Target tracking via recursive Bayesian state estimation in cognitive radar networks

Y Xiang, M Akcakaya, S Sen, D Erdogmus, A Nehorai - Signal Processing, 2019 - Elsevier
To cope with complicated environments and stealthier targets, incorporating intelligence and
cognition cycles into target tracking is of great importance in modern sensor network
management. With remarkable advances in sensor techniques and deployable platforms, a
sensing system has freedom to select a subset of available radars, plan their trajectories,
and transmit designed waveforms. In this paper, we propose a general framework for single
target tracking in cognitive networks of radars, including consideration of waveform design …

Target tracking via recursive bayesian state estimation in radar networks

Y Xiang, M Akcakaya, S Sen… - 2017 51st Asilomar …, 2017 - ieeexplore.ieee.org
Modern cognitive radar networks incorporating intelligent and cognitive support-modules
can actively adjust the radar-target geometry and optimally select a subset of radars to track
the target of interest. Based on the theories of dynamic graphical models (DGM) and
recursive Bayesian state estimation (RBSE), we propose a framework for single target
tracking in mobile and cooperative radar networks, jointly considering path planning and
radar selection. We formulate the tracking procedure as two iterative steps:(i) solving a …
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