Efficient motion parameter estimation for maneuvering target based on segment processing

The problems of range cell migration (RCM) and Doppler frequency migration (DFM) occurred during the long time integration may severely affect the integration performance for maneuvering targets. In this paper, the RCM is corrected through dividing the range frequency spectrum into several segments, which decreases the range resolution based on the relationship between the size of the range cell and the signal bandwidth. After that, a well-focused image of a maneuvering target with third-order motion is obtained via segmental dual-scaled correlation transform (SDSCT), and three motion parameters, i.e., velocity, acceleration, and acceleration rate, are effectively estimated. The proposed method can detect multiple maneuvering targets with third-order motion with low computational complexity. Compared with several representative methods, the proposed method achieves a good balance between the computational cost and the parameter estimation performance. Finally, simulated results are used to validate the effectiveness of the proposed method.