Online High Resolution Stochastic Radiation Radar Imaging using Sparse Covariance Fitting

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceeding

Abstract

Stochastic radiation radar (SRR) systems allow for the forming of radar images by transmitting stochastic signals to form the stochastic radiation field and thereby increase the target observation information to achieve high resolution imaging. In this paper, we examine the use of the online SParse Iterative Covariance-based Estimation (SPICE) algorithm to suppress the noise and improve the operational efficiency. The SPICE algorithm is based on a weighted covariance fitting criterion, and has recently been generalized to allow for an improved reconstruction performance. The used online extension can take advantage of echoes non-correlation along time, allowing for updating the imaging result through successive echo sequences. The simulation results verify the superior performance of the resulting estimator as compared to other recent SRR imaging methods.

Detaljer

Författare
Enheter & grupper
Externa organisationer
  • University of Electronic Science and Technology of China
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Signalbehandling
Originalspråkengelska
Titel på värdpublikationIGARSS 2019
Undertitel på gästpublikation2019 IEEE International Geoscience and Remote Sensing Symposium
UtgivningsortYokohama, Japan
FörlagIEEE - Institute of Electrical and Electronics Engineers Inc.
Sidor8562-8565
Antal sidor4
ISBN (elektroniskt)978-1-5386-9154-0
ISBN (tryckt)978-1-5386-9155-7
StatusPublished - 2019 nov 14
PublikationskategoriForskning
Peer review utfördJa
EvenemangIGARSS 2019 : 2019 IEEE International Geoscience and Remote Sensing Symposium - Yokohama, Japan
Varaktighet: 2019 jul 282019 aug 2

Konferens

KonferensIGARSS 2019
LandJapan
OrtYokohama
Period2019/07/282019/08/02