Sample selection and adaptive weight allocation for compressive MIMO UWB noise radar

Yangsoo Kwon, Ram Mohan Narayanan, Muralidhar Rangaswamy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a sample selection method for compressive multiple-input multiple-output (MIMO) ultra-wideband (UWB) noise radar imaging. The proposed sample selection is based on comparing norm values of the transmitted sequences, and selects the largest M samples among N candidates per antenna. Moreover, we propose an adaptive weight allocation which improves normalized mean-square error (NMSE) by maximizing the mutual information between target echoes and the transmitted signals. Further, this weighting scheme is applicable to both sample selection schemes, a conventional random sampling and the proposed selection. Simulations show that the proposed selection method can improve the multiple target detection probability and NMSE. Moreover, the proposed weight allocation scheme is applicable to those selection methods and obtains spatial diversity and signal-to-noise ratio (SNR) gains.

Original languageEnglish (US)
Title of host publicationCompressive Sensing
DOIs
StatePublished - Jul 23 2012
EventCompressive Sensing - Baltimore, MD, United States
Duration: Apr 26 2012Apr 27 2012

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8365
ISSN (Print)0277-786X

Other

OtherCompressive Sensing
CountryUnited States
CityBaltimore, MD
Period4/26/124/27/12

Fingerprint

Spurious signal noise
Sample Selection
MIMO (control systems)
Ultra-wideband (UWB)
Multiple-input multiple-output (MIMO)
Mean square error
Radar
radar
broadband
Radar imaging
Target tracking
Spatial Diversity
Radar Imaging
Signal to noise ratio
Detection Probability
Random Sampling
Target Detection
Antennas
Sampling
Mutual Information

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Kwon, Y., Narayanan, R. M., & Rangaswamy, M. (2012). Sample selection and adaptive weight allocation for compressive MIMO UWB noise radar. In Compressive Sensing [83650T] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8365). https://doi.org/10.1117/12.920937
Kwon, Yangsoo ; Narayanan, Ram Mohan ; Rangaswamy, Muralidhar. / Sample selection and adaptive weight allocation for compressive MIMO UWB noise radar. Compressive Sensing. 2012. (Proceedings of SPIE - The International Society for Optical Engineering).
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Kwon, Y, Narayanan, RM & Rangaswamy, M 2012, Sample selection and adaptive weight allocation for compressive MIMO UWB noise radar. in Compressive Sensing., 83650T, Proceedings of SPIE - The International Society for Optical Engineering, vol. 8365, Compressive Sensing, Baltimore, MD, United States, 4/26/12. https://doi.org/10.1117/12.920937

Sample selection and adaptive weight allocation for compressive MIMO UWB noise radar. / Kwon, Yangsoo; Narayanan, Ram Mohan; Rangaswamy, Muralidhar.

Compressive Sensing. 2012. 83650T (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8365).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Kwon Y, Narayanan RM, Rangaswamy M. Sample selection and adaptive weight allocation for compressive MIMO UWB noise radar. In Compressive Sensing. 2012. 83650T. (Proceedings of SPIE - The International Society for Optical Engineering). https://doi.org/10.1117/12.920937