Using the conjugate gradient algorithm for reduced-rank adaptive detection

Zhu Chen, Hongbin Li, Muralidhar Rangaswamy

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

Abstract

In this paper, we introduce a group of reduced-rank (RR) space-time adaptive processing (STAP) detectors based on the conjugate gradient (CG) algorithm. The CG algorithm can be used for efficient calculation of the weight vector of several well-known STAP detectors. As an iterative algorithm, it produces a series of approximations to the fully adaptive solution, each of which can be used to filter the test signal and form a test statistic. This effectively leads to a family of RR adaptive detectors, referred to as the CG-RR detectors, which are indexed by k the number of iterations incurred. Performance of the proposed CG-RR detectors are examined in terms of the output signal-to-interference-plus-noise ratio (SINR). The conventional RR methods for STAP such as the data-independent DFT or DCT based rank reduction, the adaptive eigencanceler and cross-spectral metric (CSM) algorithm are also considered here. Simulation results show that the computationally efficient CG-RR detector often reaches the peak output SINR with a lower rank compared with the eigencanceler and CSM based detectors.

Original languageEnglish
Title of host publication2012 International Waveform Diversity and Design Conference, WDD 2012
Pages27-31
Number of pages5
ISBN (Electronic)9781509005987
DOIs
StatePublished - 28 Oct 2015
EventInternational Waveform Diversity and Design Conference, WDD 2012 - Kauai, United States
Duration: 22 Jan 201527 Jan 2015

Publication series

Name2012 International Waveform Diversity and Design Conference, WDD 2012

Conference

ConferenceInternational Waveform Diversity and Design Conference, WDD 2012
Country/TerritoryUnited States
CityKauai
Period22/01/1527/01/15

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