Aiming at the application scenario of helmet positioning system, considering the practical requirements of the calibration process such as convenience, accuracy and easy maintenance, a visual calibration algorithm based on infrared feature control point group is proposed. This algorithm performs image processing and pixel extraction on infrared control points with known spatial coordinates under the mathematical imaging model of infrared camera, and uses a series of mathematical transformations to obtain the internal and external parameters of the infrared camera. According to the intersection results calculated by the calibration parameters, spatial coordinate verification can achieve accuracy better than ±0.5 mm, attitude angle verification can achieve accuracy better than ±1°, and relative length verification can achieve accuracy better than ±0.3 mm. The mapping relationship between the two-dimensional coordinate system of the image plane and the three-dimensional coordinate system of the space is established to provide a reliable basis for the subsequent precise positioning of the helmet.