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In this paper, we propose a Gaussian mixture model (GMM) based approach to discriminate stationary humans from their ghosts and clutter in indoor radar images. More specifically, we use a mixture of Gaussian distributions to model the image intensity histograms corresponding to target and ghost/clutter regions. The mixture parameters, namely, the means, standard deviations, and weights of the component...
We present waveform design based on signature exploitation techniques for improved detection of weapons in urban sensing applications. We consider a single-antenna monostatic radar system. Under the assumption of exact knowledge of the target orientation and, hence, known impulse response, matched illumination approach is used for optimal target detection. For the case of unknown target orientation,...
A simple radar system, based on trilateration and range estimation from three independent dual-frequency radar units, is proposed for moving target localization in urban sensing applications. The proposed scheme utilizes the bounds imposed by the nature of indoor sensing on both target location and motion.
An important task in urban sensing applications is to accurately localize moving and vibrating targets in the presence of significant background clutter. A dual-frequency CW radar, which estimates the range of a target based on the phase difference between two closely spaced frequencies, has been shown to be a cost-effective approach for range estimation of a moving target. Previous work has shown...
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