This paper takes the tracking and guidance of small moving targets in the complex background as the application scenario,and carries out the research of Strap-down imaging terminal guidance technology based on the mobile intelligent device. Using the low-cost sensor and processor components of the mobile intelligent terminal, the design, development and technical verification of Strap-down imaging guidance components are completed. The main research work is summarized as follows: (1) This paper studies the relationship between the selection of target template and the tracking stability around the problem of small moving target tracking in complex background. On this basis, in order to improve the stability of small moving target tracking in complex background, a target template extraction method based on deep learning is proposed. Firstly, a deep contour detection network is designed to extract the contour of the target. A number of experiments show that the depth contour detection network designed in this paper can extract the contour information better than other methods. Then, the area enclosed by the target contour is selected as the template for template matching and tracking, which improves the accuracy of template extraction. The experimental results show that compared with the traditional matching tracking method with rectangular template, this method has higher anti background interference ability and effectively improves the tracking stability of small moving targets in complex background. (2) In this paper, a template adaptive updating strategy is designed to solve the problem of tracking stability degradation caused by illumination change, occlusion and affine deformation, which is often encountered in target tracking. On this basis, a target tracking method based on contour template matching is proposed. The Siamese tracking network with adaptive template updating strategy is designed and implemented. The system generates the target contour template from a single initialization point. In the tracking process, the target detection branch and the contour detection branch jointly decide to update the template in time to achieve the best performance. The experimental results show that this method can effectively solve the problem of partial occlusion and deformation of the target. The statistical results of the central error show that the tracking accuracy of this method is greatly improved compared with other methods. (3) This paper presents a method to solve the LOS angle velocity signal of Strap-down imaging guidance based on multi-sensor information fusion. The calculation model of LOS angle velocity of Strap-down imaging guidance is established, and the LOS angle velocity signal of target is calculated according to the tracking result of vision channel and the attitude information obtained by gyroscope. In view of the characteristics of large gyro zero drift of mobile intelligent devices and the influence of background noise and thermal noise, the accuracy of LOS angle velocity is improved by unscented Kalman filter. The simulation results show that the method proposed in this paper can overcome the problem of large zero drift and low accuracy of pose sensor to some extent. (4) A Strap-down imaging seeker is developed by Huawei mobile intelligent device Huawei mate 9, which is based on mate 9's processor, vision sensor, inertial sensor, satellite navigation module and operating system have completed the development of target tracking, LOS angle velocity calculation and LOS angle velocity filtering algorithm, and have carried out experimental verification, which provides a feasible technical way for the development of low-cost, micro Strap-down imaging guidance module.