| Autor: |
Zeyu Wang, Jun Liu, Hongmeng Chen, Wei Yang |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Remote Sensing, Vol 14, Iss 20, p 5236 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2072-4292 |
| DOI: |
10.3390/rs14205236 |
| Popis: |
The exact knowledge of the signal steering vector is not always known, which may result in detection performance degradation when a signal mismatch occurs. In this paper, we discuss the problem of designing a robust radar target detector in the background of Gaussian noise whose covariance matrix is unknown. To improve robustness to mismatched signals, a random perturbation that follows the complex normal distribution is added under the alternative hypothesis. Since traditional detectors that divide complex parameters into real parts and imaginary parts are sometimes difficult to obtain, a new robust, complex parameter gradient test is derived directly from the complex data. Moreover, the CFAR property of the new detector is proven. The performance assessment indicates that the gradient detector exhibits suitable robustness to the mismatched signals. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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