Multi-band IR imaging system has many applications in security, national defense, petroleum and gas industry, etc. So the relevant technologies are getting more and more attention in rent years. As we know, when used in missile warning and missile seeker systems, multi-band IR imaging technology has the advantage of high target recognition capability and low false alarm rate if suitable spectral bands are selected. Compared with traditional single band IR imager, multi-band IR imager can make use of spectral features in addition to space and time domain features to discriminate target from background clutters and decoys. So, one of the key work is to select the right spectral bands in which the feature difference between target and false target is evident and is well utilized. Multi-band IR imager is a useful instrument to collect multi-band IR images of target, backgrounds and decoys for spectral band selection study at low cost and with adjustable parameters and property compared with commercial imaging spectrometer. In this paper, a multi-band IR imaging system is developed which is suitable to collect 4 spectral band images of various scenes at every turn and can be expanded to other short-wave and mid-wave IR spectral bands combination by changing filter groups. The multi-band IR imaging system consists of a broad band optical system, a cryogenic InSb large array detector, a spinning filter wheel and electronic processing system. The multi-band IR imaging system's performance is tested in real data collection experiments.
Selecting key point in airplane target as tracking aimpoint at end term is important for IR imaging missiles to improve guidance accuracy. A new aimpoint selection method proper for engineering application is proposed in this article. Other than tracking the center of plume which is the most marked property of airplanes, some point near engine is selected as aimpoint. Firstly plume and skin are extracted by using different thresholds according to their gray scale statistics and features like circularity, distance ratio and central axis are obtained to classify the image types. Then referring to these image types, the centroid of the segmented sector or a point on the line of central axis of plume sector are selected as aimpoint respectively. The algorithm has the advantage of more efficiency in both space and time consuming. Tests have shown the validity of the algorithm.
Low signal-noise-ratio(SNR) target detection is a difficult task in ATR. In this article, a small and weak
circular object detection algorithm for forward looking usage is proposed. Firstly the horizon is
detected through using the edge operator and large scales of clutters below the horizon are excluded.
Then Hough transform based on edge tracing is applied to detect the circular object. The algorithm can
be realized in DSP hardware platform in real time, and high acquisition probability is got in tests and