First upper limits from LIGO on gravitational wave bursts

We report on a search for gravitational wave bursts using data from the first science run of the LIGO detectors. Our search focuses on bursts with durations ranging from 4 ms to 100 ms, and with significant power in the LIGO sensitivity band of 150 to 3000 Hz. We bound the rate for such detected bursts at less than 1.6 events per day at 90% confidence level. This result is interpreted in terms of the detection efficiency for ad hoc waveforms (Gaussians and sine-Gaussians) as a function of their root-sum-square strain h_{rss}; typical sensitivities lie in the range h_{rss} ~ 10^{-19} - 10^{-17} strain/rtHz, depending on waveform. We discuss improvements in the search method that will be applied to future science data from LIGO and other gravitational wave detectors.Comment: 21 pages, 15 figures, accepted by Phys Rev D. Fixed a few small typos and updated a few reference

Exploring Sensor Network Communication Strategies with the Mote-in-the-Loop Approach

WISENET (NES

Multichannel Sampling of Pulse Streams at the Rate of Innovation

We consider minimal-rate sampling schemes for infinite streams of delayed and weighted versions of a known pulse shape. The minimal sampling rate for these parametric signals is referred to as the rate of innovation and is equal to the number of degrees of freedom per unit time. Although sampling of infinite pulse streams was treated in previous works, either the rate of innovation was not achieved, or the pulse shape was limited to Diracs. In this paper we propose a multichannel architecture for sampling pulse streams with arbitrary shape, operating at the rate of innovation. Our approach is based on modulating the input signal with a set of properly chosen waveforms, followed by a bank of integrators. This architecture is motivated by recent work on sub-Nyquist sampling of multiband signals. We show that the pulse stream can be recovered from the proposed minimal-rate samples using standard tools taken from spectral estimation in a stable way even at high rates of innovation. In addition, we address practical implementation issues, such as reduction of hardware complexity and immunity to failure in the sampling channels. The resulting scheme is flexible and exhibits better noise robustness than previous approaches

Modeling Selective Availability of the NAVSTAR Global Positioning System

As the development of the NAVSTAR Global Positioning System (GPS) continues, there will increasingly be the need for a software centered signal model. This model must accurately generate the observed pseudorange which would typically be encountered. The observed pseudorange varies from the true geometric (slant) range due to range measurement errors. Errors in range measurement stem from a variety of hardware and environment factors. These errors are classified as either deterministic or random and, where appropriate, their models are summarized. Of particular interest is the model for Selective Availability which is derived from actual GPS data. The procedure for the determination of this model, known as the System Identification Theory, is briefly outlined. The synthesis of these error sources into the final signal model is given along with simulation results