Adaptive detection of distributed targets in partially homogeneous environment with Rao and Wald tests
This paper deals with the problem of detecting distributed targets in the presence of partially homogeneous Gaussian disturbance with unknown covariance matrix. Since no uniformly most powerful test exists for the problem at hand, we devise and assess two detection strategies based on the Rao test,...
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| Veröffentlicht in: | Signal processing 2012-04, Vol.92 (4), p.926-930 |
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| container_title | Signal processing |
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| creator | Hao, Chengpeng Ma, Xiaochuan Shang, Xiuqin Cai, Long |
| description | This paper deals with the problem of detecting distributed targets in the presence of partially homogeneous Gaussian disturbance with unknown covariance matrix. Since no uniformly most powerful test exists for the problem at hand, we devise and assess two detection strategies based on the Rao test, and the Wald test respectively. Remarkably both tests ensure the constant false alarm rate (CFAR) property with respect to both the structure of the covariance matrix as well as the power level. A preliminary performance assessment, conducted by resorting to simulated data, also in comparison to previously proposed detectors, has confirmed the effectiveness of the newly proposed detection algorithms. |
| doi_str_mv | 10.1016/j.sigpro.2011.10.005 |
| format | Article |
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| identifier | ISSN: 0165-1684 |
| ispartof | Signal processing, 2012-04, Vol.92 (4), p.926-930 |
| issn | 0165-1684 1872-7557 |
| language | eng |
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| source | Elsevier ScienceDirect Journals |
| subjects | Adaptive detection Applied sciences Detection, estimation, filtering, equalization, prediction Exact sciences and technology Generalized likelihood ratio test (GLRT) Information, signal and communications theory Partially homogeneous environment Rao test Signal and communications theory Signal, noise Telecommunications and information theory Wald test |
| title | Adaptive detection of distributed targets in partially homogeneous environment with Rao and Wald tests |
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