脉冲噪声环境下基于稀疏重构的波达方向估计方法研究

项目名称： 脉冲噪声环境下基于稀疏重构的波达方向估计方法研究

项目编号： No.61301228

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 无线电电子学、电信技术

项目作者： 李森

作者单位： 大连海事大学

项目金额： 24万元

中文摘要： 基于压缩感知稀疏重构理论的波达方向（DOA）估计方法具有比传统的DOA估计方法更高的分辨率和估计精度，但目前关于这方面的研究大多是基于高斯噪声环境下进行的，而实际系统中广泛存在的非高斯脉冲噪声将导致原有算法的性能退化。本项目以Alpha稳定分布作为脉冲噪声的数学模型，研究在脉冲噪声环境下基于压缩感知稀疏重构理论的DOA估计方法。研究内容包括：（1）研究基于阵列接收信号稀疏表示的鲁棒去噪稀疏重构算法。（2）基于阵列接收信号的信号子空间具有稀疏性的特性，研究脉冲噪声下的韧性子空间类联合稀疏恢复算法（3）研究基于阵列接收信号分数低阶统计量和分数低阶时频分布稀疏表示的DOA估计方法。本项目首次将分数低阶统计量理论与压缩感知稀疏重构理论结合起来研究阵列信号的DOA估计问题，项目的完成将有助于完善非高斯信号处理理论和压缩感知稀疏重构理论，同时提高脉冲噪声环境下DOA估计的分辨率和精度。

中文关键词： 脉冲噪声；波达方向估计；分数低阶统计量；远/近场信号源；稀疏重构

英文摘要： The Direction of arrival (DOA) estimation methods based on sparse signal reconstruction has the higher resolution and estimation accuracy than traditional DOA estimation methods. Current researches are most on the assumption that the noise is Gaussian distribution. However, in many practical situations, the noise behavior is non-Gaussian impulsive which will cause the performance of the original algorithm degradation. Therefore, the project will take Alpha stable distribution as the mathematic model of the impulsive noise and study the DOA estimation methods based on sparse signal reconstruction under impulsive noise environment. The main researches are list as follows: (1). Study the robust denoising sparse signal reconstruction algorithms based on the sparse representation of the array received signal. (2). Study the robust subspace joint sparse recovery algorithms based on that the signal subspace has the sparse characteristic. (3). Study the DOA estimation methods based on the sparse representation of the fractional lower order statistics and the fractional lower order time-frequency distribution of the array received signal. The project firstly combines the fractional lower order statistics theory and compressive sensing sparse reconstruction theory to study the DOA estimation of the array signals. The co

英文关键词： impulsive noise；DOA；fractional lower order statistics；far/near-filed signal；sparse reconstruction