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| Main Author: | |
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| Format: | Preprint |
| Published: |
2017
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/1701.07078 |
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| _version_ | 1866916141743472640 |
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| author | Mahler, Ronald |
| author_facet | Mahler, Ronald |
| contents | This is a shortened, clarified, and mathematically more rigorous version of the original arXiv version. Its first four findings remain unchanged from the original: 1) measurement-to-track associations (MTAs) in multitarget tracking (MTT) are heuristic and physically erroneous multitarget state models; 2) MTAs occur in the labeled random finite set (LRFS) approach only as purely mathematical abstractions that do not occur singly; 3) the labeled random finite set (LRFS) approach is not a mathematically obfuscated replication of multi-hypothesis tracking (MHT); and 4) the conventional interpretation of MHT is more consistent with classical than Bayesian statistics. This version goes beyond the original in including the following additional main finding: 5) a generalized, RFS-like interpretation results in a correct Bayesian formulation of MHT, based on MTA likelihood functions and MTA Markov transitions/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1701_07078 |
| institution | arXiv |
| publishDate | 2017 |
| record_format | arxiv |
| spellingShingle | Measurement-to-Track Association and Finite-Set Statistics Mahler, Ronald Methodology This is a shortened, clarified, and mathematically more rigorous version of the original arXiv version. Its first four findings remain unchanged from the original: 1) measurement-to-track associations (MTAs) in multitarget tracking (MTT) are heuristic and physically erroneous multitarget state models; 2) MTAs occur in the labeled random finite set (LRFS) approach only as purely mathematical abstractions that do not occur singly; 3) the labeled random finite set (LRFS) approach is not a mathematically obfuscated replication of multi-hypothesis tracking (MHT); and 4) the conventional interpretation of MHT is more consistent with classical than Bayesian statistics. This version goes beyond the original in including the following additional main finding: 5) a generalized, RFS-like interpretation results in a correct Bayesian formulation of MHT, based on MTA likelihood functions and MTA Markov transitions/. |
| title | Measurement-to-Track Association and Finite-Set Statistics |
| topic | Methodology |
| url | https://arxiv.org/abs/1701.07078 |