Learn 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)
An ultra-wideband (UWB) synthetic aperture radar (SAR) simulation technique that employs physical and statistical models is developed and presented. This joint physics/statistics based technique generates images that have many of the " blob-like " and " spiky " clutter characteristics of UWB radar data in forested regions while avoiding the intensive(More)
In this paper, a new 1-D hybrid Automatic Target Recognition (ATR) algorithm is developed for sequential High Range Resolution (HRR) radar signatures. 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 proposed hybrid approach, each(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)