SBIR/STTR Research Award

Computational Intelligence Approaches to Automatic Target Recognition

Award identifier 1cbf46c2d23b2049da6fdf226d508823ce54cd3793bd6c666cb272dccbc7758dAwarding agency Department of Defense · Defense Advanced Research Projects Agency

Award amount

$374,402

Program and phase

SBIR · Phase II

Award year

1997

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Award details

Awarding agency
Department of Defense
Branch
Defense Advanced Research Projects Agency
Recipient company
I-MATH ASSOC., INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
Not reported
Topic code
Not reported

Research abstract

The Computationally Intelligent ATR Architecture (CIAA) for SAR imagery will be driven by both point (scatter) and region features. I-MATH has previously developed point extraction algorithms. SAIC will suggest various region measurements, again drawing upon the current results of the MSTAR program. All of the raw features, both point and region associated, including the (x,y) hash point coordinates, will be input into the System Dynamics "e" Genetic Algorithm program, so as to produce two sets of evolved features. The first set will be tested with fuzzy logic rules (also evolved by the Genetic Algorithm) to generate an index to the Geometric Hashing. The primary index will be target pose (3D orientation) and possibly some estimates of target class. This will decisively reduce the size of the search space for the geometric hashing; hence a much smaller group of models will need to be matched. Currently, the hash matching determines which point model is closest to the point representation of the unknown live image. A number of metrics are computed, including percent of live and model points matched, live and model basis pair distances, average point mismatch distance, and roation angle dissimilarity. These metrics are applied with ad hoc thresholds and rules to determine the match. For the CIAA, we would instead use a second fuzzy logic rule set, again derived by the Genetic Algorithms, to compute more efficient match decision metrics. The CIAA represents an innovative structure for both improving ATR performance and simplfying the model search strategy. Notwithstanding this innovation, its components are all proven algorithms with which we are developing other successful ATR systems. In Phase I, we will provide detailed estimates of the CIAA's performance by benchmarking it to the geometric hashing-only algorithm. In Phase II, we will extend the CIAA evaluation by comparing its performance to other SAR ATR's, to especially include the MSTAR algorithm suite.

Technology keywords

Not reported

Agency intelligence

Department of Defense

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