Research On Resolving Ambiguity Of Near-field Source Parameter Estimation Based On Uniform Circular Array

Near-field source localization in the field of wireless communication,electronic reconnaissance and sonar,etc.has received considerable attention.In the context of three-dimensional(3-D)parameter estimation of source,uniform circular array(UCA)has advantages over other array configuration.It should be pointed out that parameter estimation of source suffers from serious phase ambiguity problem and most literatures employ methods to avoid phase ambiguity by limiting the array aperture is smaller than half-wavelength.In practical systems with fixed UCA,however,the increased source frequency may induce serious ambiguity of phase difference,which will lead to inaccuracy of 3-D parameter estimation.This paper will focus on the phase ambiguity problem of source localization based on phase difference parameter estimation algorithm in project.By analyzing algorithm ambiguity property,this paper proposed effective resolving ambiguity methods and the results of this investigation will provide important theoretical and technical supports for designing and developing of the near-source localization system.The main work and research results are shown as follow:The first chapter is introduction.It reveals the development of near-field source localization.The research status of near-field source localization using UCA is shown in this chapter.The trouble of phase ambiguity in the context of 3-D parameter estimation is emphasized and few literature developed relevant research is pointed out.Therefore,proper and effective resolving ambiguity method of near-field parameter estimation is exigent.The second chapter mainly researches the algorithm of source's 3-D parameter estimation based on phase difference using UCA.Firstly,The signal model of multiple near-field sources with UCA is developed.Secondly,the procedure of detail algorithm is presented and extend it to the applied situation for multiple sources.Finally,we analyze the condition of ambiguity and obtain the unambiguous location area of near-field source under ambiguous condition by theoretic analysis and simulation demonstration,which could provide constructive guidelines in theoretical analysis and practical appliance.The third chapter mainly focuses on a resolving ambiguity method by adaptive rotation of UCA with a center sensor to make the same sensors form virtual short baseline.Under fixed UCA,phase ambiguity would appear for estimating 3-D location of near-field source whose frequency exceeds the threshold and resolving ambiguity could be implemented by virtual short baseline formed by rotation.In order to calibrate the initial phase difference of received signal before and after rotation,we should set a fixed sensor at the center of UCA,the delay-induced phase of which is not affected by rotation.Moreover,based on the estimated frequencies of sources,the maximal rotation angle is determined adaptively and it is the most excellent rotation angle.Simulation results indicate that the proposed algorithm could resolve ambiguity effectively and the performance of parameter estimation is excellent.However,the algorithm utilizes two groups of receiving data from different time,which is only adaptive to fixed frequency signal.The forth chapter mainly introduce the proposed algorithm of resolving ambiguity based on multiple results from subclass under fixed UCA,which utilizes the method of clustering via Euclidean distance and could adaptive to fixed-frequency and frequency-hopping signals.Firstly,the ambiguity is mainly induced by angle parameters and the separation of source's angles and range is necessary as both are interlaced with each other,which causes the difficulty of resolving ambiguity.To resolve the trouble,we found that the source's range just be counteracted by computing the phase differences of receiving data from centro-symmetric sensors,thus angles and range of the source could be separated.After that,by employing some algebraic operations based on a couple of different groups of phase differences,the source's angle parameter estimation can be obtained,but the results may be ambiguous.Considering ambiguity resolution,it can be noticed that different combinations of phase differences could estimate same source's angle parameters except for ambiguous situation as the property of ambiguity under different combinations are inconsistent.By searching ambiguity,the real source's angle parameters would be included in the results of all the combinations and the differences among other value are relatively large,thus we could obtain the unambiguous angle parameters by utilizing the method of clustering via distance.Finally,to estimate the remaining source's range and improve the estimation performance of angle parameters,we utilize the obtained real angles to resolve ambiguity of the algorithm based on phase difference retrieval parameter estimation via the approximation of steering vectors between planar wavefront and curved wavefront as the ratio of source's range and array radius is large enough.Furthermore,we further research the proper selection of CSS groups and sample in clustering by theoretic analysis and simulation experiment.Simulation results indicate that the proposed algorithm could resolve ambiguity effectively,the performance of parameter estimation is excellent and the algorithm could adaptive to fixed-frequency and frequency-hopping signals.However,the proposed algorithm demand even sensors and the number is less than eight which limits its appliance in practice.The fifth chapter makes a summary of the studies and main contributions in this thesis.The perspectives of array error calibration and multiple access interference are provided and some open problems are also presented.