SBIR-STTR Award

The development of efficient algorithms to process laser radar returns is required by the dramatic increases in capabilities of laser radar hardware. Freestyle Technologies, Inc. will develop and demonstrate three innovative algorithms that will characterize clutter, aid in the detection of occluded targets, and provide aimpoint selection. In addition, Freestyle Technologies, Inc. will design and test a new topcoat for vehicles that will form the basis of a semi-cooperative identification Friend or Foe (Semi-IFF).

The last ten years have seen dramatic increases in the capabilities of laser radars (also now as ladars). Rapid advances have occurred in every technology necessary to realize an affordable sensor for tactical application including: munitions, UAVs and ground-based surveillance systems. To effectively develop detection and discrimination algorithms a visualization environment is needed that allow the user to import data, examine it, manipulate it and evaluate algorithm concepts on it. During Phase II a public domain visualization tool, known as the Ladar Viewer, will be delivered. This tool will allow the user to import data collected with a ladar sensor and/or simulation/modeling data generated by IRMS. Phase II will define and evaluate several algorithms that may be placed in the public domain. The sequential correlation algorithm defined in Phase I will be extended and evaluated on the MILES STAR database. Algorithms that exploit polarization diverse data will also be evaluated.

Keywords:
Data Visualization, Automatic Target Recognition, Sequential Correlation, Laser Radar, Ladar