Recursive Bayesian Initialization of Localization Based on Ranging and Dead Reckoning

The initialization of the state estimation in a localization scenario based on ranging and dead reckoning is studied. Specifically, we start with a cooperative localization setup and consider the problem of recursively arriving at a uni-modal state estimate with sufficiently low covariance such that covariance based filters can be used to estimate an agent's state subsequently. A number of simplifications/assumptions are made such that the estimation problem can be seen as that of estimating the initial agent state given a deterministic surrounding and dead reckoning. This problem is solved by means of a particle filter and it is described how continual states and covariance estimates are derived from the solution. Finally, simulations are used to illustrate the characteristics of the method and experimental data are briefly presented

Understanding the Global in Global Finance and Regulation

A simple and statistically robust method for passive clock synchronization in sensor networks is presented. The method is not limited to passive (one-way communication) synchronization, but this scenario justifies the method. The recursive nature of the method and the targeted passive setup mean that it adds a minimum of requirements on the system in which it is used. Statistical characteristics of the method are quantified and real measurements are used to illustrate the robustness and performance gain relative to a naive Kalman filter based clock synchronization. Finally, C++ code that implements the suggested clock synchronization method, is provided in this article.QC 20140423</p

IR-UWB Detection and Fusion Strategies using Multiple Detector Types

Optimal detection of ultra wideband (UWB) pulses in a UWB transceiver employing multiple detector types is proposed and analyzed in this paper. We propose several fusion techniques for fusing decisions made by individual IR-UWB detectors. We assess the performance of these fusion techniques for commonly used detector types like matched filter, energy detector and amplitude detector. In order to perform this, we derive the detection performance equation for each of the detectors in terms of false alarm rate, shape of the pulse and number of UWB pulses used in the detection and apply these in the fusion algorithms. We show that the performance can be improved approximately by 4 dB in terms of signal to noise ratio (SNR) for perfect detectability of a UWB signal in a practical scenario by fusing the decisions from individual detectors.Comment: Accepted for publishing in IEEE WCNC 201

Multi Detector Fusion of Dynamic TOA Estimation using Kalman Filter

In this paper, we propose fusion of dynamic TOA (time of arrival) from multiple non-coherent detectors like energy detectors operating at sub-Nyquist rate through Kalman filtering. We also show that by using multiple of these energy detectors, we can achieve the performance of a digital matched filter implementation in the AWGN (additive white Gaussian noise) setting. We derive analytical expression for number of energy detectors needed to achieve the matched filter performance. We demonstrate in simulation the validity of our analytical approach. Results indicate that number of energy detectors needed will be high at low SNRs and converge to a constant number as the SNR increases. We also study the performance of the strategy proposed using IEEE 802.15.4a CM1 channel model and show in simulation that two sub-Nyquist detectors are sufficient to match the performance of digital matched filter

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In this paper we evaluate the application of convex optimization for PAPR reduction on OFDM 802.11a signal type. A radio frequency power amplifier is measured and characterized while excited by both original and optimized OFDM signals. A state-of-art test setup was used for the purpose. Figure of merits such as power added efficiency, in-band errors, and out-of-band spectral emissions are investigated for their relevance and a study of the power distribution in the excitation signal is evaluated.©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEEKK