A multiple targets detection method based on spatial smoothing （MTDSS） is proposed to solve the problem of the source number estimation under the colored noise background. The forward and backward smoothing based on...A multiple targets detection method based on spatial smoothing （MTDSS） is proposed to solve the problem of the source number estimation under the colored noise background. The forward and backward smoothing based on auxiliary vectors which are received data on some specific elements is computed. By the spatial smoothing with auxiliary vectors, the correlated signals are decorrelated, and the colored noise is partially alleviated. The correlation matrix formed from the cross correlations between subarray data and auxiliary vectors is computed. By exploring the second-order statistics property of the covariance matrix, a threshold based on Gerschgorin radii of the smoothing correlation matrix is set to estimate the number of sources. Simulations and experimental results validate that MTDSS has an effective performance under the condition of the colored noise background and coherent sources, and MTDSS is robust with the correlated factor of signals and noise.展开更多
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 Cri-terion using Peak-to-average Power Ratio Modified by Gerschgorin Radii)...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 Cri-terion 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.展开更多
基金supported by the National Natural Science Foundation of China (61001153)the Fundamental Research Program of Northwestern Polytechnical University (JC20100223)
文摘A multiple targets detection method based on spatial smoothing （MTDSS） is proposed to solve the problem of the source number estimation under the colored noise background. The forward and backward smoothing based on auxiliary vectors which are received data on some specific elements is computed. By the spatial smoothing with auxiliary vectors, the correlated signals are decorrelated, and the colored noise is partially alleviated. The correlation matrix formed from the cross correlations between subarray data and auxiliary vectors is computed. By exploring the second-order statistics property of the covariance matrix, a threshold based on Gerschgorin radii of the smoothing correlation matrix is set to estimate the number of sources. Simulations and experimental results validate that MTDSS has an effective performance under the condition of the colored noise background and coherent sources, and MTDSS is robust with the correlated factor of signals and noise.
文摘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 Cri-terion 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.
