In the field of target detection and tracking, the resolvability of multiple closely located targets is a significant criterion for measuring the sensing ability of radar and other sensing systems. This paper considers the problem of adaptive radar waveform design to maximize the practical resolvability of closely located targets. Conventional ambiguity function (AF)-based radar resolution considers only the waveform, regardless of the influence of noise. However, noise grreatly influences the achievable resolution as well as radar detection and tracking performance. As a result of this deficiency in conventional radar resolution, Kullback-Leibler Divergence (KLD) is introduced in this paper in order to quantify the “distance” between two probability density functions (PDFs) of radar measurements, and thus to represent practical radar resolution, which includes not only the effect of the waveform but also the signal-to-noise ratio (SNR) and measurement model. Consequently, a new adaptive radar waveform design criterion is proposed, which aims to maximize the practical radar resolution. Simulation results show the effectiveness of the proposed adaptive waveform design method.