Abstract: This paper proposes a target motion parameter estimation algorithm based on Slow Time Transformation (STT) and Keystone Transformation (KT) to effectively address range and Doppler migration issues, enabling long-term accumulation of weak target energy for high-speed and highly maneuverable targets, thereby improving radar detection performance. The algorithm corrects Doppler migration effects through slow-time conjugate multiplication transformation and Keystone transformation, while addressing first-order range migration using generalized Keystone transformation and slow-time inverse transformation. Additionally, it constructs a quadratic phase compensation function based on estimated acceleration to correct second-order range migration, achieving long-term accumulation of target energy. Simulation experiments demonstrate that the algorithm achieves a good balance between computational complexity and detection performance, and real-measured data validate its feasibility for practical implementation.