Research On Direction Of Arrival Estimation Algorithms In The Presence Of Array Gain And Phase Errors

As an important research branch of array signal processing,direction of arrival?DOA?estimation has been widely used in military and civilian areas such as sonar,radar,mobile communication and so on.Most of current direction of arrival estimation?DOA?methods are proposed based on the unbiased knowledge of the array manifold,which may not be guaranteed in some practical applications,since the aging of equipment and the change of environment.Then the performance of these algorithms will deteriorate seriously,or even fail.Therefore,DOA estimation in the presence of array errors has important value and becomes an important research area.First,we constructe the mathematical model of the array output of far-field stationary and narrowband signals based on the theory of spatial spectrum estimation.On this foundation,the model of sensor gain-phase errors is constructed.Then we analyze the effect of sensor gain and phase errors on the accuracy of MUSIC algorithm through theoretical analysis and simulation experiments.Further more,we analyze two kinds of the representative algorithms of DOA estimation under sensor gain and phase errors and summarize the shortcomings of the algorithms,therefore the follow-up research is carried based on these summaries.Second,in order to resolve the ambiguity problems of the existing array gain and phase errors non-coherent direction of arrival?DOA?estimation algorithm,we present another DOA estimation algorithm.Instead of using the magnitude squared of the measurements,the elements squared of the array covariance are adopted,which is more favorable for suppressing noise as well as eliminate the influence of sensor phase errors.The nonlinear model produced by the squared operation is approximated by a linear model under a high-power reference source.And then,the DOA estimation is efficiently obtained via the mature?₁ norm minimization.Meanwhile,we also develop an alternate work to resolve the ambiguity problems in the scenario that the sources impinging on the array.The proposed algorithm performs independent of the phase errors and can provide improved DOA estimation accuracy with reduced computational complexity in large snapshot case.Simulation results demonstrate the effectiveness and superiority of the proposed algorithm.Finally,in order to solve the problem that most of the existing DOA estimation methods can not estimate more sources with less array elements,a novel DOA estimation method that uses partly calibrated nested array is presented.The proposed method first completes the array gain-phase errors estimation by exploiting the continuous multiplication operator and simple algebraic operation,and then constructs a sparse vector model via vectorization operation on array convariance matrix in sparse representation framework,which owes consecutive degrees of freedom.Finally,the DOAs are successively estimated by applying sparse total least squares?STLS?algorithm based on the estimated result of gain-phase errors.The proposed method can provide improved resolution and estimation accuracy depending on the high DOFs provided by nested array and anti-disturbance characteristics of STLS algorithm.