285 research outputs found

    Optimization of Planck/LFI on--board data handling

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    To asses stability against 1/f noise, the Low Frequency Instrument (LFI) onboard the Planck mission will acquire data at a rate much higher than the data rate allowed by its telemetry bandwith of 35.5 kbps. The data are processed by an onboard pipeline, followed onground by a reversing step. This paper illustrates the LFI scientific onboard processing to fit the allowed datarate. This is a lossy process tuned by using a set of 5 parameters Naver, r1, r2, q, O for each of the 44 LFI detectors. The paper quantifies the level of distortion introduced by the onboard processing, EpsilonQ, as a function of these parameters. It describes the method of optimizing the onboard processing chain. The tuning procedure is based on a optimization algorithm applied to unprocessed and uncompressed raw data provided either by simulations, prelaunch tests or data taken from LFI operating in diagnostic mode. All the needed optimization steps are performed by an automated tool, OCA2, which ends with optimized parameters and produces a set of statistical indicators, among them the compression rate Cr and EpsilonQ. For Planck/LFI the requirements are Cr = 2.4 and EpsilonQ <= 10% of the rms of the instrumental white noise. To speedup the process an analytical model is developed that is able to extract most of the relevant information on EpsilonQ and Cr as a function of the signal statistics and the processing parameters. This model will be of interest for the instrument data analysis. The method was applied during ground tests when the instrument was operating in conditions representative of flight. Optimized parameters were obtained and the performance has been verified, the required data rate of 35.5 Kbps has been achieved while keeping EpsilonQ at a level of 3.8% of white noise rms well within the requirements.Comment: 51 pages, 13 fig.s, 3 tables, pdflatex, needs JINST.csl, graphicx, txfonts, rotating; Issue 1.0 10 nov 2009; Sub. to JINST 23Jun09, Accepted 10Nov09, Pub.: 29Dec09; This is a preprint, not the final versio

    Evaluation of Skylab (EREP) data for forest and rangeland surveys

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    The author has identified the following significant results. Four widely separated sites (near Augusta, Georgia; Lead, South Dakota; Manitou, Colorado; and Redding, California) were selected as typical sites for forest inventory, forest stress, rangeland inventory, and atmospheric and solar measurements, respectively. Results indicated that Skylab S190B color photography is good for classification of Level 1 forest and nonforest land (90 to 95 percent correct) and could be used as a data base for sampling by small and medium scale photography using regression techniques. The accuracy of Level 2 forest and nonforest classes, however, varied from fair to poor. Results of plant community classification tests indicate that both visual and microdensitometric techniques can separate deciduous, conifirous, and grassland classes to the region level in the Ecoclass hierarchical classification system. There was no consistency in classifying tree categories at the series level by visual photointerpretation. The relationship between ground measurements and large scale photo measurements of foliar cover had a correlation coefficient of greater than 0.75. Some of the relationships, however, were site dependent

    Towards Faster Spectrum Sensing Techniques in Cognitive Radio Architectures

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    AbstractIn the recent years, the subject of spectrum sensing techniques has been well studied in research community, highly motivated by the emergence of cognitive radio architectures. But in practice, given the complexity of proposed spectrum sensing techniques, the implementation of cognitive radio has become a tedious task. Unlike many papers in the literature, this paper focuses on implementation aspects of spectrum sensing. Especially, we attempt to reduce the time taken for spectrum sensing based on adaptive FFT approach employing statistical analysis. The first step of the many spectrum techniques is to obtain the FFT of input samples. Most of the existing spectrum analyzers like Tektronix RSA6000, Rohde & Schwarz FSVR etc employ detection and estimations algorithms based on the FFTs of the acquired samples. In this paper, we propose an algorithm to vary the FFT-size to obtain the spectrum information at a faster rate, applicable to cognitive radio environment. FFT size would be varied in accordance with statistical information obtained from the prediction engines. The proposed Adaptive FFT algorithm is studied as applied to the well known energy detection technique. Finally an implementation is carried out on USRP based on GNU Radio platform

    The Telecommunications and Data Acquisition Report

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    This quarterly publication provides archival reports on developments in programs managed by JPL's Telecommunications and Mission Operations Directorate (TMOD), which now includes the former Telecommunications and Data Acquisition (TDA) Office. In space communications, radio navigation, radio science, and ground-based radio and radar astronomy, it reports on activities of the Deep Space Network (DS) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. The preceding work is all performed for NASA's Office of Space Communications (OSC)

    User's guide to image processing applications of the NOAA satellite HRPT/AVHRR data. Part 1: Introduction to the satellite system and its applications. Part 2: Processing and analysis of AVHRR imagery

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    The use of NOAA Advanced Very High Resolution Radar/High Resolution Picture Transmission (AVHRR/HRPT) imagery for earth resource applications is provided for the applications scientist for use within the various Earth science, resource, and agricultural disciplines. A guide to processing NOAA AVHRR data using the hardware and software systems integrated for this NASA project is provided. The processing steps from raw data on computer compatible tapes (1B data format) through usable qualitative and quantitative products for applications are given. The manual is divided into two parts. The first section describes the NOAA satellite system, its sensors, and the theoretical basis for using these data for environmental applications. Part 2 is a hands-on description of how to use a specific image processing system, the International Imaging Systems, Inc. (I2S) Model 75 Array Processor and S575 software, to process these data

    The Telecommunications and Data Acquisition Report

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    This quarterly publication provides archival reports on developments in programs managed by JPL's Telecommunications and Mission Operations Directorate (TMOD), which now includes the former Telecommunications and Data Acquisition (TDA) Office. In space communications, radio navigation, radio science, and ground-based radio and radar astronomy, it reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. The preceding work is all performed for NASA's Office of Space Communications (OSC). TMOD also performs work funded by other NASA program offices through and with the cooperation of OSC. The first of these is the Orbital Debris Radar Program funded by the Office of Space Systems Development. It exists at Goldstone only and makes use of the planetary radar capability when the antennas are configured as science instruments making direct observations of the planets, their satellites, and asteroids of our solar system. The Office of Space Sciences funds the data reduction and science analyses of data obtained by the Goldstone Solar System Radar. The antennas at all three complexes are also configured for radio astronomy research and, as such, conduct experiments funded by the National Science Foundation in the U.S. and other agencies at the overseas complexes. These experiments are either in microwave spectroscopy or very long baseline interferometry. Finally, tasks funded under the JPL Director's Discretionary Fund and the Caltech President's Fund that involve TMOD are included. This and each succeeding issue of 'The Telecommunications and Data Acquisition Progress Report' will present material in some, but not necessarily all, of the aforementioned programs

    The Space and Earth Science Data Compression Workshop

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    This document is the proceedings from a Space and Earth Science Data Compression Workshop, which was held on March 27, 1992, at the Snowbird Conference Center in Snowbird, Utah. This workshop was held in conjunction with the 1992 Data Compression Conference (DCC '92), which was held at the same location, March 24-26, 1992. The workshop explored opportunities for data compression to enhance the collection and analysis of space and Earth science data. The workshop consisted of eleven papers presented in four sessions. These papers describe research that is integrated into, or has the potential of being integrated into, a particular space and/or Earth science data information system. Presenters were encouraged to take into account the scientists's data requirements, and the constraints imposed by the data collection, transmission, distribution, and archival system

    The Telecommunications and Data Acquisition Report

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    Archival reports on developments in programs managed by the Jet Propulsion Laboratory's (JPL) Office of Telecommunications and Data Acquisition (TDA) are given. Space communications, radio navigation, radio science, and ground-based radio and radar astronomy, activities of the Deep Space Network (DSN) and its associated Ground Communications Facility (GCF) in planning, supporting research and technology, implementation, and operations are reported. Also included is TDA-funded activity at JPL on data and information systems and reimbursable Deep Space Network (DSN) work performed for other space agencies through NASA

    Spectrum Sensing Algorithms for Cognitive Radio Applications

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    Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies
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