Thomas C. T. Chan

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— In this paper, we present an online stochastic approach for landmine detection based on ground penetrating radar (GPR) signals using sequential Monte Carlo (SMC) methods. The processing applies to the two-dimensional B-scans or radargrams of 3-D GPR data measurements. The proposed state-space model is essentially derived from that of Zoubir et al., which(More)
The increasing availability of genomic information from the Arthropoda continues to revolutionize our understanding of the biology of this most diverse animal phylum. However, our sampling of arthropod diversity remains uneven, and key clade such as the Myriapoda are severely underrepresented. Here we present the genome of the cosmopolitanly distributed(More)
Ground penetrating radar (GPR) is a widely used sensor for land mine detection. However, GPR signal return is very susceptible to ground bounce and reflection of clutter objects, which makes the detection a difficult problem to date. In this paper, we propose to utilize two-sided linear prediction (LP) to model the background interference and then employ(More)
In this paper, we investigate two binary detection problems for a single real tone in additive white Gaussian noise using short data records. In the first hypothesis-testing scenario, we decide if a sinusoid is present in the received signal where both cases of known and unknown sinusoidal frequency will be examined. In the second problem, differentiation(More)
Ground penetrating radar (GPR) is a widely used tool for land mine detection. However, land mine detection still remains a difficult task because of the changing conditions and the strong reflection of the ground. In this paper, a generalized two-sided linear prediction model is used to estimate the background. By effectively removing the background(More)
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