Field-programmable gate array (FPGA)-based real-time simulation serves as a powerful tool for testing and validating power electronics system (PES). However, accurate real-time simulation in high-frequency applications demands extremely small time steps, which poses significant computational and memory challenges. Explicit methods can achieve small time steps due to low-computational burdens, but have stability issues. In this article, the authors propose a topology-aware matrix partitioning (TA-MP) method, which adopts the implicit numerical algorithm to ensure stability, and uses iterative methods to solve the implicit equations. In detail, the PES matrix is partitioned into blocks with clear topological meanings, and its constant diagonal blocks are used to construct a constant iterative matrix. Since the iterative matrix is constant, the TA-MP method bypasses the limitations of using iterative methods in real-time simulations by predetermining the number of iterations. The TA-MP method eliminates the need to store inverse matrices for different topologies, requiring only matrix-vector multiplications, which are efficient on FPGA. The TA-MP method's effectiveness is validated with n-port active bridge converters on an FPGA board with a 25 ns step size, ensuring simulation accuracy at the highest switching frequency of 200 kHz while consuming only 1/15 the memory resources of the conventional method.

Multibaseline (MB) synthetic aperture radar inter-ferometry (InSAR) is capable of reconstructing steep terrain height profiles, and MB phase unwrapping (PU) is one of the most critical and challenging steps in its processing chain. Existing MB PU algorithms usually suffer from poor noise robustness or low computational efficiency. In this work, we propose a fast and robust MB PU algorithm, including three main steps: 1) construct the triangulation network guided by the quality map; 2) obtain robust estimation of ambiguity number gradients based on the intrinsic relationship between interferograms and gradient regularization; 3) solve minimum cost flow problem with modified weights. The mean absolute errors of the height profiles constructed by the proposed method are 1.6m and 1.3m for simulated data and real data experiments respectively, verifying the effectiveness of the proposed method.

Power converters become increasingly important in the power industry. To enhance design reliability and efficiency, real-time simulation is a popular method for testing control units of these devices. FPGA-based real-time simulation is considered a genuine alternative to CPU-based applications as control unit frequencies increase. Although automated tools can map simulation methods from floating-point high-level languages to fixed-point FPGA, manually selecting the fixed-point word length to meet precision requirements involves a significant amount of tedious and repetitive work. Word length selection also impacts FPGA hardware resource usage. This paper proposes an adaptive word length selection method under accuracy constraints to minimize hardware resources. The innovation lies in using error noise models to compute analytical expressions relating simulation model accuracy to word length. The adaptive word length selection process is combined with commercial high-level synthesis tools to achieve high resource optimization performance. A three-phase inverter example demonstrates the benefits of our method in calculating model accuracy and optimizing FPGA hardware resources in simulations.

Curvilinear spotlight SAR (CSSAR) has a high degree of freedom and can be used for 3-D imaging and video SAR (ViSAR) persistent imaging. The direct and effective processing of CSSAR data is an important part of CSSAR applications. However, CSSAR has higher requirements for motion compensation, especially when the motion measurement is not accurate enough. In this paper, an extended polar format algorithm (EPFA) is proposed based on the non-uniform fast Fourier transform for CSSAR. First, a theoretical derivation and analysis of the 2-D space-varying phase error in CSSAR are carried out. Then, a 2-D autofocus algorithm is proposed, which takes into account the spatial variability of the phase error. The efficiency of EPFA embedded in 2-D autofocus processing is significantly higher than that of back projection. In addition, based on the principle of small-angle approximation and spatial frequency domain sub-aperture technology, a novel ViSAR image generation scheme for CSSAR is proposed, which can significantly reduce the number of redundant calculations. The proposed algorithm is verified experimentally using data with a bandwidth of 2.4 GHz.

Lightweight multi-rotor unmanned aerial vehicles (UAVs) have shown great potential in flexible Earth observation, but they impose strict restrictions on payload, volume, and power consumption. Traditional pulse-Doppler synthetic aperture radar (SAR) systems offer high imaging performance but suffer from high peak power and large volume, making them unsuitable for lightweight UAV platforms. To meet the low-power demand, most existing lightweight UAV SAR systems adopt frequency-modulated continuous-wave (FMCW) schemes, which are compact and low cost yet limited by a low range resolution, poor anti-interference ability, and single imaging modes. Therefore, it is urgent to develop an SAR system that combines the high performance of pulse radar with the lightweight advantage of FMCW radar. To this end, this paper proposes a compact, low-power Ka-band pulse-Doppler SAR system for multi-rotor UAVs. With 1.2 GHz bandwidth and highly integrated RF and antenna design, the system achieves miniaturization and low power consumption while maintaining high-resolution imaging capability. Furthermore, two-step waveform error correction and a signal predistortion method are presented to compensate amplitude and phase errors and improve the purity of the transmitted signal. Experimental results show that the proposed system can obtain clear SAR images with a resolution better than 0.3 m, providing a practical high-performance pulse-SAR solution for lightweight UAV platforms.