인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2026.6
- 수록면
- 862 - 872 (11page)
- DOI
- 10.5302/J.ICROS.2026.26.0070
이용수
초록· 키워드
Reliable ego-velocity estimation is critically essential for autonomous vehicle navigation in complex environments degraded by Global Navigation Satellite System. Traditional radar-only methods frequently struggle in urban scenarios because dynamic objects, ghost targets, and multipath interference severely violate standard static-world assumptions. To directly resolve this fundamental limitation, we propose a robust maximum a posteriori inference framework that optimally estimates velocity across all available radar points simultaneously, eliminating the need for brittle point-selection or explicit static–dynamic classification. Our methodology minimizes a Doppler-consistency objective using iteratively reweighted least squares and a Huber loss function. Furthermore, we dynamically assigned confidence-aware weights to each individual point utilizing radar cross-section reliability and velocity-space clustering consistency. A constant-velocity motion prior guarantees essential stability during sparse measurements. We introduce a stringent quality-aware update mechanism that evaluates the normalized innovation squared to reject unreliable updates, employing a fail-soft policy to strictly preserve temporal continuity. Our robust framework achieves comparable average accuracy and suppresses considerably divergence and temporal discontinuities in highly dynamic urban environments based on extensive evaluations based on the View-of-Delft dataset against random-sample-consensus-based regression and Ego-velocity filtering for efficient and accurate 4D radar odometry. Ultimately, this mathematically grounded approach effectively prevents history contamination, ensuring continuous safe operation when external navigation infrastructure inevitably fails to provide stable and accurate localization signals.
상세정보 수정요청해당 페이지 내 제목·저자·목차·페이지정보가 잘못된 경우 알려주세요!
목차
- Abstract
- I. 서론
- II. 사전 이론
- III. 강건 최적화를 이용한 레이더 동체 속도 추정
- IV. 실험 결과 및 분석
- V. 결론
- REFERENCES
참고문헌
참고문헌 신청최근 본 자료
