Centralized Adaptive CFAR Detection With Registration Errors in Multistatic Radar
| Autor: | Yang Yang, Shenghua Zhou, Hongtao Su, Qinzhen Hu, Junsheng Huang |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
020301 aerospace & aeronautics
Computer science business.industry Detector Aerospace Engineering 020206 networking & telecommunications 02 engineering and technology Object detection law.invention Constant false alarm rate Background noise 0203 mechanical engineering law 0202 electrical engineering electronic engineering information engineering Maximum a posteriori estimation Multistatic radar Computer vision Artificial intelligence Electrical and Electronic Engineering Radar business |
| Zdroj: | IEEE Transactions on Aerospace and Electronic Systems. 54:2370-2382 |
| ISSN: | 2371-9877 0018-9251 |
| DOI: | 10.1109/taes.2018.2816467 |
| Popis: | The problem of centralized adaptive constant false alarm rate (CFAR) detection with registration errors in multistatic radar is considered. When the observation data from different radar sites are not properly aligned after transformed into a common coordinate system, registration errors occur. This can severely degrade the target detection performance and positioning accuracy of multistatic radar. In this paper, we focus on the design of adaptive detectors that are applicable for centralized target detection with registration errors in multistatic radar. A maximum likelihood estimation-based generalized likelihood ratio test detector and a maximum a posteriori estimation-based generalized likelihood ratio test detector are developed. Both detectors possess the CFAR property with regard to the unknown statistics of the background noise. Accordingly, the performance of the two proposed detectors are analyzed. |
| Databáze: | OpenAIRE |
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