Fast direct position determination method based on the sharpening function genetic algorithm |
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| Authors: | REN Yanqing LU Zhiyu BA Bin WANG Daming |
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| Affiliation: | (Institute of Information System Engineering, Information Engineering Univ., Zhengzhou 450002, China) |
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| Abstract: | The traditional DPD algorithm has a slowly-varying cost function near the peak, which makes it ineffective to get the optimization location result. To solve the problem, a fast direct position determination method based on the sharpening genetic algorithm is proposed in this paper. First, the algorithm constructs a sharpening function to sharpen the target function of DPD and enhances the algorithm selection ability. Then the algorithm combines with the initialization in the convergence process to increase the diversity of the population and preventes the algorithm into a local optimum. Finally, the algorithm realizes the fast estimation of the target's position. Simulation results show that the algorithm proposed can obtain a higher positioning accuracy than a fast DPD method based on the traditional genetic algorithm in the high SNR condition. Compared with ML-DPD, the computation can be reduced 3 orders of magnitude at 95％ probability and the computational efficiency is greatly improved. |
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| Keywords: | passive location direct position determination genetic algorithm grid search |
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