An improved exact measuring angle algorithm is proposed for parameter calibration of area array cameras. Based on a given estimated principal point of camera, the algorithm calculated deviation between the estimated and actual principal points and focal distance of the camera by using the corresponding relationship between intersection angle of two beams of parallel lights and image point of projection on the camera. The influence of image feature extraction error on intersection angle measurement accuracy of parallel lights was analyzed and an optimal estimation based on the minimum intersection angle error of parallel lights was employed so as to promote the calibration accuracy of internal parameter of the camera. Simulation experiment was conducted to analyze the influence of image feature extraction accuracy and intersection angle measurement accuracy of parallel lights on camera parameter calibration precision. The results show that the calibration accuracies of principal point and focal distance can reach 0.56 pixel and 0.06 mm respectively when image characteristics extraction accuracy is 0.1 pixel and two-dimensional rotary table accuracy is 0.5″. An two-dimensional rotary table with accuracy reaching 0.5″ is used for parameter calibration of the camera. In comparison of intersection angle error of parallel light calculated based on image point and calibration results with the calibration result, the error of the improved algorithm is 68.6% of the classic exact measuring angle method. This proves that the proposed algorithm has a better accuracy in parameter calibration of area array camera.