Abstract: A track-before-detect algorithm based on dynamic programming (DP-TBD) is proposed in this paper, aiming at the target detection problem for airborne radar in the background of heavy-tailed clutter. In this algorithm, the clutter is modeled in terms of K distribution, combined with the characteristics of K-distributed clutter and airborne radar, the multi-frame detection statistic based on generalized likelihood ratio test under the TBD framework is derived, and then the dynamic programming algorithm is used to give the specific realization method of detecting and tracking target in the range-azimuth-Doppler domain. Compared with the traditional DP-TBD algorithm and single-frame detection algorithm, simulation results show that the proposed algorithm can effectively improve the detection and tracking performance of airborne radar under the background of K-distributed clutter.