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This paper addresses the computational problem of particle-Probability Hypothesis Density filter (P-PHDF) in multitarget tracking. A parallelization implementation scheme for P-PHDF on graphics processing unit (GPU) under the Compute Unified Device Architecture (CUDA) framework is proposed. Simulation results show that nearly 20x speedup was achieved on GPU compared to its CPU version.
Estimation of the number of sources embedded in noise is a fundamental problem in statistical signal and array processing. This paper focuses on a non-parametric tool to estimate the number of sources without any information about the signature matrix. We exploit the behavior of eigenvalues of the sample covariance matrix and propose a new estimator based on a sequence of hypothesis test. A series...
The problem of direction of arrival estimation in array processing is considered in this paper. The focus is on how to estimate the source parameters accurately in the absence of a large number of snapshots. A parametric iterative adaptive algorithm based on amplitude and phase estimation with low computational complexities is proposed in this paper. Eigen-decomposition and the subspace projection...
A blind synchronization algorithm for the direct sequence code division multiple access (DS-CDMA) signals is presented in this paper without knowledge of spreading sequence, carrier frequency, or the number of users. The only a priori information used is the symbol period. The algorithm exploits the structure of the signal correlation matrix and estimate the timing offset based on l1-norm of the correlation...
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