期刊论文详细信息
Sensors
Statistical Analysis of the Performance of MDL Enumeration for Multiple-Missed Detection in Array Processing
Fei Du2  Yibo Li1  Shijiu Jin2  Yunchuan Sun2  Antonio Jara2 
[1] State Key Laboratory of Precision Measurement Technology and Instrument, Tianjin University, Tianjin 300072, China;
关键词: performance analysis;    minimum description length (MDL);    array processing;    multiple-missed detection;    source enumeration;   
DOI  :  10.3390/s150820250
来源: mdpi
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【 摘 要 】

An accurate performance analysis on the MDL criterion for source enumeration in array processing is presented in this paper. The enumeration results of MDL can be predicted precisely by the proposed procedure via the statistical analysis of the sample eigenvalues, whose distributive properties are investigated with the consideration of their interactions. A novel approach is also developed for the performance evaluation when the source number is underestimated by a number greater than one, which is denoted as “multiple-missed detection”, and the probability of a specific underestimated source number can be estimated by ratio distribution analysis. Simulation results are included to demonstrate the superiority of the presented method over available results and confirm the ability of the proposed approach to perform multiple-missed detection analysis.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.

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