Jointly Iterative Adaptive Approach Based Space Time Adaptive Processing Using MIMO Radar
IEEE Access, 2018 To solve the problem of large training samples requirement of space time adaptive processing (STAP), a jointly sparse matrices recovery-based method is proposed for clutter plus noise covariance matrix estimation by exploiting the transmitting waveform ...
Weike Feng +4 more
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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
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Fast estimation of false alarm probabilities of STAP detectors - the AMF [PDF]
, 2005 This paper describes an attempt to harness the power of adaptive importance sampling techniques for estimating false alarm probabilities of detectors that use space-time adaptive processing.
Rangaswamy, Muralidhar +1 more
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Deep learning for high‐resolution estimation of clutter angle‐Doppler spectrum in STAP
IET Radar, Sonar & Navigation, 2022 Space‐time adaptive processing (STAP) methods can provide good clutter suppression potential in airborne radar systems. However, the performance of these methods is limited by the training samples' support in practical applications. To address this issue,
Keqing Duan +3 more
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Fast-time STAP performance in pre and post range processing adaption as applied to multichannel SAR [PDF]
, 2006 Hot-clutter cancellation using fast-time Space Time Adaptive Processing (STAP) can occur either pre or post range processing (RP) and to date, there has not been a direct comparison on which method offers the best results. This paper provides an analytic
Gray, D., Rosenberg, L., Trinkle, M.
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An Efficient Sparse Bayesian Learning STAP Algorithm with Adaptive Laplace Prior
Remote Sensing, 2022 Space-time adaptive processing (STAP) encounters severe performance degradation with insufficient training samples in inhomogeneous environments. Sparse Bayesian learning (SBL) algorithms have attracted extensive attention because of their robust and ...
Weichen Cui +3 more
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Knowledge-Aided STAP Using Low Rank and Geometry Properties [PDF]
, 2013 This paper presents knowledge-aided space-time adaptive processing (KA-STAP) algorithms that exploit the low-rank dominant clutter and the array geometry properties (LRGP) for airborne radar applications.
de Lamare, Rodrigo C. +3 more
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Dimension-reduced bi-iterative space–time adaptive processing method for airborne radar
The Journal of Engineering, 2019 A novel bi-iterative dimension-reduced space–time adaptive processing (STAP) algorithm for clutter suppression and moving target detection in airborne radar system is proposed.
Yuxiang Wang, Xiaoming Li, Wei Gao
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Partially Adaptive STAP Algorithm Approaches to Functional MRI [PDF]
, 2009 In this work, the architectures of three partially adaptive STAP algorithms are introduced, one of which is explored in detail, that reduce dimensionality and improve tractability over fully adaptive STAP when used in construction of brain activation ...
Holland, S. K. +4 more
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Robust Space-Time Adaptive Processing Method for GNSS Receivers in Coherent Signal Environments
Remote Sensing, 2023 In the coherent signal environments caused by multipath propagation, the interference suppression performance of the global navigation satellite systems (GNSS) receivers decreases sharply.
Zhen Meng, Feng Shen
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