Adaptive space-time process in radar applications

1997 ◽  
Vol 1 (2) ◽  
pp. 151-161
Author(s):  
Jean Appel
2010 ◽  
Vol 2010 ◽  
pp. 1-6
Author(s):  
Yang Zhiwei ◽  
He Shun ◽  
Liao Guisheng ◽  
Ouyang Shan

We propose a subspace-tracking-based space-time adaptive processing technique for airborne radar applications. By applying a modified approximated power iteration subspace tracing algorithm, the principal subspace in which the clutter-plus-interference reside is estimated. Therefore, the moving targets are detected by projecting the data on the minor subspace which is orthogonal to the principal subspace. The proposed approach overcomes the shortcomings of the existing methods and has satisfactory performance. Simulation results confirm that the performance improvement is achieved at very small secondary sample support, a feature that is particularly attractive for applications in heterogeneous environments.


2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Zhaocheng Yang ◽  
Rodrigo C. de Lamare ◽  
Xiang Li ◽  
Hongqiang Wang

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. The core idea is to exploit the clutter subspace that is only determined by the space-time steering vectors, by employing the Gram-Schmidt orthogonalization approach to compute the clutter subspace. Simulation results illustrate the effectiveness of our proposed algorithms.


Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1169
Author(s):  
Shiyi Li ◽  
Na Wang ◽  
Jindong Zhang ◽  
Chenyan Xue ◽  
Daiyin Zhu

Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, a slow-time code design is considered for the STAP technique in airborne radar, and the principle for improving signal-to-clutter and noise ratio (SCNR) based on slow-time coding is given. We present two algorithms for the optimization of transmitted codes under the energy constraint on a predefined area of spatial-frequency and Doppler-frequency plane. The proposed algorithms are constructed based on convex optimization (CVX) and alternating direction (AD), respectively. Several criteria regarding parameter selection are also given for the optimization process. Numerical examples show the feasibility and effectiveness of the proposed methods.


Author(s):  
О. Lavryk

The problem of allocating paragenetic anthropogenic landscapes. The processes of formation, development and operation of the paragenetic and paradinamic connection in landscape complex of channel and floodplain of the Southern Bug River. On the example of the space-time process of development of the bottom of the river valley described the process of exchange of matter, energy and information between the anthropogenic landscape complexes. Key words: Southern Bug River, channel, floodplain, anthropogenic landscape, landscaped complex, paradinamic connection, paragenetic connection.


Author(s):  
James N. Druckman

Persuasion is a vital part of politics—who wins elections and policy disputes often depends on which side can persuade more people. Given this centrality, the study of persuasion has a long history with an enormous number of theories and empirical inquiries. However, the literature is fragmented, with few generalizable findings. I unify previously disparate dimensions of this topic by presenting a framework focusing on actors (speakers and receivers), treatments (topics, content, media), outcomes (attitudes, behaviors, emotions, identities), and settings (competition, space, time, process, culture). This Generalizing Persuasion (GP) Framework organizes distinct findings and offers researchers a structure in which to situate their work. I conclude with a discussion of the normative implications of persuasion. Expected final online publication date for the Annual Review of Political Science, Volume 25 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.


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