Hierarchical information fusion object recognition system and method

A hierarchical object recognition method for aggregation, interpretation and classification of information from multiple sensor sources on the detection feature attribute level, wherein the method is adapted for a hierarchical real-time SAR/FLIR air-to-ground targeting object recognition system for automated target classification on the detection feature attribute level, comprising the following steps:

• extracting information derived from each said sensor source to obtain detections and their feature attributes;
• providing at least two processing streams, one for each said sensor source, for converting said detections and their feature attributes into hypotheses on identity and class of detected objects;
• providing a plurality of fusion engines having hierarchical information fusion algorithms for fusing said hypotheses at different feature levels for each said processing streams;
• and
• sharing and combining the detection feature attributes and hypotheses about the detections between the two processing streams using hierarchical information fusion algorithms to determine which ones of said hypotheses on identity and class of detected objects have the highest probabilities, and at least one of said fusion engines providing said fused hypotheses of said one fusion engine to said processing streams for determining hypotheses based on said feature attributes.

A hierarchical object recognition system for aggregation, interpretation and classification of information from multiple sensor sources on the detection feature attribute level, said system comprising:

• an extraction information engine derived from each said sensor source using hierarchical information extraction algorithms to obtain detections and their feature attributes;
• at least two processing streams, one for each said sensor source, each said processing stream having a plurality of processing stages adapted for converting said detections and their feature attributes into hypotheses on identity and class of detected objects;
• and
• a fusion engine having a fuse decision module for sharing and combining the detection feature attributes and hypotheses about the detections between the at least two processing streams using hierarchical information fusion algorithms to determine which ones of said hypotheses on identity and class of detected objects have the highest probabilities,
• said fusion engine sharing and combining the hypotheses of at least one of said processing stages for each said sensor source in order to provide the combined hypotheses to another one of said processing stages for determining hypotheses based on said feature attributes.

A hierarchical information fusion target recognition system for classifying targets based upon target data from a plurality of sensor sources:

• an information extraction engine for processing target data from each of said sensor sources at different feature levels in order to formulate target hypotheses regarding classification of said targets;
• a plurality of fusion engines connected to said information extraction engine for fusing target hypotheses at each of said different feature levels from said sensor sources, and at least one of said fusion engines providing said fused target hypotheses of said one fusion engine to said information extraction engine for determining hypotheses on identity and class of detected objects;
• and
• a target list generator connected to said fusion engines for generating a list of targets based upon said fused target hypotheses.