ADVANCED RADAR CROSS SECTION MEASUREMENT ANALYSIS

AUTOMATIC IDENTIFICATION OF TARGET INFORMATION USING RADAR CROSS SECTIONS IS AN EXTREMELY DIFFICULT PROBLEM. A LARGE AMOUNT OF EFFORT HAS BEEN DEVOTED TO THE PROBLEM OF ESTIMATING THE RADAR CROSS SECTION OF VARIOUS SHAPES, BUT THE RANGE OF POSSIBLE OBJECTS WHICH CAN BE ENCOUNTERED IS LARGE, AND MEASURES CAN BE TAKEN TO ALTER THE APPEARANCE OF A RADAR CROSS-SECTION. IN ADDITION, AN OBJECT CAN BE VIEWED FROM MANY VIEWPOINTS, ADDING TO THE COMPLEXITY OF THE ANALYSIS TASK. IDENTIFICATION OF "HOT SPOTS" USING RADAR CROSS SECTIONS IS USEFUL FOR BOTH TARGET RECOGNITION AND FOR COUNTERMEASURE PURPOSES. WE ARE PROPOSING TO STUDY THE APPLICABILITY OF SEVERAL RELATED AND COMPLEMENTARY ARTIFICIAL INTELLIGENCE APPROACHES FOR THE ANALYSIS OF RADAR CROSS SECTIONS. ONE TECHNIQUE OPERATES PRIMARILY IN THE FREQUENCY DOMAIN AND THE OTHER MAINLY IN THE SPATIAL DOMAIN. WE WILL EVALUATE THESE TECHNIQUES AND EXPLORE THE POSSIBILITY OF COMBINING THEM TO ACHIEVE A ROBUST MULTI-DOMAIN ANALYSIS TOOL. THE TECHNIQUES BEING STUDIED HAVE ALREADY PROVEN USEFUL IN A VARIETY OF DOMAINS INCLUDING SPEECH, MEDICAL WAVEFORM ANALYSIS, AND IMAGE ANALYSIS.