Study On Misorientation Calibration And Interference Rejection Based On Electromagnetic Vector Sensors

The calibration of vector-sensor misorientation and SPF filtering based on the polarization sensor array are discussed in this dissertation.First, two calibration methods for electromagnetic vector-sensor misorientation have been proposed. One method used two reference signals with unknown parameters to estimate the rotation matrix. The sample matrix can be calibrated according to the difference of Poynting vectors between unideal and ideal array element. The rotation matrix was simplified by the Taylor approximation in another method, only one signal with unknown parameters was used to calibrate the misorientation. The rotation matrix was obtained by the difference of Poynting vectors between unideal and ideal array element, too. Compared with other calibration methods, the two methods need no search and use fewer reference signals, they reduce the complexity of calibration, so can be realized in engineering.Second, the spacr-polarization cancellation based on the orthogonal triple dipoles (loops) and electromagnetic vector sensors has been studied. When the dipoles and electromagnetic vector sensors were used as the main and auxiliary antenna, the polarization information of signals could be received, the performance of adaptive side lobe canceller was greatly improved compared with the space cancellation based on ordinary scalar antennas. Polarization filtering can overcome the signal effect by utilizing the polarization information to reduce the desired signals in auxiliary antenna, so that ISR is improved greatly. Finally, Simulation results verified the effectiveness of the space-polarization cancellation.Finally, the SFP robust beamforming has been studied. The information of space and frequency and polarization was used in robust Capon beamforming based on the LCMV filtering. As the actual steering vector of the desired signal has a maximum projection in signal subspace, the optimal weight can be found. Changing the restriction in LCMV, another method of robust beamforming was proposed. The optimal steering vector of the desired signal was obtained by using the Lagrange multiplier. Both the two methods can full utilize the information in three fields to suppress interference.