ISAR Imaging with Envelope Information

To achieve high-quality inverse synthetic aperture radar (ISAR) imaging, measuring amplitude and phase precisely is crucial. However, for moving targets with complex motions such as rotation or rocking, the coherence between pulses deteriorates, making it difficult to estimate phase information accurately. This leads to azimuth defocusing issues with the traditional range-Doppler (RD) algorithm. To overcome this obstacle, we propose a novel ISAR imaging method based on the expectation maximization (EM) algorithm. This method accurately estimates the motion trajectory of the target by using only the envelope information of time-varying amplitudes and the dynamic observation model established within the Bayesian framework. The parameters are adjusted with great precision through iterative optimization of the EM algorithm, which includes both the expectation and maximization steps, to achieve high-quality ISAR images and track target trajectory effectively. The effectiveness of the proposed algorithm is verified using simulation data based on the millimeter-wave (MMW) radar on the Yak-42 aircraft model.