<p>Aerial surveys are dynamic and continuous processes, and there are different height distributions of the ground in the measurement area, which leads to problems such as overlapping measurement areas and inaccurate altitude correction during the survey process. Commonly used terrain correction methods are based on the concept of finite elementization of ground surface radioactive sources, using GPS coordinates, radar altitude, and ground elevation distribution information from aerial surveys, combined with the sourceless efficiency calibration method to construct a response matrix, which is then inverted for surface nuclide content. However, most of the sourceless efficiency calibration methods used are numerical calculations that consider the body detector as a point detector and do not consider the changes in intrinsic detection efficiency under different incident directions of gamma rays. Therefore, when the altitude of the measurement area varies significantly or the flight altitude of the aerial survey is relatively low, such sourceless efficiency calibration method calculations tend to have a large bias, which affects the accuracy of the terrain correction. To address the above problems, this study employs a novel sourceless efficiency calibration method based on the Boolean operation of the ray deposition process and simplifies the traditional body source measurement model to a surface source measurement model to achieve fast and accurate efficiency calibration. Then, through the discretization of the measurement process, the static measurement process is superposed as equivalent to the dynamic measurement process, and the dynamic measurement response matrix is built and optimized based on the calibration method. Finally, the PSO-MLEM algorithm was used to solve the dynamic measurement response matrix to achieve dynamic terrain correction of aerial survey data. Analysis of the Baiyun’ebo test area revealed that, after applying dynamic terrain correction, the inverted anomalies in uranium (eU), thorium (eTh), and potassium (K) concentrations were closer to ground measurements (within 5.72%–30.79%) and exhibited clearer anomaly boundaries compared to traditional height-based corrections. However, owing to the inherent statistical fluctuations and characteristics of matrix inversion, higher measurement values tend to absorb lower ones, potentially enlarging the anomalous regions. Nevertheless, the high-anomaly regions after inversion largely coincided with the ground truth validation, demonstrating that the proposed method can effectively correct airborne gamma spectrometry data.</p>