It is commonly known that the ionosphere has significant effects on a low-frequency (particularly P-band) radar signal. It causes the degradation of the image quality in synthetic aperture radar (SAR) and inverse SAR (ISAR) imaging systems. In this letter, we analyze the ionospheric effects on radar signals and find that the total electron content (TEC) is a key to the ionospheric effects. A method is proposed to evaluate the TEC from a received ISAR signal and to correct the ionospheric effects. Some real experimental results, using a ground-based P-band ISAR system to observe a space target in the ionosphere, are used to validate the proposed method.

In multiple-input multiple-output synthetic aperture radar (MIMO–SAR) signal processing, a reliable separation of multiple transmitted waveforms is one of the most important and challenging issues, for the unseparated signal will degrade the performance of most MIMO–SAR applications. As a solution to this problem, a novel APC–MIMO–SAR system is proposed based on the azimuth phase coding (APC) technique to transmit multiple waveforms simultaneously. Although the echo aliasing occurs in the time domain and Doppler domain, the echoes can be separated well without performance degradation by implementing the azimuth digital beamforming (DBF) technique, comparing to the performance of the orthogonal waveforms. The proposed MIMO–SAR solution based on the APC waveforms indicates the feasibility and the spatial diversity of the MIMO–SAR system. It forms a longer baseline in elevation, which gives the potential to expand the application of MIMO–SAR in elevation, such as improving the performance of multibaseline InSAR and three-dimensional SAR imaging. Simulated results on both a point target and distributed targets validate the effectiveness of the echo separation and reconstruction method with the azimuth DBF. The feasibility and advantage of the proposed MIMO–SAR solution based on the APC waveforms are demonstrated by comparing with the imaging result of the up- and down-chirp waveforms.

Multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) using stepped frequency (SF) waveforms enables a high two-dimensional (2D) resolution with wider imaging swath at relatively low cost. However, only the stripmap mode has been discussed for SF MIMO-SAR. This paper presents an efficient algorithm to reconstruct the signal of SF MIMO-SAR in the spotlight and sliding spotlight modes, which includes Doppler ambiguity resolving algorithm based on subaperture division and an improved frequency-domain bandwidth synthesis (FBS) method. Both simulated and constructed data are used to validate the effectiveness of the proposed algorithm.

This paper first introduces an accurate inverse synthetic aperture radar echo model for the fast moving targets. In this model, the target's motion during the time periods of the pulse transmitting, propagating and receiving have been taken into account, and some problems, which have been ignored in the ‘stop–go’ model, may occur, for example, the varied ambiguity numbers and the drifted frequency centre. These problems will cause many difficulties in obtaining a high resolution range profile (HRRP) synthesis. To deal with these problems, a stepped frequency synthetic preprocessing (SFSP) algorithm is presented. The key of the proposed algorithm is synthetic preprocessing, including Doppler ambiguity suppression, echo coherence restoration and frequency centre correction, respectively. By completing the preprocessing, the HRRP can be achieved by a bandwidth synthesis and a well‐focused image can be obtained by a keystone transform and an azimuth process, respectively. The simulation results validate the proposed SFSP algorithm by comparing it with the algorithm in the existing extended ‘stop–go’ model.