A new method of spatial-spectrum detection based on noise suppression in signal subspace

Hui Hui Wang, Qun Fei Zhang, Zhen Hua Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a new method to overcome the poor spatial-spectrum detective performance of Minimum Variance Distortionless Response (MVDR) is proposed for weak broadband signal. The new approach, called EBMVDR in this paper, is based on noise suppression in signal subspace. Firstly, Eigen decomposition is used in covariance matrix of the received data vector in frequency domain, and then estimate noise power using the pre-estimated signal dimension. Next, the covariance matrix is reconstructed by suppressing noise in the signal subspace. Finally, the weight vector can be got for the new method. At the same time, array gain of EBMVDR is deduced. Theory analysis and statistical simulation results show that: when the noise is white, the lowest detection signal-noise ratio (SNR) performance improves 6dB compared to the conventional MVDR method. Moreover, the new method has good robustness and stable array gain within the whole bandwidth.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2011
DOIs
StatePublished - 2011
Event2011 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2011 - Xi'an, China
Duration: 14 Sep 201116 Sep 2011

Publication series

Name2011 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2011

Conference

Conference2011 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2011
Country/TerritoryChina
CityXi'an
Period14/09/1116/09/11

Keywords

  • noise suppression
  • signal subspace
  • spatial spectrum detection
  • weak signal

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