In 1965, Grace Wahba introduced the problem of attitude estimation within the estimate of satellite attitude and aerospace applications. Over the past few years, there has been an increasing interest in multidisciplinary research on multisensor attitude estimation technology. This interest is motivated by the versatility of the diverse areas of application such as aerial and underwater navigation, pedestrian navigation, biomedicine, motion analysis, and smartphone applications. Attitude estimation consists in the determination of rigid body orientation in 3D space (principally in terms of Euler angles, rotation matrix, or quaternion). This research area is a multilevel, multifaceted process involving the automatic association, correlation, estimation, and combination of data and information from several sources. Another interest consists in the fact that redundant and complementary sensor data can be fused and integrated using multisensor fusion techniques to enhance system capability and reliability. Data fusion for attitude estimation is therefore a research area that borrows ideas from diverse felds, such as signal processing, sensor fusion, and estimation theory, where enhancements are involved in point-of-view data authenticity or availability. Data fusion for attitude estimation is motivated by several issues and problems, such as data imperfection, data multimodality, data dimensionality, and processing framework. As a majority of these problems have been identifed and heavily investigated, no single data fusion algorithm is capable of addressing all the aforementioned challenges. Consequently, a variety of methods in the literature focuses on a subset of these issues. The idea of this book comes as a response to the immense interest and strong activities in the feld of multisensor attitude estimation during the past few years, both in theoretical and practical aspects. This book is targeted toward researchers, academics, engineers, and graduate students working in the feld of sensor fusion, fltering, and signal processing for attitude estimation. This book, Multisensor Attitude Estimation: Fundamental Concepts and Applications, captures the latest data fusion concepts and techniques for attitude estimation drawn from a broad array of disciplines. It is intended to provide the reader with a generic and comprehensive view of contemporary data fusion methodologies for attitude estimation, as well as the most recent researches and novel advances on multisensor attitude estimation task exploring the design of algorithms and architectures, benefts, and challenging aspects, as well as a potential broad array of disciplines, including navigation, robotics, biomedicine, and motion analysis. These issues arise from the data to be fused, imperfection and diversity of sensor technologies, and the nature of the application environment. The issues that make data fusion for attitude estimation a challenging task, and which will be discussed through the different chapters of the book, are related to (1) the nature of sensors and information sources (accelerometer, gyroscope, magnetometer, GPS, inclinometer, etc.); (2) the computational ability at the sensors; (3) the theoretical developments and convergence proofs; and (4) the system architecture, computational resources, and fusion level. With contributions from world’s leading fusion researchers and academicians, this book consisting of 31 chapters, is roughly divided into two sections. Each chapter is complete in itself and can be read in isolation or in conjunction with other chapters. This book is introduced by Grace Wahba with a brief historical note on attitude estimation problem. In Section I, Chapters 1 through 3 are devoted to some preliminaries on attitude representations, rotations, kinematics, and dynamics. In Section II, Chapters 4 through 31 focus mostly on the main theories and novel advances in multisensor fltering for attitude estimation with several experimental tests and showcase advancements such as aerial navigation, motion analysis, and satellite. We are grateful to all the contributors for making their valuable contributions to this book, and we expect to offer here a good balance between academic and industrial researches in this book. We sincerely hope that this book will be a source of inspiration for new concepts and applications and stimulate further the development of attitude estimation architectures. We also acknowledge the technical and editorial assistance provided by CRC Press and its staff, which helped to improve the quality of this work.