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At least 883 records · Page 49

Discrete-time Design of Tracking Control Loop for Optical Communications

The methodology for discrete-time design of a fine steering mirror tracking control loop is presented. It is shown tha high tracking accuracy can be achieve for optical communications by using low cost fine steering mirrors and moderate sampling rates.

Optical Communications Tracking Discrete-Time Cont↗

Target Tracking, Approach, and Camera Handoff for Automated Instrument Placement

This paper describes the target designation, tracking, approach, and camera handoff technologies required to achieve accurate, single-command autonomous instrument placement for a planetary rover. It focuses on robust tracking integrated with obstacle avoidance during the approach phase, and image-based camera handoff to allow vision-based instrument placement. It also provides initial results from a complete system combining these technologies with rover base placement to maximize arm manipulability and image-based instrument placement.

target tracking↗

Earth-Image Tracking in the IR for Deep Space Optical Communications

Sub-microradian level laser beam pointing to an Earth-based receiver is required for deep space optical communications. This requires a beacon emanated from Earth towards the spacecraft. The beacon could be a laser or reflected sunlight from Earth. Earth image tracking in the visible is hampered by significant albedo variations and/or crescent Earth image yielding large central errors. Here, we report results of Earth-image tracking in the infrared (8 to 13 micron) region of the spectrum with the aim of substantially alleviating the two challenges mentioned earlier.

earth image tracking↗

Using WorldView-2 Imagery to Track Flooding in Thailand in a Multi-Asset Sensorweb

For the flooding seasons of 2011-2012 multiple space assets were used in a "sensorweb" to track major flooding in Thailand. Worldview-2 multispectral data was used in this effort and provided extremely high spatial resolution (2m / pixel) multispectral (8 bands at 0.45-1.05 micrometer spectra) data from which mostly automated workflows derived surface water extent and volumetric water information for use by a range of NGO and national authorities. We first describe how Worldview-2 and its data was integrated into the overall flood tracking sensorweb. We next describe the use of Support Vector Machine learning techniques that were used to derive surface water extent classifiers. Then we describe the fusion of surface water extent and digital elevation map (DEM) data to derive volumetric water calculations. Finally we discuss key future work such as speeding up the workflows and automating the data registration process (the only portion of the workflow requiring human input).

surface water extent↗

Tracking Performance of Upgraded "Polished Panel" Optical Receiver on NASA's 34 Meter Research Antenna

There has been considerable interest in developing and demonstrating a hybrid "polished panel" optical receiver concept that would replace the microwave panels on the Deep Space Network's (DSN) 34 meter antennas with highly polished aluminum panels, thus enabling simultaneous opticaland microwave reception. A test setup has been installed on the 34 meter research antenna at DSS-13 (Deep Space Station 13) at NASA's Goldstone Deep Space Communications Complex in California in order to assess the feasibility of this concept. Here we describe the results of a recent effort todramatically reduce the dimensions of the point-spread function (PSF) generated by a custom polished panel, thus enabling improved optical communications performance. The latest results are compared to the previous configuration in terms of quantifiable PSF improvement. In addition, the performance of acquisition and tracking algorithms designed specifically for the polished panel PSF are evaluated and compared, based on data obtained from real-time tracking of planets and bright stars with the 34 meter research antenna at DSS-13.

optima↗

Detection, Localization, and Tracking of Unauthorized UAS and Jammers

Small unmanned aircraft systems (UASs) are expected to take major roles in future smart cities, for example, by delivering goods and merchandise, potentially serving as mobile hot spots for broadband wireless access, and maintaining surveillance and security. Although they can be used for the betterment of the society, they can also be used by malicious entities to conduct physical and cyber attacks to infrastructure, private/public property, and people. Even for legitimate use-cases of small UASs, air traffic management (ATM) for UASs becomes of critical importance for maintaining safe and collusion-free operation. Therefore, various ways to detect, track, and interdict potentially unauthorized drones carries critical importance for surveillance and ATM applications. In this paper, we will review techniques that rely on ambient radio frequency signals (emitted from UASs), radars, acoustic sensors, and computer vision techniques for detection of malicious UASs. We will present some early experimental and simulation results on radar-based range estimation of UASs, and receding horizon tracking of UASs. Subsequently, we will overview common techniques that are considered for interdiction of UASs.

surveillance↗

Fire Front Detection and Tracking for Autonomous sUAS in STEReO

The Scalable Traffic Management Emergency Response Operations (STEReO) project aims to incorporate unmanned aerial systems (UAS) into wildfire incident response to safely quicken response times, improve operator awareness, and scale-up aircraft operations.Autonomous UAS can be used to relieve human operators of dull, dirty, and dangerous tasks such as checking for re-ignitions and geo-locating fires. To geo-locate fires, the UAS must be able to detect whether a fire is present and also have the necessary information to stamp a location. Furthermore, the UAS should be able to track the fire front to determine the extent of the fire. This study presents a fire front detection and tracking methodology for an autonomous small UAS (sUAS). The methodology is evaluated in simulation.

Autonomous UAV,Wildfire,Detection,Tracking↗

Automated Generation of Tracking Plans for a Network of Communication Antennas

This paper describes the Deep Space Network Antenna Operations Planner (DPLAN), a system for automatically generating antenna tracking plans for an automated set of highly sensitive radio science and telecommunications antennas. DPLAN accepts current equipment configuration information and a set of requested track services and uses a knowledge base of antenna operations procedures to produce a plan of activities to provide the services using the allocated equipment.

Deep↗

Radiotelescope Low Rate Tracking Using Dither

Radiotelescope access to a certain part of the sky requires very low tracking rate in azimuth. The improvement of the low-rate tracking pointing throught the dither implementation is discussed in this paper

Radiotelescope↗

Chapter 10: Development of a Precipitation Retrieval Scheme for Cross-track Passive Microwave Sounding Instruments

The measurement of precipitation (snowfall and rainfall) across the globe is of great importance to both science and society. Despite the importance, measurements from surface-based instruments are limited in extent and are generally absent from sparsely populated or inhospitable regions, including over the world’s oceans. Satellite-based observations have the potential to provide the necessary information to generate estimates of precipitation across the whole of the Earth’s surface. However, adequate temporal and spatial sampling is required to capture vagaries of precipitation and it is necessary to exploit all possible satellite (and, where appropriate surface) information. While much research has been carried out into the retrieval of precipitation from observations gathered by conically-scanning passive microwave imagers in previous decades, relatively little has been done to fully utilise the observations from the cross-track scanning passive microwave sounding instruments. This paper will review a number of cross-track precipitation retrieval schemes, together an evaluation of their performance, and future directions.

Precipitation retrievals↗

Adaptive Multi-Sensor Fusion Based Object Tracking for Autonomous Urban Air Mobility Operations

Autonomous operations are a crucial aspect in the context of Urban Air Mobility and other emerging aviation markets. In order to enable this autonomy, systems must be able to build independently an accurate and detailed understanding of the own vehicle state as well as the surrounding environment, this includes detecting and avoiding moving objects in the sky, which can be cooperative (aircraft, UAM vehicles, etc.) as well as noncooperative (smaller drones, birds, ...). This paper focuses on the object tracking part that relies on adaptive multi-sensor fusion, taking into account specific properties and limitations of different sensor types. Results show the impact of dropouts of individual sensors on the accuracy of the tracking results for this adaptive sensor fusion approach.

sensor fusion↗