Device Free Localisation Techniques in Indoor Environments

The location estimation of a target for a long period was performed only by device based localisation technique which is difficult in applications where target especially human is non-cooperative. A target was detected by equipping a device using global positioning systems, radio frequency systems, ultrasonic frequency systems, etc. Device free localisation (DFL) is an upcoming technology in automated localisation in which target need not equip any device for identifying its position by the user. For achieving this objective, the wireless sensor network is a better choice due to its growing popularity. This paper describes the possible categorisation of recently developed DFL techniques using wireless sensor network. The scope of each category of techniques is analysed by comparing their potential benefits and drawbacks. Finally, future scope and research directions in this field are also summarised

Fast LASSO based DOA tracking

In this paper, we propose a sequential, fast DOA tracking technique using the measurements of a uniform linear sensor array in the far field of a set of narrow band sources. Our approach is based on sparse approximation technique LASSO (Least Absolute Shrincage and Selection Operator), which has recently gained considerable interest for DOA and other estimation problems. Considering the LASSO optimization as a Bayesian estimation, we first define a class of prior distributions suitable for the sparse representation of the model and discuss its relation to the priors over DOAs and waveforms. Inspired by the Kalman filtering method, we introduce a nonlinear sequential filter on this family of distributions. We derive the filter for a simple random walk motion model of the DOAs. The method consists of consecutive implementation of weighted LASSO optimizations using each new measurement and updating the LASSO weights for the next step

An Upper Limit on the Albedo of HD 209458b: Direct Imaging Photometry with the MOST Satellite

We present space-based photometry of the transiting exoplanetary system HD 209458 obtained with the MOST (Microvariablity and Oscillations of STars) satellite, spanning 14 days and covering 4 transits and 4 secondary eclipses. The HD 209458 photometry was obtained in MOST's lower-precision Direct Imaging mode, which is used for targets in the brightness range $6.5 < V < 13$. We describe the photometric reduction techniques for this mode of observing, in particular the corrections for stray Earthshine. We do not detect the secondary eclipse in the MOST data, to a limit in depth of 0.053 mmag (1 \sigma). We set a 1 \sigma upper limit on the planet-star flux ratio of 4.88 x 10^-5 corresponding to a geometric albedo upper limit in the MOST bandpass (400 to 700 nm) of 0.25. The corresponding numbers at the 3 \sigma level are 1.34 x 10^-4 and 0.68 respectively. HD 209458b is half as bright as Jupiter in the MOST bandpass. This low geometric albedo value is an important constraint for theoretical models of the HD209458b atmosphere, in particular ruling out the presence of reflective clouds. A second MOST campaign on HD 209458 is expected to be sensitive to an exoplanet albedo as low as 0.13 (1 sigma), if the star does not become more intrinsically variable in the meantime.Comment: 29 pages, 9 figures. Accepted for publication in the Astrophysical Journal (July 2006, v645n1

Review of computer vision in intelligent environment design

This paper discusses and compares the use of vision based and non-vision based technologies in developing intelligent environments. By reviewing the related projects that use vision based techniques in intelligent environment design, the achieved functions, technical issues and drawbacks of those projects are discussed and summarized, and the potential solutions for future improvement are proposed, which leads to the prospective direction of my PhD research