Results 1 to 10 of about 4,896 (201)

Performance of two Low-Rank STAP Filters in a Heterogeneous Noise [PDF]

open access: yes, 2013
International audienceThis paper considers the Space Time Adaptive Processing (STAP) problem where the disturbance is modeled as the sum of a Low-Rank (LR) Spherically Invariant Random Vector (SIRV) clutter and a zero-mean white Gaussian noise. To derive
Forster, Philippe   +3 more
core   +3 more sources

Robust Space-Time Adaptive Processing Method for GNSS Receivers in Coherent Signal Environments

open access: yesRemote 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
doaj   +1 more source

Fast-time STAP performance in pre and post range processing adaption as applied to multichannel SAR [PDF]

open access: yes, 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.
core   +1 more source

MIMO radar space–time adaptive processing using prolate spheroidal wave functions [PDF]

open access: yes, 2008
In the traditional transmitting beamforming radar system, the transmitting antennas send coherent waveforms which form a highly focused beam. In the multiple-input multiple-output (MIMO) radar system, the transmitter sends noncoherent (possibly ...
Chun-yang Chen   +2 more
core   +2 more sources

Unified Theoretical Frame of a Joint Transmitter-Receiver Reduced Dimensional STAP Method for an Airborne MIMO Radar

open access: yesLeida xuebao, 2016
The unified theoretical frame of a joint transmitter-receiver reduced dimensional Space-Time Adaptive Processing (STAP) method is studied for an airborne Multiple-Input Multiple-Output (MIMO) radar.
Guo Yiduo   +3 more
doaj   +1 more source

An adaptive detection of spread targets in locally Gaussian clutter using a long integration time [PDF]

open access: yes, 2012
This paper deals with the problem of detecting a collision target in ground clutter, using a long integration time. A single reception channel being available, classical space time adaptive processing (STAP) cannot be used. After range processing, ground
Goy, Philippe   +2 more
core   +1 more source

Knowledge-aided STAP in heterogeneous clutter using a hierarchical bayesian algorithm [PDF]

open access: yes, 2011
This paper addresses the problem of estimating the covariance matrix of a primary vector from heterogeneous samples and some prior knowledge, under the framework of knowledge-aided space-time adaptive processing (KA-STAP).
Besson, Olivier   +2 more
core   +2 more sources

Sparse Representation Based Algorithm for Airborne Radar in Beam-Space Post-Doppler Reduced-Dimension Space-Time Adaptive Processing

open access: yesIEEE Access, 2017
An efficient and training-sample-reducing space-time adaptive processing (STAP) algorithm based on sparse representation for ground clutter suppression in airborne radar is proposed in this paper. First of all, the principle and problems of sample matrix
Yiduo Guo, Guisheng Liao, Weike Feng
doaj   +1 more source

Fast estimation of false alarm probabilities of STAP detectors - the AMF [PDF]

open access: yes, 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
core   +2 more sources

Robust STAP With Reduced Mutual Coupling and Enhanced DOF Based on Super Nested Sampling Structure

open access: yesIEEE Access, 2019
In practical airborne radar, mutual coupling between array elements usually leads to space-time steering vector distortion for space-time adaptive processing (STAP), which seriously degrades radar performance.
Mingxin Liu, Xuegang Wang, Lin Zou
doaj   +1 more source

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