In order to reduce the impact of satellite signal loss and cumulative error of inertial navigation during vehicle driving, a vehicle heading angle estimation method based on line detection and digital map matching is proposed by combining scene feature extraction and expression with digital map information. Firstly, according to the coordinate points of the map matching, the corresponding points azimuth of the lane line map is calculated, and the angle difference between the vehicle heading angle and the lane line point azimuth is calculated. Secondly, the angle of lane line in image is recognized and calculated by the improved FLD line detection method. The angle of bilateral lane lines is taken as the input of BP neural network, and the predicted angle difference is taken as the output of the network. Finally, the vehicle heading angle is obtained by combining the angle difference and lane line azimuth. The results of the experiments show that the proposed heading angle estimation algorithm has certain advantages over the existing methods and ordinary measurement sensors.