Artificial metasurfaces can rapidly modulate their electromagnetic scattering properties and the characteristics of echo signals, which can lead to different imaging features in synthetic aperture radar (SAR) imaging results. Based on this, for the first time, this paper proposes an approach for SAR feature reconfiguring based on periodic phase modulation with inter-pulse time bias. Considering the position and energy requirements of the expected reconfigured imaging target, this approach optimizes the metasurface modulation parameters via a dual algorithm collaborative optimization system, i.e., a modulation parameter generation algorithm (MPGA) and a parameter mapping matching algorithm (PMMA). Time-modulated metasurface targets can reconfigure imaging features of different targets at SAR reconnaissance moments under the guidance of optimized modulation parameters obtained using this approach. Compared with the previous single-point target research on the combination of SAR and metasurfaces, this method is expanded to include the combined analysis of multi-point targets and the reconfigurability of SAR features. Experiments have proved that the programmable reconfigurability of different target features (such as passenger plane targets and truck targets) can be achieved in SAR imaging results through dynamic adjustment of the modulation parameter set. The reconfigured imaging features maintain geometric consistency within the resolution error range, and the size and position of the target can be set as required.

In this paper, an active polarization conversion metasurface (APCM) operating in the X-band (8–12 GHz) is presented. Active unit cells consist of three metal layers and two substrate layers. Anisotropic metal patches, positive-intrinsic-negative (PIN) diodes, and bias lines are integrated into the surface layer to form a chiral structure. A simple and efficient polarization conversion function is realized in this designed structure. The operating mode is switched between linear-to-linear (LTL) polarization conversion and linear-to-circular (LTC) polarization conversion by switching the loaded PIN diode. In the LTL polarization conversion state, the polarization conversion ratio of APCM is over 90% in X-band. Reflected wave circular polarization axis ratio <3 dB in 8–12 GHz when in LTC state. The proposed structure is verified by experimental measurements.

Track processing is the foundation of radar multi-target tracking, and the processing performance for jamming has particular research significance when it comes to protecting high-value targets. At present, passive jamming using a modulated metasurface exhibits a fast response and a flexible operation mode. However, most research in this area has been carried out at the radar signal processing level and less at the data processing level. In this paper, a range of false target track deception method based on a phase-switched screen (PSS) is proposed, and the relationship between the matched filtering output, radar detection, and track processing is derived. This method uses PSS to generate multiple false targets with controlled spatial distribution and magnitude, which can form high-fidelity false tracking tracks. The number of false tracking tracks can be flexibly altered by controlling the modulation parameters. The simulation results validate the effectiveness of the proposed method.

With respect to the detection and recognition of an Artificial Modulation Target (AMT) with different modulated types, the state-of-the-art methods generally suffer the deficiencies of overfitting and insufficient generalization of existing neural network solutions. To address these problems, this paper proposes a multi-scale amplitude-phase feature discrimination method for AMTs in SAR images. First, a multi-type modulated AMT Dataset is generated (AMT Detection and Modulation Type Recognition Dataset, ADMTR Dataset), wherein the factors of jamming position, jamming-to-signal ratio (JSR), and the modulated parameter are considered to enhance the generalization. Second, a Multi-Input Multi-Output Fusion Wavelet Neural Network (MIMOFWTNN) is established, which not only uses the amplitude information of the scene but also adequately makes use of the phase and high-frequency information. This empowers us to detect the AMT in a higher dimensional feature space such that the type recognition can be implemented with more certainty. Analysis and discussions conducted on comparison experiments and ablation experiments demonstrate that the proposed network can achieve an average accuracy of 96.96% on the cross-validation set and a correct rate of 99.0% on the completely independent test set, which outperforms the compared methods.

Time-modulated metasurfaces have attracted much attention due to their flexible manipulation of electromagnetic waves. Time-varying response leads to spread-spectrum and reallocation of energy. Thus, an amplitude-phase joint modulation (TAJM) method is proposed based on a time-modulated active polarization conversion metasurface (APCM). Taking radar high resolution range profile (HRRP) as the object, the distance transformation and multi-target phenomena are further discovered. The proposed method achieves a flexible manipulation of target amplitude and phase. The relationship between the modulation parameters and HRRP feature is studied. It is revealed that the absorption depth is the dominant factor for the energy distribution of TAJM. The method can be applied to multi-target generation and target feature manipulation.

Interrupted-sampling repeater modulation (ISRM) can generate multiple virtual target images by sampling and forwarding radar signals to confront the inverse synthetic aperture radar (ISAR). However, the repeating delay is unavoidable and the system is complex. Moreover, numerous works mainly discuss the ISAR image deception based on periodic modulation, and the modulation effect is relatively limited. Active frequency selective surface (AFSS) can perform intermittent amplitude modulation to the reflected signal by varying target reflectivity, thus, it can achieve the function of ISRM. In this paper, the possibility of AFSS applied in the multiple virtual target generation is discussed, and an ISAR image-modulation method is proposed. The radar signal is periodically modulated by varying target reflectivity, which is accomplished by the AFSS-loaded PIN diodes. On this basis, the AFSS modulating frequency is randomly varied in a slow time domain. When the modulation signal is processed by the ISAR system, the produced target image is unfocused and cannot be recognized by radar. Simulation results are utilized to demonstrate the effectiveness of the proposed method.