Research On Infrared Weak Small Targets Detection And Tracking Technology Under Complex Backgrounds

Infrared imaging targets detection and tracking system is an optical mechanical and electronic integration system based on passive detection technology, which has the advantage of self-hiding, and strong capacity of resisting disturbance. It's widely applied in infrared warning and precision-guided weapons systems. In the actual application, in order to increase the early warning time of the fire control system (FCS) and enhance the safety factor of our own side, infrared detection system is required to capture the targets and obtain relevant information at far range from the detector as much as possible. However, the longer the distance of targets, the less the imaging area of targets and weaker the targets' signal will be. Therefore, the targets may be submerged into background. So, the question that how weak small targets can be steadily detected and tracked under complex background has become the forefront and highly difficult techniques. On the other hand, as the mobility of targets grow, the further development of the real-time implementation of weak small targets detection and tracking is necessary. Therefore, researches on infrared weak small targets detection, tracking technology and its real-time implementation technology under complex backgrounds have great significance both theoretically and practically.Based on thorough study on the present state and the latest progress of weak small targets detection, combining with our research projects, an implementation scheme of weak small targets detection and tracking system under complex background is designed. The key technologies in target detection, maneuvering targets, implementation of hardware and software are studied deeply to the point of developing effective weak small targets detection and tracking project under complex background. As a result, a series of suitable technologies whose feasibility and effectiveness have been verified by practice have been put forward.The main contributions of this dissertation are as follows:Firstly, aiming at different types of complex background, several kinds of background suppression algorithms are proposed. For the case that the field of view contains highlighted and large area background, a novel markov random field (MRF) based adaptive regularizing filtering algorithm is proposed. To effectively suppress strong undulant background with complex texture, a new filtering method based on cubic fact image model and bidirectional diffusion is introduced. Besides, to improve the real-time capability of the system, a new background suppression method which is based on adaptive differencing quantization and can accomplish image acquisition and background suppression simultaneouly is proposed. Experiment results indicate that the image pre-processing algorithms can efficiently suppress the complex background with the advantage of its logical structure simple to be implemented in real-time system.Secondly, benefit from background suppression process, is that the signal-to-noise ratio (SNR) of the images is improved to some degree. However some residual background still exits, as a consequence, traditional targets detection algorithms have some difficulties in detecting accurately and fast. So, a fast detection algorithm for small targets based on iso-elevation contour map (IECM) feature matching is designed. Theoretical analysis and experiment results show that this method can provide good detection performance and promote the real time capacity.Thirdly, since the actual targets usually have high maneuverability, which have strong non-linear motion equation, a fast tracking method focusing on the purpose of tracking this type of targets fast and accurately, which is based on multi-rate interacting multiple model (IMM) algorithm, is proposed. Experiment results show that the algorithm significantly reduces the computational complexity and improves tracking accuracy to some extent, which has practical value in engineering.Lastly, aiming at the performance indicators of research project, a high-speed and parallel image signal processing system based on FPGA and multi DSP is presented, which can detect and track small targets in real-time. Meanwhile, to facilitate expanding the functions of system, parallel image process real time operation system (PIPRTOS) is designed for this hardware platform to accomplish the distributed processing of the software. Experiment results show that the system can not only detect and track small targets in real-time, but also have good stability and scalability.The proposed algorithms and hardware platform have been assembled into"infrared small targets detection and tracking technology"principle prototype, and several prototype field experiments has been done in certain airports. Experiment results show that the function and performance of the system have met the design requirement, which verifies the accuracy and effectiveness of proposed hardware and software programs.