On two-dimensional statistical resolution limit with Rao test

Statistical Resolution Limit (SRL) is defined as the minimal separation to resolve two closely-spaced signals. It is a significant metric to quantify performance in parameter estimation problems. For SRL analysis, since the method based on the Generalized Likelihood Ratio test (GLRT) has the problem of high computational complexity, we put forward a Rao-test-based approach. It only needs to calculate the maximum likelihood estimation (MLE) of the unknown parameters under the hypothesis H
₀
, which effectively reduces the computational complexity. This paper analyzes two dimensional SRL of two adjacent signals exploiting a Rao-test-based method. Simulations are carried out to compare the detection performance of this approach and the GLRT-based method. The simulation results verify the validity of the proposed method.