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首页> 外文期刊>IEEE Transactions on Signal Processing >Locating the Few: Sparsity-Aware Waveform Design for Active Radar
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Locating the Few: Sparsity-Aware Waveform Design for Active Radar

机译：定位很少：有源雷达的稀疏感知波形设计

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摘要

Owing to the inherent sparsity of the target scene, compressed sensing (CS) has been successfully employed in radar applications. It is known that the performance of target scene recovery in CS scenarios depends highly on the coherence of the sensing matrix, which is determined by the radar transmit waveform. In this paper, we propose efficient transmit waveform optimization approaches for two different structures of the radar waveform, namely, the single-pulse and the more general pulse-train scenarios. By determining the identical coherence values associated with the sensing matrices of CS-based radars, the suggested methods provide a considerable reduction in the number of optimization variables. We show that, in the single-pulse scenario, fast Fourier transform operations can be used to improve the computation speed, whereas efficient power method-like iterations may be employed in the pulse-train scenarios. The effectiveness of the proposed algorithms is illustrated through several numerical examples.
机译：由于目标场景固有的稀疏性，压缩传感（CS）已成功应用于雷达应用中。众所周知，CS场景中目标场景恢复的性能在很大程度上取决于传感矩阵的相干性，而相干性是由雷达发射波形确定的。在本文中，我们针对雷达波形的两种不同结构（即单脉冲和更通用的脉冲序列方案）提出了有效的发射波形优化方法。通过确定与基于CS的雷达的感测矩阵相关的相同相干值，建议的方法可显着减少优化变量的数量。我们表明，在单脉冲场景中，可以使用快速傅立叶变换操作来提高计算速度，而在脉冲序列场景中可以采用类似于幂方法的有效迭代。通过几个数值示例说明了所提出算法的有效性。

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