Monitoring of INS based on chaos PSO algorithm optimization parameters of LS-SVM

WANG Cheng1; HAO Shun-yi1; WENG Da-qing2; FENG Wen1

doi:10.13873/j.1000-97872011.02.012

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Monitoring of INS based on chaos PSO algorithm optimization parameters of LS-SVM

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- Monitoring of INS based on chaos PSO algorithm optimization parameters of LS-SVM
- Vol. 30, Issue 2, Pages: 125-128(2011)
- 作者机构：
  
  1. 空军工程大学工程学院
  2. 中国人民解放军94371部队装备部
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872011.02.012
  CLC： V249.322
- Published：2011
- 稿件说明：
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[1]王成,郝顺义,翁大庆,冯文.基于混沌PSO算法优化LS-SVM的惯导系统测试[J].传感器与微系统,2011,30(02):125-128.

WANG Cheng1, HAO Shun-yi1, WENG Da-qing2, et al. Monitoring of INS based on chaos PSO algorithm optimization parameters of LS-SVM[J]. 2011, 30(2): 125-128.
[1]王成,郝顺义,翁大庆,冯文.基于混沌PSO算法优化LS-SVM的惯导系统测试[J].传感器与微系统,2011,30(02):125-128. DOI： 10.13873/j.1000-97872011.02.012.

WANG Cheng1, HAO Shun-yi1, WENG Da-qing2, et al. Monitoring of INS based on chaos PSO algorithm optimization parameters of LS-SVM[J]. 2011, 30(2): 125-128. DOI： 10.13873/j.1000-97872011.02.012.

摘要

基于混沌PSO算法优化最小二乘支持向量机（LS-SVM）实现惯导系统初始对准测试。通过小波包分解消除陀螺漂移数据的噪声

获取LS-SVM的训练与测试样本。针对LS-SVM解决大规模数据样本回归问题时所出现的训练时间长、收敛速度慢等缺点

提出了混沌PSO算法优化LS-SVM的模型参数。该方法不仅克服了传统PSO算法早熟、容易陷入局部最小值等缺点

同时显著提高了LS-SVM的预测能力。将一般LS-SVM和GM（1

1）模型的预测结果与本算法预测结果进行对比

验证了本方法在预测精度上具有明显优势。

Abstract

Based on chaos PSO algorithm optimization parameters of LS-SVM

monitoring of INS’s initial alignment is realized.Noises in INS’s error data are eliminated by wavelet decomposition

learning and testing samples for LS-SVM are also acquired.Aimed at LS-SVM solving large scale data regression led to long training time and slow convergence speed

chaos PSO algorithm optimization parameters of LS-SVM is proposed.The disadvantages of earliness and tending to get into local solution in traditional PSO algorithm are overcomed by this method.It also remarkably improves forecasting ability of LS-SVM.The results of general LS-SVM and GM（1

1） forecasting model is compared with the results of this article

it proves this method has a transparent superior in forecasting precision.

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references

H ∞ 滤波在惯导系统地面快速对准中的应用 [J]. 王艳东,范跃祖. 北京航空航天大学学报 . 2000(05)

H ∞ 滤波及其在惯导地面自对准中的应用 [J]. 冯绍军,袁信. 南京航空航天大学学报 . 1998(04)

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