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Exploiting persymmetry for low-rank Space Time Adaptive Processing
2014
Signal Processing
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Reducing 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. ...
By using other features of the radar system, other properties of the CM can be exploited to further reduce the number of secondary data: this is the case for active systems using a symmetrically spaced ...
Acknowledgment We thank the French DGA/MI Agency for providing us the STAP Data set. ...
doi:10.1016/j.sigpro.2013.10.026
fatcat:wpjkukfm6zhadfzfo64pqqcsya
Exploiting Persymmetry For Low-Rank Space Time Adaptive Processing
2012
Zenodo
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INTRODUCTION In Space Time Adaptive Processing (STAP) for radar applications [1] , the disturbance is composed of white Gaussian thermal noise plus ground clutter. ...
This low rank-structure can be exploited for target detection by designing adaptive filters which require much less secondary data than conventional adaptive schemes with equivalent performance [4, 5] ...
doi:10.5281/zenodo.52583
fatcat:y3dceszdkfbwtkitjmimwi4wnq
Space-time adaptive processing in bistatic passive radar exploiting complex Bayesian learning
2014
2014 IEEE Radar Conference
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In this paper, we develop a new space-time adaptive processing (STAP) technique for bistatic passive radar by exploiting clutter sparsity so as to enable effective clutter suppression with a small set ...
The Bayesian compressive sensing (BCS) technique is utilized for sparse clutter reconstruction, and the persymmetry property of the STAP processor is used to cast the complex sparse signal recovery problem ...
CONCLUSION We have examined the application of compressive sensing techniques for the implementation of space-time adaptive processing (STAP) in a bistatic passive radar. ...
doi:10.1109/radar.2014.6875723
fatcat:tsyidtciebgjxn3efi6rc7updm
A fast STAP method using persymmetry covariance matrix estimation for clutter suppression in airborne MIMO radar
2019
EURASIP Journal on Advances in Signal Processing
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In general, the space-time adaptive processing (STAP) can achieve excellent clutter suppression and moving target detection performance in the airborne multiple-input multiple-output (MIMO) radar for the ...
As one of the most efficient dimension-reduced STAP methods, the extended factored approach (EFA) transforms the full-dimension STAP problem into several small-scale adaptive processing problems, and therefore ...
Although the rank-reduced STAP methods exploit the low rank property of clutter and reduce the number of required training samples to twice of the clutter rank, they are computational intensive due to ...
doi:10.1186/s13634-019-0610-z
fatcat:tko3h2ksrrgjzpztf6rfyjl7dy
Introduction to the Issue on Advanced Signal Processing Techniques for Radar Applications
2015
IEEE Journal on Selected Topics in Signal Processing
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Sen, applies the idea of sparse signal processing for estimating the interference covariance matrix in a space-time adaptive processing (STAP) radar. ...
for vectors, low-rankness for matrices etc. ...
doi:10.1109/jstsp.2015.2497458
fatcat:7tssxg3xw5g7pnxku5zjahhg7e
Multichannel adaptive signal detection: Basic theory and literature review
[article]
2021
arXiv
pre-print
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We present the main deign criteria for adaptive detectors, investigate the relationship between adaptive detection and filtering-then-CFAR detection, relationship between adaptive detectors and adaptive ...
Filtering is not needed as a processing procedure either, since the function of filtering is embedded in the adaptive detector. ...
Precisely, the reduced-rank versions of the KGLRT, AMF, and ACE were exploited in [226] for the problem of space-time adaptive detection (STAD) in airborne radar with the data received by multiple sensors ...
arXiv:2102.03474v1
fatcat:iqj2pbyrhvam3apfsnnecljynq
Persymmetric Parametric Adaptive Matched Filter for Multichannel Adaptive Signal Detection
2012
IEEE Transactions on Signal Processing
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Index Terms-Multichannel adaptive signal detection, maximum likelihood estimation, multichannel autoregressive process, parametric approach, persymmetry. ...
This paper considers a parametric approach for adaptive multichannel signal detection, where the disturbance is modeled by a multichannel auto-regressive (AR) process. ...
Combining (34) and (44), the overall space-time covariance matrix R of a persymmetric AR process is proved to be a persymmetric-block-Toeplitz matrix. ...
doi:10.1109/tsp.2012.2190411
fatcat:3eagi7bngnfclbyuefp2y4xrvq
Kronecker STAP and SAR GMTI
[article]
2016
arXiv
pre-print
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2016
Algorithms for Synthetic Aperture Radar Imagery XXIII
unpublished
doi:10.1117/12.2223896 fatcat:pnkr4q6h7zfkzh2lubnpvjgyza
doi:10.1117/12.2223896 fatcat:pnkr4q6h7zfkzh2lubnpvjgyza
Space-time adaptive processing (STAP) is often used on multiantenna SAR to remove the stationary clutter and enhance the moving targets. ...
., 2016) it was shown that the performance of STAP can be improved by modeling the clutter covariance as a space vs. time Kronecker product with low rank factors, providing robustness and reducing the ...
Our goal in 1 and this work is to remove the disadvantages of MTI and SAR by combining their strengths (the ability to detect Doppler shifts and high spatial resolution) using space time adaptive processing ...
arXiv:1604.03622v1
fatcat:mq7dpjrl7rbvro6lsd7ll5a4de
RAPIDLY ADAPTIVE CFAR DETECTION IN ANTENNA ARRAYS
2018
Progress In Electromagnetics Research M
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For several representative scenarios when the interference CM has m dominant eigenvalues, comparative performance analysis for the proposed rapidly adaptive detectors is provided using Monte-Carlo simulations ...
N CME to be used for estimating this CM. ...
CONDITION OF RELIABLE ADAPTIVE DETECTION Q = Q TDS /Q FRV General 2M × 2M M × 2M 2 Low-rank (LR) 2m × 2M m × 2M 2 LR + Persymmetry m × 2M m × M 2 LR + Toeplitz m/2 × 2M m × M/2 2 Analysis of the Q = Q ...
doi:10.2528/pierm18092401
fatcat:77yldxl6kfaapeuttc2djki7xa
Robust SAR STAP via Kronecker Decomposition
[article]
2016
arXiv
pre-print
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Space-time adaptive processing (STAP) is often used to remove the stationary clutter and enhance the moving targets. ...
In this work, it is shown that the performance of STAP can be improved by modeling the clutter covariance as a space vs. time Kronecker product with low rank factors. ...
Space-time adaptive processing (STAP) is often used to remove the stationary clutter and enhance the moving targets. ...
arXiv:1605.01790v1
fatcat:2ewlsl4ebrhxtlolwpey6karea
Rank-Constrained Maximum Likelihood Estimation of Structured Covariance Matrices
2014
IEEE Transactions on Aerospace and Electronic Systems
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This paper develops and analyzes the performance of a structured covariance matrix estimate for the important practical problem of radar space-time adaptive processing in the face of severely limited training ...
Crucially, the RCML estimator excels for low training, including the notoriously difficult regime of K ≤ N training samples. ...
INTRODUCTION Space-time adaptive processing (STAP), i.e., joint adaptive processing in the spatial and temporal domains [1] [2] [3] , is the cornerstone of radar signal processing and creates the ability ...
doi:10.1109/taes.2013.120389
fatcat:qlmy2isbo5aqjp4wjy62ye4nce
Kronecker PCA Based Robust SAR STAP
[article]
2015
arXiv
pre-print
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In this work, it is noted that in addition to the oft noted low rank structure, the clutter covariance is also naturally in the form of a space vs time Kronecker product with low rank factors. ...
Moving target detection is more challenging due to the "burying" of moving targets in the clutter and is often achieved using space-time adaptive processing (STAP) (based on learning filters from the spatio-temporal ...
Space Time Adaptive Processing Let the vector d be a spatio-temporal "steering vector" [18] , that is, a matched filter for a specific target location/motion profile. ...
arXiv:1501.07481v3
fatcat:dcljnmzbibbkplsydzjcvpf6tq
Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP)
[article]
2016
arXiv
pre-print
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Estimating the disturbance or clutter covariance is a centrally important problem in radar space time adaptive processing (STAP). ...
In particular, we exploit both the structure of the disturbance covariance and importantly the knowledge of the clutter rank to yield a new rank constrained maximum likelihood (RCML) estimator. ...
Figure 2 .1 uses the angle-Doppler space to illustrate the need for space-time adaptive processing (STAP). ...
arXiv:1602.05069v1
fatcat:mxy33joebrchdirix3k6vepg3e
2019 Index IEEE Transactions on Signal Processing Vol. 67
2019
IEEE Transactions on Signal Processing
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., TSP Sept. 1, 2019 4624-4635
Distributed Target Detection Exploiting Persymmetry in Gaussian Clutter. ...
., +, TSP May 1, 2019 2263-2274
Awards
Awards for the IEEE Transactions on Signal Processing. TSP May 1, 2019
2469-2470
AWGN
Adaptive Detection of Structured Signals in Low-Rank Interference. ...
doi:10.1109/tsp.2020.2968163
fatcat:dvvpqntb2rc2bjed5nnk4xora4
Space–Time Adaptive Processing and Motion Parameter Estimation in Multistatic Passive Radar Using Sparse Bayesian Learning
2016
IEEE Transactions on Geoscience and Remote Sensing
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Conventional space-time adaptive processing suffers from the requirement of a large number of secondary samples. ...
By taking advantage of the intrinsic sparsity of the clutter in the angle-Doppler domain, the recently developed sparse Bayesian learning technique is employed for high-resolution clutter profile estimation ...
Space-time adaptive processing (STAP) is considered an effective technique to MTI in cluttered environments. ...
doi:10.1109/tgrs.2015.2470518
fatcat:quph3qqmnffdjn3jye7xj6o6j4
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