ScholarGate
Trợ lý

So sánh phương pháp

Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.

Dead Reckoning×Mô hình lỗi INS×
Lĩnh vựcHàng không vũ trụHàng không vũ trụ
HọProcess / pipelineProcess / pipeline
Năm ra đời1940s1960s
Người khởi xướngMaritime navigation traditionSchuler and others
LoạiNavigation methodStochastic model
Công trình gốcSavage, P. G. (2007). Strapdown Inertial Integration Technology (2nd ed.). Strapdown Associates. link ↗Titterton, D. H., & Weston, J. L. (2004). Strapdown Inertial Navigation Technology (2nd ed.). Institution of Engineering and Technology. DOI ↗
Tên gọi khácded reckoning, inertial navigation, odometryINS error analysis, error state kalman filter, ESKF
Liên quan33
Tóm tắtDead Reckoning is a fundamental navigation method that estimates position and heading by integrating velocity and angular rate measurements from inertial sensors over time, without external references such as GPS. The term derives from maritime tradition ('deduced reckoning') and remains a cornerstone of aerospace and autonomous vehicle navigation. Dead reckoning works reliably in GPS-denied environments and is the baseline navigation method when external navigation aids are unavailable.The INS Error Model is a mathematical framework that characterizes how errors in inertial sensor measurements propagate through a navigation system's estimates of position, velocity, and attitude. Developed during the 1960s and refined through decades of navigation research, the error model enables design of optimal estimation filters (e.g., Kalman filters) that fuse inertial measurements with external references (GNSS, LiDAR, cameras) to bound and correct accumulated errors. The error model is fundamental to understanding and improving inertial navigation performance.
ScholarGateBộ dữ liệu
  1. v1
  2. 3 Nguồn tài liệu
  3. PUBLISHED
  1. v1
  2. 3 Nguồn tài liệu
  3. PUBLISHED

Đến trang tìm kiếm Tải xuống bản trình chiếu

ScholarGateSo sánh phương pháp: Dead Reckoning · INS Error Model. Truy cập ngày 2026-06-17 từ https://scholargate.app/vi/compare