首页> 外文期刊>IEEE Transactions on Signal Processing >Performance comparison of subspace rotation and MUSIC methods for direction estimation
【24h】

Performance comparison of subspace rotation and MUSIC methods for direction estimation

机译:子空间旋转和MUSIC方向估计的性能比较

获取原文
获取原文并翻译 | 示例

摘要

The statistical performance of subspace rotation (SR) methods (such as the Toeplitz approximation method and a variant of ESPRIT) for direction estimation using arrays composed of matched sensor doublets is studied. The distributional properties of these methods are established, and a compact explicit formula for the covariance matrix of their estimation error is provided. Next, using this formula and a similar formula for MUSIC covariance matrix, it is shown that the SR methods are statistically less efficient than MUSIC, at least for a sufficiently large number of snapshots. The difference in statistical performance between the commonly used SR method and MUSIC may be substantial if the number of sensors in the array is large. An optimally weighted SR method which may approach the MUSIC level of statistical performance for one direction parameter (specified by the user) is introduced.
机译:研究了子空间旋转(SR)方法(例如Toeplitz近似方法和ESPRIT的一种变体)在使用匹配的传感器对偶构成的阵列进行方向估计时的统计性能。建立了这些方法的分布特性,并为其估计误差的协方差矩阵提供了一个紧凑的显式公式。接下来,使用该公式和MUSIC协方差矩阵的相似公式,表明SR方法在统计上比MUSIC效率低,至少对于足够多的快照而言。如果阵列中的传感器数量很大,则常用的SR方法和MUSIC之间的统计性能差异可能很大。介绍了一种最佳加权SR方法,该方法可以接近一个方向参数(由用户指定)的统计性能的MUSIC水平。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号