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Cited by 546

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Efficient mixed-spectrum estimation with applications to target feature extraction

Li, Jian, Stoica, P.·1996·IEEE Transactions on Signal Processing

Abstract

We present a decoupled parameter estimation (DPE) algorithm for estimating sinusoidal parameters from both 1-D and 2-D data sequences corrupted by autoregressive (AR) noise. In the first step of the DPE algorithm, we use a relaxation (RELAX) algorithm that requires simple fast Fourier transforms (FFTs) to obtain the estimates of the sinusoidal parameters. We describe how the RELAX algorithm may be used to extract radar target features from both 1-D and 2-D data sequences. In the second step of the DPE algorithm, a linear least-squares approach is used to estimate the AR noise parameters. The DPE algorithm is both conceptually and computationally simple. The algorithm not only provides excellent estimation performance under the model assumptions, in which case the estimates obtained with the DPE algorithm are asymptotically statistically efficient, but is also robust to mismodeling errors.

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Metadata

Authors
Li, J., & Stoica, P.
Venue
IEEE Transactions on Signal Processing
Published
1996-02
Volume
44
Issue
2
Pages
281-295
ISSN
  • 1053-587X (ISSN-L)
  • 1941-0476
OpenAlex
W2156893865
Cited by
546
References
0
FWCI
29.92
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Efficient mixed-spectrum estimation with applications to target feature extraction. https://app.cochat.ai/papers/10.1109/78.485924
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Li, J., & Stoica, P. (1996). Efficient mixed-spectrum estimation with applications to target feature extraction. IEEE Transactions on Signal Processing. https://doi.org/10.1109/78.485924

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.