frft-cswsf: estimating cross-range velocities of ground moving targets using multistatic synthetic aperture radar
Clicks: 202
ID: 220925
2014
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Popular Article
30.0
/100
202 views
28 readers
AI Quality Assessment
Not analyzed
Readership in this journal
PopularRanked #53 of 90 articles by views in Cancer epidemiology
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Estimating cross-range velocity is a challenging task for space-borne synthetic aperture radar (SAR), which is important for ground moving target indication (GMTI). Because the velocity of a target is very small compared with that of the satellite, it is difficult to correctly estimate it using a conventional monostatic platform algorithm. To overcome this problem, a novel method employing multistatic SAR is presented in this letter. The proposed hybrid method, which is based on an extended space-time model (ESTIM) of the azimuth signal, has two steps: first, a set of finite impulse response (FIR) filter banks based on a fractional Fourier transform (FrFT) is used to separate multiple targets within a range gate; second, a cross-correlation spectrum weighted subspace fitting (CSWSF) algorithm is applied to each of the separated signals in order to estimate their respective parameters. As verified through computer simulation with the constellations of Cartwheel, Pendulum and Helix, this proposed time-frequency-subspace method effectively improves the estimation precision of the cross-range velocities of multiple targets.
| Reference Key |
chenlei2014chinesefrft-cswsf:
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Li Chenlei;Liu Mei;Zhao Bowen;Zhang Lei |
| Journal | Cancer epidemiology |
| Year | 2014 |
| DOI |
10.1016/j.cja.2014.08.011
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.