The calibration of three-axis magnetic field sensors is reviewed. Seven representative algorithms for in-situ calibration of magnetic field sensors without requiring any special piece of equipment are reviewed. The algorithms are presented in a user friendly, directly applicable step-by-step form, and are compared in terms of accuracy, computational efficiency and robustness using both real sensors’ data and artificial data with known sensor’s measurement distortion.

An Inertial Measurement Unit (IMU) architecture estimating angular velocity is introduced. It expands the concept of multi-accelerometers gyroscope-free IMUs (GF-IMUs), taking advantage of their excellent noise performance and resolving their inability to compensate for accelerometers’ bias and their requirement for specific accelerometers placement, which makes GF-IMUs inappropriate for real world applications. It does so by embedding the accelerometers in a low-bandwidth closed-loop configuration with a three-axis gyroscope and by addressing the complete non-linear dynamics. Extensive theoretical analysis provides a complete framework for designing low-noise IMUs including sufficient stability criteria for the non-linear system’s dynamics. Simulation and experimental results support the theoretical analysis and indicate that even a minimal system using the proposed architecture can outperform the gyroscope in noise performance by at most 15dB in some frequency range.

This work presents a power stage architecture that combines high–linearity with high–efficiency. The power stage is configured as a push–pull Class–A topology with two buck–converters providing its supply rails. The buck–converters continuously track the stage’s output with a small constant margin, creating a minimum, constant voltage drop on the output devices; thus, the stage’s efficiency is increased and its linearity is improved. Theoretical analysis of the topology and its feedback control are presented, while a design example is implemented and simulated in Cadence Spectre as proof–of–concept.

In this work we propose a near-optimal Bang-Bang controller for the longitudinal motion of a quadrotor UAV which minimizes the active flight time. The proposed controller is closed loop, has simple cascaded structure and can be used in online navigation since it has minimum computational requirements compared to other approaches in the literature. It is evaluated via numerical simulation for a standard quadrotor nonlinear model.