rssi -神经网络定位算法的优化

2014 Fourth International Conference on Instrumentation and Measurement, Computer, Communication and Control Pub Date : 2014-09-18 DOI:10.1109/IMCCC.2014.135

Zhang Xuhui, Gao Baojiang, L. Yukun, Wang Juan, Chang Huimin

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引用次数: 5

摘要

本文对RSSI神经网络定位算法进行了优化。深入分析了卡尔曼滤波器的原理，并利用卡尔曼滤波器对接收信号强度指标(RSSI)值进行滤波。分析了反向传播神经网络的结构，优化了rssi -神经网络算法的结构。MATLAB仿真验证了优化算法具有更高的精度和更强的鲁棒性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The Optimization of RSSI-Neural Network Positioning Algorithm

This paper optimized the RSSI neural network positioning algorithm. In-depth analysis of the principles of the Kalman filter and using the Kalman filter to filter the Received Signal Strength Indicator (RSSI) value. Analysis the structure of back propagation neural network and optimized the structure of the RSSI-neural network algorithm. MATLAB simulation verified the optimization algorithm has higher accuracy and more robustness.

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来源期刊

2014 Fourth International Conference on Instrumentation and Measurement, Computer, Communication and Control

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