An Experimental and Theoretical Analysis of a Laser Beam Propagating Through Multiple Phase Screens

An experimental and a theoretical analysis for a laser beam propagating through multiple phase screens was performed. The theoretical analysis showed that the statistics for the intensity fluctuations, which can be predicted by the HK and the I-K distributions, could be derived from a multiplicative process using statistical distributions derived from Gaussian statistics. For the single phase screen experiment, the experimental normalized moments were compared with the normalized moments of both the HK and I-K distributions . In addition, the intensity data was lowpass filtered to yield moments that are predicted by the gamma distribution. The single phase screen data was segmented into small time intervals, and all time segments with approximately the same variance were grouped together into bins to yield normalized moments for each bin that are predicted by the Rician distribution. Also, the normalized moments for two and three phase screen experiments were measured. Finally, a computer program was written to simulate K distributed noise from two independent Gaussian noise sources

Reference-less detection, astrometry, and photometry of faint companions with adaptive optics

We propose a complete framework for the detection, astrometry, and photometry of faint companions from a sequence of adaptive optics corrected short exposures. The algorithms exploit the difference in statistics between the on-axis and off-axis intensity. Using moderate-Strehl ratio data obtained with the natural guide star adaptive optics system on the Lick Observatory's 3-m Shane Telescope, we compare these methods to the standard approach of PSF fitting. We give detection limits for the Lick system, as well as a first guide to expected accuracy of differential photometry and astrometry with the new techniques. The proposed approach to detection offers a new way of determining dynamic range, while the new algorithms for differential photometry and astrometry yield accurate results for very faint and close-in companions where PSF fitting fails. All three proposed algorithms are self-calibrating, i.e. they do not require observation of a calibration star thus improving the observing efficiency.Comment: Astrophysical Journal 698 (2009) 28-4

Time-Scale Domain Characterization of Time-Varying Ultrawideband Infostation Channel

The time-scale domain geometrical-based method for the characterization of the time varying ultrawideband (UWB) channel typical of an infostation channel is presented. Compared to methods that use Doppler shift as a measure of time-variation in the channel this model provides a more reliable measure of frequency dispersion caused by terminal mobility in the UWB infostation channel. Particularly, it offers carrier frequency independent method of computing wideband channel responses and parameters which are important for ultrawideband systems. Results show that the frequency dispersion of the channel depends on the frequency and not on the choice of bandwidth. And time dispersion depends on bandwidth and not on the frequency. It is also shown that for time-varying UWB, frame length defined over the coherence time obtained with reference to the carrier frequency results in an error margin which can be reduced by using the coherence time defined with respect to the maximum frequency in a given frequency band. And the estimation of the frequency offset using the time-scale domain (wideband) model presented here (especially in the case of multiband UWB frequency synchronization) is more accurate than using frequency offset estimate obtained from narrowband models

Nonparametric detection using extreme-value theory

Nonparametric extreme value statistics for constant signal detection in additive nois

Wavelet Based Denoising of the Simulated Chest Wall Motion Detected by SFCW Radar

Low power and compact radars have emerged with the development of electronic technology. This has enabled the use of radars in indoor environments and the realization of many applications. The detection, tracking and classification of human movements by radar are among the remarkable applications. Contactless detection of human vital signs improves the quality of life of patients being kept under observation and facilitates the work of experts. In this study, it was simulated that the movement of the chest wall was modeled and detected by the SFCW radar. Gaussian, Rician and uniformly distributed random noise types were added to the modeled chest motion at different levels. The noisy signal obtained at the receiver is denoised with different mother wavelet functions and the performances of these functions are presented comparatively

Signal Processing and Propagation for Aeroacoustic Sensor Networking,” Ch

Passive sensing of acoustic sources is attractive in many respects, including the relatively low signal bandwidth of sound waves, the loudness of most sources of interest, and the inherent difficulty of disguising or concealing emitted acoustic signals. The availability of inexpensive, low-power sensing and signal-processing hardware enables application of sophisticated real-time signal processing. Among th

A Comprehensive Overview and Characterization of Wireless Channels for Networked Robotic and Control Systems

The goal of this overview paper is to serve as a reference for researchers that are interested in the realistic modeling of wireless channels for the purpose of analysis and optimization of networked robotic systems. By utilizing the knowledge available in the wireless communication literature, we first summarize a probabilistic framework for the characterization of the underlying multiscale dynamics of a wireless link. We furthermore confirm this framework with our robotic testbed, by making an extensive number of channel measurements. To show the usefulness of this framework for networked robotic applications, we then discuss a few recent examples where this probabilistic channel characterization has been utilized for the theoretical analysis and communication-aware design of networked robotic systems. Finally, we show how to develop a realistic yet simple channel simulator, which can be used to verify cooperative robotic operations in the presence of realistic communication links

Use of Time-Frequency Analysis and Neural Networks for Mode Identification in a Wireless Software-Defined Radio Approach

The use of time-frequency distributions is proposed as a nonlinear signal processing technique that is combined with a pattern recognition approach to identify superimposed transmission modes in a reconfigurable wireless terminal based on software-defined radio techniques. In particular, a software-defined radio receiver is described aiming at the identification of two coexistent communication modes: frequency hopping code division multiple access and direct sequence code division multiple access. As a case study, two standards, based on the previous modes and operating in the same band (industrial, scientific, and medical), are considered: IEEE WLAN 802.11b (direct sequence) and Bluetooth (frequency hopping). Neural classifiers are used to obtain identification results. A comparison between two different neural classifiers is made in terms of relative error frequency