ISAR Range Alignment Based on a Spatiotemporal Attention-Seq2Seq Network
Range alignment is the first step of translational compensation processing for inverse synthetic aperture radar(ISAR)imaging,and the accuracy of range alignment has a notable impact on the quality of azimuth focusing and final imaging.To solve the problem of the serious impairment of the performance of traditional range alignment algorithms un-der the condition of sparse aperture and low signal-to-noise ratio(SNR),a novel range alignment method based on a spatiotemporal attention-sequence-to-sequence(Seq2Seq)network is proposed.A gated recurrent unit(GRU)was ad-opted in this model as the encoding and decoding unit.The spatial attention mechanism was modified according to the unique energy distribution characteristics of the range profile of point-targets.The ability to align the ISAR range profile was finally formed by incorporating the temporal and spatial attention mechanism.For training data generation,an ISAR echo dataset was constructed through imaging simulation based on electromagnetic wave simulation parameters and target motion simulation parameters.After 8-fold interpolation,it was input into the network for training,allowing the network to learn the mapping relationship from unaligned echoes to aligned echoes.The proposed method replaced online correlation calculations with offline training.By integrating the advantages of the Seq2Seq network model in han-dling Seq2Seq problems,the advantages of the temporal attention mechanism in capturing long-term dependencies,and the advantages of the spatial attention mechanism in extracting regional features,the proposed method achieved auto-matic alignment of ISAR echoes in the range slow-time domain under sparse aperture and low SNR conditions.By input-ting unaligned echo sequences into the trained spatiotemporal attention-Seq2Seq network,range alignment could be au-tomatically achieved without changing the echo phase structure.Simulation and experimental data show that,compared with traditional range alignment methods,the proposed method obtained better alignment accuracy under sparse aper-ture and low SNR conditions.A range alignment experiment was performed using measured echo data for the Yak-42 air-craft under the conditions of a 50%under-sampling rate and a 0 dB signal-to-noise ratio.The cyclic shift error was re-duced from 39 and 26 to 6,and the image entropy of the imaging results was reduced from 4.58 and 4.22 to 1.71 using the proposed method,verifying its good performance.
inverse synthetic aperture radar imagingrange alignmentspatiotemporal attention mechanismsequence-to-sequence model
万方数据
维普
