Short-Time Velocity Identification and Coherent-Like Detection of Ultra-High Speed Targets
- Submitting institution
-
The University of Leicester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2392
- Type
- D - Journal article
- DOI
-
10.1109/TSP.2018.2862407
- Title of journal
- IEEE Transactions on Signal Processing
- Article number
- -
- First page
- 4811
- Volume
- 66
- Issue
- 18
- ISSN
- 1053-587X
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
https://doi.org/10.1109/TSP.2018.2862407
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents a novel framework for the detection of ultrahigh speed targets, based on the finite-dimension theory of Wigner matrices, and is an important theoretical breakthrough. The research direction of calculating the eigenvalues of the Wigner matrices for velocity identification has been followed by Xie et al. (Sensors, 2019). The concept of constructing coherence-like integration has been used by Zhang et al. (IET Radar, Sonar & Navigation, 2019) for pulse-Doppler radar detection. The detection concept in this paper was used to support the research of the H2020-MSCA-ITN project (FoodSmartPhone) and included in the Keynote Speech of CECNet’17.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -