Study On Methods Of DOA And Polarization Estimation Based On Electromagnetic Vector Sensor Array

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.