Radar Maneuvering Target Motion Parameter Estimation Based on Hough Transform and Polynomial Chirplet Transform

This paper considers the problem of estimating the motion parameters of a low-observable high-speed maneuvering target with high-order motions, where the target’s complex motions will result in the range migration (RM) and Doppler frequency migration (DFM) effects within the observation time interval, which will significantly affect the radar performance. Based on the Hough transform (HT) and the polynomial Chirplet transform (PCT), a novel method for the motion parameter estimation, which we coin as HPCT, is proposed in this paper. It first employs the trajectory feature extracted from the image of range profiles by the HT to correct the first-order RM and resolve the Doppler ambiguity. Then, it compensates the residual range curvature and the DFM with the motion parameters estimated from the time-frequency ridge, which is extracted from the highly concentrated time-frequency representation (TFR) generated by the PCT. After that, the energy of radar returns can be coherently integrated along the target’s moving trajectory. In addition, we evaluate the parameter estimation performance, integration performance and computational cost of the proposed method via theoretical analysis or numerical experiments. The results show that in terms of the anti-noise ability, cross-term interference avoidance, measurement accuracy and computational complexity, the HPCT is superior to some common methods for the motion parameter estimation. Finally, we extend it to the scenario of multiple targets with different motion orders.