Abstract: To solve the performance degrade problem of DOA estimation with few snapshots under nonuniform noise in the traditional discretization free methods, a discretization free parameter estimation method was proposed based on atomic norm minimization and annihilation filter. Firstly, the continuity of parameter space was exploited to construct a sparse representation model of array signal based on atom gathering situation, converting the signal covariance matrix recovery into the atomic norm minimization problem. Then, making full use of the Hermit Toeplitz structure and low-rank characteristics of the signal covariance matrix, the atomic norm minimization problem was transformed into a low-rank matrix approximation based practically solvable semi-definite programming problem. Thereby, the signal covariance matrix was restored.
Finally, the annihilating filter coefficients were solved based on the annihilating filter theory to carry out DOA parameter estimation. Simulation results show that the proposed method can provide higher estimation accuracy and more robustness than existing similar methods under the condition of non-uniform noise and few snapshots. The root mean sguare error of this method was reduced by 59.4% on average compared with existing methods, under different maximum noise power ratio conditions.