Analysis and correction of meteorological disturbance observed by ground radars in complex environment

Ground radar interferometry technology, as a new tool for active remote sensing, has been widely used in the detection of a variety of targets, including landslides, bridges, mines, and dams. This technique usually employs a continuous observation mode with no space baseline. The detection accuracy is mainly affected by meteorological disturbances and noise in the observation environment. In a complex observation environment, meteorological disturbances can lead to phase errors of 10 mm or more, and the effects are different in the range and azimuth directions; this can seriously affect the accuracy of the measurement. In this paper, we analyze the spatial distribution of the phase of meteorological disturbances based on radar monitoring experiments in a complex environment, and propose a correction method that reduces the atmospheric disturbance phase to less than 0.6 mm and effectively improves radar observation accuracy.

An Adaptability Analysis of the Space-Vehicle Traffic State Estimation Model for Sparsely Distributed Observation Environment

The autonomous driving has shown its enormous potential to become the new generation of transportation in the last decade. Based on the automated technology, vehicles can drive in a new form, vehicle platoon, which can significantly increase the efficiency of the road system and save road resources. The space-vehicle traffic state estimation model has shown its benefits in modeling autonomous vehicle platoon in nonpipeline corridors with on- and off-ramps in ideal observation environment. However, in the current initial stage of automated connected vehicles’ application, the observation environment is quite imperfect. Limited by financial and investment, traffic flow observation equipment is sparsely distributed on the road. How to adapt to the sparse observer layout is a critical issue in the current application of the space-time traffic state estimation, which is originally designed for the autonomous transportation. Therefore, this manuscript overviews the observation environment in practice and summarizes three key observation problems. This article designs 22 numerical experiments focusing on the three key issues and implements the space-time estimation model in different observation scenarios. Finally, the observation environment adaptability is analyzed in detail based on the experiment results. It is found that the accuracy of the estimation results can be improved with the highest efficiency under the premise of limited equipment input by reducing the observation interval to 1000 m and increasing the density of the observer to 1/km. For the road sections with relatively homogeneous traffic conditions, the layout of observation equipment can be relatively reduced to save the investment input. Also, the maintenance of observation equipment for the ramp with larger flow can be slowed down appropriately in limited equipment investment. This manuscript is of great practical significance to the popularization and application of connected automatic transportation.

Analysis of Space Debris Orbit Prediction Using Angle and Laser Ranging Data from Two Tracking Sites under Limited Observation Environment

The global electro-optical (EO) and laser tracking sensor network was considered to investigate improvements to orbit prediction (OP) accuracy of space debris by combining angle and laser ranging data. However, it is worth noting that weather, schedule and visibility constraints can frequently limit the operations of such sensors, which may not result in sufficient tracking data for accurate OP. In this study, several 1-day OP results for low Earth orbit (LEO) space debris targets were demonstrated under a limited observation environment to verify the OP accuracy through the combination of angle and laser ranging data from two sites. For orbit determination (OD) processes, it was considered to analyze the OP accuracy by one site providing both 2–day arc angle data and 1-day arc laser ranging data, while the other was limited to 1-day arc angle data. In addition, the initial ballistic coefficient ( B C ) application method was proposed and implemented for the improvement of OD/OP accuracy, which introduces the modified correction factor depending on the drag coefficient. In the cases of combining the angle and laser ranging data, the OP results show the 3D position difference values are below 100 m root mean square (RMS) with small position uncertainty. This value satisfies the target OP accuracy for conjunction assessments and blind laser ranging (about 50–100 m at 1000 km altitude). The initial B C application method also shows better OP accuracy than the method without the correction factor.

Use of Smartphone-Based Head-Mounted Display Devices to View a Three-Dimensional Dissection Model in a Virtual Reality Environment: Pilot Questionnaire Study (Preprint)

BACKGROUND Virtual reality (VR) technology has started to gain attention as a form of surgical support in medical settings. Likewise, the widespread use of smartphones has resulted in the development of various medical applications; for example, Google Cardboard, which can be used to build simple head-mounted displays (HMDs). However, because of the absence of observed and reported outcomes of the use of three-dimensional (3D) organ models in relevant environments, we have yet to determine the effects of or issues with the use of such VR technology. OBJECTIVE The aim of this paper was to study the issues that arise while observing a 3D model of an organ that is created based on an actual surgical case through the use of a smartphone-based simple HMD. Upon completion, we evaluated and gathered feedback on the performance and usability of the simple observation environment we had created. METHODS We downloaded our data to a smartphone (Galaxy S6; Samsung, Seoul, Korea) and created a simple HMD system using Google Cardboard (Google). A total of 17 medical students performed 2 experiments: an observation conducted by a single observer and another one carried out by multiple observers using a simple HMD. Afterward, they assessed the results by responding to a questionnaire survey. RESULTS We received a largely favorable response in the evaluation of the dissection model, but also a low score because of visually induced motion sickness and eye fatigue. In an introspective report on simultaneous observations made by multiple observers, positive opinions indicated clear image quality and shared understanding, but displeasure caused by visually induced motion sickness, eye fatigue, and hardware problems was also expressed. CONCLUSIONS We established a simple system that enables multiple persons to observe a 3D model. Although the observation conducted by multiple observers was successful, problems likely arose because of poor smartphone performance. Therefore, smartphone performance improvement may be a key factor in establishing a low-cost and user-friendly 3D observation environment.