May 17, 2019 · The mSKL is a Bayesian inference algorithm that can reject incorrect subspace bases, recover missing bases, and benefit approximately correct ...
Apr 26, 2019 · Adaptive Subspace Signal Detection with Uncertain. Partial Prior Knowledge: Off-Grid Problem and. Efficient Implementation. Yuan Jiang, Hongbin ...
A unique advantage of the proposed approach is that it allows the prior knowledge to be incomplete and uncertain, consisting of both correct and incorrect basis ...
合著作者 ; Adaptive Subspace Signal Detection with Uncertain Partial Prior Knowledge: Off-Grid Problem and Efficient Implementation. Y Jiang, H Li, M Rangaswamy.
In this paper, we consider the problem of adaptive detection for distributed targets in zero-mean Gaussian clutter with unknown persymmetric covariance matrix.
Adaptive Subspace Signal Detection with Uncertain Partial Prior Knowledge: Off-Grid Problem and Efficient Implementation. Y Jiang, H Li, M Rangaswamy.
This paper investigates the adaptive detection problem of a distributed target embedded in Gaussian noise with unknown covariance matrix.
This paper deals with the problem of detecting a signal, known only to lie on a line in a subspace, in the presence of unknown noise, using multiple ...
Feb 4, 2020 · This study examines moving target detection for airborne radar in heterogeneous environments. The non-homogeneity of the clutter may lead to a shortage of ...
Jul 22, 2020 · We propose here to use adaptive subspace detectors to solve this issue, a suitable sub- space (that coincides with the Discrete Prolate ...
Missing: Partial Prior Efficient