Currently, the Norwegian Avalanche Warning Service is using our processing system for pre-operational use in three regions in Norway.

A novel analytical model for interference estimation in CR‐enabled femtocells

SummaryCommercial, multideployed cognitive femtocell base stations (CFBSs) with cognitive capabilities are envisioned as a promising approach to meet the requirement of the higher data rate in today's wireless communications with nomadic users. However, random deployment of CFBSs results in interference between primary links, ie, the link between a macrocell base station (MBS) and macrocell user equipment (MUE), and secondary links, ie, the link between a femtocell base station (FBS) and femtocell user equipment (FUE). In this research paper, different analytical expressions for statistical measures such as cumulative distribution function of outage probability (Fout) and probability distribution function (Pout) have been proposed for the CFBS system. The fading channel for the secondary and primary links is taken as mixture gamma (MG) and Rayleigh distribution, respectively. It should be noticed that MG fading is one of the most generic fading channels and has not been included for analysis of the CFBS system to date. In addition, this paper presents average detection probability ( ) for cognitive radio (CR)–enabled femtocells or the CFBS system. The numerical analysis presents the effects of various parameters such as spatial density of CFBS nodes (λ), interference tolerance threshold (βth), and transmitting power of MBS (p) and fading parameters of the channel on Fout, Pout, and . Also, the numerical analysis shows perfect agreement with the theoretical background.

Improving Hydrologic Modeling Using Cloud-Free MODIS Flood Maps

Abstract Flood mapping from satellites provides large-scale observations of flood events, but cloud obstruction in satellite optical sensors limits its practical usability. In this study, we implemented the Variational Interpolation (VI) algorithm to remove clouds from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow-Covered Area (SCA) products. The VI algorithm estimated states of cloud-hindered pixels by constructing three-dimensional space–time surfaces based on assumptions of snow persistence. The resulting cloud-free flood maps, while maintaining the temporal resolution of the original MODIS product, showed an improvement of nearly 70% in average probability of detection (POD) (from 0.29 to 0.49) when validated with flood maps derived from Landsat-8 imagery. The second part of this study utilized the cloud-free flood maps for calibration of a hydrologic model to improve simulation of flood inundation maps. The results demonstrated the utility of the cloud-free maps, as simulated inundation maps had average POD, false alarm ratio (FAR), and Hanssen–Kuipers (HK) skill score of 0.87, 0.49, and 0.84, respectively, compared to POD, FAR, and HK of 0.70, 0.61, and 0.67 when original maps were used for calibration.

Energy detector performance over log-normal fading channel with diversity reception

ABSTRACTIn this work, the performance of energy detection (ED)-based spectrum-sensing in cognitive radio (CR) networks over the Log-Normal (LN) fading channel has been analyzed. More specifically, accurate analytical expressions for the average detection probability using various diversity techniques, namely maximal ratio combining (MRC), equal gain combining (EGC), and selection combining (SC) are derived and evaluated. To get the improved system performance, the detection threshold parameter is optimized by minimizing the probability of error. The impact of the shadowing parameters on the performance of energy detectors is studied in the light of complimentary receiver operating characteristics (CROC) and area under the receiver operating characteristics curve (AUC). The derived analytical framework is generic which can be used for both integer and non-integer values of the shadowing parameters. To verify the correctness of our analysis, the derived results are corroborated via Monte-Carlo simulations.

Performance of the State-Of-The-Art Gridded Precipitation Products over Mountainous Terrain: A Regional Study over Austria

During the last decade, satellite-based precipitation products have been believed to be a potential source for forcing inputs in hydro-meteorological and agricultural models, which are essential especially over the mountains area or in basins where ground gauges are generally sparse or nonexistent. This study comprehensively evaluates several newly released precipitation products, i.e., MSWEP-V2.2, IMERG-V05B, IMERG-V06A, IMERG-V05-RT, ERA5, and SM2RAIN-ASCAT, at daily and monthly time-scales over Austria. We show that all the examined products are able to reproduce the spatial precipitation distribution over the country. MSWEP, followed by IMERG-V05B and -V06A, show the strongest agreement with in situ observations and perform better than other products with respect to spatial patterns and statistical metrics. Both IMERG and ERA5 products seem to have systematic precipitation overestimation at the monthly time-scale. IMERG-V06A performs slightly better than IMERG-V05B. With respect to heavy precipitation (P > 10 mm/day), MSWEP compare to other products demonstrate advantages in detecting precipitation events with a higher spatial average of probability of detection (POD) and lower false alarm ratio (FAR) scores skill (0.74 and 0.28), while SM2RAIN and ERA5 reveal lower POD (0.35) and higher FAR (0.56) in this precipitation range in comparison with other products. However, the ERA5 and MSWEP indicate robust average POD and FAR values with respect to light/moderate precipitation (10 mm > P ≥ 0.1 mm) with 0.94 and 0.11, respectively. Such robustness of MSWEP may be rooted in applying the daily rain gauges in calibration processes. Moreover, although all products accurately map the spatial precipitation distribution they still have difficulty capturing the effects of topography on precipitation. The overall performance of the precipitation products was lower in the peripheries of the study area where most stations are situated in the mountainous area and was higher over the low altitude regions. However, according to our analysis of the considered products, MSWEP-V2.2, followed by IMERG-V06S and -V05B, are the most suitable for driving hydro-meteorological, agricultural, and other models over mountainous terrain.

The soft-release of captive-born Kaiser’s Mountain Newt Neurergus kaiseri (Amphibia: Caudata) into a highland stream, western Iran

Captive breeding and reintroduction programs are important conservation tools and are used for increasing the number of plant and animal species worldwide. The endemic Kaiser’s Mountain Newt Neurergus kaiseri is listed as Vulnerable on the Red List by the International Union for Conservation of Nature (IUCN) and is amended to Appendix I of the Convention of International Trade on Endangered Species (CITES). In the present study, in order to learn about the survival ability of captive-born newts of N. kaiseri, we conducted a trial translocation of 15 two-year-old captive-born N. kaiseri into the highland stream in Sartakht Village, western Iran. The survival rate of these newts were determined in two stages, involving early acclimatization in mesh bags and direct release in a highland brook. In 12 surveys to the translocation site, a total of 86 individuals were identified during spring and summer. The average survival rate during the acclimatizing phase was 98 ± 0.04 %, while an average survival rate of 12 ± 0.04 % was obtained when the newts were released in the brook. Applying an average diurnal detection probability obtained for the Yellow Spotted Mountain Newt Neurergus derjugini, the overall survival rate in September when newts began the autumn withdrawal was 13%. These findings demonstrate that captive-born N. kaiseri released into the wild in controlled conditions can survive during spring and summer and provide information for future reintroduction plan of this species.

A Double Threshold-Based Cooperative Spectrum Sensing With Novel Hard-Soft Combining Over Fading Channels

In this letter, a double threshold-based log-likelihood ratio (LLR) detector with a novel hard-soft combining rule (DT-LLR-HSC) is proposed for spectrum sensing in cooperative cognitive radio networks (CRNs) under the block Rayleigh fading scenario. A novel weighted hard-soft combining scheme is adopted at the fusion center to combine local binary/energy information resulting in global binary decision. A trust-based novel weight vector estimation considering both the sensing and reporting channel signal-to-noise ratio is also proposed. Further, the proposed DT-LLR-HSC scheme is adopted in full-duplex cooperative CRNs under Nakagami-m fading channel. The analytical expressions for the average probability of detection are derived and verified for both the half-duplex and full-duplex cases.

Beam‐shape loss for multiple‐beam digital array radars

This study considers beam-shape loss (BSL) for pencil-beam digital array radars (DARs), when multiple simultaneous receive beams are formed to cover the volume illuminated by each transmit beam. A general and valid computation procedure for the BSL is derived, and curves of BSL versus average detection probability and transmit beam spacing are given, for various kinds of receive beam arrangements and target types. The results show that the BSL for multiple-beam mode is commonly less than that for single-beam mode. The computation procedure and results are extensions of conventional ones for single-beam scanning radars and would be useful for range calculation and optimum beam spacing determination for modern multiple-beam DARs.

On the Energy Detection Performance of Arbitrarily Correlated Dual Antenna Receiver for Vehicular Communication

In this letter, we investigate the energy detection performance over arbitrarily correlated Nakagami-m channels under vehicle mobility. We consider that vehicle is under the protection range of the primary user. We derive the probability density function of the received signal-to-noise ratio by means of the ratio of two distributions. Next, closed-form expression for the average probability of detection is derived considering maximal ratio combining diversity for dual-antenna branches under vehicle mobility. The numerical results demonstrate that that the impact of the arbitrary correlation under vehicle mobility in terms of receiver operating characteristic. Detection performance may vary under various antenna correlation types, such as exponential or uniform. Based on the numerical results obtained, we posit that the joint effect of high-antenna correlation and mobility of vehicle can degrade detection performance with a single antenna; furthermore, dual-antenna branches can provide a remedy to the deterioration.

Smart Traffic-Aware Primary User Emulation Attack and Its Impact on Secondary User Throughput Under Rayleigh Flat Fading Channel

In this paper, an agile smart attacker model in spectrum sensing of cognitive radio network (CRN) is introduced. This smart attacker does not make the channel busy all the time, instead it senses spectrum and when a primary user leaves, it occupies the spectrum by mimicking the signal characteristics of the primary users. To model such a smart attacker, we use a dependent Markov chain to model the primary user and primary user emulation attacker activities, simultaneously. We derive the transition probabilities for the assumed dependent Markov model. Then, the effect of the primary user and attacker traffic on a secondary user’s throughput under Rayleigh flat fading channel is investigated and closed form expressions are derived for the average probability of detection and false alarm. Furthermore, the impact of this attacker on the performance of a CRN and the throughput of the secondary user network is studied analytically. We also derive a test rule based on the generalized likelihood ratio test, to detect the legitimate user from smart illegitimate user. In addition, launching primary user emulation attacker in the conventional and proposed smart attacking procedures are compared, where the results demonstrate that by using smart attacking, the deterioration in throughput of the secondary user’s network is considerable. In fact, it is shown that under proper selection of the traffic parameters, the secondary user’s network throughput may tend toward zero. Finally, the accuracy of the obtained results are analyzed and verified by the simulation results.

Entropy and Energy Detection-Based Spectrum Sensing Over $\mathcal{F}$ -Composite Fading Channels

In this paper, we investigate the performance of energy detection-based spectrum sensing over $\mathcal {F}$ composite fading channels. To this end, an analytical expression for the average detection probability is first derived. This expression is then extended to account for collaborative spectrum sensing, square-law selection diversity reception, and noise power uncertainty. The corresponding receiver operating characteristics (ROC) are analyzed for different conditions of the average signal-to-noise ratio (SNR), noise power uncertainty, time-bandwidth product, multipath fading, shadowing, number of diversity branches, and number of collaborating users. It is shown that the energy detection performance is sensitive to the severity of the multipath fading and the amount of shadowing, whereby even small variations in either of these physical phenomena can significantly impact the detection probability. As a figure of merit to evaluate the detection performance, the area under the ROC curve (AUC) is derived and evaluated for different multipath fading and shadowing conditions. Closed-form expressions for the differential entropy and cross entropy are also formulated and assessed for different average SNR, multipath fading, and shadowing conditions. Then, the relationship between the differential entropy of $\mathcal {F}$ composite fading channels and the corresponding ROC/AUC is examined where it is shown that the average number of bits required for encoding a signal becomes small (i.e., low differential entropy) when the detection probability is high or when the AUC is large. The difference between composite fading and traditional small-scale fading is emphasized by comparing the cross entropy for Rayleigh and Nakagami- $m$ fading. A validation of the analytical results is provided through a careful comparison with the results of some simulations.

An integrated performance evaluation of ED‐based spectrum sensing over α−κ−μ and α−κ−μ‐Extreme fading channels

AbstractThis paper presents a comparative performance evaluation of energy detector (ED) under the assumption that the propagation signal experiences fading modeled by the nonlinear generalized α−κ−μ or α−κ−μ‐Extreme fading channels. Novel closed‐form analytical expressions for the average probability of detection and the average area under the receiver operating characteristic (ROC) curve (AUC) are derived in terms of the now highly prevalent bivariate Fox H‐function under single‐user spectrum sensing, cooperative spectrum sensing, and square law selection diversity reception. The results derived in the present work are generic as both channel models are compound distributions containing as special cases several other well‐known fading models such as the Nakagami‐m, Rice, the one‐sided Gaussian distribution, and the Weibull distribution, among others. The performance of ED is evaluated by employing the traditional ROC and AUC curves over additive white Gaussian noise by varying model parameters and observing system performances. Analytical results are verified via Monte Carlo simulations in MATLAB®.

Performance Analysis of Improved Energy Detector With Hardware Impairments for Accurate Spectrum Sensing

The impact of transceiver hardware impairments on the accuracy of spectrum sensing cannot be ignored in low-cost and high data rate cognitive radio systems. Nevertheless, ideal hardware for spectrum sensing is widely assumed in the technical literature. This paper presents a novel method for evaluating the improved energy detector (IED) statistics using α-μ distribution over additive white Gaussian noise (AWGN) and Nakagami-m fading channel by considering transceiver hardware imperfections. Moreover, the performance of the IED over AWGN channel is highlighted by the area under the receiver operating curve. Furthermore, the average probability of detection is evaluated for both fading and non-fading environments. An asymptotic analysis studies detection probability over fading channels at a low average signal-to-noise-ratio region. Moreover, p-order law combining and p-order law selecting diversity techniques are proposed to increase the performance of the detector. Our simulation results demonstrate that the diversity techniques significantly improve the detector performance.

Quantum Multi-User Detection Based on Coherent State Signals

Multi-user detection is one of the important technical problems for modern communications. In the field of quantum communication, the multi-access channel on which we apply the technology of quantum information processing is still an open question. In this work, we investigate the multi-user detection problem based on the binary coherent-state signals whose communication way is supposed to be seen as a quantum channel. A binary phase shift keying model of this multi-access channel is studied and a novel method of quantum detection proposed according to the conclusion of the quantum measurement theory. As a result, the average interference between deferent users is presented and the average error probability of the quantum detection is derived theoretically. Finally, we show the maximum channel capacity of this effective detection for a two-access quantum channel

Modelling and performance analysis of energy detector-based spectrum sensing with maximum ratio combining over Nakagami-m/log-normal fading channels

Spectrum sensing (SS) is one of the crucial functions of cognitive radio networks (CRNs). It decides whether the band or sub-band of the spectrum is available or not for secondary users (SUs). Energy detection (ED) is one of the very fundamental approaches of SS to detect whether primary users (PUs) are present or absent. It is mathematically intractable to derive closed-form expressions of composite multipath/shadowing for average probability of detection and average area under the receiver operating characteristic curve. In this paper, we have considered Nakagami-m/log-normal as composite fading with maximum ratio combining (MRC) diversity, and it is approximated by Gaussian-Hermite integration (G-HI). In addition, adaptive threshold or optimised threshold has been incorporated to overcome the problem of spectrum sensing at low signal-to-noise ratio (SNR). To verify the correctness of exact results and obtained analytical expression is collaborated with Monte Carlo simulations.

Impact of Interbranch Correlation on Multichannel Spectrum Sensing With SC and SSC Diversity Combining Schemes

Multiantenna receivers are often deployed in cognitive radio systems for accurate spectrum sensing. However, correlation among signals received by multiple antennas in these receivers is often ignored which yields unrealistic results. In this paper, the effect of this correlation is accurately quantified by deriving analytical expressions for the average probability of detection. Alternative simpler expressions are also derived. These are done for selection combining (SC) and switch and stay combining (SSC) diversity techniques in dual arbitrarily correlated Nakagami- $m$ fading channels. Then, it is repeated for triple exponentially and identically correlated Nakagami- $m$ fading channels with SC diversity technique. Analysis results show that the interbranch correlation impacts the detector performance significantly, especially in deep fading scenarios. Also, SC outperforms SSC as expected. However, the difference between them becomes very small in low fading and highly correlated scenarios, which indicates that the simpler SSC scheme can as well be deployed in such situations.

Plume detection modeling of a drone-based natural gas leak detection system

Interest has grown in using new screening technologies such as drones to search for methane leaks in hydrocarbon production infrastructure. Screening technologies may be less expensive and faster than traditional methods. However, including new technologies in emissions monitoring programs requires an accurate understanding of what leaks a system will detect and the resultant emissions mitigation. Here we examine source detection of a drone-based system with controlled releases. We examine different detection algorithm parameters to understand trade-offs between false positive rate and detection probability. Leak detection was poor under all conditions with an average detection probability of 0.21. Detection probability was not affected by emission rate, suggesting similar systems may commonly miss large leaks. Detection was best in moderate wind speeds and at 750–2000 m downwind from the source where the plume had diffused vertically above the minimum flight level of 40–50 m. Predicted concentration enhancement from a Gaussian plume model was a reasonable predictor of detection within the test suite. Enabling lower flight elevations may increase detection probability. Overall, the experiments suggest that controlled releases are useful and necessary to provide an understanding of detection probability of screening technologies for regulatory and deployment purposes, and the testing must be representative to support broad application.

Development of Fog Detection Algorithm during Nighttime Using Himawari-8/AHI Satellite and Ground Observation Data

In this study, we developed a hybrid nighttime fog detection algorithm based on the optical and textural characteristics of fog from Himawari-8/ advanced Himawari imager (AHI) data and ground temperature data. The Dual Cannel Difference (DCD) caused by the emissivity difference between the 3.9 and 11.2 μm is the main evaluation element for fog detection. And, the local standard deviation of Brightness Temperature (BT) and difference between fog top BT and ground temperature (sea surface temperature) were used to distinguish between fog and low cloud. The thresholds and weights of the three evaluation elements were initially determined by visual inspection of fog cases and optimized through receiver operating characteristics analysis using training cases. Although the level of fog detection differs depending on the fog intensity and weather conditions, the quantitative evaluation of results using ground observed visibility data showed that average probability of detection and false alarm ratio are 0.64 (0.24 ~ 0.89) and 0.56 (0.33 ~ 0.71), respectively. We performed sensitivity tests for fog detection methods because the detection levels can be affected by fog detection method. As a result, the Weighted Sum Method (WSM) showed a slightly lowered detection level compared to that of the Simple Decision Tree (SDT), average differences, hit rate, hanssen-kuiper skill score, threat score, and bias are −0.31, 0.01, −0.12, and 2.07, respectively. And more works are needed for the improvement of fog detection levels through the sophistication of thresholds and weights using more cases, because detection level is sensitive to fog cases.

New approximate expressions of average symbol error probability, probability of detection and AUC with MRC over generic and composite fading channels

The present work covers the wide range of distributions and proposes the moment generating function (MGF) based analytical framework to derive the average symbol error probability (SEP), the average probability of detection (PD), and the average area under the receiver operating characteristic curve (AUC) for the wireless system with maximal ratio combining (MRC) diversity. The proposed solutions are expressed in terms of Fox’s H and bivariate Fox’s H-functions which are widely being used in the current literature. Finally, the analytical framework, thus proposed has been used in applications, such as ultra-wideband (UWB) single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) system and the impact of the number of transmitting and receiving antennas for MIMO system over the average SEP has been analysed. The correctness of the proposed solutions has been corroborated by comparing them with Monte-Carlo simulation.

ED performance over [formula omitted]/IG and [formula omitted]/IG generalized fading channels with diversity reception and cooperative sensing: A unified approach

This study investigates the unified performance analysis of an energy detector (ED) over α-η-μ/IG and α-κ-μ/IG generalized fading channels. The probability density functions (PDF) of the received signal-to-noise ratio (SNR) for the composite fading channels are derived using Gauss-Laguerre method. Novel analytical expressions for the average probability of detection (PD) for a single user and cooperative spectrum sensing (SS) are derived. The effects of diversity and noise uncertainty on the average PD are also presented. Rapidly convergent infinite series representations for the average PD are derived in terms of the upper bound of the truncation error. These expressions are used to analyze the behavior of ED-based SS over moderate, severe and extreme fading conditions, and to investigate the use of cooperation and diversity as a means of mitigating the fading effects. The accuracy of the derived expressions is validated through comparison of results obtained by Monte-Carlo simulations.