転送アライナメントのためのフージーロジックベースの適応フィルタリング
Zhaohui Gao1, Jiahui Yang2, Chengfan Gu3
1School of Electronic Engineering, Xi'an Shiyou University, Xi'an 710065, China.
Sensors (Basel, Switzerland)
|August 28, 2025
まとめ
この研究では,ストラップダウン慣性ナビゲーションシステム (SINS) の転送アライナメントの精度を改善するために,フージーロジック適応フィルターを導入します. この新しい方法は,システムモデルのエラーを効果的に管理することで,SINS状態の推定を強化し,18%以上の精度を達成します.
科学分野:
- ナビゲーションシステム
- 制御理論
- シグナル処理
背景:
- ストラップダウン慣性ナビゲーションシステム (SINS) は,機内戦術車両の正確な転送配列を必要とします.
- カルマンフィルターのシステムモデルエラーは,SINS状態推定精度を低下させる.
研究 の 目的:
- 曖昧な論理に基づいた適応フィルタリング方法をSINS転送アライナメントに開発する.
- システムモデルのエラーがSINS状態推定に与える影響を軽減する.
主な方法:
- 曖昧な論理に基づいた適応フィルタリングアプローチを SINS 転送アライナメントのために設計した.
- カルマンフィルターフレームワークに残留値を含む状態と測定エラーモデルを埋め込みます.
- システム測定を推定し,残留を最小限に抑えることで状態コヴァリアンスを予測するために,フージルルを使用した.
主要な成果:
- 提案された方法は,SINS転送アライナメントにおけるシステムモデルのエラーを効果的に処理します.
- ベンチマーク方法と比較して少なくとも18.83%高い精度を達成しました.
- シミュレーションと実験で 方法の性能が確認されました
結論:
- 曖昧なロジック・アダプティブ・フィルターは,SINSの転送アライナメントの精度を大幅に改善します.
- このアプローチは,空中戦術車両のナビゲーションに 堅固な解決策を提供します.
- この方法は,モデルの不確実性を管理する上で優れたパフォーマンスを示しています.
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