Enhanced Detection of Hidden Targets Using Multi-Discriminant Ladar

Precision weapons using Ladar seekers with automatic target recognition (ATR) will be challenged by an enemy’s efforts to hide, and it will be necessary for these Ladar systems to have enhanced target detection capability. The design features that show the most potential for providing enhanced “hidden” target detection include: multi-pulse detection logic and the use of polarized multi-spectral laser transceivers. The more ways a sensor samples the environment, the harder it is to effectively camouflage an object. However, more complex sampling leads to a greater volume of data, and more dimensionality. This generally means that the discrimination / recognition problem requires more technical sophistication. In recognition of this fact the Air Force Research Lab has expressed a desire to apply recent advances in non-linear dimensionality reduction analysis to the multi-discriminant Ladar ATR problem. The objective of this proposed research is to exploit the use of multi-discriminant Ladar and non-dimensionality reduction analysis to develop algorithms for improving the detection of hidden objects and targets employing camouflage, concealment, or deception. The results of this research could lead to a significant improvement in weapons system effectiveness.