Qi Zhao, Jincheng Wang, Zixuan Fang, Guoqing Wang, Ran Wang, Yue Lou
Proceedings Volume AOPC 2019: Display Technology and Optical Storage, 113350M (2019) https://doi.org/10.1117/12.2548010
This paper proposes a combination detection and fusion method for targets on sea surface, which is based on radar and infrared channels, this method is also suitable for sea surface target combination detection and fusion of radar and visible light camera at the same time. Radar detection has the advantages of full-time, all-weather, and large detection range, but the ability to acquire target details is poor. In comparison with radar, infrared detection has higher angular resolution and can acquire the target's thermal radiation characteristics, which allows for a wealth of detailed information. However, the infrared field of view is small. Based on the advantages and disadvantages of these two detection methods, the radar is used for target detection. Then, according to the azimuth angle and the distance of the target in the radar image, the infrared camera is guided to observe the target. The combined detection method of radar-guide-infrared can combine the advantages of radar’s long detection range, large coverage area with the high resolution and rich detail information of infrared, which covers the details missing of radar detection and the small view field of infrared. After the radar directs the infrared to the target, we will get the infrared image of target. If there is more than one target, it is necessary to merge the data of the radar channel and infrared channel, so that the targets detected by the radar correspond to the targets of the infrared detection. However, due to the different error sources of radar and infrared detection, the error characteristics of the two channels are greatly different, which makes the target fusion of radar and infrared channel difficult. In order to deal with this problem, first of all, the Extend Kalman filter models for radar channel and infrared channel are designed respectively, which are on the base of the imaging characteristics of radar and infrared. After the filtering of the target position information obtained from radar and infrared channels, the random error of the target and the error of target solution will be reduced. What’s more, the velocity information of the targets will be solved at the same time. After that, the error distribution mathematical models of the radar and the infrared channels will be established. Combine the error distribution models with the filtering results and the relationship between the radar coordinate system and the infrared coordinate system, the probability distribution of the targets in radar image and infrared image will be obtained. Finally, according to the probability of the target distribution, numerical method is used to compute the matching matrix of the targets in radar and infrared images. After dealing with the matching matrix, the target fusion of radar channel and infrared channel is accomplished. After that, according to the target matching result, the radar and infrared data are fused to obtain higher-precision target position information.