統一線形センサー配列との未知の相互結合下で,遠場と近場の混合源定位のための改良された2段階のレアアルゴリズム.
Keyu Chen1, Ke Deng1, Jianguo Zhang1
1Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Sensors (Basel, Switzerland)
|February 13, 2026
まとめ
ITS-RAREアルゴリズムは,未知の相互結合であっても,混合された遠場と近場源を正確に特定します. この新しい方法は,計算負荷を軽減しながら,ソース分類と推定精度を向上させます.
科学分野:
- シグナル処理 信号処理
- 配列信号処理 配列信号処理
- エレクトロマグネティクス 電子磁気学
背景:
- 精密なソースローカライゼーションは,さまざまなアプリケーションにおいて極めて重要です.
- 既存の方法は,遠くのフィールド/近くのフィールドの混合源と未知の相互結合と闘っています.
- 相互結合は,配列の性能を著しく低下させる.
研究 の 目的:
- 改善された2段階のランク削減アルゴリズム (ITS-RARE) を提案する.
- 遠場 (FF) ソースのDOAと相互結合因子の共同推定を事前校正なしで可能にします.
- 近場源 (NFS) のクローズド形式の範囲推定を達成し,コンピューティングの複雑さを軽減します.
主な方法:
- ランク減少のための自己ベクトルを利用して,相互結合係数を特定する.
- FF源のDOAと相互結合因子の共同推定.
- FF/NFソース分類中に全配列の光開を保持するためのコヴァリアンスマトリックス再構築 (CMR).
- NFS のクローズドフォームの範囲推定.
主要な成果:
- FF源 DOAと相互結合因子の共同推定を成功裏に達成しました.
- NFSのクローズドフォーム範囲の正確な推定を有効にしました.
- 既存のアルゴリズムと比較して計算複雑性が著しく低下した.
- 全配列の開口が保たれ,推定精度が向上する.
結論:
- ITS-RAREアルゴリズムは,混合FF/NFソースをローカライズするための計算効率の良い,効果的なソリューションを提供します.
- この方法は,未知の相互結合を処理しながらも,DOAと範囲を正確に推定します.
- 効果的な配列開口を保持すると,局所化の精度が向上します.
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