改进的混响数据分段Itakura距离估计算法

发布时间：2018-10-25 18:08

【摘要】：在主动探测自导系统设计中,混响数据分段Itakura距离的准确估计是实现自导系统测距,提高目标信号检测性能的基础,且Itakura距离可以评价对混响数据的局部平稳性。当前的混响数据Itakura距离估计算法采用基于局部高斯色噪声混响估计模型,当相邻数据段与需检测信号脉宽一致时,距离估计精度不好。提出一种基于Rayleigh分布分段副本相关检测的混响数据Itakura距离算法,构建混响数据包络模型实现对混响包络概率分布特征的准确描述,采用基于频率选择性衰落的自适应噪声抵消算法对混响数据包络模型进行简化,对混响数据进行Rayleigh分布下的概率密度特征分割,设计分段副本相关检测器,计算该组数据中相邻数据段之间Itakura距离,实现目标Itakura测距。实验结果表明,改进算法对Itakura距离估计精度较高,局部平稳性影响较小。在精确探测制导等领域具有很好应用价值。
[Abstract]:In the design of active detection homing system, the accurate estimation of segmental Itakura distance of reverberation data is the basis of realizing homing system ranging and improving the detection performance of target signal, and Itakura distance can evaluate the local stability of reverberation data. The current reverberation data Itakura distance estimation algorithm based on local Gao Si color noise reverberation estimation model, when the adjacent data segment and the signal pulse width to be detected, the range estimation accuracy is not good. A reverberation data Itakura distance algorithm based on Rayleigh distributed piecewise replica correlation detection is proposed. A reverberation data envelope model is constructed to accurately describe the characteristics of reverberation envelope probability distribution. The adaptive noise cancellation algorithm based on frequency selective fading is used to simplify the envelope model of reverberation data, to segment the probability density feature of reverberation data under Rayleigh distribution, and to design a piecewise replica correlation detector. The Itakura distance between adjacent data segments is calculated and the target Itakura ranging is realized. The experimental results show that the improved algorithm has higher accuracy and less influence on the local stationarity of Itakura distance estimation. It has good application value in the field of precision detection and guidance.
【作者单位】：广西经济管理干部学院计算机系;
【基金】：广西壮族自治自然科学基金项目(2011GXNSFA018170)
【分类号】：TN911.72

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