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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >Sequence CLEAN technique using BGA for contiguous radar target images with high sidelobes
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Sequence CLEAN technique using BGA for contiguous radar target images with high sidelobes

机译：使用BGA的序列CLEAN技术处理具有高旁瓣的连续雷达目标图像

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摘要

High resolution range profiles usually suffer from range sidelobe artifacts which cause reduction in the dynamic range. The sidelobes can be greatly reduced by a deconvolution technique called Coherent CLEAN. The Coherent CLEAN algorithm is based on the assumption that the scene consists of isolated and independent targets. However, many real-life targets are contiguous. The sidelobes and the mainlobes of these closely spaced point sources interact constructively and destructively causing spurious peaks and peak mislocations. A technique called Sequence CLEAN uses the highest m peaks at a time to determine the best sequence of target subtraction. This involves searching an m-ary tree, which is computationally expensive. We propose the use of the breeder genetic algorithm (BGA) to determine the optimal sequence of target cancellation for Sequence CLEAN. This results in a substantial decrease in the computational complexity. The parameters required for the genetic algorithm have been analytically derived. An expression for the number of generations required to reach convergence by BGA is also derived. It is found that the BGA is able to determine the best sequence of subtraction without performing the exhaustive tree search. Analytical results have been verified by simulations.
机译：高分辨率范围配置文件通常会遭受范围旁瓣伪像的影响，从而导致动态范围减小。旁瓣可以通过一种称为相干CLEAN的反卷积技术来大大减少。相干CLEAN算法基于以下假设：场景由孤立且独立的目标组成。但是，许多现实生活中的目标是连续的。这些紧密间隔的点源的旁瓣和主瓣进行建设性和破坏性的相互作用，从而导致杂散峰和峰错位。称为序​​列清除的技术一次使用最高的m个峰来确定目标减法的最佳序列。这涉及到搜索一元树，这在计算上是昂贵的。我们建议使用种鸡遗传算法（BGA）来确定用于序列清除的目标消除的最佳序列。这导致计算复杂度大大降低。遗传算法所需的参数已通过分析得出。还导出了BGA达到收敛所需的世代数的表达式。发现BGA能够确定最佳的减法顺序，而无需执行详尽的树搜索。分析结果已通过仿真验证。

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