期刊
SIGNAL PROCESSING
卷 154, 期 -, 页码 207-216出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.sigpro.2018.09.005
关键词
Threshold optimization; Weak-signal detection; Quantization; Generalized gaussian noise
资金
- Zhejiang Provincial Natural Science Foundation of China [LQ18F010001]
- Fundamental Research Funds for the Central Universities [2017QNA4042]
- National Natural Science Foundation of China [NSFC 61731019]
In this paper, quantizer design for weak-signal detection under arbitrary binary channel in generalized Gaussian noise is studied. Since the performances of the generalized likelihood ratio test (GLRT) and Rao test are asymptotically characterized by the noncentral chi-squared probability density function (PDF), the threshold design problem can be formulated as a noncentrality parameter maximization problem. The theoretical property of the noncentrality parameter with respect to the threshold is investigated, and the optimal threshold is shown to be found in polynomial time with appropriate numerical algorithm and proper initializations. In certain cases, the optimal threshold is proved to be zero. Finally, numerical experiments are conducted to substantiate the theoretical analysis. (C) 2018 Elsevier B.V. All rights reserved.
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