【作者】 周欣；

【导师】 石要武；

【作者基本信息】 吉林大学 ， 控制理论与控制工程， 2006， 硕士

【摘要】 电磁矢量传感器阵列信号处理是阵列信号处理领域中一个新兴的学科分支,它在雷达、声纳、通信和生物医学等领域有着广泛的应用前景。本文将现代信号处理中的优秀方法与电磁矢量传感器阵列信号处理相结合,研究了在有色噪声背景下非平稳信号的波达方向和极化参数同时估计的问题。这样可以充分利用信号的具体特性和接收的冗余信息来实现算法性能的真正突破。首先,针对一类特殊的非平稳信号——循环平稳信号,利用其循环平稳特性,提出了几种方法分别解决了非相干信号和相干信号参数估计问题。又针对非平稳信号(如LFM信号)入射到单电磁矢量传感器上,利用其时频特性构造空间极化时频分布矩阵,提出了WVD-MUSIC算法和WHT-MUSIC算法。本文所提的方法都具有很好的信号选择性、抗干扰和抑制噪声的性能。更多还原

【Abstract】 The electromagnetic vector sensor array signal processing is a new emergingsubdiscipline in array signal processing domain. In recent years, DOA andpolarization parameters estimation of signals using array of electromagnetic (EM)vector sensors(VS’s) has become a hotspot, which is widely used in radar, sonarand communication etc.The research on DOA and polarization parameters simultaneous estimationusing an array of electromagnetic vector sensor is of great significance in practicalapplication and academy. People have used traditional scalar sensor array on DOAestimation for a long time, and have massive academic achievements. Through thissystem we cannot obtain the integrated electric and magnetic fields information butonly the information on one field component. The array element output onlyreflected the receive signal intensity and the absolute phase. The lack ofinformation will eventually affects the algorithm performance. However, EMVScan provide complete electric and magnetic fields, which is composed of threeorthogonal electric dipoles and three corresponding orthogonal magnetic dipoles.Not only it can use its array geometry structure to acquire the spatial information ofthe signal, but also can acquire all polarization information. So it has higherinformation acquire ability than the common arrays due to the additionalpolarization information. Compared with traditional scalar sensors, electromagneticvector sensor array has a better performance: steady detective ability, strongeranti-jamming ability as well as higher space resolution.At present the mass of method used in electromagnetic vector sensor arraysignal processing domain is based on supposition of the white Gaussian noise andthe steady signal. But in practical environment, the white Gaussian noisesupposition may not always be true, and many signals exited are not steady. Forexample, many man-made signals ,such as BPSK, FSK, AM signals, exhibit in thecyclostationarity, and LFM signals used in radar applications. As a result, theperformance of subspace-based DOA and polarization estimation techniques maydegrade when dealing with non-stationary signals.The electromagnetic vector sensor array has rich redundant information.Using this characteristic and with the concrete characteristic of the signal, weresearch the estimations of DOA and polarization in colored noise.Firstly, considering a kind of special non-stationary signal-cyclostationaritysignal, this paper do some research on the cyclostationarity characteristic in timedomain. Based on single electromagnetic vector sensor, we propose cyclic MUSIC,Cyclic ESPRIT and Cyclic TLS-ESPRIT for estimating the DOA and polarizationparameters of uncorrelated EM signals on the same time using one EMVS. Thealgorithms we proposed are able to separate the signals with different cyclefrequencies. Meanwhile, they can suppress the colored noise and interferentialsignal. Simulation results show that these algorithms have good performances inDOA and polarization parameters estimation.In reality, due to the impact of the multi-path aspects, there are many coherentsignal sources in space. But the general subspace DOA methods such as CyclicMUSIC and Cyclic ESPRIT can not estimate accurately DOA and polarizationparameters of the coherent signal sources because the signal subspace and the noisesubspace influence mutually. In order to solve the problem of the DOA andpolarization estimation of coherent signals, we propose Cyclic MUSIC and CyclicTLS-ESPRIT based on vector sensor smoothing. The proposed methods canremove the singularity in the signal correlation matrix in scenarios with coherentsources. Also it can suppress the colored noise and interference. Simulation resultsshow that these algorithms have good performances.The non-stationary signals such as LFM signal, were widely used in manysignal processing applications, and one of the most important application is onradar and sonar. About the non-stationary signals, time-frequency analysis iscombined with EMVS array processing to develop a DOA and polarizationestimation method. Spatial polar time-frequency distribution (SPTFD) isgeneralized by using a single EMVS and the time-frequency (TF) distribution. Wedevelop TF-MUSIC based on Wigner-Ville Distribution and TF-MUSIC based onWigner-Hough Translation for estimating the DOA and polarization parameters.The proposed methods have the ability to select the signal of interesting,and aresuitable for non-stationary signals.更多还原