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

@inproceedings{citeulike:5738720, abstract = {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.}, author = {Genc, H. M. and Hocaoglu, A. K.}, booktitle = {Computing in the Global Information Technology, 2008. ICCGI '08. The Third International Multi-Conference on}, citeulike-article-id = {5738720}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/ICCGI.2008.53}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4591373}, doi = {10.1109/ICCGI.2008.53}, journal = {Computing in the Global Information Technology, 2008. ICCGI '08. The Third International Multi-Conference on}, keywords = {rp}, pages = {229--233}, posted-at = {2009-09-08 04:29:32}, priority = {2}, title = {Bearing-Only Target Tracking Based on Big Bang \&\#150; Big Crunch Algorithm}, url = {http://dx.doi.org/10.1109/ICCGI.2008.53}, year = {2008} }

TY - CONF ID - citeulike:5738720 L3 - citeulike-article-id:5738720 N2 - 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. JF - Computing in the Global Information Technology, 2008. ICCGI '08. The Third International Multi-Conference on EP - 233 TI - Bearing-Only Target Tracking Based on Big Bang – Big Crunch Algorithm T2 - Computing in the Global Information Technology, 2008. ICCGI '08. The Third International Multi-Conference on SP - 229 KW - rp AU - Genc, HM AU - Hocaoglu, AK PY - 2008/// UR - http://dx.doi.org/10.1109/ICCGI.2008.53 ER -