In this paper, we propose a received signal interpolation method for enhancing the performance of multiple signal classification (MUSIC) algorithm. In general, the performance of the conventional MUSIC algorithm is very sensitive to signal-to-noise ratio (SNR) of the received signal. When array elements receive the signals with nonuniform SNR values, the resolution performance is degraded compared to elements receiving the signals with uniform SNR values. Hence, we propose a signal calibration technique for improving the resolution of the algorithm. First, based on original signals, rough direction of arrival (DOA) estimation is conducted. In this stage, using frequency-domain received signals, SNR values of each antenna element in the array are estimated. Then, a deteriorated element that has a relatively lower SNR value than those of the other elements is selected by our proposed scheme. Next, the received signal of the selected element is spatially interpolated based on the signals received from the neighboring elements and the DOA information extracted from the rough estimation. Finally, fine DOA estimation is performed again with the calibrated signal. Simulation results show that the angular resolution of the proposed method is better than that of the conventional MUSIC algorithm. Also, we apply the proposed scheme to actual data measured in the testing ground, and it gives us more enhanced DOA estimation result.