TY - GEN
T1 - Using the conjugate gradient algorithm for reduced-rank adaptive detection
AU - Chen, Zhu
AU - Li, Hongbin
AU - Rangaswamy, Muralidhar
N1 - Publisher Copyright:
© 2012 IEEE.
PY - 2015/10/28
Y1 - 2015/10/28
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84962109520&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84962109520&partnerID=8YFLogxK
U2 - 10.1109/WDD.2012.7311258
DO - 10.1109/WDD.2012.7311258
M3 - Conference contribution
AN - SCOPUS:84962109520
T3 - 2012 International Waveform Diversity and Design Conference, WDD 2012
SP - 27
EP - 31
BT - 2012 International Waveform Diversity and Design Conference, WDD 2012
T2 - International Waveform Diversity and Design Conference, WDD 2012
Y2 - 22 January 2015 through 27 January 2015
ER -