The maximum a posteriori （MAP） algorithm is the most commonly used parameter estimation method. However， the MAP algorithm focuses on the position of the maximum peak of the posterior distribution and does not fully utilize the complete information of the posterior distribution. This article proposes a minimum divergence （MD） radar ranging estimation method based on relative entropy. Firstly， the posterior distribution of the parameters is derived. Secondly， a distribution similar to them is constructed. Therefore， the value is estimated by finding the minimum value of their divergence. Simulation results indicate that in radar ranging scenarios， the MD algorithm achieves approximately 1 dB gain in performance compared to the MAP algorithm， demonstrating its superior estimation performance.