采用盖尔圆半径修正峰均功率比的检测方法

焦亚萌; 黄建国; 侯云山

采用盖尔圆半径修正峰均功率比的检测方法

西北工业大学航海学院, 西安 710072

基金项目: 国家自然科学基金资助项目(60972152);国家重点实验室基金资助项目(90140C2304080607);航空科学基金资助项目(2009ZC53031);西北工业大学基础研究基金资助项目(NPU-FFR-W018102)

详细信息

中图分类号: TN 911.7
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出版历程
- 收稿日期: 2010-12-31
- 网络出版日期: 2012-04-30

Detection of the number of sources using peak-to-average power ratio modified by Gerschgorin radii

College of Marine, Northwestern Polytechnical University, Xi-an 710072, China

摘要

摘要: 针对无人水下航行器工作环境复杂迫切需要提高其对多目标的检测能力的问题,提出了一种采用盖尔圆半径修正峰均功率比的信息论方法(PGAIC, An Information Criterion using Peak-to-average Power Ratio Modified by Gerschgorin Radii).该方法首先用采样协方差矩阵的特征向量对接收数据进行加权,计算其峰均功率比,然后对采样协方差矩阵用转换矩阵进行盖尔圆变换,用盖尔圆半径修正对应的峰均功率比值,并将修正后的峰均功率比值应用于新的信息论方法得到PGAIC判源准则.仿真结果表明,PGAIC方法低信噪比下检测性能优于传统的AIC(Akaike Information Criterion)和MDL(Minimum Description Length)等方法,且不受目标强度差的影响.
- 无人水下航行器 /
- 多目标检测 /
- 盖尔圆半径 /
- 峰均功率比 /
- 信息论准则
Abstract: Aiming at solving the problem of improving detection ability of unmanned underwater vehicle. An information criterion for source number detection with the peak-to-average power ratio modified by Gerschgorin radii (PGAIC) was proposed. The method first employed eigenvectors of the sample covariance matrix to weight the received data and calculated the peak-to-average power ratio, then took a Gerschgorin transform to the sample covariance matrix, next the new peak-to-average power ratios modified by Gerschgorin radii were introduced to Akaike information criterion(AIC) with the transformed covariance matrix. Simulation results show that PGAIC method is superior to conventional detection methods such as AIC and minimum descrition lengh(MDL) at lower signal to noise ratio, not affected by the intensity difference between the targets.
- unmanned underwater vehicle /
- multi-target detection /
- Gerschgorin radii /
- peak-to-average power ratio /
- information criterion

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参考文献(11)

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