Spectral Norm Feature Detection Method in FRFT Domain of Targets in Sea Clutter

In order to optimize the coherent accumulation, repeated searches are required. However, due to the randomness and time variability, it is difficult to search for the optimal transformation order. In order to solve this problem, singular value decomposition in matrix theory is used to realize the feature extraction of FRFT spectrum under the condition of each transformation order, designs feature detection, and proposes sea clutter suppression and target detection based on singular value in the FRFT domain. The method avoids the search for the optimal transformation order while increasing the use of the shape information of the maneuvering target in the FRFT domain. Under the condition of Gaussian white noise simulation data evaluation, the proposed method can achieve a detection probability of 60% when the SNR is -2.5 dB; Verified by the measured data, the method can be stably completed under the condition that the SNR is 4.7 dB Target detection has good detection performance and is easy to implement in engineering.