High-speed target detection algorithm based on FRPAF-MSFT

With the emergence of various highly maneuverable vehicles, high-speed weak target detection has become a current research hotspot. The high maneuverability of targets can lead to range migration and doppler frequency migration in echo signals, affecting the effective convergence and accumulation of signals. Therefore, this paper proposes an algorithm based on the frequency-domain inversion parameterized autocorrelation function -improved Scaled Fourier Transform. This algorithm first eliminates distance migration through frequency-domain inversion, then extracts the distance unit where the target is located for parametric autocorrelation processing. It performs slow-time variable replacement and applies MSFT processing . The target acceleration is estimated from the peak information. The compensation function is constructed based on the obtained acceleration value to compensate for the signal after pulse compression. A compensation function is constructed using the estimated acceleration values to compensate the signal after pulse compression. Subsequently, frequency - domain conjugate inversion multiplication is carried out once more, and a second MSFT is performed to acquire the distance and velocity information of the target. Simulation experiments prove that this algorithm can eliminate the influence of range migration and doppler frequency migration without any parameter search process. The complexity is about one order of magnitude lower than that of similar non-search algorithms in this paper under the parameter Settings. It still has good detection performance in the scenario of -3dB after pulse compression.