S. Chakravorty

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In this paper, we present a randomized version of the finite set statistics (FISST) Bayesian recursions for multi-object tracking problems with application to the space situational awareness (SSA) problem. We introduce a hypothesis level derivation of the FISST equations that shows that the multi-object tracking problem may be considered as a finite state(More)
Orthogonal Frequency Division Multiplexing (OFDM) is an emerging field of research in the field of wireless communication and finds its application where high data rate is required at low latency and better spectral efficiency. Peak to Average Power Ratio (PAPR) is the limiting factor for an OFDM system as it degrades the system performance by reducing SQNR(More)
—Multiple input multiple output (MIMO) systems using multiple transmit and receive antennas are widely recognized as the vital breakthrough that will allow future wireless systems to achieve higher data rates with limited bandwidth and power resources. The capacity of MIMO systems depends strongly on whether the channel state information (CSI) is available(More)
In this paper, we present a graphics processing unit (GPU) based implementation of a receding horizon solution to the optimal sensor scheduling problem. The optimal sensor scheduling problem can be posed as a Partially Observed Markov Decision Process (POMDP) whose solution is given by an Information Space (I-space) Dynamic Programming (DP) problem. In(More)
In multi-object tracking one may encounter situations were at any time step the number of possible hypotheses is too large to generate exhaustively. These situations generally occur when there are multiple ambiguous measurement returns that can be associated to many objects. This paper contains a newly developed approach that keeps the aforementioned(More)
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