Knowledge-aided covariance estimate via geometric mean for adaptive detection
Article Properties
-
LanguageEnglish
-
DOI (url)
-
Publication Date2020/02/01
-
Journal
-
Indian UGC (journal)
-
Refrences49
-
Citations5
-
Zheran Shang ORCID (unauthenticated)
-
Kai Huo
-
Weijian Liu ORCID (unauthenticated)
-
Yang Sun
-
Yongliang Wang
Cite
Shang, Zheran, et al. “Knowledge-Aided Covariance Estimate via Geometric Mean for Adaptive Detection”. Digital Signal Processing, vol. 97, 2020, p. 102616, https://doi.org/10.1016/j.dsp.2019.102616.
Shang, Z., Huo, K., Liu, W., Sun, Y., & Wang, Y. (2020). Knowledge-aided covariance estimate via geometric mean for adaptive detection. Digital Signal Processing, 97, 102616. https://doi.org/10.1016/j.dsp.2019.102616
Shang, Zheran, Kai Huo, Weijian Liu, Yang Sun, and Yongliang Wang. “Knowledge-Aided Covariance Estimate via Geometric Mean for Adaptive Detection”. Digital Signal Processing 97 (2020): 102616. https://doi.org/10.1016/j.dsp.2019.102616.
Shang Z, Huo K, Liu W, Sun Y, Wang Y. Knowledge-aided covariance estimate via geometric mean for adaptive detection. Digital Signal Processing. 2020;97:102616.
Journal Categories
Technology
Electrical engineering
Electronics
Nuclear engineering
Electric apparatus and materials
Electric circuits
Electric networks
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Knowledge-aided range-spread target detection for distributed mimo radar in nonhomogeneous environments | IEEE Transactions on Signal Processing |
| 2017 | |
| Adaptive detection in partially homogeneous clutter with symmetric spectrum | IEEE Transactions on Aerospace and Electronic Systems |
| 2017 | |
| Geometric means and medians with applications to target detection | IET Signal Processing |
| 46 | 2017 |
| Geometric barycenters for covariance estimation in compound‐Gaussian clutter | IET Radar, Sonar & Navigation |
| 30 | 2017 |
| Knowledge-based adaptive detection: joint exploitation of clutter and system symmetry properties | IEEE Signal Processing Letters |
| 2016 |
Refrences Analysis
The category
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics 53
is the most frequently represented among the references in this article. It primarily includes studies from IEEE Transactions on Aerospace and Electronic Systems and IEEE Transactions on Signal Processing. The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Persymmetric design of jointly detection and bearing estimation for a 2D array radar in training demanding scenarios | Digital Signal Processing |
| 2024 | |
Underwater Reverberation Suppression via Attention and Cepstrum Analysis-Guided Network | Journal of Marine Science and Engineering |
| 1 | 2023 |
Clutter Covariance Matrix Estimation for Radar Adaptive Detection Based on a Complex-Valued Convolutional Neural Network | Remote Sensing |
| 2023 | |
BER analysis of truncated SVD‐based MU‐MIMO ZF detection scheme under correlated Rayleigh fading channel | International Journal of Communication Systems |
| 2 | 2021 |
| Solvability for Two Forms of Nonlinear Matrix Equations | Bulletin of the Iranian Mathematical Society |
| 2 | 2020 |
Citations Analysis
The category
Science: Geology 2
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Solvability for Two Forms of Nonlinear Matrix Equations and was published in 2020. The most recent citation comes from a 2024 study titled Persymmetric design of jointly detection and bearing estimation for a 2D array radar in training demanding scenarios. This article reached its peak citation in 2023, with 2 citations. It has been cited in 5 different journals, 40% of which are open access. Among related journals, the Digital Signal Processing cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.