8 accepted papers
Maximum Likelihood (ML) Direction-of-Arrival (DoA) estimation on the Vectorized Covariance Matrix Model (VCMM) exhibits improved performance in severe conditions compared to standard methods. Indeed, it benefits from the VCMM capacities summarized through the Virtual Array (VA) concept. Due to finit…
In sparse DOA estimation methods, the regularization parameter λ is generally empirically tuned. In this paper, we provide a statistical method allowing to estimate an admissible interval where λ must be chosen. This work is conducted in the case of an Uniform Circular Array, well known for its θ in…
This paper investigates calibration of sensor arrays in the radio astronomy context. Current and future radio telescopes require computationally efficient algorithms to overcome the new technical challenges as large collecting area, wide field of view and huge data volume. Specifically, we study the…
In many deterministic estimation problems, the probability density function (p.d.f.) parameterized by unknown deterministic parameters results from the marginalization of a joint p.d.f. depending on additional random variables. Unfortunately, this marginalization is often mathematically intractable,…
This paper investigates parametric direction-of-arrival (DOA) estimation in a particular context: i) each sensor is characterized by an unknown complex gain and ii) the array consists of a collection of subarrays which are substantially separated from each other leading ] to a structured noise covar…
In statistical signal processing, hybrid parameter estimation refers to the case where the parameters vector to estimate contains both non-random and random parameters. Numerous works have shown the versatility of deterministic constrained Cramér-Rao bound for estimation performance analysis and des…
In the literature of direct blind geolocalization algorithms, two algorithms are mainly concurrent: DPD and LOST. The first one appears to be very sensitive to the spectral contents and the second, although presenting wide scope of scenarii with better performance than DPD, does not exploit the TDoA…
This paper addresses the direct geolocation of sources in one step via a multi-base (or multi-array) context. The 1-step methods such as DPD and LOST are working on a global array composed of all the sensors of each base. However, even if these algorithms introduce a narrowband decomposition (unfort…