Results 51 to 60 of about 4,959 (205)
Exploiting persymmetry for low-rank Space Time Adaptive Processing [PDF]
, 2012 International audienceReducing the number of secondary data used to estimate the Covariance Matrix (CM) for Space Time Adaptive Processing (STAP) techniques is still an active research topic.
Forster, Philippe +3 more
core +5 more sources
Australian Journal of Agricultural and Resource Economics, Volume 70, Issue 2, Page 395-409, April 2026.ABSTRACT Large‐scale solar generation is critical for energy transitions. In Australia, increased solar production to meet emission targets means its land footprint increasingly competes with agricultural land. Understanding the scale and location of agricultural land use change and potential profitability losses from large‐scale solar farms is ...
Raymundo Marcos‐Martinez +6 more
wiley +1 more source
Covariance matrix estimation with heterogeneous samples [PDF]
, 2008 We consider the problem of estimating the covariance matrix Mp of an observation vector, using heterogeneous training samples, i.e., samples whose covariance matrices are not exactly Mp.
Besson, Olivier +2 more
core +2 more sources
Stap2Go Test: Validity and Sensitivity/Specificity for Attention and Executive Function Assessment
Applied Cognitive Psychology, Volume 40, Issue 2, March/April 2026.ABSTRACT Attention and executive function difficulties are common in many neurodevelopmental conditions and significantly impact psychological well‐being. However, access to cognitive assessment remains limited due to high costs and resource constraints.
Teresa Rossignoli‐Palomeque +1 more
wiley +1 more source
Best Practice in Climate Change Adaptation
WIREs Climate Change, Volume 17, Issue 2, March/April 2026.The seven elements of best practice in climate change adaptation. ABSTRACT Climate change adaptation has become a core business for international organizations, firms, and all levels of government in almost every country. Practitioners seek to implement adaptation in the face of myriad barriers and uncertainties and so seek guidance as to what ...
Jon Barnett +3 more
wiley +1 more source
A Grid-Less Total Variation Minimization-Based Space-Time Adaptive Processing for Airborne Radar
IEEE Access, 2020 Sparse recovery (SR) based space-time adaptive processing (STAP) has attracted much attention due to its small requirement of snapshots in the estimation of the clutter plus noise covariance matrix (CNCM).
Yuyu Su +3 more
doaj +1 more source
Space-Time Adaptive Processing by Employing Structure-Aware Two-Level Block Sparsity
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Traditional radar space-time adaptive processing (STAP) cannot efficiently suppress heterogeneous clutter because of a small number of independent and identically distributed training snapshots.
Zhizhuo Jiang +4 more
doaj +1 more source
Knowledge-aided bayesian detection in heterogeneous environments [PDF]
, 2007 We address the problem of detecting a signal of interest in the presence of noise with unknown covariance matrix, using a set of training samples. We consider a situation where the environment is not homogeneous, i.e., when the covariance matrices of the
Jean-yves Tourneret +4 more
core +2 more sources
A Joint Sparse Space-Time Adaptive Processing Method
IEEE AccessAt present, most of the sparse space-time adaptive processing(STAP) methods focus on exploiting the clutter sparsity. In this paper, different from the present sparse STAP methods, both the clutter sparsity and the target sparsity in STAP are considered ...
Jinfeng Hu +4 more
doaj +1 more source
Remote Sensing, 2022 Space-time adaptive processing (STAP) is a fundamental topic in airborne radar applications due to its clutter suppression ability. Reduced-dimension (RD)-STAP can release the requirement of the number of training samples and reduce the computational ...
Di Song +4 more
doaj +1 more source