39,970 research outputs found
Adaptive Non-myopic Quantizer Design for Target Tracking in Wireless Sensor Networks
In this paper, we investigate the problem of nonmyopic (multi-step ahead)
quantizer design for target tracking using a wireless sensor network. Adopting
the alternative conditional posterior Cramer-Rao lower bound (A-CPCRLB) as the
optimization metric, we theoretically show that this problem can be temporally
decomposed over a certain time window. Based on sequential Monte-Carlo methods
for tracking, i.e., particle filters, we design the local quantizer adaptively
by solving a particlebased non-linear optimization problem which is well suited
for the use of interior-point algorithm and easily embedded in the filtering
process. Simulation results are provided to illustrate the effectiveness of our
proposed approach.Comment: Submitted to 2013 Asilomar Conference on Signals, Systems, and
Computer
Active Classification for POMDPs: a Kalman-like State Estimator
The problem of state tracking with active observation control is considered
for a system modeled by a discrete-time, finite-state Markov chain observed
through conditionally Gaussian measurement vectors. The measurement model
statistics are shaped by the underlying state and an exogenous control input,
which influence the observations' quality. Exploiting an innovations approach,
an approximate minimum mean-squared error (MMSE) filter is derived to estimate
the Markov chain system state. To optimize the control strategy, the associated
mean-squared error is used as an optimization criterion in a partially
observable Markov decision process formulation. A stochastic dynamic
programming algorithm is proposed to solve for the optimal solution. To enhance
the quality of system state estimates, approximate MMSE smoothing estimators
are also derived. Finally, the performance of the proposed framework is
illustrated on the problem of physical activity detection in wireless body
sensing networks. The power of the proposed framework lies within its ability
to accommodate a broad spectrum of active classification applications including
sensor management for object classification and tracking, estimation of sparse
signals and radar scheduling.Comment: 38 pages, 6 figure
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