Sequential maximum-likelihood estimation of wideband polynomial-phase signals on sensor array

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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Signal processing Ročník 238; s. 110105
Hlavní autoři: Debre, Kaleb, Fei, Tai, Pesavento, Marius
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.01.2026
Témata:
Maximum-likelihood estimation
Polynomial-phase signal
Radar signal processing
Random sampling consensus (RANSAC)
Sensor array processing
Space time-frequency analysis
Wideband direction-of-arrival estimation
Sensor array processing
Polynomial-phase signal
Space time-frequency analysis
Wideband direction-of-arrival estimation
Maximum-likelihood estimation
Random sampling consensus (RANSAC)
Radar signal processing
ISSN:0165-1684
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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. •FMCW radar detection of multiple targets with time-varying radial velocities.•Joint estimation of direction-of-arrival and time-frequency signatures.•Computationally tractable approximate maximum-likelihood estimation method.•Wideband space–time-frequency coherent processing.•Achieves Cramér-Rao bound for all parameters in challenging multi-source scenarios.
ISSN:0165-1684
DOI:10.1016/j.sigpro.2025.110105