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Published in 2017 at "Journal of Central South University"
DOI: 10.1007/s11771-017-3591-9
Abstract: As a typical implementation of the probability hypothesis density (PHD) filter, sequential Monte Carlo PHD (SMC-PHD) is widely employed in highly nonlinear systems. However, the particle impoverishment problem introduced by the resampling step, together with…
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Keywords:
smc phd;
phd filter;
particle;
phd ... See more keywords
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Published in 2018 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2017.2757905
Abstract: The Probability Hypothesis Density (PHD) and Cardinalized PHD (CPHD) filters are popular solutions to the multitarget tracking problem due to their low complexity and ability to estimate the number and states of targets in cluttered…
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Keywords:
order;
phd filter;
number targets;
number ... See more keywords
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Published in 2022 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2022.3171040
Abstract: Advanced driver assistance systems and highly automated driving functions require an enhanced frontal perception system. The requirements of a frontal environment perception system cannot be satisfied by either of the existing automotive sensors. A commonly…
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Keywords:
perception system;
phd filter;
sensor;
perception ... See more keywords
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Published in 2017 at "International Journal of Electronics and Telecommunications"
DOI: 10.1515/eletel-2017-0033
Abstract: Probability hypothesis density (PHD) filter is a suboptimal Bayesian multi-target filter based on random finite set. The Gaussian mixture PHD filter is an analytic solution to the PHD filter for linear Gaussian multi-target models. However,…
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Keywords:
probability hypothesis;
spaced targets;
hypothesis density;
phd filter ... See more keywords