Synthetic aperture radar (SAR) is a high-resolution imaging radar. With the deteriorating electromagnetic environment, SAR systems are susceptible to various forms of electromagnetic interference, including deception jamming. This jamming notably impacts SAR signal processing and subsequently worsens the quality of acquired images. Chaotic frequency modulation (CFM) signals could effectively counteract deception jamming. Nevertheless, due to the inadequate band-limited performance of CFM signals, higher oversampling factors are needed for achieving optimal low sidelobe levels, leading to increased system costs and excessively high data rates. Additionally, not all chaotic sentences meet the CFM signal requirements. In response, this paper proposes a novel signal modulation method called chaotic-nonlinear frequency modulation (C-NLFM) that enhances band-limited performance. The optimum parameters for C-NLFM signals are selected using the particle swarm optimization (PSO) algorithm. In this way, C-NLFM signals attain ideal low sidelobe levels even when faced with reduced oversampling factors. Meanwhile, this chaotic coding mode retains its capability to effectively suppress deception jamming. Moreover, C-NLFM signals demonstrate versatility in adapting to various chaotic sequences, thereby enhancing their flexibility to modify the signals as required. Through comprehensive simulations, data analysis, and a semi-physical experiment, the effectiveness and superiority of this proposed method have been confirmed.

Typically, synthetic aperture radar (SAR) utilizes linear frequency modulation (LFM) signal to acquire high-resolution images, requiring spectral windowing to suppress sidelobes while sacrificing signal-to-noise ratio (SNR). In contrast to LFM signal, nonlinear frequency modulation (NLFM) signal can reconstruct the signal power spectral density (PSD) without sacrificing SNR, providing autocorrelation outputs with lower sidelobes. Despite the excellent application potential of NLFM signal, the real-time generation of NLFM faces numerous challenges due to the high complexity of the systems involved and constraints imposed by waveform generator devices. In this letter, a low-complexity, high-precision and high-resolution intermediate-frequency NLFM signal generation device is developed, requiring only eleven parameters to generate real-time NLFM signal of arbitrary time width and bandwidth, with a maximum bandwidth reaching 1.2 GHz. This NLFM signal generator will be employed in the unmanned aerial vehicle (UAV) SAR system. Finally, the performance of the NLFM signal generator has been validated through ground experimental results.

The primary technical challenge for multi-input multi-output synthetic aperture radar (MIMO-SAR) systems is separating independent channel responses from aliased echoes while maintaining imaging performance. However, the most promising short-term shift-orthogonal (STSO) and segmented-phase-code (SPC) waveform require the use of elevation digital beamforming (DBF) to achieve echo separation. The cost of using elevation DBF for echo separation is the loss of elevation degrees of freedom and a significant increase in system complexity. To solve this problem, this paper proposes a novel coded waveform that introduces phase characteristics for echo separation through two-dimensional phase encoding of the transmitted waveform in both elevation and inter-pulse (azimuth) direction. In this scheme, azimuth DBF is used in the Doppler frequency domain to suppress interference signals, while elevation phase demodulation is employed to separate the echoes. This scheme eliminates the dependence of MIMO-SAR on waveform orthogonality and allows the direct use of a large number of single-station waveforms, providing flexibility in waveform selection. Additionally, retaining more degrees of freedom enables the multi-modal operation of MIMO-SAR. Finally, detailed simulation experiments are performed to verify the potential of the proposed scheme, and advantages and contributions are systematically analyzed.

Elevation Digital Beamforming (DBF) technology is key to achieving high-resolution wide-swath (HRWS) imaging in spaceborne Synthetic Aperture Radar (SAR) systems. However, multi-channel DBF-SAR systems face a prominent conflict between the need for real-time channel error calibration and the constraints of limited on-board hardware resources. To address this bottleneck, this paper proposes a real-time channel error calibration method based on Fast Fourier Transform (FFT) pulse compression and introduces a “calibration-operation” dual-mode control with a parameter-persistence architecture. This scheme decouples high-complexity computations by confining them to the system initialization phase, enabling on-board, real-time, closed-loop compensation for multi-channel signals with low resource overhead. Test results from a high-performance Field-Programmable Gate Array (FPGA) platform demonstrate that the system achieves high-precision compensation for inter-channel amplitude, phase, and time-delay errors. In the 4-channel system validation, the DBF synthesized signal-to-noise ratio (SNR) improved by 5.93 dB, reaching a final SNR of 44.26 dB. This performance approaches the theoretical ideal gain and significantly enhances the coherent integration gain of multi-channel signals. This research fully validates the feasibility of on-board, real-time calibration with low resource consumption, providing key technical support for the engineering robustness and efficient data processing of new-generation SAR systems.

Echo separation has long been a challenging and prominent research focus for Multiple-Input Multiple-Output Synthetic Aperture Radar (MIMO SAR) systems. Digital beamforming (DBF) plays a critical role in achieving effective echo separation, but it often comes at the cost of high system complexity. This paper proposes a novel MIMO SAR scheme based on phase-coded waveforms applied to both inter-pulses and intra-pulses. By introducing phase coding in both dimensions and performing joint azimuth–elevation processing, the proposed method effectively suppresses interference arising during the echo separation process, thereby significantly improving separation performance. Additionally, the approach allows for a significantly simplified array configuration, reducing both hardware requirements and computational burden. The effectiveness and practicality of the proposed scheme are validated through numerical simulations and distributed scene experiments, highlighting its strong potential for application in MIMO SAR systems—particularly in cost-sensitive scenarios and systems with limited elevation channels.