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A modified method of passive ranging from optical flow (OF) of infrared target was proposed. The range was achieved through analyze of the movement of the imaging sensor and the OF of the target. As the traditional passive ranging algorithm was only using the definition but no OF in the range estimation. The resolution of the imaging system will influence the ranging result strongly. The OF of the potential target image from an adequate length of temporal changing rate. The direct use of OF in range estimation is supported by a modified 3D gradient operator. We present the OF parameters clustering method to achieve more robust result. Firstly, we use median filter to remove the wildpoints and outliers of the image sequences. Secondly, the moving target was segmented with auto-adaptive threshold algorithm. The whole target was obtained by the OF of the pixels inside the smallest rectangle that surrounds the target. A range expression at each pixel may directly calculate from the pixel location, the motion parameter and OF. Finally, the range to the target is the average range of the target area pixels. The experiment result shows that the algorithm can be applied to the infrared target passive ranging applications.

Signal processing algorithms (SPA) play a key role in an imaging IR tracker which is widely used in infrared search and track (IRST) system. When being used to target detection, recognition and tracking, SPA has a significant influence on the performance of the IRST system. Due to the variety and complexity of field scenes and countermeasures, SPA should be robust enough for military use. The question arises as to how to measure and assess the performance of SPA efficiently and properly. On the other hand, the study on SPA performance evaluation will not only give an assessment to a specific algorithm, but also help the development of signal processing technology. In this paper we propose a way to set up an evaluating system in the SPA research laboratory and study the criteria for the evaluation.