Comparer des méthodes

	Navigation Proportionnelle	Filtre de Madgwick
Domaine	Aérospatiale	Aérospatiale
Famille	Process / pipeline	Process / pipeline
Année d'origine	1957	2010
Auteur d'origine	Lin-Hsiung Chu	Sebastian Madgwick
Type	Guidance law	Filter algorithm
Source fondatrice	Knox, W. P. (1971). On optimal proportional navigation. IEEE Transactions on Aerospace and Electronic Systems, AES-7(3), 417–426.	Madgwick, S. O. H., Harrison, A. J. L., & Vaidyanathan, R. (2011). Estimation of IMU and MARG orientation using a gradient descent algorithm. IEEE International Conference on Rehabilitation Robotics (ICORR), 1–7.
Alias	PN, PN law	Madgwick AHRS, gradient descent attitude filter
Apparentées	3	3
Résumé	Proportional Navigation (PN) is a guidance law that generates command accelerations proportional to the rate of change of the line-of-sight angle between a pursuer and target. Introduced by Lin-Hsiung Chu in the 1950s, it became the foundation of modern missile guidance systems. PN solves the pursuit-evasion problem by ensuring that the pursuer intercepts a moving target with minimal computational overhead.	The Madgwick Filter is a computationally lightweight attitude estimation algorithm that fuses inertial measurements (accelerometer, gyroscope) with magnetic measurements (magnetometer) to compute a quaternion orientation. Introduced by Sebastian Madgwick in 2010, the algorithm uses gradient descent optimization to minimize the error between measured and expected sensor outputs, yielding accurate, drift-free attitude estimates on embedded systems with minimal computational cost. The Madgwick Filter is now ubiquitous in consumer electronics, robotics, and aerospace systems.