Object classification simulation for ladar-passive-infrared imaging combination

The imaging ladar is good at classifying objects because it can send laser actively, receive the reflected wave, and produce angle-angle-range-intensity image. The combination of ladar and passive-infrared (IR) imaging can get more information, and improve the ability of object classification and anti-interference. A fused classification method based on the pixel fusion of ladar range-intensity image is presented for ladar-passive-IR imaging combination. Classification simulation is finished through Dempster-Shafer (D-S) evidence theory with 8-value-template. Correlation coefficients in template matching are obtained by maximum close distance (MCD). The results show that the pixel fusion of ladar range-intensity image makes fused classification uncertainty descend by 40%, and increases discrimination on objects which is difficult to classify, 8-value-template classification is better than 2-value-template, and differences in object mass functions increase by 60%.