Most of the 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 clock drifting and sensor position uncertainties always exist. To match the actual array reception condition

a DOA estimation method that uses partly calibrated nested array is presented. The proposed method 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 covariance matrix in sparse representation framework

which owes consecutive degrees of freedom. Finally

the influence of the finite number of samples is considered

and the DOAs are successively estimated by applying sparse total squares (STLS) algorithm based on the estimated result of gain-phase errors. The proposed method not only performs independent of gain-phase errors

but also can provide improved resolution and estimation accuracy

by depending on the high DOFs provided by nested array and anti-disturbance characteristics of STLS algorithm. Simulation results validate the effectiveness of the proposed method.