The capability of a radar system to detect and identify the low-slow-small rotor unmanned aerial vehicle (UAV) is intensely important for management and control in low altitude, and it can be enhanced by the characteristics of UAV, which inherently carries micro-Doppler information. In this paper, we establish a micro-motion model of rotor UAV, and analyze the range walking and Doppler broadening caused by micro-motion. Hence, based on the characteristics of micro-Doppler of the rotors apart from the main body for the moving UAV, a micro-motion target detection and micro-Doppler parameters estimation method is proposed. Firstly, a method based on datashift in range dimension is used to compensate the translational component of the main body. Secondly, for the echo after translation compensation, a parameter estimation method of micro-Doppler based on the optimal demodulation operator is proposed. The operator contents the maximum likelihood criterion, which strengthens the difference between the micro-Doppler signal and the background clutters, so that more signal energy can be accumulated while the clutter is suppressed. Subsequently, the micro-Doppler parameters of the micro-motion component are obtained by the optimal demodulator, so that the detection and identification of the target are realized. Additionally, the performance of proposed method, including parameter estimation, signal-to-noise ratio (SNR) improvement and the calculation efficiency is analyzed. Finally, the simulation and experimental results reveal that the proposed method does possess the capability to improve the performance of detection and recognition of rotor UAV.

The purpose of barrage jamming against the synthetic aperture radar (SAR) is to conceal the targets to be protected, but the jamming blocks on the regions of interest (ROIs) generated by the existing barrage jamming methods cannot fully destroy the structural information of the targets in the SAR images, resulting in jamming effects that need to be improved. Aiming at this deficiency, we analyze the relationship between the statistical characteristics of the jamming templates and the jamming effects using the structural similarity (SSIM), and design a multi-scale jamming template. The jamming blocks corresponding to this template can better disturb the structural information of the targets. In addition, in order to reduce the complexity of signal modulation and ensure a large effective jamming coverage, we propose a two-step jamming signal modulation method. Simulation experiments demonstrate the performances of the signal modulation method and the jamming effect of the multi-scale template.

Synthetic aperture radar (SAR) systems have the capacity for day-and-night and all-weather surveillance, which has become increasingly indispensable for military surveillance and global comprehensive environmental monitoring. With the development of the high-resolution SAR imaging technique, studies on SAR jamming have also received much interest. Traditional jamming methods are based on linear-frequency-modulated (LFM) signals, and this method can achieve high main-lobe jamming gain. However, its sidelobe jamming energy is very low. To solve this issue, a novel nonlinear frequency modulation (NLFM) waveform design method for SAR jamming is proposed in this paper. Compared with LFM waveforms, the designed waveforms have the same main-lobe jamming gain and very high sidelobes, which can significantly improve jamming performance. Moreover, detailed simulation experiments were carried out to verify the effectiveness of the newly proposed jamming scheme.

The convolution modulation jamming method based on noise template has received widespread attention and application due to its advantages such as having the ability to obtain synthetic aperture radar (SAR) system processing gain. However, there are few studies on the evaluation analysis and optimization design of noise templates. In this letter, an optimal noise template generation method based on weighted combination is proposed and the multiscale structural similarity (MS-SSIM) index is used to evaluate the jamming effect of the obtained optimal noise template. The experimental results show that the optimal combination noise template can achieve better jamming effect than traditional noise templates under the same jamming-to-signal ratio (JSR), which verifies the effectiveness of the proposed method.

Operating mode identification is an important prerequisite for precise deceptive jamming technology against synthetic aperture radar (SAR). In order to solve the problems of traditional spaceborne SAR operating mode identification, such as low identification accuracy, poor timeliness, and limitation to main lobe reconnaissance, an efficient identification method based on sidelobe reconnaissance and machine learning is proposed in this paper. It can identify four classical SAR operating modes, including stripmap, scan, spotlight and ground moving target indication (GMTI). Firstly, the signal models of different operating modes are presented from the perspective of sidelobe reconnaissance. By setting the parameters differently, such as the SAR trajectory height, antenna length, transmit/receive gain and loss, signal–noise ratio, and so on, the feature samples based on multiple parameters can be obtained, respectively. Then, based on the generated database of feature samples, the initialized neural network can be pre-trained. As a result, in practice, with the intercepted sidelobe signal and the pre-trained network, we can precisely infer the SAR operating mode before the arrival of the main lobe beam footprint. Finally, the effect of SNR and the jammer’s position on the identification accuracy is experimentally detailed in the simulation. The simulation results show that the identification accuracy can reach above 91%.

The forwarding (repeater) jamming has been widely used in Synthetic Aperture Radar (SAR) countermeasures. However, when the jammer has a time division requirement for reception and transmission, the operation that the jammer first receives the entire SAR pulse and then transmits the jamming signal will result in a long forwarding delay. Especially for spaceborne SAR with a pulse duration of tens of microseconds, the long delay means that the jamming can only cover areas several kilometers away from the jammer, and targets close to the jammer are difficult to protect. To address this issue, a partial-pulse-reception and full-pulse-recovery jamming scheme is proposed in this paper. The core of this scheme is to recover the partial pulses intercepted by the jammer into a pulse with a complete pulse duration. A pulse recovery method based on two-dimensional joint parameter estimation is proposed, in which the problem of pulse recovery is transformed into a parameter estimation problem for single tone signals. In addition, with the help of processing tools such as wave gate limitation and Kalman filtering, the robustness of this method is improved and it can still work at an SNR as low as -30dB. The effectiveness of the proposed method is verified through experiments using measured and simulated data under different SNR conditions.