4 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…
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…