| Citation: | Qingli YAN, Jianfeng CHEN. Sensor Selection Method Based on Multi-objective Optimal Optimization for Mixture Gaussian Noise[J]. Journal of Electronics & Information Technology, 2021, 43(2): 341-348. doi: 10.11999/JEIT191031
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To overcome the flaw that the sensor selection methods based on either of Bayesian Fisher information matrix or mutual information could not provide coincident results, the multiple objective optimal technology is developed for sensor selection by minimizing the number of sensors, maximizing corresponding Bayesian Fisher information matrix and mutual information of the selected sensors. Then, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach is proposed to find the candidate that can better trade off the cost and two performance metrics. Comparison results demonstrate that the proposed method can find a better sensor group, and ultimately, its overall localization performance is more stable and accurate.
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