Two-Step Low-Complexity Space-Time Adaptive Processing (STAP)

    •  Pun, M.-O.; Sahinoglu, Z.; Shah, S.; Hara, Y.; Wang, P., "Two-Step Low-Complexity Space-Time Adaptive Processing (STAP)", IEEE Global Telecommunications Conference (GLOBECOM), ISSN: 1930-529X, December 2010, pp. 1-5.
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      • @inproceedings{Pun2010dec,
      • author = {Pun, M.-O. and Sahinoglu, Z. and Shah, S. and Hara, Y. and Wang, P.},
      • title = {Two-Step Low-Complexity Space-Time Adaptive Processing (STAP)},
      • booktitle = {IEEE Global Telecommunications Conference (GLOBECOM)},
      • year = 2010,
      • pages = {1--5},
      • month = dec,
      • issn = {1930-529X},
      • url = {}
      • }
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  • Research Area:

    Signal Processing

This work proposes a low-complexity space-time adaptive processing (STAP) algorithm for sensing applications built on a moving platform in the presence of strong clutters. The proposed algorithm achieves low-complexity computation via two steps. First, it utilizes improved fast approximated power iteration methods to compress the data into a much smaller subspace. To further reduce the computational complexity, a progressive singular value decomposition (SVD) approach is employed to update the inverse of the covariance matrix of the compressed data. As a result, the proposed low complexity STAP algorithm can achieve order-of-magnitude computational complexity reduction as compared to conventional STAP algorithms. Simulation results are shown to confirm the validity of the proposed algorithm.