Computational and Numerical Properties of a Broadband Subspace-Based Likelihood Ratio Test
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| Main Authors: | , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866917788690415616 |
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| author | Pahalson, Cornelius A. H. Crockett, Louise H. Weiss, Stephan |
| author_facet | Pahalson, Cornelius A. H. Crockett, Louise H. Weiss, Stephan |
| contents | This paper investigates the performance of a likelihood ratio test in combination with a polynomial subspace projection approach to detect weak transient signals in broadband array data. Based on previous empirical evidence that a likelihood ratio test is advantageously applied in a lower-dimensional subspace, we present analysis that highlights how the polynomial subspace projection whitens a crucial part of the signals, enabling a detector to operate with a shortened temporal window. This reduction in temporal correlation, together with a spatial compaction of the data, also leads to both computational and numerical advantages over a likelihood ratio test that is directly applied to the array data. The results of our analysis are illustrated by examples and simulations. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2409_18712 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Computational and Numerical Properties of a Broadband Subspace-Based Likelihood Ratio Test Pahalson, Cornelius A. H. Crockett, Louise H. Weiss, Stephan Methodology Signal Processing This paper investigates the performance of a likelihood ratio test in combination with a polynomial subspace projection approach to detect weak transient signals in broadband array data. Based on previous empirical evidence that a likelihood ratio test is advantageously applied in a lower-dimensional subspace, we present analysis that highlights how the polynomial subspace projection whitens a crucial part of the signals, enabling a detector to operate with a shortened temporal window. This reduction in temporal correlation, together with a spatial compaction of the data, also leads to both computational and numerical advantages over a likelihood ratio test that is directly applied to the array data. The results of our analysis are illustrated by examples and simulations. |
| title | Computational and Numerical Properties of a Broadband Subspace-Based Likelihood Ratio Test |
| topic | Methodology Signal Processing |
| url | https://arxiv.org/abs/2409.18712 |