Sequential Maximum-Likelihood Estimation of Wideband Polynomial-Phase Signals on Sensor Array
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866909444459200512 |
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| author | Debre, Kaleb Fei, Tai Pesavento, Marius |
| author_facet | Debre, Kaleb Fei, Tai Pesavento, Marius |
| contents | This paper presents a novel sequential estimator for the direction-of-arrival and polynomial coefficients of wideband polynomial-phase signals impinging on a sensor array. Addressing the computational challenges of Maximum-likelihood estimation for this problem, we propose a method leveraging random sampling consensus (RANSAC) applied to the time-frequency spatial signatures of sources. Our approach supports multiple sources and higher-order polynomials by employing coherent array processing and sequential approximations of the Maximum-likelihood cost function. We also propose a low-complexity variant that estimates source directions via angular domain random sampling. Numerical evaluations demonstrate that the proposed methods achieve Cramér-Rao bounds in challenging multi-source scenarios, including closely spaced time-frequency spatial signatures, highlighting their suitability for advanced radar signal processing applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_20975 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Sequential Maximum-Likelihood Estimation of Wideband Polynomial-Phase Signals on Sensor Array Debre, Kaleb Fei, Tai Pesavento, Marius Signal Processing This paper presents a novel sequential estimator for the direction-of-arrival and polynomial coefficients of wideband polynomial-phase signals impinging on a sensor array. Addressing the computational challenges of Maximum-likelihood estimation for this problem, we propose a method leveraging random sampling consensus (RANSAC) applied to the time-frequency spatial signatures of sources. Our approach supports multiple sources and higher-order polynomials by employing coherent array processing and sequential approximations of the Maximum-likelihood cost function. We also propose a low-complexity variant that estimates source directions via angular domain random sampling. Numerical evaluations demonstrate that the proposed methods achieve Cramér-Rao bounds in challenging multi-source scenarios, including closely spaced time-frequency spatial signatures, highlighting their suitability for advanced radar signal processing applications. |
| title | Sequential Maximum-Likelihood Estimation of Wideband Polynomial-Phase Signals on Sensor Array |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2412.20975 |