Bearing-Only Target Tracking Based on Big Bang – Big Crunch Algorithm

Bearing-Only Target Tracking Based on Big Bang – Big Crunch Algorithm
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DOI：
10.1109/iccgi.2008.53
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发表时间：
2008-07
期刊：
2008 The Third International Multi-Conference on Computing in the Global Information Technology (iccgi 2008)
影响因子：
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通讯作者：
H. Genç;A. K. Hocaoglu
H. Genç;A. K. Hocaoglu
中科院分区：
其他
文献类型：
--
作者：
H. Genç;A. K. Hocaoglu

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Target tracking based on passive sensor data is of great importance in practical applications. In bearing only target tracking, the basic parameters defining the target motion is estimated through noise corrupted measurement data. Depending on the noise characteristics, the search space has many local minima. Obtaining the global minimum -that is the optimal solution - is an active area of research over the past few decades. In this work, a new optimization algorithm, namely Big Bang - Big Crunch algorithm is shown to fit this problem. The results are superior relative to classical genetic algorithm approach both in terms of speed and accuracy.