Injection locking in selfoscillating magnetometers Injection locking (IL) is a wellknown phenomenon that occurs in nonlinear oscillators subject to external periodic or nonperiodic signals. It is a phenomenon of induced synchronization that occurs when an external (injection) signal locks the frequency of the oscillator to the frequency of the external signal. This form of synchronization is relatively straightforward to implement because it does not require specially organized feedback as is the case with phase locked loop. Circuits that exploit IL can have very simple designs and be applied to a broad range of applications, such as to synchronize frames and lines in early television sets, to synchronize lasers, and to function as ac voltmeters, fieldintensity meters, amplifierlimiters and AM and FM detectors. However, the focus of this article is the recent application of IL to magnetic field sensors. This novel application highlights the potential benefits of the IL approach but also some of the complexities and opportunities for further development. As with all measurement systems, the consideration of noise is paramount in the design of magnetic sensors. Noise reduction and mitigation strategies are essential. IL can be employed as a noise mitigation strategy in magnetometers that utilize selfoscillations as part of their detection paradigm; it can stabilize the oscillation frequency, potentially simplifying the measurement circuitry, and in some circumstances improve the signaltonoise ratio. Here we review some magnetometers that have successfully exploited IL principles and highlight design options. We also propose a new circuit that is simple to implement and more straightforward to analyze.

RealTime Calibration of Magnetometers Using the RLSML Algorithm This study presents a new realtime calibration algorithm for threeaxis magnetometers by combining the recursive least square (RLS) estimation and maximum likelihood (ML) estimation methods. Magnetometers are widely employed to determine the heading information by sensing the magnetic field of earth; however, they are vulnerable to ambient magnetic disturbances. This makes the calibration of a magnetometer inevitable before it is employed. In this paper, first, a complete measurement error model of the magnetometer is studied, and a simplified model is developed. Then, the realtime RLS algorithm is introduced and discussed in detail, and the unbiased optimal ML is utilized to improve the accuracy of the parameter estimation. The proposed algorithm is advantageous in correcting the parameters in real time and simultaneously obtaining unbiased parameter estimation. Finally, the simulation and experimental results demonstrate that both the accuracy and computational speed of the proposed algorithm is better than those of the widely used bathprocessing method. Moreover, the proposed calibration method can be adopted for calibrating other threeaxis sensors.