A Real-Time Gaze Position Estimation Method Based on a 3-D Eye Model

The effective reproduction number [Formula: see text], the average number of secondary cases that are generated by a single primary case at calendar time [Formula: see text], plays a critical role in interpreting the temporal transmission dynamics of an infectious disease epidemic, while the case fatality risk (CFR) is an indispensable measure of the severity of disease. In many instances, [Formula: see text] is estimated using the reported number of cases (i.e., the incidence data), but such report often does not arrive on time, and moreover, the rate of diagnosis could change as a function of time, especially if we handle diseases that involve substantial number of asymptomatic and mild infections and large outbreaks that go beyond the local capacity of reporting. In addition, CFR is well known to be prone to ascertainment bias, often erroneously overestimated. In this paper, we propose a joint estimation method of [Formula: see text] and CFR of Ebola virus disease (EVD), analyzing the early epidemic data of EVD from March to October 2014 and addressing the ascertainment bias in real time. To assess the reliability of the proposed method, coverage probabilities were computed. When ascertainment effort plays a role in interpreting the epidemiological dynamics, it is useful to analyze not only reported (confirmed or suspected) cases, but also the temporal distribution of deceased individuals to avoid any strong impact of time dependent changes in diagnosis and reporting.

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Real-time Array Shape Estimation Method of Horizontal Suspended Linear Array Based on Non-acoustic Auxiliary Sensors

IEEE Access ◽

10.1109/access.2021.3061446 ◽

2021 ◽

pp. 1-1

Author(s):

Zonglun Che ◽

Jun Wang ◽

Jing Zhu ◽

Bingbing Zhang ◽

Yang Zhang ◽

...

Keyword(s):

Real Time ◽

Linear Array ◽

Estimation Method ◽

Shape Estimation ◽

Array Shape Estimation

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Improvement of Reliability Determination Performance of Real Time Kinematic Solutions Using Height Trajectory

Sensors ◽

10.3390/s21020657 ◽

2021 ◽

Vol 21 (2) ◽

pp. 657

Author(s):

Aoki Takanose ◽

Yoshiki Atsumi ◽

Kanamu Takikawa ◽

Junichi Meguro

Keyword(s):

Real Time ◽

Urban Areas ◽

Estimation Method ◽

Tall Buildings ◽

Autonomous Driving ◽

Reliability Estimation ◽

Height Variation ◽

Position Information ◽

Real Time Kinematic ◽

Evaluation Test

Autonomous driving support systems and self-driving cars require the determination of reliable vehicle positions with high accuracy. The real time kinematic (RTK) algorithm with global navigation satellite system (GNSS) is generally employed to obtain highly accurate position information. Because RTK can estimate the fix solution, which is a centimeter-level positioning solution, it is also used as an indicator of the position reliability. However, in urban areas, the degradation of the GNSS signal environment poses a challenge. Multipath noise caused by surrounding tall buildings degrades the positioning accuracy. This leads to large errors in the fix solution, which is used as a measure of reliability. We propose a novel position reliability estimation method by considering two factors; one is that GNSS errors are more likely to occur in the height than in the plane direction; the other is that the height variation of the actual vehicle travel path is small compared to the amount of movement in the horizontal directions. Based on these considerations, we proposed a method to detect a reliable fix solution by estimating the height variation during driving. To verify the effectiveness of the proposed method, an evaluation test was conducted in an urban area of Tokyo. According to the evaluation test, a reliability judgment rate of 99% was achieved in an urban environment, and a plane accuracy of less than 0.3 m in RMS was achieved. The results indicate that the accuracy of the proposed method is higher than that of the conventional fix solution, demonstratingits effectiveness.

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Calibration Method of Array Errors for Wideband MIMO Imaging Radar Based on Multiple Prominent Targets

Remote Sensing ◽

10.3390/rs13152997 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2997

Author(s):

Zheng Zhao ◽

Weiming Tian ◽

Yunkai Deng ◽

Cheng Hu ◽

Tao Zeng

Keyword(s):

Multiple Input Multiple Output ◽

Estimation Method ◽

Target Position ◽

Position Estimation ◽

Least Square ◽

Antenna Structure ◽

Imaging Radar ◽

Position Errors ◽

Calibration Methods ◽

Array Errors

Wideband multiple-input-multiple-output (MIMO) imaging radar can achieve high-resolution imaging with a specific multi-antenna structure. However, its imaging performance is severely affected by the array errors, including the inter-channel errors and the position errors of all the transmitting and receiving elements (TEs/REs). Conventional calibration methods are suitable for the narrow-band signal model, and cannot separate the element position errors from the array errors. This paper proposes a method for estimating and compensating the array errors of wideband MIMO imaging radar based on multiple prominent targets. Firstly, a high-precision target position estimation method is proposed to acquire the prominent targets’ positions without other equipment. Secondly, the inter-channel amplitude and delay errors are estimated by solving an equation-constrained least square problem. After this, the element position errors are estimated with the genetic algorithm to eliminate the spatial-variant error phase. Finally, the feasibility and correctness of this method are validated with both simulated and experimental datasets.

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