繊維光学ジロ ランダム エラー 抑制 ダブル アダプティブ カルマン フィルター
Hongcai Li1, Zhe Liang1, Zhaofa Zhou1
1Intelligent Control Laboratory, PLA Rocket Force University of Engineering, Xi'an 710025, China.
Micromachines
|August 28, 2025
まとめ
この研究は,光ファイバー・ギロの精度を向上させるための新しい再帰的ダイナミック・アラン・バリエンス・メソッドを導入しています. このアプローチは,カルマンフィルターパラメータを適応することによって,角的ランダムウォークエラーの抑制を強化します.
科学分野:
- 計測装置
- シグナル処理
背景:
- 光ファイバー・ジャイロ (FOG) の衝撃測定の精度におけるランダムなエラー
- 時間の変動によるエラー特性により,従来のエラー抑制アルゴリズムが劣化します.
研究 の 目的:
- 動的アラン分散をリアルタイムで計算するための改良された方法を開発する.
- FOGのランダムエラー抑制アルゴリズムのパフォーマンスを向上させる.
主な方法:
- 従来の方法の限界を克服するために再帰的ダイナミックアラン分散計算を提案した.
- カルマンフィルタリングプロセスの分散推定と再帰的ダイナミックアラン分散を統合した二重適応カルマンフィルタを開発した.
- 静的および動的検証実験を行った.
主要な成果:
- 提案された再帰的ダイナミック・アラン・バリエンス・メソッドは,リアルタイムのパフォーマンスを向上させ,スペクトルの漏れを軽減します.
- デュアルアダプティブカルマンフィルターは,モデルパラメータとノイズ分散を自律的に調整します.
- 実験結果は,角形のランダムな歩行エラーの抑制に有意な改善を示しています.
結論:
- この新しいアプローチは,FOGの時間変動のエラー特性を効果的に対処します.
- 提案された方法は,既存のアルゴリズムと比較して優れたランダムエラー抑制を提供します.
- この進歩により 光ファイバー・ジャイロの全体的な精度と信頼性が向上します
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