摘要
波达方向(DOA)估计的经典算法,诸如MUSIC算法和ESPRIT算法均可以高精度地估计出信号的波达方向,但是它们只在阵列模型是均匀线阵(ULA)的情况下才适用。基于均匀圆阵(UCA)的波达方向估计方法可以同时估计信号的方向角和俯仰角,另外,均匀圆阵在方向角上具有近似的各向同性,使得在任何方向上,都具有近似相同的分辨能力和估计精度,在无线电监测领域有重要应用。
在无线电监测系统中处理的许多信号均是循环平稳信号,循环统计量可以实现无线信道中的平稳信号与循环平稳信号的有效分离,并且能够抑制循环频率不同的干扰信号,因此,循环统计量成为无线电监测系统中实现波达方向估计的重要手段。然而,在无线信道中,由于自然因素和人为因素的影响,信号噪声实测数据中往往伴随着较强的脉冲干扰,通常采用α稳定分布模型来描述。因此,本文主要研究脉冲噪声环境下基于均匀圆阵的DOA估计。
首先,研究了循环平稳信号的特性,包括循环均值、循环相关函数和循环谱相关函数,并对AM信号、BPSK信号和QPSK信号的循环相关函数和循环谱相关函数作了详细地分析和仿真实验。
其次,研究了均匀线阵下基于分数低阶循环自相关的DOA估计方法,包括均匀线阵下基于分数低阶循环自相关的MUSIC算法和均匀线阵下基于分数低阶循环自相关的ESPRIT算法,并做了详细地分析和仿真实验。
第三,针对传统基于UCA的循环DOA估计方法在脉冲噪声条件下失效的问题,提出了基于均匀圆阵的分数低阶循环相关矩阵；在此基础上提出了脉冲噪声环境下基于均匀圆阵的循环MUSIC (FLOCC-UCA-MUSIC)算法。计算机仿真实验结果表明,本文提出的FLOCC-UCA-MUSIC算法可以有效抑制脉冲噪声干扰,准确估计出信号的方向角和俯仰角。
第四,提出了脉冲噪声环境下基于均匀圆阵的循环ESPRIT(FLOCC-UCA-ESPRIT)算法。计算机仿真实验结果表明,本文提出的FLOCC-UCA-ESPRIT算法可以有效抑制脉冲噪声干扰,准确估计出信号的方向角和俯仰角。
最后,通过对本文工作的总结,展望下一步的工作计划。
The classical methods of direction of arrival estimation can estimate the direction of arrival accurately, such as MUSIC algorithm and ESPRIT algorithm. But they are effective only when the array model is uniform linear array. The DOA estimation methods based on uniform circular array can estimate the azimuth and elevation. In addition, uniform circular array can get same distinguishing ability and estimation accuracy in any direction for its approximate isotropy. So it has important application in the field of radio monitoring.
Cyclostationary signals are usually processed in the radio monitoring system. Cyclic statistics can identify stationary signal and circular stationary signal effectively and restrain the interference signals with different cyclic frequencies, so cyclic statistics is an important tool to wireless locating in the radio monitoring system. Noise measurement data often occurs with strong impulse due to natural and human factors in the radio channel. We usually adopt Alpha-stable distribution model to describe noise. So this paper works on the DOA estimation problem based on UCA in impulsive noise environment.
Firstly, the paper researches properties of cyclostationary signals, including cyclic mean, cyclic correlation function and cyclic spectrum correlation function. Then, the detailed analysis and simulation test have been made to AM, BPSK and QPSK signals.
Secondly, the DOA estimation methods based on the fractional lower-order cyclic correlation have been studied in ULA, which include the MUSIC algorithm and the ESPRIT algorithm. Then the detailed analysis and test are made to them.
Thirdly, since the conventional DOA estimation methods based on UCA degenerate severely in the impulsive noise environment, this paper presents a new concept referred to as the fractional lower order cyclic correlation matrix based on UCA. Then two methods have been proposed, which are called cyclic MUSIC algorithm based on UCA in impulsive noise environment. Simulation results show that the proposed FLOCC-UCA-MUSIC algorithm can restrain the impulsive noise effectively and estimate the azimuth and elevation of signals accurately.
Fourth, this paper have proposed cyclic ESPRIT algorithm based on UCA in impulsive noise environment. Simulation results show that the proposed FLOCC-UCA-ESPRIT algorithm can restrain the impulsive noise effectively and estimate the azimuth and elevation of signals accurately.
At last, the plan for next step is made based on the summarization of the paper.
引文
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