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2000, IEEE Signal Processing Magazine
2007 •
A fundamental issue in knowledge-aided space-time adaptive processing (KA-STAP) is to determine the degree of accuracy of the a priori knowledge and the optimal emphasis that should be placed on it. In KA-STAP, the a priori knowledge consists usually of an initial guess of the clutter covariance matrix. This can be obtained either by previous radar probings or by a map-based study. In this paper, we consider a linear combination of the a priori clutter covariance matrix with the sample covariance matrix obtained from secondary data, and derive an optimal weighting factor on the a priori knowledge by a two-step maximum likelihood (ML) approach. The performance of the two-step ML approach is compared with that of the convex combination (CC) approach and is evaluated using the KASSPER data.
2009 IEEE International Geoscience and Remote Sensing Symposium
A novel STAP algorithm using sparse recovery technique2009 •
Digital Signal Processing
Knowledge based adaptive processing for ground moving target indication2007 •
2006 IEEE Conference on Radar
Adaptive Processor Convergence Improvement using Reiterative Projection Statistics2006 •
The performance of space–time adaptive processing (STAP) may degrade dramatically if some undesired mismatches exist in real scenarios, such as array calibration error, distorted antenna shape, direction of arrival (DOA) and Doppler frequency mismatches between the actual and presumed responses to the desired target signal, insufficient training data samples and so on. In this paper, we develop a new approach to STAP that is robust to different variations in real scenarios. This method is based on the iterative optimization for the spatial–temporal separate filter. It is confirmed that this method belongs to the class of colored loading algorithms. The loading factor can be efficiently calculated based on the known level of the uncertainty mismatch sets of spatial temporal steering vectors. Computer simulations demonstrate that the proposed robust two-dimensional (2-D) beamformer with colored loading has attained better performance as compared to the conventional STAP algorithm
IEEE Transactions on Signal Processing
On Using <emphasis emphasistype="boldital">a priori</emphasis> Knowledge in Space-Time Adaptive Processing2000 •
Computing Research Repository
Airborne Radar STAP using Sparse Recovery of Clutter Spectrum2010 •
Space-time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Statistical-based STAP methods generally need sufficient statistically independent and identically distributed (IID) training data to estimate the clutter characteristics. However, most actual clutter scenarios appear only locally stationary and lack sufficient IID training data. In this paper, by exploiting the intrinsic
IEE Proceedings - Radar, Sonar and Navigation
Demonstration of knowledge-aided space-time adaptive processing using measured airborne data2006 •
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2010 •
2010 IEEE International Conference on Acoustics, Speech and Signal Processing
Knowledge-aided STAP algorithm using convex combination of inverse covariance matrices for heterogenous clutter2010 •
2005 IEEE Aerospace Conference
Robust cascaded canceller using projection statistics for adaptive radar2005 •
2011 •
International Journal of Antennas and Propagation
Direct Data Domain Sparsity-Based STAP Utilizing Subaperture Smoothing Techniques2015 •
IEEE Transactions on Aerospace and Electronic Systems
Stochastic-constraints method in nonstationary hot-clutter cancellation. II. Unsupervised training applications2000 •
2011 •
IEEE Transactions on Aerospace and Electronic Systems
Reduced-Rank STAP Algorithms using Joint Iterative Optimization of Filters2000 •
IEE Proceedings - Radar, Sonar and Navigation
KB-GLRT: exploiting knowledge of the clutter ridge in airborne radar2005 •
IEEE Transactions on Aerospace and Electronic Systems
Small-Target Detection in High-Resolution Heterogeneous Sea-Clutter: An Empirical Analysis2011 •
IEEE Transactions on Signal Processing
Interference mitigation in STAP using the two-dimensional wold decomposition model2003 •
IEEE Transactions on Signal Processing
Reduced-Rank STAP Schemes for Airborne Radar Based on Switched Joint Interpolation, Decimation and Filtering Algorithm2000 •
IEE Proceedings - Radar, Sonar and Navigation
Anti-jamming techniques for multichannel SAR imaging2006 •
2004 •
Iee Proceedings-radar Sonar and Navigation
Robust space–time adaptive processing (STAP) in non-Gaussian clutter environments1999 •
2006 IEEE Conference on Radar
Feasibility of STAP for Passive GSM-Based Radar2006 •
Digital Signal Processing
Statistical analysis of the non-homogeneity detector for STAP applications2004 •
Progress In Electromagnetics Research C
An Adaptive Reduced Rank Stap Selection with Staggered PRF, Effect of Array Dimensionality2009 •
Signal Processing, …
Code design for radar STAP via optimization theory2010 •
Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)
Improved STAP performance using knowledge-aided secondary data selection2004 •
Traitement du signal
STAP à rang réduit, robuste et persymétrique2011 •
Digital Signal Processing
Performance comparison between statistical-based and direct data domain STAPs2007 •
2011 •
IET Radar, Sonar & Navigation
Models and performance evaluation for multiple-input multiple-output space–time adaptive processing radar2009 •
2006 International Radar Symposium
Fast-time STAP Performance in pre and post Range Processing Adaption as applied to Multichannel SAR2006 •
Digital Signal Processing
Detection of heterogeneous samples based on loaded generalized inner product method2012 •
IEEE Transactions on Geoscience and Remote Sensing
Improved Space-Based Moving Target Indication via Alternate Transmission and Receiver Switching2000 •
Signal Processing
Robust STAP detection in a dense signal airborne radar environment2004 •
IEEE International Radar Conference, 2005.
Improved detection of strong nonhomogeneities for STAP via projection statistics2005 •
IEEE International Radar Conference, 2005.
Radar waveform optimization for colored noise mitigation2005 •
IEEE Transactions on Signal Processing
A CFAR adaptive subspace detector for second-order Gaussian signals2000 •
Algorithms for Synthetic Aperture Radar Imagery XIV
<title>Waveform preconditioning for clutter rejection in multipath for sparse distributed apertures</title>2007 •