A Research On The Method Of Sidelobe Suppression For Nonuniform Sparse Array

The non-uniform sparse array(NUSA),whose locations of elements are placed sparsely,has a large aperture,thus sharing these capabilities to enhance the directivity,narrow the scanning beam,improve the spatial resolution as well as weaken the effect of mutual coupling between the elements.NUSA also provides the ability to achieve the estimate of direction of arrival(DOA)without ambiguity because of its non-uniform characteristics.However,there are many factors on the actual array environment such as mountains,rivers,swamps which could limit the scope of the array.Therefore,it is necessary to seek for some effective methods of sparse array design.In addition,the performance of DOA estimation is based on the accurate knowlege of the array manifold.Unfortunately,in practical engineering applications,the real array manifold often changes following the climate,environment and the change of the device itself.These errors would make the performance deterioration of DOA algorithm,and even lead to failure.In this paper,a NUSA configuration method accounting for antenna size and geographical environment constraints is studied.Additionally,aiming at the near-filed source location problem under array error,the self-calibration method is studied.The work mainly includes the following aspects:(1)To study the method of random sparse array configuration,the model of the non-uniform sparse array is given.The mathematical model of sparse array optimization is designed and the solution without constraints based on pattern search is investigated.Aiming at antenna size and geographical constraints which exist in the actual array configuration environment,the method based on particle swarm optimization(PSO)is studied.(2)In order to solve the problem of the near-field narrowband signal model,we first analyze these reasons on the generation of sensor position error,array gain and array phase error;Then,we derive the general model of receiving signal under these error conditions,respectively.Finally,simulation results are provided to illustrate the array error would give rise to the performance deterioration of DOA estimation algorithm.(3)A self-calibration algorithm based on iterative optimization for near field signal source is proposed.The proposed algorithm jointly estimates the signal source locations and array errors and its each iteration splits a two-dimensional search problem into two one-dimensional problems thus reducing the computation complexity.Simulation results show that source locations and error parameters can be estimated effectively using the proposed algorithm for these systems with the fast and slow change of errors.(4)Some specific scenarios are exploited to vertify the performance of the proposed sidelobe suppression technique.Precisely,the simulation data for 50-meter sparse linear array with two near-field coherent sources and the measured data for 5.8-meter sparse linear array with one near-field target are provided to test the ability of the proposed algorithm.