摘要
提出一种基于平行因子分析的近场循环平稳信源方位角和距离联合估计算法,该算法利用阵元的观测数据计算三个三阶循环矩矩阵,构建循环统计量域的平行因子模型,并利用三线性交替最小二乘法分解,由分解矩阵求出信源参数.算法能有效抑制任意统计分布的平稳噪声,去除循环平稳干扰,且无需谱峰搜索和参数配对过程.均方根误差的仿真实验结果表明所提算法对信号参数具有较高估计精度.
Abstract： This paper proposes a new algorithm based on parallel factor（PARAFAC） analysis for direction of ardval（DOA） and range estimation of near-field cyclostationary sources. We compute three third-order cyclic moment matrices using the uniform linear array outputs. A parallel factor model is constructed in the cyclic statistics domain and solved via trilinear alternating least squares （TALS）. Both DO A and range of each source can be obtained without spectral searching and pairing paramenters. This algo- rithm can effectively suppress the additive stationary noise with any distribution and the cyclostationary interference. The simulation results of the root mean square error （RMSE） confirm the satisfactory performance of the proposed method.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2013年第10期1958-1963,共6页
Acta Electronica Sinica
基金
国家自然科学基金(No.61171137)
教育部新世纪优秀人才计划(No.NCET-09-0426)
关键词
无线定位
参数估计
DOA
近场源
平行因子
wireless location
parameter estimation
direction of arrival （DOA）
near-field source
parallel factor（PARAFAC）
