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The accuracy of the airborne vector magnetic (VM) survey mainly depends on the attitude measurement precision of the aircraft. An orientation change of 0.001° can produce an error of approximately 1 nT in VM components for a geomagnetic field of 50,000 nT. Therefore, noise estimation or accurate understanding of noise characteristics of measured airborne VM data plays an important role in geophysical applications. A new airborne VM system with high-precision attitude measurement (0.003°–0.007° root-mean square [rms]) for geophysical prospecting was developed. We have analyzed the results from test flights, compared the difference between measured and calculated VM data, and we developed two methods to estimate the noise in VM data derived from the new system, which include (1) VM noise, that is, the rms error of the difference between the total magnetic intensity calculated from the measured VM data and measured by the scalar sensor, to mainly estimate the error of calibration and compensation, and (2) rms error of the difference between the data from repeat flight lines, to mainly estimate the error of multiple measurements. The noise estimation results of the two methods based on data from test flights in the Qixin area of the East Tianshan Mountains in China indicate that the new system has high accuracy: VM noise is 2.32 nT; the error of the repeat flight lines is 4.86, 6.08, and 2.80 nT for the [Formula: see text], [Formula: see text], and [Formula: see text] components, respectively.

The remanent magnetization vector records the Earth’s magnetic field at the time of the formation process of magnetized geologic units. Recovering the magnetization vector from magnetic data can provide extra information regarding the source properties to differentiate geologic units and reveal thermal evolution or tectonic history. To provide this information, magnetization vector inversion method has been used to invert for the magnetization vector. The magnetization vector inversion usually works with the total-field magnetic anomaly magnitude (Δ T). The magnitude is an approximation of the projection of the magnetic anomaly vector onto the normal geomagnetic field. For highly magnetic sources, the approximation error of Δ T cannot be ignored. However, this approximation error can be avoided by using measured vector magnetic data. In order to reduce the severe ambiguity of 3D magnetization vector inversion, specific constraints based on extra prior information are usually used. For 2D or 2.5D cases, magnetization vector inversion only inverts for magnitude and inclination of the magnetization, which encounters less ambiguity than that of the 3D case. We have developed a 2.5D magnetization vector inversion approach using vector magnetic data. To reduce the divergent and smooth trend in magnetization vectors recovered by the magnetization-vector inversion method in the Cartesian framework, we make use of a focusing constraint method to improve the imaging. The inversion results of synthetic data show that the method is able to recover magnetization magnitude and inclinations close to the true values, and is fairly robust to inappropriate choice of the profile location and heading. Finally, the method is applied to the measured airborne vector magnetic data from the Qixin area of the East Tianshan Mountains in China. The distributions and directions of magnetization of the mafic-ultramafic rocks and linear structures are revealed, which provides the information for distinguishing geologic units and geological differentiation.

The total-field magnetic anomaly [Formula: see text] is an approximation of the projection [Formula: see text] of the magnetic anomaly vector [Formula: see text] onto the normal geomagnetic field [Formula: see text]. However, for highly magnetic sources, the approximation error of [Formula: see text] cannot be ignored. To reduce the error, we have developed a method for calculating [Formula: see text] by using airborne vector magnetic data based on the vector relationship of geomagnetic field [Formula: see text]. The calculation uses the magnitude of the vectors [Formula: see text], [Formula: see text], and [Formula: see text] through a simple approach. To ensure that each magnitude has the same level, we normalize the magnitude of [Formula: see text] using the total-field magnetic data measured by the scalar magnetic sensor. The method is applied to the measured airborne vector magnetic data at the Qixin area of the East Tianshan Mountains in China. The results indicate that the calculated [Formula: see text] has high precision and can distinguish the approximation error less than 3.5 nT. We also analyze the characteristics of the approximation error that are caused by the effects of different total magnetization inclinations. These error characteristics are used to predict the total magnetization inclination of a 2D magnetic source based on the measured airborne vector magnetic data.

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