Study On Parameters Estimation Of Polarization Sensitive Array Signal

Array signal processing is a new field of signal processing, and it is a very important content of modern signal processing. Array signal processing has wide engineering application such as radar, sonar, weather predicting, land and ocean exploring, seismic and biomedical signal processing etc. On different spatial positions, a few of sensors are placed by some rules so that these sensors form an array of sensors. Though the type of these sensors may be different, such as antenna, sound sensor under water, sound sensor under earth, ultrasonic sensor, X-radial sensor etc, but the function of these sensors is the same, that is, the interested spatial information is connected to signal processor. By the array of sensors, the electromagnetic wave is sent or the spatial signal is received. So the information of spatial sources is gain by signal processor. The process above is called as array signal processing. The aim of array signal processing is to acquire the useful information of spatial sources form received signal.The space electromagnetic signal is vector signal, which comprises total of three electric-field components and three magnetic-field components. If all or part of the electric-field and magnetic-field information can be acquired and exploited, then the performance of the array signal processing will be improved greatly. The electromagnetic vector sensor, which can acquire the complete electric-field components and magnetic-field components, attracts much more attention in recent year. An electromagnetic vector sensor is composed of six spatially co-located, orthogonally oriented and diversely polarized antennas, separately measuring all six electromagnetic-field components of an incident wave-field. The array formed by electromagnetic vectors sensor or trimmed vector sensors called vector sensors array. In other hand, as the vector sensors array can acquire the polarization state of the impinging signals, it is often called polarization-sensitive array (PSA).From 1990's, scholars of the world pay much more attention on the PSA, which becomes a new highlights of the array signal processing, and the array signal processing has stepped in a new period. The polarization-sensitive array signal processing mainly consists of two parts: signals filtering of PSA and multi-parameters estimation of PSA. The aim of the signals filtering of PSA is to suppress the interference signals and to enhance the expected signals by using the difference in spatial-field and polarization-field of the interference signals and the expected signals, and the precondition of the signals filtering of PSA is that the spatial and polarization information of the signal must be known. The aim of the multi-parameters estimation of PSA is to estimate the direction of arrival (DOA) and polarization parameters and so on based on the PSA without any prior knowledge if the spatial and polarization information of the signal. This paper mainly discusses the problem of multi-parameters estimation of PSA.Coherent source is familiar in practice. For example, in the case of multipath or multi-targets, the reflected waves received by radar or sonar are coherent. DOA estimation of coherent source is an important content in radar, communication and sonar. In the fifth chapter, by exploiting the polarization information and the cyclostationarity of the signal, we propose the following methods: (1) DOA and Polarization Estimation of Multipath Cyclostationary Signals under the Misorientation of Vector Sensors; (2) 2-D Direction of Arrival Estimation for Wideband Coherent Signals.According to the distance from the PSA, the source is generally departed as near-field source and far-field source. For the parameters estimation of far-field source, it generally assumes that the received signal has planar wavefront, so the range of the source is unnecessary for the DOA and polarization estimation. Most existing parameters estimation algorithms of PSA generally modeled on the far-field source. But when the source is near to the PSA,then the planar wavefront approximation is not suitable, and the DOA and polarization parameters should be jointly estimated along with the range of the source. For the problem of near-field source parameters estimation, the third chapter proposes the following methods: (1) Joint DOA, Range and Polarization Estimation of Near-Field Sources Using Cyclic Statistics; (2) Fourth-order cumulant based method. Without any frequency information, this method is effective in arbitrary Gaussian distribution noise background, and all parameters are directly given by the eigendecomposition of the constructed cumulant matrices.The final chapter is the summarization of whole dissertation.