scholarly journals Measurement-Driven Multi-Target Multi-Bernoulli Filter

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Shijie Li ◽  
Humin Lei
Keyword(s):  
Detection Probability ◽  
Traditional Methods ◽  
Target Distribution ◽  
Detection Probabilities ◽  
High Detection ◽  
Bernoulli Filter ◽  
Simulation Results ◽  
The Stability ◽  
Stability And Accuracy

A measurement-driven multi-target multi-Bernoulli (MeMBer) filter which modifies the MeMBer filter by the measurements information is proposed in this paper. The proposed filter refines both the legacy estimates and the data-induced estimates of the MeMBer filter. For the targets under the legacy track set, the detection probabilities derived from the measurements are employed to refine the multi-target distribution. And for the targets under the data-induced track set, the multi-target distribution is further improved by the modified existence probabilities of the legacy tracks. Unlike the cardinality balanced MeMBer (CBMeMBer) filter, the proposed filter removes the cardinality bias in the MeMBer filter by utilizing the measurements information. Simulation results show that, compared with the traditional methods, the proposed filter can improve the stability and accuracy of the estimates and does not need the high detection probability hypothesis.

scholarly journals A Novel Structure for a Multi-Bernoulli Filter without a Cardinality Bias

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1484
Author(s):  
Weijian Si ◽  
Hongfan Zhu ◽  
Zhiyu Qu
Keyword(s):  
Detection Probability ◽  
Posterior Probability ◽  
Density Approximation ◽  
Signal To Noise ◽  
Generating Functional ◽  
Significant Bias ◽  
Novel Structure ◽  
High Detection ◽  
Multi Target Tracking ◽  
Bernoulli Filter

The original multi-target multi-Bernoulli (MeMBer) filter for multi-target tracking (MTT) is shown analytically to have a significant bias in its cardinality estimation. A novel cardinality balance multi-Bernoulli (CBMeMBer) filter reduces the cardinality bias by calculating the exact cardinality of the posterior probability generating functional (PGFl) without the second assumption of the original MeMBer filter. However, the CBMeMBer filter can only have a good performance under a high detection probability, and retains the first assumption of the MeMBer filter, which requires measurements that are well separated in the surveillance region. An improved MeMBer filter proposed by Baser et al. alleviates the cardinality bias by modifying the legacy tracks. Although the cardinality is balanced, the improved algorithm employs a low clutter density approximation. In this paper, we propose a novel structure for a multi-Bernoulli filter without a cardinality bias, termed as a novel multi-Bernoulli (N-MB) filter. We remove the approximations employed in the original MeMBer filter, and consequently, the N-MB filter performs well in a high clutter intensity and low signal-to-noise environment. Numerical simulations highlight the improved tracking performance of the proposed filter.

Factors influencing detection probabilities of frogs in the monsoonal tropics of northern Australia: implications for the design of monitoring studies

2013 ◽  
Vol 40 (5) ◽  
pp. 393 ◽  
Author(s):  
P. L. Dostine ◽  
S. J. Reynolds ◽  
A. D. Griffiths ◽  
G. R. Gillespie
Keyword(s):  
Detection Probability ◽  
Individual Species ◽  
Sampling Effort ◽  
Northern Australia ◽  
Wet Season ◽  
Factors Influencing ◽  
Detection Probabilities ◽  
High Detection ◽  
Frog Species ◽  
A Site

Context Failure to acknowledge potential bias from imperfect detection of cryptic organisms such as frogs may compromise survey and monitoring programmes targeting these species. Aims The aims of the present study were to identify proximate factors influencing detection probabilities of a range of frog species in monsoonal northern Australia, and to estimate the number of repeat censuses required at a site to have confidence that non-detected species are absent. Methods Data on detection or non-detection of frog species based on calling individuals were recorded during 10 wet-season censuses of 29 survey sites in the Darwin region. Factors influencing detection probabilities were identified using occupancy models; model selection was based on the Akaike information criterion. Sampling effort for individual species was calculated using model predictions at different stages of the wet season. Key results The covariate water temperature featured in the best-supported models for 7 of the 14 frog species. Six of these species were more likely to be detected when water temperatures were below 30°C. Detection probabilities were also correlated with the number of days since the commencement of the wet season, time since last significant rainfall, air temperature and time after sunset. Required sampling effort for individual species varied throughout the wet season. For example, a minimum of two repeat censuses was required for detection of Litoria caerulea in the early wet season, but this number increased to 13 in the middle stage of the wet season. Conclusions Variability in environmental conditions throughout the wet season leads to variability in detection probabilities of frog species in northern Australia. Lower water temperatures, mediated by rainfall immediately before or during surveys, enhances detectability of a range of species. For most species, three repeat surveys under conditions resulting in a high detection probability are sufficient to determine presence at a site. Implications Survey and monitoring programmes for frogs in tropical northern Australia will benefit from the results of the present study by allowing targeting of conditions of high detection probability for individual species, and by incorporating sufficient repeat censuses to provide accurate assessment of the status of individual species at a site.

Detection Probability of Airborne AIS

2013 ◽  
Vol 401-403 ◽  
pp. 1204-1207 ◽  
Author(s):  
She Xiang Ma ◽  
Jin Sun ◽  
Yong Qiang Guan
Keyword(s):  
Calculation Method ◽  
Detection Probability ◽  
Probability Model ◽  
Complicated Structure ◽  
Transmission Distance ◽  
Detection Probabilities ◽  
Simulation Results ◽  
The Relationship ◽  
Maximum Transmission

Aiming at the small coverage of shore-based AIS and complicated structure of space-based AIS, airborne AIS is chosen to increase the coverage effectively. This paper gives the calculation method of the maximum transmission distance, and then establishes the detection probability model of the airborne AIS. The relationship between reporting interval, ship densities and detection probabilities is established. At the end of the paper, simulation results of the model are given.

scholarly journals Horizontal or vertical? Camera trap orientations and recording modes for detecting potoroos, bandicoots and pademelons

2014 ◽  
Vol 36 (1) ◽  
pp. 60 ◽  
Author(s):  
Brendan D. Taylor ◽  
Ross L. Goldingay ◽  
John M. Lindsay
Keyword(s):  
Detection Probability ◽  
New South ◽  
Population Monitoring ◽  
Camera Trap ◽  
Probability Of Detection ◽  
Camera Traps ◽  
North East ◽  
South Wales ◽  
Detection Probabilities ◽  
The Stability

Camera traps can detect rare and cryptic species, and may enable description of the stability of populations of threatened species. We investigated the relative performance of cameras oriented horizontally or vertically, and recording mode (still and video) to detect the vulnerable long-nosed potoroo (Potorous tridactylus) as a precursor to population monitoring. We established camera traps for periods of 13–21 days across 21 sites in Richmond Range National Park in north-east New South Wales. Each camera trap set consisted of three KeepGuard KG680V cameras directed at a bait container – one horizontal and one vertical camera in still mode and one horizontal camera in video mode. Potoroos and bandicoots (Perameles nasuta and Isoodon macrourus) were detected at 14 sites and pademelons (Thylogale stigmatica and T. thetis) were detected at 19 sites. We used program Presence to compare detection probabilities for each camera category. The detection probability for all three taxa groups was lowest for the vertical still and similar for the horizontal cameras. The detection probability (horizontal still) was highest for the potoroos (0.43) compared with the bandicoots (0.16) and pademelons (0.25). We estimate that the horizontal stills camera could achieve a 95% probability of detection of a potoroo within 6 days compared with 8 days using a vertical stills camera. This suggests that horizontal cameras in still mode have great potential for monitoring the dynamics of this potoroo population.

scholarly journals Analysis of Low Probability of Detection Capability for Chaotic Standard Map-Based FH-OFDMA System

2021 ◽  
Vol 11 (5) ◽  
pp. 2198
Author(s):  
Junwoo Jung ◽  
Jaesung Lim ◽  
Sungyeol Park ◽  
Haengik Kang ◽  
Seungbok Kwon
Keyword(s):  
Detection Probability ◽  
Probability Of Detection ◽  
Lower Probability ◽  
Symbol Sequence ◽  
Ofdma System ◽  
Standard Map ◽  
Detection Probabilities ◽  
Low Probability ◽  
Transmitted Symbol ◽  
Basic Symbol

A frequency hopping orthogonal frequency division multiple access (FH-OFDMA) can provide low probability of detection (LPD) and anti-jamming capabilities to users against adversary detectors. To obtain an extreme LPD capability that cannot be provided by the basic symbol-by-symbol (SBS)-based FH pattern, we proposed two FH patterns, namely chaotic standard map (CSM) and cat map for FH-OFDMA systems. In our previous work, through analysis of complexity to regenerate the transmitted symbol sequence, at the point of adversary detectors, we found that the CSM had a lower probability of intercept than the cat map and SBS. It is possible when a detector already knows symbol and frame structures, and the detector has been synchronized to the FH-OFDMA system. Unlike the previous work, here, we analyze whether the CSM provides greater LPD capability than the cat map and SBS by detection probability using spectrum sensing technique. We analyze the detection probability of the CSM and provide detection probabilities of the cat map and SBS compared to the CSM. Based on our analysis of the detection probability and numerical results, it is evident that the CSM provides greater LPD capability than both the cat map and SBS-based FH-OFDMA systems.

scholarly journals Underground Microseismic Event Monitoring and Localization within Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2830
Author(s):  
Sili Wang ◽  
Mark P. Panning ◽  
Steven D. Vance ◽  
Wenzhan Song
Keyword(s):  
Sensor Networks ◽  
Real Time ◽  
Information Needs ◽  
Localization Algorithm ◽  
Distributed Sensors ◽  
Distributed Sensor ◽  
Microseismic Events ◽  
The Stability ◽  
Stability And Accuracy

Locating underground microseismic events is important for monitoring subsurface activity and understanding the planetary subsurface evolution. Due to bandwidth limitations, especially in applications involving planetarily-distributed sensor networks, networks should be designed to perform the localization algorithm in-situ, so that only the source location information needs to be sent out, not the raw data. In this paper, we propose a decentralized Gaussian beam time-reverse imaging (GB-TRI) algorithm that can be incorporated to the distributed sensors to detect and locate underground microseismic events with reduced usage of computational resources and communication bandwidth of the network. After the in-situ distributed computation, the final real-time location result is generated and delivered. We used a real-time simulation platform to test the performance of the system. We also evaluated the stability and accuracy of our proposed GB-TRI localization algorithm using extensive experiments and tests.

scholarly journals Explicit parallel co-simulation approach: analysis and improved coupling method based on H-infinity synthesis

2021 ◽  
Author(s):  
Weitao Chen ◽  
Shenhai Ran ◽  
Canhui Wu ◽  
Bengt Jacobson
Keyword(s):  
Frequency Domain ◽  
Wide Frequency Range ◽  
Coupling Method ◽  
Sampled Data ◽  
H Infinity ◽  
First Case ◽  
Communication Step ◽  
Coupling Variables ◽  
The Stability ◽  
Stability And Accuracy

AbstractCo-simulation is widely used in the industry for the simulation of multidomain systems. Because the coupling variables cannot be communicated continuously, the co-simulation results can be unstable and inaccurate, especially when an explicit parallel approach is applied. To address this issue, new coupling methods to improve the stability and accuracy have been developed in recent years. However, the assessment of their performance is sometimes not straightforward or is even impossible owing to the case-dependent effect. The selection of the coupling method and its tuning cannot be performed before running the co-simulation, especially with a time-varying system.In this work, the co-simulation system is analyzed in the frequency domain as a sampled-data interconnection. Then a new coupling method based on the H-infinity synthesis is developed. The method intends to reconstruct the coupling variable by adding a compensator and smoother at the interface and to minimize the error from the sample-hold process. A convergence analysis in the frequency domain shows that the coupling error can be reduced in a wide frequency range, which implies good robustness. The new method is verified using two co-simulation cases. The first case is a dual mass–spring–damper system with random parameters and the second case is a co-simulation of a multibody dynamic (MBD) vehicle model and an electric power-assisted steering (EPAS) system model. Experimental results show that the method can improve the stability and accuracy, which enables a larger communication step to speed up the explicit parallel co-simulation.

scholarly journals A Digital Framework to Predict the Sunshine Requirements of Landscape Plants

2021 ◽  
Vol 11 (5) ◽  
pp. 2098
Author(s):  
Heyi Wei ◽  
Wenhua Jiang ◽  
Xuejun Liu ◽  
Bo Huang
Keyword(s):  
Solar Radiation ◽  
Plant Species ◽  
Large Scale ◽  
Normal Growth ◽  
Adaptive Selection ◽  
Landscape Plant ◽  
Landscape Plants ◽  
The Stability ◽  
Stability And Accuracy ◽  
The City

Knowledge of the sunshine requirements of landscape plants is important information for the adaptive selection and configuration of plants for urban greening, and is also a basic attribute of plant databases. In the existing studies, the light compensation point (LCP) and light saturation point (LSP) have been commonly used to indicate the shade tolerance for a specific plant; however, these values are difficult to adopt in practice because the landscape architect does not always know what range of solar radiation is the best for maintaining plant health, i.e., normal growth and reproduction. In this paper, to bridge the gap, we present a novel digital framework to predict the sunshine requirements of landscape plants. First, the research introduces the proposed framework, which is composed of a black-box model, solar radiation simulation, and a health standard system for plants. Then, the data fitting between solar radiation and plant growth response is used to obtain the value of solar radiation at different health levels. Finally, we adopt the LI-6400XT Portable Photosynthetic System (Li-Cor Inc., Lincoln, NE, USA) to verify the stability and accuracy of the digital framework through 15 landscape plant species of a residential area in the city of Wuhan, China, and also compared and analyzed the results of other researchers on the same plant species. The results show that the digital framework can robustly obtain the values of the healthy, sub-healthy, and unhealthy levels for the 15 landscape plant species. The purpose of this study is to provide an efficient forecasting tool for large-scale surveys of plant sunshine requirements. The proposed framework will be beneficial for the adaptive selection and configuration of urban plants and will facilitate the construction of landscape plant databases in future studies.

scholarly journals Prediction and Stability Assessment of Soft Foundation Settlement of the Fishbone-Shaped Dike Near the Estuary of the Yangtze River Using Machine Learning Methods

2021 ◽  
Vol 13 (7) ◽  
pp. 3744
Author(s):  
Mingcheng Zhu ◽  
Shouqian Li ◽  
Xianglong Wei ◽  
Peng Wang
Keyword(s):  
Extreme Learning Machine ◽  
Prediction Models ◽  
Good Prediction ◽  
Foundation Settlement ◽  
Machine Method ◽  
Settlement Prediction ◽  
Soft Foundation ◽  
Simulation Results ◽  
Learning Machine ◽  
The Stability

Fishbone-shaped dikes are always built on the soft soil submerged in the water, and the soft foundation settlement plays a key role in the stability of these dikes. In this paper, a novel and simple approach was proposed to predict the soft foundation settlement of fishbone dikes by using the extreme learning machine. The extreme learning machine is a single-hidden-layer feedforward network with high regression and classification prediction accuracy. The data-driven settlement prediction models were built based on a small training sample size with a fast learning speed. The simulation results showed that the proposed methods had good prediction performances by facilitating comparisons of the measured data and the predicted data. Furthermore, the final settlement of the dike was predicted by using the models, and the stability of the soft foundation of the fishbone-shaped dikes was assessed based on the simulation results of the proposed model. The findings in this paper suggested that the extreme learning machine method could be an effective tool for the soft foundation settlement prediction and assessment of the fishbone-shaped dikes.

scholarly journals Latency-Optimal Computational Offloading Strategy for Sensitive Tasks in Smart Homes

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2347
Author(s):  
Yanyan Wang ◽  
Lin Wang ◽  
Ruijuan Zheng ◽  
Xuhui Zhao ◽  
Muhua Liu
Keyword(s):  
Queue Length ◽  
Optimization Problem ◽  
Time Slot ◽  
Smart Homes ◽  
Back Pressure ◽  
Smart Devices ◽  
Smart Device ◽  
Simulation Results ◽  
Computational Offloading ◽  
The Stability

In smart homes, the computational offloading technology of edge cloud computing (ECC) can effectively deal with the large amount of computation generated by smart devices. In this paper, we propose a computational offloading strategy for minimizing delay based on the back-pressure algorithm (BMDCO) to get the offloading decision and the number of tasks that can be offloaded. Specifically, we first construct a system with multiple local smart device task queues and multiple edge processor task queues. Then, we formulate an offloading strategy to minimize the queue length of tasks in each time slot by minimizing the Lyapunov drift optimization problem, so as to realize the stability of queues and improve the offloading performance. In addition, we give a theoretical analysis on the stability of the BMDCO algorithm by deducing the upper bound of all queues in this system. The simulation results show the stability of the proposed algorithm, and demonstrate that the BMDCO algorithm is superior to other alternatives. Compared with other algorithms, this algorithm can effectively reduce the computation delay.

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