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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进行邻接雷达目标图像的序列清洁技术，具有高侧链

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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：高分辨率范围曲线通常遭受范围侧瓣伪像，其导致动态范围减少。通过称为连贯清洁的解卷积技术，可以大大减少侧面细胞。相干的清洁算法基于场景由隔离和独立的目标组成的假设。然而，许多现实生活目标是连续的。这些紧密间隔点的侧链和主板建设性地和破坏性地造成虚假峰值和峰值错误分配。一种称为序列清洁的技术一次使用最高的M峰来确定最佳的目标减法序列。这涉及搜索一个正在计算地昂贵的M-ary树。我们提出使用育种者遗传算法（BGA）来确定序列清洁的目标消除的最佳序列。这导致计算复杂性的显着降低。遗传算法所需的参数已被分析地导出。也导出了BGA达到收敛所需的几代人数的表达。发现BGA能够确定最佳的减法序列而不执行穷举树搜索。通过模拟验证了分析结果。

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