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Range-only tracking problems arise in extended data collection for inverse synthetic radar applications, robotics, navigation and other areas. For such problems, the conditional density of the state variable given the measurement history is multi-modal or exhibits curvature, even in seemingly benign scenarios. For this reason, the use of extended Kalman filter (EKF) and other nonlinear filtering techniques...
We investigate the problem of tracking a target using a wireless sensor network, where quantized sensor measurements are utilized because of inherent communication and energy constraints. Due to the severe nonlinearity of the measurement model, we resort to sequential Monte Carlo methods for tracking, i.e., particle filters. The tracking performance is a function of local sensor quantizer thresholds...
The problem addressed in this work is to separate the signals of moving sources with independent component analysis (ICA) and tracking the kinematics (position, velocity, acceleration) of each individual source in the working space using particle filters. To identify the unpredictable movement of the speaker over time, the new proposed state switching scheme handles the uncertainty of the speaker's...
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