Autocalibration Techniques In Array Signal Processing

As an important branch of the modern signal processing,array signal processing has been applied in many fields such as radar,sonar,communication,seismic prospecting and so on.Since most of existing array processing methods need the exact information of the array manifold,they will suffer from severe performance degradation in the presence of array perturbation such as mutual coupling with few exceptions.Therefore, a lot of researchers have made a good effort on this area,and have presented many calibration algorithms.However,there are still some problems need to be resolved.Since it is difficult to set calibration sources in some circumstances and the array perturbations may be changed with the environment,we focus on the autocalibration method of the mutual coupling between array elements without any iterative process or calibration sources.Several algorithms are presented to improved the performance against the mutual coupling in this paper,and the main contributions are illustrated as follows:First,we give a detail analysis on the mutual coupling effect of uniform linear array (ULA),which indicate the existence of some blind angles in direction finding.Due to the severe effect of the blind angles,we should avoid this condition in array designing. Based on the mutual coupling model of ULA,we prove the non-sensitivity of the subspace based direction finding algorithm,such as MUSIC(multiple signal classification) and ESPRIT(estimation of signal parameters via rotation invariance techniques), against array sensor coupling by applying a group of auxiliary sensors on the side of the array.After getting the preliminary estimation of the DOAs(directions of arrival), we can estimate the mutual coupling coefficients by utilizing an extended sensor array including the auxiliary sensors.After that,a method for refining the DOA estimates can be carried out to further improve the estimation accuracy.Moreover,the auxiliary sensor technique can also be extend to beamforming area.It can not only greatly decrease the sensitivity of the standard Capon beamformer(SCB) against mutual coupling,but also be applied united with other robust beamforming method to further improve their performances.The unknown mutual coupling can also be blindly compensated by the inherent mechanism of the proposed method and the DOA of signals can be accurately estimated based on the fourth-order cumulants(FOC) in colored noise environment.Second,we study the mutual coupling model of the uniform rectangular array (URA).Since it has a similar structure with the ULA,we also use the auxiliary technique to eliminate the mutual coupling effect during the 2-D DOA estimation.We prove that by setting the sensors on the boundary of the URA as auxiliary sensors,the MUSIC algorithm can still has a significant performance improvement.In order to reduce the computation of the 2-D spectrum search,we give a twice search technique, which can obviously shorten the computation time.Similar with the above,we can estimate the mutual coupling coefficients by using the 2-D DOA estimates.We also provide the Cramer-Rao lower bound(CRB) for the parameter estimations of a general planar array in the presence of unknown of mutual coupling as the benchmark.At last,take the uniform hexagon array for example,two autocalibration methods are proposed for the 2-D DOA estimation with a planar array.One of them can be applied in any type of planar array with a little high computation.The other one can only be applied in the array with some linearity geometric configuration.However, both of them can achieve an obvious performance improvement even when there is a coupling model mismatch.After getting the DOA estimations,two methods are proposed to estimate the mutual coupling coefficients from the view of eigen-subspace and constrained optimization,respectively.Furthermore,these coefficient estimates can also be used to further improve the accuracy of DOA estimations.The superior performance of them have been validated in the numerical examples.Some significant conclusions and prospect is also included in the end.