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Solutions for indoor tracking and localization have become more critical with recent advancement in context and location-aware technologies. The accuracy of explicit positioning sensors such as global positioning system (GPS) is often limited for indoor environments. In this paper, we evaluate the feasibility of building an indoor location tracking system(More)
A new formulation for nonlinear smoothing is derived using forward-backward sigma-point Kalman filtering (SPKF). The forward filter uses the standard SPKF. The backward filter requires the use of the inverse dynamics of the forward filter. While smoothers based on the extended Kalman filter (EKF) simply invert the linearized dynamics, with the SPKF the(More)
Estimating the location of people and tracking them in an indoor environment poses a fundamental challenge in ubiquitous computing. The accuracy of explicit positioning sensors such as GPS is often limited for indoor environments. In this study, we evaluate the feasibility of building an indoor location tracking system that is cost effective for large scale(More)
In this paper, a new 1-D hybrid Automatic Target Recognition (ATR) algorithm is developed for High Range Resolution (HRR) profiles. The proposed hybrid algorithm combines Eigen-Template based Matched Filtering (ETMF) and Hidden Markov modeling (HMM) techniques to achieve superior HRR-ATR performance. In the algorithm, each HRR test profile is first scored(More)
In this paper, we present a method for single channel noise reduction of heart sound recordings. Multiple noise sources, such as lung sounds, muscle contraction, and background noise can contaminate the heart sound collection making subsequent analysis difficult. Our approach is based on a spectral domain minimum-mean squared error (MMSE) estimation,(More)
We present a <i>device-free</i> indoor tracking system that uses received signal strength (RSS) from radio frequency (RF) transceivers to estimate the location of a person. While many RSS-based tracking systems use a body-worn device or tag, this approach requires no such tag. The approach is based on the key principle that RF signals between wall-mounted(More)
Several groups have proposed the state-space approach to track time-varying frequencies ofmulti-harmonic quasi-periodic signals contaminated with white Gaussian noise. We compared the extended Kalman filter (EKF) and sigma-point Kalman filter (SPKF) algorithms on this problem. On average, the SPKF outperformed the EKF and more accurately tracked the(More)
Several groups have proposed the state-space approach to tracking time-varying frequencies of multiharmonic quasiperiodic signals. The extended Kalman filter/smoother (EKF/EKS) is one of the common frequency tracking approaches seen in the literature. We introduce a multiharmonic frequency tracker based on the forward-backward statistical linearized(More)
1. Lucrări ştiinţifice publicate în reviste indexate ISI 2. Lucrări ştiinţifice publicate în volumele unor manifestări ştiinţifice (Proceedings) indexate ISI Feedback Tuning approach to a class of state feedback-controlled servo systems " , Iterative Learning Control experimental results for inverted pendulum crane mode control " , Proceedings of 7 th
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