| 基于粒子群优化卡尔曼滤波的水下机器人信号处理 |
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| 引用本文： | 王翠翠,朱大奇,刘静.基于粒子群优化卡尔曼滤波的水下机器人信号处理[J].船海工程,2010,39(1). |
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| 作者姓名： | 王翠翠 朱大奇 刘静 |
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| 作者单位： | 上海海事大学,水下机器人与智能系统实验室,上海,200135 |
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| 摘 要： | 在卡尔曼滤波的基础上,引入粒子群优化算法,对卡尔曼滤波方法进行改进,提出基于粒子群优化的卡尔曼滤波器模型,从而提高水下机器人测量数据的精度,降低系统噪声和量测噪声所带来的误差。水池仿真试验结果表明改进的滤波方法有效、实用。
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| 关 键 词： | 卡尔曼滤波器 粒子群算法 水下机器人 信号处理 |
Underwater Vehicle Signal Processing Based on Particle Swarm Optimization Kalman Filter |
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| Authors: | WANG Cui-cui ZHU Da-qi LIU Jing |
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| Institution: | WANG Cui-cui,ZHU Da-qi,LIU Jing(Laboratory of Underwater Vehicles Intelligent Systems,Shanghai Maritime University,Shanghai 200135,China) |
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| Abstract: | A Kalman filter model based on particle swarm optimization(PSO) algorithm was proposed,and the filtering precision of underwater vehicle measurements was improved to reduce the measurement noise.This filtering method is proved to be effective by pool simulation test for Gyro Sensor of OUTLAND1000 underwater vehicles. |
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| Keywords: | Kalman filter particle swarm optimization underwater vehicles signal processing |
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