首页> 外文会议>Radar Sensor Technology X >STATISTICAL ANALYSIS OF BERNOULLI, LOGISTIC AND TENT MAPS WITH APPLICATIONS TO RADAR SIGNAL DESIGN
【24h】

STATISTICAL ANALYSIS OF BERNOULLI, LOGISTIC AND TENT MAPS WITH APPLICATIONS TO RADAR SIGNAL DESIGN

机译:BERNOULLI,逻辑和帐篷映射的统计分析及其在雷达信号设计中的应用

获取原文
获取原文并翻译 | 示例

摘要

The uniqueness of the Bernoulli frequency modulated signal, and other chaos-based FM signals, can be exploited to improve the performance of the Synthetic Aperture Radar systems. Recent work suggests that the Bernoulli map has an unusual behavior compared to other one dimensional discrete maps, such as Logistic or Tent maps. Additional work indicates that the sum of consecutive Bernoulli samples is generally non-Gaussian, except when the map parameters A= 0.5 and B = 1.8. This motivates us to analyze the behavioral differences of the maps for various parameters using the Lyapunov exponent, pseudo-phase spatial trajectory and neighbor samples correlation. Specifically, the correlation of Bernoulli samples is analyzed in terms of the probability density function which is derived from experimental data. Some of statistical tools used include the Forbenius-Perron Operator, and the correlation properties of chaotic sequences. In addition, other measurements of chaos derived from nonlinear dynamical modeling will be used such as: the Lyapunov exponent and the bifurcation diagram. Results show differences between the calculated features; for example, the Lyapunov exponent is bigger for Bernoulli FM than Logistic or Tent FM. In summary, we determined that Bernoulli FM is more chaotic than Logistic or Tent FM. We have also found another singularity in the correlation of sequence samples for the Bernoulli map.
机译:可以利用伯努利调频信号和其他基于混沌的FM信号的独特性来改善合成孔径雷达系统的性能。最近的工作表明,与其他一维离散地图(例如Logistic或Tent地图)相比,伯努利地图具有不寻常的行为。额外的工作表明,连续的伯努利样本的总和通常是非高斯的,除非图参数A = 0.5和B = 1.8。这促使我们使用Lyapunov指数,伪相位空间轨迹和邻居样本相关性分析各种参数的映射的行为差异。具体而言,根据从实验数据得出的概率密度函数来分析伯努利样本的相关性。使用的一些统计工具包括Forbenius-Perron算子和混沌序列的相关属性。另外,还将使用从非线性动力学模型得出的混沌的其他度量,例如:Lyapunov指数和分叉图。结果表明计算出的特征之间存在差异;例如,伯努利FM的Lyapunov指数大于Logistic或Tent FM。总之,我们确定伯努利FM比Logistic或Tent FM更混乱。我们还在伯努利图的序列样本的相关性中发现了另一个奇点。

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