Fluxgate sensors are currently widely used for weak magnetic field measurement because of their relatively great performance, such as resolution, power consumption, and measurement of vector magnetic fields directly. Since the analog fluxgate sensor has some drawbacks, e.g., it would be influenced by the noise of the analog circuit. Hence, in recent years, the analog circuit is gradually inclined to be realized by digital processing in which the software parameter adjustment is employed to replace the analog components, which can greatly improve the flexibility of the design. This paper proposes a digital single-axis fluxgate sensor according to the cobalt-based amorphous effect. To be specific, the analog signal output by the fluxgate is sampled directly by an analog-to-digital converter to obtain the signal waveform in digital form after amplification. The demodulation, filtering, and integration of the signal are all solved by mathematical algorithms. Based on the working principle of the fluxgate sensor, the selection of the magnetic core material and coil winding method of the fluxgate sensor probe is introduced in detail. The design and function of the excitation circuit and preamplifier circuit, as well as the specific realization of digital signal processing, are described. Finally, the performance test of the digital fluxgate sensor was performed under laboratory conditions, and the magnetic anomaly detection comparison experiment was performed outdoors with commercial fluxgate sensors. To sum up, the linearity of the digital single-axis fluxgate sensor is better than 1 × 10−5, and the root mean square noise value is below 0.1 nT. At the same time, it has good magnetic field tracking performance and is extremely sensitive to the magnetic field of the measurement area.

Magnetic anomaly detection technologies have been widely used for tracking moving targets. In this paper, we present a fast-tracking method for magnetic abnormalities using a distributed Overhauser magnetometer system based on the genetic algorithm. Our proposed framework of the Overhauser magnetometer system employs multiple sensors to eliminate background interference, and the genetic algorithm efficiently solves magnetic anomaly data without requiring the derivation of the objective function. Test platforms were built to evaluate the distributed Overhauser magnetometer system and the genetic algorithm. Results from the natural outdoor magnetism laboratories showed that the noise of our presented magnetometers was below 0.134 nT. The optimal factors for solution precision and effectiveness in the genetic algorithm were obtained from the simulation. Moreover, the outdoor tracking experiments indicated that the proposed method could accurately and quickly detect the moving ferromagnetic object within 6.9% maximum positioning error in 0.55 m, and the tracking precision of the object velocity can get 5.88% maximum error in 4.33 km/h.