Study On Methods Of Parameters' Estimation Of Cyclostationary Signals Based On Electromagnetic Vector Sensor Array

The electromagnetic vector sensor array signal processing is a new emerging subdiscipline in array signal processing domain. In recent years, DOA and polarization parameters estimation of signals using array of electromagnetic (EM) vector sensors(VS's) has become a hotspot, which is widely used in radar, sonar and communication etc.The research on DOA and polarization parameters simultaneous estimation using an array of electromagnetic vector sensor is of great significance in practical application and academy. People have used traditional scalar sensor array on DOA estimation for a long time, and have massive academic achievements. Through this system we cannot obtain the integrated electric and magnetic fields information but only the information on one field component. The array element output only reflected the receive signal intensity and the absolute phase. The lack of information will eventually affects the algorithm performance. However, EMVS can provide complete electric and magnetic fields, which is composed of three orthogonal electric dipoles and three corresponding orthogonal magnetic dipoles. Not only it can use its array geometry structure to acquire the spatial information of the signal, but also can acquire all polarization information. So it has higher information acquire ability than the common arrays due to the additional polarization information. Compared with traditional scalar sensors, electromagnetic vector sensor array has a better performance: steady detective ability, stronger anti-jamming ability as well as higher space resolution.At present the mass of method used in electromagnetic vector sensor array signal processing domain is based on supposition of the white Gaussian noise and the steady signal. But in practical environment, the white Gaussian noise supposition may not always be true, and many signals exited are not steady. For example, many man-made signals ,such as BPSK, FSK, AM signals, exhibit in the cyclostationarity, and LFM signals used in radar applications. As a result, theperformance of subspace-based DOA and polarization estimation techniques may degrade 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, we research the estimations of DOA and polarization in colored noise. Considering a kind of special non-stationary signal-cyclostationarity signal-Cyclostationarity signals (QPSK) from the incident to the uniform linear array composed of electromagnetic vector sensor modules, we construct a four-order cyclostationarity matrix ,using the cyclostationarity characteristic in time domain. We propose cyclic MUSIC for estimating the DOA and polarization parameters of cyclostationary signals. However,using cyclic MUSIC based on four-order cyclostationarity accumulation to get the peak value by searching the four-dimensional region will bring large volume.Therefore we also propose cyclic ESPRIT based on four-order cyclostationarity accumulation .By using shift invariant character of cyclic ESPRIT ,we can estimate the DOA and polarization parameters directly .The problem of large volume for seaching can be solved by this way. Meanwhile the estimation accuracy can be ensured according to lower SNR.The two methods we proposed in this paper ,have advantage of both high-order cumulant and cyclostationary cumulant.The two methods also offset the disadvantage of cyclic relevant MUSIC which can not estimate the parameters of QPSK in colored noise. The methods we propose in this paper expense the array's aperture than cyclic MUSIC based on single electromagnetic vector sensor.and have the anti-jamming ability of both relavant cyclic of smooth Gaussian noise and irrelevant cyclic smooth noise distribute random in space. The effectiveness of the methods we propose in this paper is proved by simulation.